˜e First Step Guide to Technical Analysis - IFTA

Hibiscus Petroleum Berhad (5199.KL)


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In light of the recent fall in oil prices due to the Saudi-Russian dispute and dampening demand for oil due to the lockdowns implemented globally, O&G stocks have taken a severe beating, falling approximately 50% from their highs at the beginning of the year. Not spared from this onslaught is Hibiscus Petroleum Berhad (Hibiscus), a listed oil and gas (O&G) exploration and production (E&P) company.
Why invest in O&G stocks in this particularly uncertain period? For one, valuations of these stocks have fallen to multi-year lows, bringing the potential ROI on these stocks to attractive levels. Oil prices are cyclical, and are bound to return to the mean given a sufficiently long time horizon. The trick is to find those companies who can survive through this downturn and emerge into “normal” profitability once oil prices rebound.
In this article, I will explore the upsides and downsides of investing in Hibiscus. I will do my best to cater this report to newcomers to the O&G industry – rather than address exclusively experts and veterans of the O&G sector. As an equity analyst, I aim to provide a view on the company primarily, and will generally refrain from providing macro views on oil or opinions about secular trends of the sector. I hope you enjoy reading it!
Stock code: 5199.KL
Stock name: Hibiscus Petroleum Berhad
Financial information and financial reports: https://www.malaysiastock.biz/Corporate-Infomation.aspx?securityCode=5199
Company website: https://www.hibiscuspetroleum.com/

Company Snapshot

Hibiscus Petroleum Berhad (5199.KL) is an oil and gas (O&G) upstream exploration and production (E&P) company located in Malaysia. As an E&P company, their business can be basically described as:
· looking for oil,
· drawing it out of the ground, and
· selling it on global oil markets.
This means Hibiscus’s profits are particularly exposed to fluctuating oil prices. With oil prices falling to sub-$30 from about $60 at the beginning of the year, Hibiscus’s stock price has also fallen by about 50% YTD – from around RM 1.00 to RM 0.45 (as of 5 April 2020).
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While the company is domiciled in Malaysia, its two main oil producing fields are located in both Malaysia and the UK. The Malaysian oil field is commonly referred to as the North Sabah field, while the UK oil field is commonly referred to as the Anasuria oil field. Hibiscus has licenses to other oil fields in different parts of the world, notably the Marigold/Sunflower oil fields in the UK and the VIC cluster in Australia, but its revenues and profits mainly stem from the former two oil producing fields.
Given that it’s a small player and has only two primary producing oil fields, it’s not surprising that Hibiscus sells its oil to a concentrated pool of customers, with 2 of them representing 80% of its revenues (i.e. Petronas and BP). Fortunately, both these customers are oil supermajors, and are unlikely to default on their obligations despite low oil prices.
At RM 0.45 per share, the market capitalization is RM 714.7m and it has a trailing PE ratio of about 5x. It doesn’t carry any debt, and it hasn’t paid a dividend in its listing history. The MD, Mr. Kenneth Gerard Pereira, owns about 10% of the company’s outstanding shares.

Reserves (Total recoverable oil) & Production (bbl/day)

To begin analyzing the company, it’s necessary to understand a little of the industry jargon. We’ll start with Reserves and Production.
In general, there are three types of categories for a company’s recoverable oil volumes – Reserves, Contingent Resources and Prospective Resources. Reserves are those oil fields which are “commercial”, which is defined as below:
As defined by the SPE PRMS, Reserves are “… quantities of petroleum anticipated to be commercially recoverable by application of development projects to known accumulations from a given date forward under defined conditions.” Therefore, Reserves must be discovered (by drilling, recoverable (with current technology), remaining in the subsurface (at the effective date of the evaluation) and “commercial” based on the development project proposed.)
Note that Reserves are associated with development projects. To be considered as “commercial”, there must be a firm intention to proceed with the project in a reasonable time frame (typically 5 years, and such intention must be based upon all of the following criteria:)
- A reasonable assessment of the future economics of the development project meeting defined investment and operating criteria; - A reasonable expectation that there will be a market for all or at least the expected sales quantities of production required to justify development; - Evidence that the necessary production and transportation facilities are available or can be made available; and - Evidence that legal, contractual, environmental and other social and economic concerns will allow for the actual implementation of the recovery project being evaluated.
Contingent Resources and Prospective Resources are further defined as below:
- Contingent Resources: potentially recoverable volumes associated with a development plan that targets discovered volumes but is not (yet commercial (as defined above); and) - Prospective Resources: potentially recoverable volumes associated with a development plan that targets as yet undiscovered volumes.
In the industry lingo, we generally refer to Reserves as ‘P’ and Contingent Resources as ‘C’. These ‘P’ and ‘C’ resources can be further categorized into 1P/2P/3P resources and 1C/2C/3C resources, each referring to a low/medium/high estimate of the company’s potential recoverable oil volumes:
- Low/1C/1P estimate: there should be reasonable certainty that volumes actually recovered will equal or exceed the estimate; - Best/2C/2P estimate: there should be an equal likelihood of the actual volumes of petroleum being larger or smaller than the estimate; and - High/3C/3P estimate: there is a low probability that the estimate will be exceeded.
Hence in the E&P industry, it is easy to see why most investors and analysts refer to the 2P estimate as the best estimate for a company’s actual recoverable oil volumes. This is because 2P reserves (‘2P’ referring to ‘Proved and Probable’) are a middle estimate of the recoverable oil volumes legally recognized as “commercial”.
However, there’s nothing stopping you from including 2C resources (riskier) or utilizing 1P resources (conservative) as your estimate for total recoverable oil volumes, depending on your risk appetite. In this instance, the company has provided a snapshot of its 2P and 2C resources in its analyst presentation:
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Basically, what the company is saying here is that by 2021, it will have classified as 2P reserves at least 23.7 million bbl from its Anasuria field and 20.5 million bbl from its North Sabah field – for total 2P reserves of 44.2 million bbl (we are ignoring the Australian VIC cluster as it is only estimated to reach first oil by 2022).
Furthermore, the company is stating that they have discovered (but not yet legally classified as “commercial”) a further 71 million bbl of oil from both the Anasuria and North Sabah fields, as well as the Marigold/Sunflower fields. If we include these 2C resources, the total potential recoverable oil volumes could exceed 100 million bbl.
In this report, we shall explore all valuation scenarios giving consideration to both 2P and 2C resources.
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The company further targets a 2021 production rate of 20,000 bbl (LTM: 8,000 bbl), which includes 5,000 bbl from its Anasuria field (LTM: 2,500 bbl) and 7,000 bbl from its North Sabah field (LTM: 5,300 bbl).
This is a substantial increase in forecasted production from both existing and prospective oil fields. If it materializes, annual production rate could be as high as 7,300 mmbbl, and 2021 revenues (given FY20 USD/bbl of $60) could exceed RM 1.5 billion (FY20: RM 988 million).
However, this targeted forecast is quite a stretch from current production levels. Nevertheless, we shall consider all provided information in estimating a valuation for Hibiscus.
To understand Hibiscus’s oil production capacity and forecast its revenues and profits, we need to have a better appreciation of the performance of its two main cash-generating assets – the North Sabah field and the Anasuria field.

North Sabah oil field
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Hibiscus owns a 50% interest in the North Sabah field together with its partner Petronas, and has production rights over the field up to year 2040. The asset contains 4 oil fields, namely the St Joseph field, South Furious field, SF 30 field and Barton field.
For the sake of brevity, we shall not delve deep into the operational aspects of the fields or the contractual nature of its production sharing contract (PSC). We’ll just focus on the factors which relate to its financial performance. These are:
· Average uptime
· Total oil sold
· Average realized oil price
· Average OPEX per bbl
With regards to average uptime, we can see that the company maintains relative high facility availability, exceeding 90% uptime in all quarters of the LTM with exception of Jul-Sep 2019. The dip in average uptime was due to production enhancement projects and maintenance activities undertaken to improve the production capacity of the St Joseph and SF30 oil fields.
Hence, we can conclude that management has a good handle on operational performance. It also implies that there is little room for further improvement in production resulting from increased uptime.
As North Sabah is under a production sharing contract (PSC), there is a distinction between gross oil production and net oil production. The former relates to total oil drawn out of the ground, whereas the latter refers to Hibiscus’s share of oil production after taxes, royalties and expenses are accounted for. In this case, we want to pay attention to net oil production, not gross.
We can arrive at Hibiscus’s total oil sold for the last twelve months (LTM) by adding up the total oil sold for each of the last 4 quarters. Summing up the figures yields total oil sold for the LTM of approximately 2,075,305 bbl.
Then, we can arrive at an average realized oil price over the LTM by averaging the average realized oil price for the last 4 quarters, giving us an average realized oil price over the LTM of USD 68.57/bbl. We can do the same for average OPEX per bbl, giving us an average OPEX per bbl over the LTM of USD 13.23/bbl.
Thus, we can sum up the above financial performance of the North Sabah field with the following figures:
· Total oil sold: 2,075,305 bbl
· Average realized oil price: USD 68.57/bbl
· Average OPEX per bbl: USD 13.23/bbl

Anasuria oil field
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Doing the same exercise as above for the Anasuria field, we arrive at the following financial performance for the Anasuria field:
· Total oil sold: 1,073,304 bbl
· Average realized oil price: USD 63.57/bbl
· Average OPEX per bbl: USD 23.22/bbl
As gas production is relatively immaterial, and to be conservative, we shall only consider the crude oil production from the Anasuria field in forecasting revenues.

Valuation (Method 1)

Putting the figures from both oil fields together, we get the following data:
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Given that we have determined LTM EBITDA of RM 632m, the next step would be to subtract ITDA (interest, tax, depreciation & amortization) from it to obtain estimated LTM Net Profit. Using FY2020’s ITDA of approximately RM 318m as a guideline, we arrive at an estimated LTM Net Profit of RM 314m (FY20: 230m). Given the current market capitalization of RM 714.7m, this implies a trailing LTM PE of 2.3x.
Performing a sensitivity analysis given different oil prices, we arrive at the following net profit table for the company under different oil price scenarios, assuming oil production rate and ITDA remain constant:
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From the above exercise, it becomes apparent that Hibiscus has a breakeven oil price of about USD 41.8863/bbl, and has a lot of operating leverage given the exponential rate of increase in its Net Profit with each consequent increase in oil prices.
Considering that the oil production rate (EBITDA) is likely to increase faster than ITDA’s proportion to revenues (fixed costs), at an implied PE of 4.33x, it seems likely that an investment in Hibiscus will be profitable over the next 10 years (with the assumption that oil prices will revert to the mean in the long-term).

Valuation (Method 2)

Of course, there are a lot of assumptions behind the above method of valuation. Hence, it would be prudent to perform multiple methods of valuation and compare the figures to one another.
As opposed to the profit/loss assessment in Valuation (Method 1), another way of performing a valuation would be to estimate its balance sheet value, i.e. total revenues from 2P Reserves, and assign a reasonable margin to it.
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From the above, we understand that Hibiscus’s 2P reserves from the North Sabah and Anasuria fields alone are approximately 44.2 mmbbl (we ignore contribution from Australia’s VIC cluster as it hasn’t been developed yet).
Doing a similar sensitivity analysis of different oil prices as above, we arrive at the following estimated total revenues and accumulated net profit:
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Let’s assume that the above average of RM 9.68 billion in total realizable revenues from current 2P reserves holds true. If we assign a conservative Net Profit margin of 15% (FY20: 23%; past 5 years average: 16%), we arrive at estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion. Given the current market capitalization of RM 714 million, we might be able to say that the equity is worth about twice the current share price.
However, it is understandable that some readers might feel that the figures used in the above estimate (e.g. net profit margin of 15%) were randomly plucked from the sky. So how do we reconcile them with figures from the financial statements? Fortunately, there appears to be a way to do just that.
Intangible Assets
I refer you to a figure in the financial statements which provides a shortcut to the valuation of 2P Reserves. This is the carrying value of Intangible Assets on the Balance Sheet.
As of 2QFY21, that amount was RM 1,468,860,000 (i.e. RM 1.468 billion).
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Quite coincidentally, one might observe that this figure is dangerously close to the estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion we calculated earlier. But why would this amount matter at all?
To answer that, I refer you to the notes of the Annual Report FY20 (AR20). On page 148 of the AR20, we find the following two paragraphs:
E&E assets comprise of rights and concession and conventional studies. Following the acquisition of a concession right to explore a licensed area, the costs incurred such as geological and geophysical surveys, drilling, commercial appraisal costs and other directly attributable costs of exploration and appraisal including technical and administrative costs, are capitalised as conventional studies, presented as intangible assets.
E&E assets are assessed for impairment when facts and circumstances suggest that the carrying amount of an E&E asset may exceed its recoverable amount. The Group will allocate E&E assets to cash generating unit (“CGU”s or groups of CGUs for the purpose of assessing such assets for impairment. Each CGU or group of units to which an E&E asset is allocated will not be larger than an operating segment as disclosed in Note 39 to the financial statements.)
Hence, we can determine that firstly, the intangible asset value represents capitalized costs of acquisition of the oil fields, including technical exploration costs and costs of acquiring the relevant licenses. Secondly, an impairment review will be carried out when “the carrying amount of an E&E asset may exceed its recoverable amount”, with E&E assets being allocated to “cash generating units” (CGU) for the purposes of assessment.
On page 169 of the AR20, we find the following:
Carrying amounts of the Group’s intangible assets, oil and gas assets and FPSO are reviewed for possible impairment annually including any indicators of impairment. For the purpose of assessing impairment, assets are grouped at the lowest level CGUs for which there is a separately identifiable cash flow available. These CGUs are based on operating areas, represented by the 2011 North Sabah EOR PSC (“North Sabah”, the Anasuria Cluster, the Marigold and Sunflower fields, the VIC/P57 exploration permit (“VIC/P57”) and the VIC/L31 production license (“VIC/L31”).)
So apparently, the CGUs that have been assigned refer to the respective oil producing fields, two of which include the North Sabah field and the Anasuria field. In order to perform the impairment review, estimates of future cash flow will be made by management to assess the “recoverable amount” (as described above), subject to assumptions and an appropriate discount rate.
Hence, what we can gather up to now is that management will estimate future recoverable cash flows from a CGU (i.e. the North Sabah and Anasuria oil fields), compare that to their carrying value, and perform an impairment if their future recoverable cash flows are less than their carrying value. In other words, if estimated accumulated profits from the North Sabah and Anasuria oil fields are less than their carrying value, an impairment is required.
So where do we find the carrying values for the North Sabah and Anasuria oil fields? Further down on page 184 in the AR20, we see the following:
Included in rights and concession are the carrying amounts of producing field licenses in the Anasuria Cluster amounting to RM668,211,518 (2018: RM687,664,530, producing field licenses in North Sabah amounting to RM471,031,008 (2018: RM414,333,116))
Hence, we can determine that the carrying values for the North Sabah and Anasuria oil fields are RM 471m and RM 668m respectively. But where do we find the future recoverable cash flows of the fields as estimated by management, and what are the assumptions used in that calculation?
Fortunately, we find just that on page 185:
17 INTANGIBLE ASSETS (CONTINUED)
(a Anasuria Cluster)
The Directors have concluded that there is no impairment indicator for Anasuria Cluster during the current financial year. In the previous financial year, due to uncertainties in crude oil prices, the Group has assessed the recoverable amount of the intangible assets, oil and gas assets and FPSO relating to the Anasuria Cluster. The recoverable amount is determined using the FVLCTS model based on discounted cash flows (“DCF” derived from the expected cash in/outflow pattern over the production lives.)
The key assumptions used to determine the recoverable amount for the Anasuria Cluster were as follows:
(i Discount rate of 10%;)
(ii Future cost inflation factor of 2% per annum;)
(iii Oil price forecast based on the oil price forward curve from independent parties; and,)
(iv Oil production profile based on the assessment by independent oil and gas reserve experts.)
Based on the assessments performed, the Directors concluded that the recoverable amount calculated based on the valuation model is higher than the carrying amount.
(b North Sabah)
The acquisition of the North Sabah assets was completed in the previous financial year. Details of the acquisition are as disclosed in Note 15 to the financial statements.
The Directors have concluded that there is no impairment indicator for North Sabah during the current financial year.
Here, we can see that the recoverable amount of the Anasuria field was estimated based on a DCF of expected future cash flows over the production life of the asset. The key assumptions used by management all seem appropriate, including a discount rate of 10% and oil price and oil production estimates based on independent assessment. From there, management concludes that the recoverable amount of the Anasuria field is higher than its carrying amount (i.e. no impairment required). Likewise, for the North Sabah field.
How do we interpret this? Basically, what management is saying is that given a 10% discount rate and independent oil price and oil production estimates, the accumulated profits (i.e. recoverable amount) from both the North Sabah and the Anasuria fields exceed their carrying amounts of RM 471m and RM 668m respectively.
In other words, according to management’s own estimates, the carrying value of the Intangible Assets of RM 1.468 billion approximates the accumulated Net Profit recoverable from 2P reserves.
To conclude Valuation (Method 2), we arrive at the following:

Our estimates Management estimates
Accumulated Net Profit from 2P Reserves RM 1.452 billion RM 1.468 billion

Financials

By now, we have established the basic economics of Hibiscus’s business, including its revenues (i.e. oil production and oil price scenarios), costs (OPEX, ITDA), profitability (breakeven, future earnings potential) and balance sheet value (2P reserves, valuation). Moving on, we want to gain a deeper understanding of the 3 statements to anticipate any blind spots and risks. We’ll refer to the financial statements of both the FY20 annual report and the 2Q21 quarterly report in this analysis.
For the sake of brevity, I’ll only point out those line items which need extra attention, and skip over the rest. Feel free to go through the financial statements on your own to gain a better familiarity of the business.
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Income Statement
First, we’ll start with the Income Statement on page 135 of the AR20. Revenues are straightforward, as we’ve discussed above. Cost of Sales and Administrative Expenses fall under the jurisdiction of OPEX, which we’ve also seen earlier. Other Expenses are mostly made up of Depreciation & Amortization of RM 115m.
Finance Costs are where things start to get tricky. Why does a company which carries no debt have such huge amounts of finance costs? The reason can be found in Note 8, where it is revealed that the bulk of finance costs relate to the unwinding of discount of provision for decommissioning costs of RM 25m (Note 32).
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This actually refers to the expected future costs of restoring the Anasuria and North Sabah fields to their original condition once the oil reserves have been depleted. Accounting standards require the company to provide for these decommissioning costs as they are estimable and probable. The way the decommissioning costs are accounted for is the same as an amortized loan, where the initial carrying value is recognized as a liability and the discount rate applied is reversed each year as an expense on the Income Statement. However, these expenses are largely non-cash in nature and do not necessitate a cash outflow every year (FY20: RM 69m).
Unwinding of discount on non-current other payables of RM 12m relate to contractual payments to the North Sabah sellers. We will discuss it later.
Taxation is another tricky subject, and is even more significant than Finance Costs at RM 161m. In gist, Hibiscus is subject to the 38% PITA (Petroleum Income Tax Act) under Malaysian jurisdiction, and the 30% Petroleum tax + 10% Supplementary tax under UK jurisdiction. Of the RM 161m, RM 41m of it relates to deferred tax which originates from the difference between tax treatment and accounting treatment on capitalized assets (accelerated depreciation vs straight-line depreciation). Nonetheless, what you should take away from this is that the tax expense is a tangible expense and material to breakeven analysis.
Fortunately, tax is a variable expense, and should not materially impact the cash flow of Hibiscus in today’s low oil price environment.
Note: Cash outflows for Tax Paid in FY20 was RM 97m, substantially below the RM 161m tax expense.
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Balance Sheet
The balance sheet of Hibiscus is unexciting; I’ll just bring your attention to those line items which need additional scrutiny. I’ll use the figures in the latest 2Q21 quarterly report (2Q21) and refer to the notes in AR20 for clarity.
We’ve already discussed Intangible Assets in the section above, so I won’t dwell on it again.
Moving on, the company has Equipment of RM 582m, largely relating to O&G assets (e.g. the Anasuria FPSO vessel and CAPEX incurred on production enhancement projects). Restricted cash and bank balances represent contractual obligations for decommissioning costs of the Anasuria Cluster, and are inaccessible for use in operations.
Inventories are relatively low, despite Hibiscus being an E&P company, so forex fluctuations on carrying value of inventories are relatively immaterial. Trade receivables largely relate to entitlements from Petronas and BP (both oil supermajors), and are hence quite safe from impairment. Other receivables, deposits and prepayments are significant as they relate to security deposits placed with sellers of the oil fields acquired; these should be ignored for cash flow purposes.
Note: Total cash and bank balances do not include approximately RM 105 m proceeds from the North Sabah December 2019 offtake (which was received in January 2020)
Cash and bank balances of RM 90m do not include RM 105m of proceeds from offtake received in 3Q21 (Jan 2020). Hence, the actual cash and bank balances as of 2Q21 approximate RM 200m.
Liabilities are a little more interesting. First, I’ll draw your attention to the significant Deferred tax liabilities of RM 457m. These largely relate to the amortization of CAPEX (i.e. Equipment and capitalized E&E expenses), which is given an accelerated depreciation treatment for tax purposes.
The way this works is that the government gives Hibiscus a favorable tax treatment on capital expenditures incurred via an accelerated depreciation schedule, so that the taxable income is less than usual. However, this leads to the taxable depreciation being utilized quicker than accounting depreciation, hence the tax payable merely deferred to a later period – when the tax depreciation runs out but accounting depreciation remains. Given the capital intensive nature of the business, it is understandable why Deferred tax liabilities are so large.
We’ve discussed Provision for decommissioning costs under the Finance Costs section earlier. They are also quite significant at RM 266m.
Notably, the Other Payables and Accruals are a hefty RM 431m. What do they relate to? Basically, they are contractual obligations to the sellers of the oil fields which are only payable upon oil prices reaching certain thresholds. Hence, while they are current in nature, they will only become payable when oil prices recover to previous highs, and are hence not an immediate cash outflow concern given today’s low oil prices.
Cash Flow Statement
There is nothing in the cash flow statement which warrants concern.
Notably, the company generated OCF of approximately RM 500m in FY20 and RM 116m in 2Q21. It further incurred RM 330m and RM 234m of CAPEX in FY20 and 2Q21 respectively, largely owing to production enhancement projects to increase the production rate of the Anasuria and North Sabah fields, which according to management estimates are accretive to ROI.
Tax paid was RM 97m in FY20 and RM 61m in 2Q21 (tax expense: RM 161m and RM 62m respectively).

Risks

There are a few obvious and not-so-obvious risks that one should be aware of before investing in Hibiscus. We shall not consider operational risks (e.g. uptime, OPEX) as they are outside the jurisdiction of the equity analyst. Instead, we shall focus on the financial and strategic risks largely outside the control of management. The main ones are:
· Oil prices remaining subdued for long periods of time
· Fluctuation of exchange rates
· Customer concentration risk
· 2P Reserves being less than estimated
· Significant current and non-current liabilities
· Potential issuance of equity
Oil prices remaining subdued
Of topmost concern in the minds of most analysts is whether Hibiscus has the wherewithal to sustain itself through this period of low oil prices (sub-$30). A quick and dirty estimate of annual cash outflow (i.e. burn rate) assuming a $20 oil world and historical production rates is between RM 50m-70m per year, which considering the RM 200m cash balance implies about 3-4 years of sustainability before the company runs out of cash and has to rely on external assistance for financing.
Table 1: Hibiscus EBITDA at different oil price and exchange rates
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The above table shows different EBITDA scenarios (RM ‘m) given different oil prices (left column) and USD:MYR exchange rates (top row). Currently, oil prices are $27 and USD:MYR is 1:4.36.
Given conservative assumptions of average OPEX/bbl of $20 (current: $15), we can safely say that the company will be loss-making as long as oil remains at $20 or below (red). However, we can see that once oil prices hit $25, the company can tank the lower-end estimate of the annual burn rate of RM 50m (orange), while at RM $27 it can sufficiently muddle through the higher-end estimate of the annual burn rate of RM 70m (green).
Hence, we can assume that as long as the average oil price over the next 3-4 years remains above $25, Hibiscus should come out of this fine without the need for any external financing.
Customer Concentration Risk
With regards to customer concentration risk, there is not much the analyst or investor can do except to accept the risk. Fortunately, 80% of revenues can be attributed to two oil supermajors (Petronas and BP), hence the risk of default on contractual obligations and trade receivables seems to be quite diminished.
2P Reserves being less than estimated
2P Reserves being less than estimated is another risk that one should keep in mind. Fortunately, the current market cap is merely RM 714m – at half of estimated recoverable amounts of RM 1.468 billion – so there’s a decent margin of safety. In addition, there are other mitigating factors which shall be discussed in the next section (‘Opportunities’).
Significant non-current and current liabilities
The significant non-current and current liabilities have been addressed in the previous section. It has been determined that they pose no threat to immediate cash flow due to them being long-term in nature (e.g. decommissioning costs, deferred tax, etc). Hence, for the purpose of assessing going concern, their amounts should not be a cause for concern.
Potential issuance of equity
Finally, we come to the possibility of external financing being required in this low oil price environment. While the company should last 3-4 years on existing cash reserves, there is always the risk of other black swan events materializing (e.g. coronavirus) or simply oil prices remaining muted for longer than 4 years.
Furthermore, management has hinted that they wish to acquire new oil assets at presently depressed prices to increase daily production rate to a targeted 20,000 bbl by end-2021. They have room to acquire debt, but they may also wish to issue equity for this purpose. Hence, the possibility of dilution to existing shareholders cannot be entirely ruled out.
However, given management’s historical track record of prioritizing ROI and optimal capital allocation, and in consideration of the fact that the MD owns 10% of outstanding shares, there is some assurance that any potential acquisitions will be accretive to EPS and therefore valuations.

Opportunities

As with the existence of risk, the presence of material opportunities also looms over the company. Some of them are discussed below:
· Increased Daily Oil Production Rate
· Inclusion of 2C Resources
· Future oil prices exceeding $50 and effects from coronavirus dissipating
Increased Daily Oil Production Rate
The first and most obvious opportunity is the potential for increased production rate. We’ve seen in the last quarter (2Q21) that the North Sabah field increased its daily production rate by approximately 20% as a result of production enhancement projects (infill drilling), lowering OPEX/bbl as a result. To vastly oversimplify, infill drilling is the process of maximizing well density by drilling in the spaces between existing wells to improve oil production.
The same improvements are being undertaken at the Anasuria field via infill drilling, subsea debottlenecking, water injection and sidetracking of existing wells. Without boring you with industry jargon, this basically means future production rate is likely to improve going forward.
By how much can the oil production rate be improved by? Management estimates in their analyst presentation that enhancements in the Anasuria field will be able to yield 5,000 bbl/day by 2021 (current: 2,500 bbl/day).
Similarly, improvements in the North Sabah field is expected to yield 7,000 bbl/day by 2021 (current: 5,300 bbl/day).
This implies a total 2021 expected daily production rate from the two fields alone of 12,000 bbl/day (current: 8,000 bbl/day). That’s a 50% increase in yields which we haven’t factored into our valuation yet.
Furthermore, we haven’t considered any production from existing 2C resources (e.g. Marigold/Sunflower) or any potential acquisitions which may occur in the future. By management estimates, this can potentially increase production by another 8,000 bbl/day, bringing total production to 20,000 bbl/day.
While this seems like a stretch of the imagination, it pays to keep them in mind when forecasting future revenues and valuations.
Just to play around with the numbers, I’ve come up with a sensitivity analysis of possible annual EBITDA at different oil prices and daily oil production rates:
Table 2: Hibiscus EBITDA at different oil price and daily oil production rates
https://preview.redd.it/jnpfhr5n9br41.png?width=814&format=png&auto=webp&s=bbe4b512bc17f576d87529651140cc74cde3d159
The left column represents different oil prices while the top row represents different daily oil production rates.
The green column represents EBITDA at current daily production rate of 8,000 bbl/day; the orange column represents EBITDA at targeted daily production rate of 12,000 bbl/day; while the purple column represents EBITDA at maximum daily production rate of 20,000 bbl/day.
Even conservatively assuming increased estimated annual ITDA of RM 500m (FY20: RM 318m), and long-term average oil prices of $50 (FY20: $60), the estimated Net Profit and P/E ratio is potentially lucrative at daily oil production rates of 12,000 bbl/day and above.
2C Resources
Since we’re on the topic of improved daily oil production rate, it bears to pay in mind the relatively enormous potential from Hibiscus’s 2C Resources. North Sabah’s 2C Resources alone exceed 30 mmbbl; while those from the yet undiagnosed Marigold/Sunflower fields also reach 30 mmbbl. Altogether, 2C Resources exceed 70 mmbbl, which dwarfs the 44 mmbbl of 2P Reserves we have considered up to this point in our valuation estimates.
To refresh your memory, 2C Resources represents oil volumes which have been discovered but are not yet classified as “commercial”. This means that there is reasonable certainty of the oil being recoverable, as opposed to simply being in the very early stages of exploration. So, to be conservative, we will imagine that only 50% of 2C Resources are eligible for reclassification to 2P reserves, i.e. 35 mmbbl of oil.
https://preview.redd.it/mto11iz7abr41.png?width=375&format=png&auto=webp&s=e9028ab0816b3d3e25067447f2c70acd3ebfc41a
This additional 35 mmbbl of oil represents an 80% increase to existing 2P reserves. Assuming the daily oil production rate increases similarly by 80%, we will arrive at 14,400 bbl/day of oil production. According to Table 2 above, this would yield an EBITDA of roughly RM 630m assuming $50 oil.
Comparing that estimated EBITDA to FY20’s actual EBITDA:
FY20 FY21 (incl. 2C) Difference
Daily oil production (bbl/day) 8,626 14,400 +66%
Average oil price (USD/bbl) $68.57 $50 -27%
Average OPEX/bbl (USD) $16.64 $20 +20%
EBITDA (RM ‘m) 632 630 -
Hence, even conservatively assuming lower oil prices and higher OPEX/bbl (which should decrease in the presence of higher oil volumes) than last year, we get approximately the same EBITDA as FY20.
For the sake of completeness, let’s assume that Hibiscus issues twice the no. of existing shares over the next 10 years, effectively diluting shareholders by 50%. Even without accounting for the possibility of the acquisition of new oil fields, at the current market capitalization of RM 714m, the prospective P/E would be about 10x. Not too shabby.
Future oil prices exceeding $50 and effects from coronavirus dissipating
Hibiscus shares have recently been hit by a one-two punch from oil prices cratering from $60 to $30, as a result of both the Saudi-Russian dispute and depressed demand for oil due to coronavirus. This has massively increased supply and at the same time hugely depressed demand for oil (due to the globally coordinated lockdowns being implemented).
Given a long enough timeframe, I fully expect OPEC+ to come to an agreement and the economic effects from the coronavirus to dissipate, allowing oil prices to rebound. As we equity investors are aware, oil prices are cyclical and are bound to recover over the next 10 years.
When it does, valuations of O&G stocks (including Hibiscus’s) are likely to improve as investors overshoot expectations and begin to forecast higher oil prices into perpetuity, as they always tend to do in good times. When that time arrives, Hibiscus’s valuations are likely to become overoptimistic as all O&G stocks tend to do during oil upcycles, resulting in valuations far exceeding reasonable estimates of future earnings. If you can hold the shares up until then, it’s likely you will make much more on your investment than what we’ve been estimating.

Conclusion

Wrapping up what we’ve discussed so far, we can conclude that Hibiscus’s market capitalization of RM 714m far undershoots reasonable estimates of fair value even under conservative assumptions of recoverable oil volumes and long-term average oil prices. As a value investor, I hesitate to assign a target share price, but it’s safe to say that this stock is worth at least RM 1.00 (current: RM 0.45). Risk is relatively contained and the upside far exceeds the downside. While I have no opinion on the short-term trajectory of oil prices, I can safely recommend this stock as a long-term Buy based on fundamental research.
submitted by investorinvestor to SecurityAnalysis [link] [comments]

[educational] Technical analysis, patterns, and charts analysis for the day trader

[educational] Technical analysis, patterns, and charts analysis for the day trader
Chart patterns form a key part of day trading. Candlestick and other charts produce frequent signals that cut through price action “noise”.
The best patterns will be those that can form the backbone of a profitable day trading strategy, whether trading stocks, cryptocurrency of forex pairs.
Every day you have to choose between hundreds of trading opportunities. This is a result of a wide range of factors influencing the market. Day trading patterns enable you to decipher the multitude of options and motivations – from hope of gain and fear of loss, to short-covering, stop-loss triggers, hedging, tax consequences and plenty more.
Candlestick patterns help by painting a clear picture, and flagging up trading signals and signs of future price movements. Whilst it’s said you’ll need to use technical analysis to succeed day trading with candlestick and other patterns, it’s important to note utilizing them to your advantage is more of an art form than a rigid science.
You have to learn the power of chart patterns and the theory that governs them in order to identify the best patterns to supplement your trading style and strategies.

Use In Day Trading

Used correctly trading patterns can add a powerful tool to your arsenal. This is because history has a habit of repeating itself and the financial markets are no exception. This repetition can help you identify opportunities and anticipate potential pitfalls.
RSI, volume, plus support and resistance levels all aide your technical analysis when you’re trading. But crypto chart patterns play a crucial role in identifying breakouts and trend reversals. Mastering the art of reading these patterns will help you make smarter trades and bolster your profits, as highlighted in the highly regarded, ‘stock patterns for day trading’, by Barry Rudd.

Breakouts & Reversals

In the patterns and charts below you’ll see two recurring themes, breakouts and reversals.
  • Breakout – A breakout is simply when the price clears a specified critical level on your chart. This level could by any number of things, from a Fibonacci level, to support, resistance or trend lines.
  • Reversal – A reversal is simply a change in direction of a price trend. That change could be either positive or negative against the prevailing trend. You may also hear it called a ‘rally’, ‘correction’, or ‘trend reversal’.

Candlestick Charts

Candlestick charts are a technical tool at your disposal. They consolidate data within given time frames into single bars. Not only are the patterns relatively straightforward to interpret, but trading with candle patterns can help you attain that competitive edge over the rest of the market.
They first originated in the 18th century where they were used by Japanese rice traders. Since Steve Nison introduced them to the West with his 1991 book ‘Japanese Candlestick Charting Techniques’, their popularity has surged.
Below is a break down of three of the most popular candlestick patterns used for day trading.

Shooting Star Candlestick

This is often one of the first you see when you open a chart with candlestick patterns. This bearish reversal candlestick suggests a peak. It is precisely the opposite of a hammer candle. It won’t form until at least three subsequent green candles have materialized. This will indicate an increase in price and demand. Usually, buyers lose their cool and clamber for the price to increasing highs before they realize they’ve overpaid.
The upper shadow is usually twice the size of the body. This tells you the last frantic buyers have entered trading just as those that have turned a profit have off-loaded their positions. Short-sellers then usually force the price down to the close of the candle either near or below the open. This traps the late arrivals who pushed the price high. Panic often kicks in at this point as those late arrivals swiftly exit their positions.

https://preview.redd.it/gf5dwjhbrdh31.png?width=300&format=png&auto=webp&s=437ff856bfd6ebc95da34528462ba224d964f01f

Doji Candlestick

One of the most popular candlestick patterns for trading forex is the doji candlestick (doji signifies indecision). This reversal pattern is either bearish or bullish depending on the previous candles. It will have nearly, or the same open and closing price with long shadows. It may look like a cross, but it can have an extremely small body. You will often get an indicator as to which way the reversal will head from the previous candles.
If you see previous candles are bullish, you can anticipate the next one near the underneath of the body low will trigger a short/sell signal when the doji lows break. You’ll then see trail stops above the doji highs.
Alternatively, if the previous candles are bearish then the doji will probably form a bullish reversal. Above the candlestick high, long triggers usually form with a trail stop directly under the doji low.
These candlestick patterns could be used for intraday trading with forex, stocks, cryptocurrencies and any number of other assets. But using candlestick patterns for trading interpretations requires experience, so practice on a demo account before you put real money on the line.

https://preview.redd.it/4yo650lcrdh31.png?width=300&format=png&auto=webp&s=b2aa3cdeef23e44e1e3e3047bbe2604fce0a4768

Hammer Candlestick

This is a bullish reversal candlestick. You can use this candlestick to establish capitulation bottoms. These are then normally followed by a price bump, allowing you to enter a long position.
The hammer candlestick forms at the end of a downtrend and suggests a near-term price bottom. The lower shadow is made by a new low in the downtrend pattern that then closes back near the open. The tail (lower shadow), must be a minimum of twice the size of the actual body.
The tails are those that stopped out as shorts started to cover their positions and those looking for a bargain decided to feast. Volume can also help hammer home the candle. To be certain it is a hammer candle, check where the next candle closes. It must close above the hammer candle low.
Trading with Japanese candlestick patterns has become increasingly popular in recent decades, as a result of the easy to glean and detailed information they provide. This makes them ideal for charts for beginners to get familiar with.

https://preview.redd.it/7snzz8qdrdh31.png?width=300&format=png&auto=webp&s=f83ff82f0980dd30c33bc6886ae7e7ed3a98b72f

More Popular Day Trading Patterns

Using Price Action

Many strategies using simple price action patterns are mistakenly thought to be too basic to yield significant profits. Yet price action strategies are often straightforward to employ and effective, making them ideal for both beginners and experienced traders.
Put simply, price action is how the price is likely to respond at certain levels of resistance or support. Using price action patterns from pdfs and charts will help you identify both swings and trendlines.
Whether you’re day trading stocks or forex or crypto with price patterns, these easy to follow strategies can be applied across the board.

Zone Strategy

So, how do you start day trading with short-term price patterns? you will likely employ a ‘zone strategy’. One obvious bonus to this system is it creates straightforward charts, free from complex indicators and distractions.

https://preview.redd.it/7e5x37zerdh31.png?width=300&format=png&auto=webp&s=2098a4c9df4a4556c3024cec1c176ce50c9806c0

Dead Zone

This empty zone tells you that the price action isn’t headed anywhere. There is no clear up or down trend, the market is at a standoff. If you want big profits, avoid the dead zone completely. No indicator will help you makes thousands of pips here.

The Red Zone

This is where things start to get a little interesting. Once you’re in the red zone the end goal is in sight, and that one hundred pip winner within reach. For example, if the price hits the red zone and continues to the upside, you might want to make a buy trade. It could be giving you higher highs and an indication that it will become an uptrend.
This will be likely when the sellers take hold. If the price hits the red zone and continues to the downside, a sell trade may be on the cards. You’d have new lower lows and a suggestion that it will become a downtrend.

The End Zone

This is where the magic happens. With this strategy, you want to consistently get from the red zone to the end zone. Draw rectangles on your charts like the ones found in the example. Then only trade the zones. If you draw the red zones anywhere from 10-20 pips wide, you’ll have room for the price action to do its usual retracement before heading to the downside or upside.

Outside Bar At Resistance Or Support

You’ll see a bullish outside bar if today’s low exceeded yesterdays, but the stock still rallies and closes above yesterday’s high. If the complete opposite price action took place, you’d have yourself the perfect bearish example.
Unfortunately, it isn’t as straightforward as identifying an outside candlestick and then just placing a trade. It’s prudent to find an outside day after a major break of a trend.

https://preview.redd.it/egb0lp6grdh31.png?width=300&format=png&auto=webp&s=b0170eceea5006464e5832bc3a9083c72ee677ad

Spring At Support

The spring is when the stock tests the low of a range, but then swiftly comes back into trading zone and sets off a new trend. One common mistake traders make is waiting for the last swing low to be reached. However, as you’ve probably realized already, trading setups don’t usually meet your precise requirements so don’t stress about a few pennies.

https://preview.redd.it/q82lap2hrdh31.png?width=300&format=png&auto=webp&s=9e40f0bc25c2df06a1d93edb68b293c858a32592

Little To No Price Retracement

Put simply, less retracement is proof the primary trend is robust and probably going to continue. Forget about coughing up on the numerous Fibonacci retracement levels. The main thing to remember is that you want the retracement to be less than 38.2%. This means even when today’s asset tests the previous swing, you’ll have a greater chance that the breakout will either hold or continue towards the direction of the primary trend.

https://preview.redd.it/ey997b2irdh31.png?width=300&format=png&auto=webp&s=c938aac51e3b3bbf1f45a11c46f4ae3dfd1b6dd4
Trading with price patterns to hand enables you to try any of these strategies. Find the one that fits in with your individual trading style. Remember, you’ll often find the best trading chart patterns aren’t overly complex, instead they paint a clear picture using minimal indicators, reducing the likelihood of mistakes and distraction.

Consider Time Frames

When you start trading with your short term price patterns pdf to hand, it’s essential you also consider time frames in your calculations. In your market, you’ll find a number of time frames simultaneously co-existing. This means you can find conflicting trends within the particular asset your trading. Your stock could be in a primary downtrend whilst also being in an intermediate short-term uptrend.
Many traders make the mistake of focusing on a specific time frame and ignoring the underlying influential primary trend. Usually, the longer the time frame the more reliable the signals. When you reduce your time frames you’ll be distracted by false moves and noise.
Many traders download examples of short-term price patterns but overlook the underlying primary trend, do not make this mistake. You should trade-off 15-minute charts, but utilize 60-minute charts to define the primary trend and 5-minute charts to establish the short-term trend.

Wrapping Up

Our understanding of chart patterns has come along way since the initial 1932 work of Richard Schabacker in ‘Technical Analysis and Stock Market Profits’. Schabacker asserted then, ‘any general stock chart is a combination of countless different patterns and its accurate analysis depends upon constant study, long experience and knowledge of all the fine points, both technical and fundamental…’ So whilst there is an abundance of patterns out there, remember accurate analysis and sustained practice is required to fully reap their benefits.

The source : https://www.daytrading.com/patterns
submitted by JalelTounsi to ethfinance [link] [comments]

WolfpackBOT - The world's fastest and most secure trading bot

WolfpackBOT - The world's fastest and most secure trading bot

https://preview.redd.it/b2ffej55zfd21.png?width=768&format=png&auto=webp&s=196c912c5d4250be54d647648613545f74faec7d

INTRODUCTION

According to wikipedia, Blockchain is originally known as bloc chain, It is a growing list of records known as blocks which is linked using cryptography, each of these blocks contain a cryptographic hash of the initial block, a transaction data and a time stamp.
Since its emergence in the year 2008, when Nakamoto satoshi discovered and introduced bitcoin, there has been serious efforts to integrate the blockchain technology into several aspects of various process of global business , The blockchain technology has been described as having the potential to disrupt many industries with immutability, low-cost transaction, and enhanced maximum security. So many other blockchain implementations have been deployed and developed with unique features designed to specific use-cases.
The blockchain technology has made possible to issue assets through a distributed ledger framework. With cryptocurrency tokens, Assets can be given economic value in order to validate and initiate transactional processes.

ADVANTAGES OF BLOCKCHAIN:

  1. Decentralised payment processing,
  2. Creating an immutable system of recording,
  3. Reducing Cost of Transaction and
  4. Enhanced Security.
  5. Now that we have reminded ourselves of what blockchain technology is, let’s look into the subject matter.

ABOUT WolfpackBOT

WolfpackBOT is a highly advanced cryptocurrency trading software that allows for the execution of trades at lightning speed using proprietary trading algorithms, proprietary “Werewolf” Trading Analysis configurations, or user customized settings based on personal trading style. WolfpackBOT also allows for simultaneous trading access to all compatible cryptocurrency exchanges that are available to the bot, and all trading pairs with the WerewolfBOT subscription package.
WolfpackBOT is introducing an industry first, a beautiful automated cryptocurrency trading console: The WolfBOX. This efficient and sleek piece of hardware will conveniently allow for the full utilization of a bot subscription without the need for a VPS or dedicated computer. The WolfBOX will also include a built-in secure Hardware Wallet and RFID card reader to optimize ease-of-use and functionality.
WolfpackBOT trading software is enabled with limit, market, and “Wolf Trade” orders on all trading candles, including one-minute candles, with the widest array of technical trading indicators available on the market. WolfpackBOT's proprietary “Wolf Trade” orders provide superior market sell orders with a bite! WolfpackBOT is the only trading bot to feature live price scanning on your positions and also handles partial fills with ease, meaning you don’t miss out on orders. WolfpackBOT is incredibly fast and can fulfill up to 10,000 trades per day depending on market conditions and subscription package.
WolfpackBOT allows simultaneous trading access to all cryptocurrency exchanges that are available to the bot, and all trading pairs through the WerewolfBOT subscription plan. Not only do inferior bots allow limited access to one exchange and one trading pair per bot, they also store your API keys remotely on servers which are potentially susceptible to hacks and pump and dump attacks. User security and API key protection holds a high priority within the WolfpackBOT framework which is why it is the only trading bot that gives users full control with local management of their API keys.
Masternode and Proof of Work X11 Blockchain
Wolfcoin Blockchain with X11 Proof of Work Mining and Masternode Reward Systems The Wolfcoin blockchain and network are both designed and engineered to ensure store of value, transactional speed and security, and fungibility. The main goal of the Wolfcoin blockchain is to facilitate fast and secure transactions with a governance that helps sustain the network for the benefit of all users. The Wolfcoin blockchain is a two-tier network comprised of a Proof of Work (PoW) consensus mechanism powered by miners and a Proof of Service (PoSe) system powered by masternodes.
The Wolfcoin blockchain is secured through Proof of Work (PoW) in which miners attempt to solve difficult problems with specialized computers. When a problem is solved, the miner receives the right to add a new block to the blockchain. If the problem was solved correctly, the miner is rewarded once the block is added.
The second tier, which is powered by masternodes, enables Wolfcoin to facilitate private and instant transactions with Private Send and Instant Send. Masternodes are also rewarded when miners discover new blocks.
The block reward is distributed with 80% going to the masternodes and 20% going to miners. The masternode system is referred to as Proof of Service (PoSe), since the masternodes provide crucial services that support the features of the network.
Masternodes also oversee the network and have the power to reject improperly formed blocks from miners. If a miner tried to take the entire block reward for themselves, the masternode network would orphan the block ensuring that it would not be added to the blockchain.
In short, miners power the first tier, which is the basic sending and receiving of funds and prevention of double spending. Masternodes power the second tier, which provide the added features that make Wolfcoin different from other cryptocurrencies. Masternodes do not mine, and mining computers cannot serve as masternodes.
Additionally, each masternode is “secured” by 10,000 WOLF. Those WOLF remain under the sole control of their owner at all times. The funds are not locked in any way; however, if enough of the funds are moved or spent to cause the user’s holdings to drop below 10,000 Wolfcoin, the associated masternode will go offline and stop receiving rewards.
By pre-ordering your WolfpackBOT subscription, you will also receive Wolfcoin as a reward that can be utilized in the following ways:
  • Redeemable for WolfpackBOT subscriptions
  • Redeemable for the WolfBOX Console
  • Redeemable for WolfpackBOT and Wolfcoin apparel and merchandise
  • Fungible utility that can be exchanged for like value on exchanges
When you hold at least 10,000 Wolfcoin in your Wolfcoin wallet connected to a static IP address, you will become a masternode, meaning you will have a chance to receive 80 percent of the block reward every sixty seconds.

THE FEATURES

WolfpackBOT Automated Trading Software:

After the crowdsale, Wolfcoin will be the exclusive method of payment for WolfpackBOT Automated Trading Software subscriptions.

Multiple Technical Analysis Indicators:

WolfpackBOT offers the widest array of multiple Technical Analysis indicators, oscillators, configurations and settings available in the world of Automated Cryptocurrency Trading Bots. WolfpackBOT provides Bollinger Bands, Double EMA, Elliot Wave, EMA, EMA Cross, Fibonacci Sequence, KAMA, MA Cross, MACD, RSI, SMA, Stochastic, Stochastic RSI, Triple EMA, and many more!

Shorting Features:

WolfpackBOT includes Cryptocurrency Shorting Features that allow users to short their positions and buy them back at the lower price to maximize their returns.

Copyrighted Crash Protection:

Crash Protection, one of WolfpackBOT's most advanced features, enables users the option to automatically scan and convert all positions to a stable coin at the sign of our proprietary Hidden Bear Divergence Indicator, and then buy back into base currency to resume trading at the sign of our proprietary Hidden Bull Divergence Indicator.

Language Translator:

WolfpackBOT has a built in Language Translator that instantly translates the entire BOT into Dutch, English, French, German, or Spanish.

All Trading Pairs on all available Exchanges:

WolfpackBOT allows our customers to simultaneously trade on multiple cryptocurrency exchanges, and with all the exchange’s trading pairs available for trading. The best part is that it’s all possible on one bot with one subscription to the WerewolfBOT package!

Coin Selector:

While other automated trading platforms only allow for a limited amount of coins per subscription, WolfpackBOT allows all trading pairs and all coins to be traded on all the available major exchanges with the WerewolfBOT subscription. WolfpackBOT's proprietary Coin Selector allows for users to choose whether to trade all cryptocurrencies or blacklist some, thus not trading them at all, as well as search for the highest volume, greatest performing, or a specific volatility range of coins for a given timeframe.

Werewolf Configurations and Settings:

Werewolf Configurations and Settings are copyrighted trading algorithms that use proprietary optimum settings for trading: the perfect configuration for experienced and inexperienced traders alike. These settings can be adjusted to the current market trend, with preset configurations for bear, sideways, and bull markets.

Werewolf Ultimate:

Werewolf Ultimate is the ultimate choice when trading. It doesn't trade a particular trading pair or particular coins, it trades them all. It goes in for the kill to increase the potential returns. Crash Protection is a built-in feature in Werewolf Ultimate.

Werewolf Bull Market:

Werewolf Bull Market are preset settings and configurations that are usable when your Base Trading Pair is in a Bull Run. Werewolf Bull Market settings are optimized for such conditions and should only be used in a Bull Run Market.

Werewolf Sideways Market:

Werewolf Sideways Market are preset settings and configurations that are usable when your Base Trading Pair is trading sideways. Werewolf Sideways Market settings are optimized for such conditions and should only be used in a Sideways Trading Market.

Werewolf Bear Market:

Werewolf Bear Market are preset settings and configurations that are usable when your Base Trading Pair is in a Bear Run. Werewolf Bear Market settings are optimized for such conditions and should only be used in a Bear Run Market.

The WolfBOX Hardware Console:

WolfpackBOT also offers an industry first: a beautiful hardware console, The WolfBOX. Our console comes preloaded with WolfpackBOT Automated Trading Software and also includes a built-in secure hardware wallet. Some of the key features of the WolfBOX include our high-speed CPU, solid-state hard drive, built-in RFID card reader, and integrated Bitpay and Coinbase wallets.

Wolfpack Consulting

Our company offers its services and expertise as Cryptocurrency and Blockchain Specialists to individuals and companies. We offer consulting services in the fields of blockchain and cryptocurrency development and management.

Wolfpack Philanthropy

We are dedicated to the proposition that we have a responsibility to use a portion of our company’s revenue to help create a better world and a brighter future. As we move forward, our philanthropic efforts include environmental stewardship, renewable energy, human rights, economic development, as well as animal and wildlife rescue and conservation with an emphasis on dogs and wolves.

Wolfcoin Information

THE WOLFCOIN Wolfcoin is the coin that fuels all WolfpackBOT's projects.
This utility, coupled with the reward systems with mining and Masternoding capabilities, makes the use of Wolfcoin potentially appealing to all WolfpackBOT users whom are interested in receiving additional Wolfcoin for subscriptions, merchandise and other rewards such as passive cryptocurrency portfolio growth.
THE WOLFCOIN WALLET WolfpackBOT uses our proprietary Wolfcoin Core QT wallet.
February 2018 Conceptual development of WolfpackBOT Software
May 2018 Company Roadmap development Alpha models of WolfpackBOT Software
June 2018 Ongoing research, development, and testing
October 2018 Advertising and Marketing Campaign Starts Wallets available for payment; BTC, BTG, DASH, DOGE, ETC, ETH, LTC October 15 - Pre-registration begins
November 2018 November 1 - Crowdsale Stage I begins
December 2018 Official presentation of WolfpackBOT beta Software Preview Creation of Wolfcoin (WOLF: 300,000,000 coins pre-mined on Genesis Block) WolfpackBOT beta Software release to selected customers
December 21 - Launch network and mine Genesis block
December 22 - PoW / Mainnet
December 23 - Blockchain and network testing
December 28 - Iquidis Wolfcoin Block Explorer released on our website
January 2019 January 1 - Wolfcoin Core wallets available for download on the website January 1 - Wallet and Masternode Tutorial available January 1 - Masternode and PoW instructional videos available January 1 - Subscription Pre-order Coin Rewards disbursed Announcement listing WOLF on top-10 Exchange
February 2019 February 1 - Crowdsale Stage I Ends February 1 - Crowdsale Stage II Begins
March 2019 March 15 - Crowdsale Stage II Ends March 15 - Crowdsale Stage III Begins WolfpackBOT Software roll-out to contributors WolfBOX Console available for Pre-order
April 2019 WolfpackBOT Subscriptions available for customers First Major version released: automated, manual, and paper trading WolfpackBOT Live support center April 30 - Crowdsale Stage III Ends
May 2019 WolfBOX Consoles Pre-orders first shipment
June 2019 New trading features such as new exchanges, strategy options and indicators
July 2019 New trading features such as new exchanges, strategy options or indicators
August 2019 WolfpackBOT Software Trading Platform V2.0 Second major release: Strategy Marketplace and Back-testing
September 2019 New trading features such as new exchanges, strategy options or indicators
October 2019 WolfpackBOT Software Trading Platform V3.0 Third major release: Signals Marketplace (Supporting 3rd Party App Signals) Mobile Application for WolfpackBOT Software and Trading Platform
November 2019 New trading features such as new exchanges, strategy options or indicator
December 2019 WolfpackBOT Software Trading Platform V4.0
January 2020 WolfpackBOT Software Trading Platform V5.0 Fourth major release: Machine Learning Strategy Optimization

THE AMAZING TEAM

Philip Longhurst Chief Executive Officer The leader of our pack and the man behind the WolfpackBOT trading bot, Philip Longhurst is a mathematical genius, engineer, day trader, and animal rescuer. As an account manager for J.P. Morgan and MBNA Bank, Phil managed the accounts of several high-profile clients and businesses. He has been successfully trading stocks for over twenty-five years and has successfully applied his trading expertise and mathematical acumen to the cryptocurrency market since 2013.
Philip holds bachelor's degrees in mechanical engineering and business administration and is a loving husband, father, and family man who has been rescuing dogs since 1995. His driving desire is to use the success of Wolfpack Group to create a brighter future for humanity. He currently resides in the United States of America with his wife, daughter, and dogs.
Rogier Pointl Chief Financial Officer Rogier Pointl is a successful entrepreneur with nearly twenty-five years of experience in business management, marketing, financial administration, economics, and fintech. Rogier holds bachelor's degrees in Business Communications and Financial Administration. He is a pioneer in the field of virtual reality, having served as CEO and owner of Simworld, the first virtual reality racing center in Europe, where he oversaw the development of advanced simulator and virtual reality hardware and software.
Rogier is an experienced trader and has been trading stocks since 2007. He began applying his expertise to the cryptocurrency market in 2010, gaining experience as a Bitcoin miner along the way. Rogier is a loving husband and father and currently resides in the Netherlands with his wife and two daughters.
Jason Cormier Chief Technical Officer Jason Cormier is a humble -but extraordinary- individual who is blessed with a Mensa IQ of 151, he is continually driven by a desire for knowledge and self-growth. He is self-taught in Visual Basics, C#, C++, HTML, and CSS and began developing programs and applications at the age of 14, including the TCB Wallet, which was the first ever wallet program that held its users' log in names and passwords. Jason is a cryptocurrency guru whose expertise includes cryptocurrency mining farms, proof-of-stake, masternodes, and cryptocurrency trading.
Jason holds Associate degrees in Computer Science and Psychology, and currently resides in the United States of America with his wife and son.
Jay McKinney Chief Web Development and Design Officer Jay is a veteran of the Iraq War who put his life on the line in combat to protect our freedoms. To center himself while stationed in the Iraqi warzone, he taught himself C# as he knew honing his Web Development skills would help him provide a better future for himself and his family. Upon returning home safely, he worked his way through college and holds bachelor's degrees in Computer Programming and Web Development & Design.
Jay has worked for the Kentucky Housing Corporation, serving as a software engineer and web developer. He is a loving family man who currently resides in the United States of America with his wife and two children.
David Johnson Chief Software Development Officer David holds a Master of Science degree in Information Systems and a Bachelor's degree in Business Administration with a specialization in Information Systems, graduating with Magna Cum Laude status. He has worked for the Kentucky Housing Corporation, serving as a network analyst and software engineer. As an entrepreneur, he has owned his own web and software development company since 2009, creating and maintaining several websites in C# and PHP, and has been operating the crypto-oriented YouTube channel BigBits since 2017, where he discusses automated Cryptocurrency trading strategies.
David is a proud father of two and resides in the United States of America with his wife and children. Like any good Kentuckian, he is a huge fan of the University of Kentucky's college sports teams.
Gabriel Condrea Software and Web Development Officer Gabriel Condrea holds a bachelor's degree in electrical and computer engineering and has worked as a software developer and senior systems engineer in both the United States and the United Kingdom, working with a variety of programming languages and IDEs. He has used his expertise to create Manufacturing and SCADA systems in industrial applications.
Gabriel also applies his engineering skills to cryptocurrency day trading, seeking to automate the process. He loves to travel and currently resides in the United States with his girlfriend.
Igor Otorepec Chief Hardware Development Officer Igor is an engineer with twenty years of experience specializing in advanced PLC programming and industrial robotics. He is also an IT security expert and a CEC Certified Ethical Cracker who uses his skills to expose and patch security vulnerabilities in blockchain codes.
Igor is an advanced cryptocurrency trader and Kung Fu master who uses bio-hacking as a way of life to keep his 'chi' constantly centered. He currently resides in Austria with his loving wife.
Manik Ehhsan Director of Marketing and Public Relations Manik holds a Bachelor's degree in Computer Science and has over five years of experience in Web Development, Digital Marketing and Graphics Design. He has also managed the marketing for more than 30 successful Cryptocurrency start-ups and projects, and specializes in SEO and ASO. Manik is also a Cryptocurrency project promotion expert with an emphasis on Masternodes and building Social Media Communities.
Manik has focused his life on Cryptocurrency and currently resides in Bangladesh with his loving family.
Rance Garrison Chief Marketing Officer Rance Garrison holds a bachelor's degree in Business Administration and specialized in Seminary Studies for his Master's degree. He served as an AmeriCorps VISTA at WMMT-FM, the radio station owned by Appalshop, an arts and education center in Kentucky, and has also specialized in local cable television advertising. Rance is also a musician who has released several albums independently over the last decade.
Rance is very dedicated to his local community and is most excited by the potential implications of cryptocurrencies and blockchain technology for rural and remote economies. He currently resides in the United States of America with his wife, dog, and cats.
Paul Gabens Chief Public Relations Officer A master negotiator with a penchant for strategy, Paul Gabens brings more than twenty years of marketing and promotional experience in the automotive, hospitality, and entertainment industries to the Wolfpack. He is also an avid stock and cryptocurrency trader, having first entered into the cryptocurrency market two years ago, embracing his passion for crypto with the same vigor as his love for travel, classic cars, extreme roller coasters, and surfing.
Paul holds degrees in business management, marketing, and automotive aftermarket. He currently resides in the United States with his fiancé and two cats.
Blake Stanley Marketing and Social Media Officer Blake Stanley is a cryptocurrency enthusiast who also has over six years of experience managing both government and private sector client and customer relations. A strategic thinker and expert in the field of social media-based advertising, Blake also owns and manages his own online marketing company where he has been successfully curating and implementing online marketing and advertising strategies for his clients for the past three years.
Blake is a proud father and family man and currently lives in the United States with his daughter and fiancé.
Martin Kilgore Market and Trading Analyst Martin Kilgore holds bachelor’s degrees in both accounting and mathematics, having researched Knot Theory and the Jones Polynomial during his undergraduate studies, giving him a firm edge when analyzing market conditions. He has worked as a staff accountant for several governmental organizations.
Martin lives in the United States with his fiancé.
Jonathan McDonald Chief Trading Strategy Officer Jonathan has honed his trading skills over the past five years by studying and implementing economics, financial strategy, Forex trading analysis and trading bots. Through his constant learning, he discovered Cryptocurrency after seeing the difference in market volatility and high yield trading. His fine-tuned trading strategies complement Crypto markets perfectly, and he has been implementing trading strategies to the Cryptocurrency market for over a year with phenomenal results. Jonathan is constantly improving his trading skills with an emphasis on scalping techniques. He has applied his trading skillset to the WolfpackBOT and enjoys working alongside the Wolfpack in creating the fastest trading bot on the market.
Jonathan currently resides in Canada with his supportive girlfriend and family.
Web site: https://www.wolfpackbot.com/
Technical document: https://www.wolfpackbot.com/Pdf/whitepaper_en.pdf
Bounty0x username: idrixoxo
submitted by idrixoxo2015 to u/idrixoxo2015 [link] [comments]

WolfpackBOT - The world's fastest and most secure trading bot

WolfpackBOT - The world's fastest and most secure trading bot

https://preview.redd.it/n7wutgsuzfd21.png?width=800&format=png&auto=webp&s=d0dac7147b8e70584305f997732a248d6b088ff9

INTRODUCTION

Cryptocurrency is essentially digital money traded from one person to another through the use of pseudonyms. There are no intermediaries like banks, no governmental oversight or authority, and no fees. The “crypto” in cryptocurrency refers to the use of cryptography to ensure the security and privacy of every transaction.
New coins are created through a technique called mining. The process requires powerful computers that solve complex math problems. Each problem should take about 10 minutes to solve, and results in the creation of a predetermined number of coins. The total number of coins that can be created is fixed — there’s a limit of 21 million bitcoins that can be created. The number of coins rewarded for solving each problem dwindles as time goes on.
Bitcoin is believed to have been created in 2009 by Satoshi Nakamoto, an enigmatic figure who has so far proven all but impossible to definitively identify. By using cryptography to control the creation and tracking of a digital currency, Nakamoto took that power away from central authorities like governments.
Bitcoin was the first and most famous digital currency, but you can choose from more than 1,500, including ether, litecoin and even cryptokitties. For awhile, you saw these currencies only in the darkest corners of the internet, where people used them for all sorts of questionable, even illegal, activities. Drug dealers liked them because they made transactions all but invisible, and trolls at the Kremlin-backed Internet Research Agency used bitcoin to finance their campaign to influence the 2016 election.
That started to change in 2014, when Overstock became the first major US retailer to accept bitcoin. Companies like Expedia and Microsoft followed suit.
One of the biggest misconceptions about cryptocurrencies is that you need thousands of dollars to invest. It’s an easy assumption to make, especially in the case of bitcoin, which stayed under $1,000 from about 2010 to 2017. But then it took off, surpassing thousand-dollar milestones at a pace that seemed quicker than you could refresh your phone.
The staggering value is off-putting to many. But unlike most stocks, you can buy a fraction of a bitcoin so you don’t need thousands to get into the crypto game.

OVERVIEW OF WolfpackBOT

WolfpackBOT is a highly advanced cryptocurrency trading software that allows for the execution of trades at lightning speed using proprietary trading algorithms, proprietary “Werewolf” Trading Analysis configurations, or user customized settings based on personal trading style. WolfpackBOT also allows for simultaneous trading access to all compatible cryptocurrency exchanges that are available to the bot, and all trading pairs with the WerewolfBOT subscription package.
WolfpackBOT is introducing an industry first, a beautiful automated cryptocurrency trading console: The WolfBOX. This efficient and sleek piece of hardware will conveniently allow for the full utilization of a bot subscription without the need for a VPS or dedicated computer. The WolfBOX will also include a built-in secure Hardware Wallet and RFID card reader to optimize ease-of-use and functionality.
WolfpackBOT trading software is enabled with limit, market, and “Wolf Trade” orders on all trading candles, including one-minute candles, with the widest array of technical trading indicators available on the market. WolfpackBOT's proprietary “Wolf Trade” orders provide superior market sell orders with a bite! WolfpackBOT is the only trading bot to feature live price scanning on your positions and also handles partial fills with ease, meaning you don’t miss out on orders. WolfpackBOT is incredibly fast and can fulfill up to 10,000 trades per day depending on market conditions and subscription package.
WolfpackBOT allows simultaneous trading access to all cryptocurrency exchanges that are available to the bot, and all trading pairs through the WerewolfBOT subscription plan. Not only do inferior bots allow limited access to one exchange and one trading pair per bot, they also store your API keys remotely on servers which are potentially susceptible to hacks and pump and dump attacks. User security and API key protection holds a high priority within the WolfpackBOT framework which is why it is the only trading bot that gives users full control with local management of their API keys.
Masternode and Proof of Work X11 Blockchain
Wolfcoin Blockchain with X11 Proof of Work Mining and Masternode Reward Systems The Wolfcoin blockchain and network are both designed and engineered to ensure store of value, transactional speed and security, and fungibility. The main goal of the Wolfcoin blockchain is to facilitate fast and secure transactions with a governance that helps sustain the network for the benefit of all users. The Wolfcoin blockchain is a two-tier network comprised of a Proof of Work (PoW) consensus mechanism powered by miners and a Proof of Service (PoSe) system powered by masternodes.
The Wolfcoin blockchain is secured through Proof of Work (PoW) in which miners attempt to solve difficult problems with specialized computers. When a problem is solved, the miner receives the right to add a new block to the blockchain. If the problem was solved correctly, the miner is rewarded once the block is added.
The second tier, which is powered by masternodes, enables Wolfcoin to facilitate private and instant transactions with Private Send and Instant Send. Masternodes are also rewarded when miners discover new blocks.
The block reward is distributed with 80% going to the masternodes and 20% going to miners. The masternode system is referred to as Proof of Service (PoSe), since the masternodes provide crucial services that support the features of the network.
Masternodes also oversee the network and have the power to reject improperly formed blocks from miners. If a miner tried to take the entire block reward for themselves, the masternode network would orphan the block ensuring that it would not be added to the blockchain.
In short, miners power the first tier, which is the basic sending and receiving of funds and prevention of double spending. Masternodes power the second tier, which provide the added features that make Wolfcoin different from other cryptocurrencies. Masternodes do not mine, and mining computers cannot serve as masternodes.
Additionally, each masternode is “secured” by 10,000 WOLF. Those WOLF remain under the sole control of their owner at all times. The funds are not locked in any way; however, if enough of the funds are moved or spent to cause the user’s holdings to drop below 10,000 Wolfcoin, the associated masternode will go offline and stop receiving rewards.
By pre-ordering your WolfpackBOT subscription, you will also receive Wolfcoin as a reward that can be utilized in the following ways:
  • Redeemable for WolfpackBOT subscriptions
  • Redeemable for the WolfBOX Console
  • Redeemable for WolfpackBOT and Wolfcoin apparel and merchandise
  • Fungible utility that can be exchanged for like value on exchanges
When you hold at least 10,000 Wolfcoin in your Wolfcoin wallet connected to a static IP address, you will become a masternode, meaning you will have a chance to receive 80 percent of the block reward every sixty seconds.

THE FEATURES

WolfpackBOT Automated Trading Software:

After the crowdsale, Wolfcoin will be the exclusive method of payment for WolfpackBOT Automated Trading Software subscriptions.

Multiple Technical Analysis Indicators:

WolfpackBOT offers the widest array of multiple Technical Analysis indicators, oscillators, configurations and settings available in the world of Automated Cryptocurrency Trading Bots. WolfpackBOT provides Bollinger Bands, Double EMA, Elliot Wave, EMA, EMA Cross, Fibonacci Sequence, KAMA, MA Cross, MACD, RSI, SMA, Stochastic, Stochastic RSI, Triple EMA, and many more!

Shorting Features:

WolfpackBOT includes Cryptocurrency Shorting Features that allow users to short their positions and buy them back at the lower price to maximize their returns.

Copyrighted Crash Protection:

Crash Protection, one of WolfpackBOT's most advanced features, enables users the option to automatically scan and convert all positions to a stable coin at the sign of our proprietary Hidden Bear Divergence Indicator, and then buy back into base currency to resume trading at the sign of our proprietary Hidden Bull Divergence Indicator.

Language Translator:

WolfpackBOT has a built in Language Translator that instantly translates the entire BOT into Dutch, English, French, German, or Spanish.

All Trading Pairs on all available Exchanges:

WolfpackBOT allows our customers to simultaneously trade on multiple cryptocurrency exchanges, and with all the exchange’s trading pairs available for trading. The best part is that it’s all possible on one bot with one subscription to the WerewolfBOT package!

Coin Selector:

While other automated trading platforms only allow for a limited amount of coins per subscription, WolfpackBOT allows all trading pairs and all coins to be traded on all the available major exchanges with the WerewolfBOT subscription. WolfpackBOT's proprietary Coin Selector allows for users to choose whether to trade all cryptocurrencies or blacklist some, thus not trading them at all, as well as search for the highest volume, greatest performing, or a specific volatility range of coins for a given timeframe.

Werewolf Configurations and Settings:

Werewolf Configurations and Settings are copyrighted trading algorithms that use proprietary optimum settings for trading: the perfect configuration for experienced and inexperienced traders alike. These settings can be adjusted to the current market trend, with preset configurations for bear, sideways, and bull markets.

Werewolf Ultimate:

Werewolf Ultimate is the ultimate choice when trading. It doesn't trade a particular trading pair or particular coins, it trades them all. It goes in for the kill to increase the potential returns. Crash Protection is a built-in feature in Werewolf Ultimate.

Werewolf Bull Market:

Werewolf Bull Market are preset settings and configurations that are usable when your Base Trading Pair is in a Bull Run. Werewolf Bull Market settings are optimized for such conditions and should only be used in a Bull Run Market.

Werewolf Sideways Market:

Werewolf Sideways Market are preset settings and configurations that are usable when your Base Trading Pair is trading sideways. Werewolf Sideways Market settings are optimized for such conditions and should only be used in a Sideways Trading Market.

Werewolf Bear Market:

Werewolf Bear Market are preset settings and configurations that are usable when your Base Trading Pair is in a Bear Run. Werewolf Bear Market settings are optimized for such conditions and should only be used in a Bear Run Market.

The WolfBOX Hardware Console:

WolfpackBOT also offers an industry first: a beautiful hardware console, The WolfBOX. Our console comes preloaded with WolfpackBOT Automated Trading Software and also includes a built-in secure hardware wallet. Some of the key features of the WolfBOX include our high-speed CPU, solid-state hard drive, built-in RFID card reader, and integrated Bitpay and Coinbase wallets.

Wolfpack Consulting

Our company offers its services and expertise as Cryptocurrency and Blockchain Specialists to individuals and companies. We offer consulting services in the fields of blockchain and cryptocurrency development and management.

Wolfpack Philanthropy

We are dedicated to the proposition that we have a responsibility to use a portion of our company’s revenue to help create a better world and a brighter future. As we move forward, our philanthropic efforts include environmental stewardship, renewable energy, human rights, economic development, as well as animal and wildlife rescue and conservation with an emphasis on dogs and wolves.

Wolfcoin Information

THE WOLFCOIN Wolfcoin is the coin that fuels all WolfpackBOT's projects.
This utility, coupled with the reward systems with mining and Masternoding capabilities, makes the use of Wolfcoin potentially appealing to all WolfpackBOT users whom are interested in receiving additional Wolfcoin for subscriptions, merchandise and other rewards such as passive cryptocurrency portfolio growth.
THE WOLFCOIN WALLET WolfpackBOT uses our proprietary Wolfcoin Core QT wallet.
February 2018 Conceptual development of WolfpackBOT Software
May 2018 Company Roadmap development Alpha models of WolfpackBOT Software
June 2018 Ongoing research, development, and testing
October 2018 Advertising and Marketing Campaign Starts Wallets available for payment; BTC, BTG, DASH, DOGE, ETC, ETH, LTC October 15 - Pre-registration begins
November 2018 November 1 - Crowdsale Stage I begins
December 2018 Official presentation of WolfpackBOT beta Software Preview Creation of Wolfcoin (WOLF: 300,000,000 coins pre-mined on Genesis Block) WolfpackBOT beta Software release to selected customers
December 21 - Launch network and mine Genesis block
December 22 - PoW / Mainnet
December 23 - Blockchain and network testing
December 28 - Iquidis Wolfcoin Block Explorer released on our website
January 2019 January 1 - Wolfcoin Core wallets available for download on the website January 1 - Wallet and Masternode Tutorial available January 1 - Masternode and PoW instructional videos available January 1 - Subscription Pre-order Coin Rewards disbursed Announcement listing WOLF on top-10 Exchange
February 2019 February 1 - Crowdsale Stage I Ends February 1 - Crowdsale Stage II Begins
March 2019 March 15 - Crowdsale Stage II Ends March 15 - Crowdsale Stage III Begins WolfpackBOT Software roll-out to contributors WolfBOX Console available for Pre-order
April 2019 WolfpackBOT Subscriptions available for customers First Major version released: automated, manual, and paper trading WolfpackBOT Live support center April 30 - Crowdsale Stage III Ends
May 2019 WolfBOX Consoles Pre-orders first shipment
June 2019 New trading features such as new exchanges, strategy options and indicators
July 2019 New trading features such as new exchanges, strategy options or indicators
August 2019 WolfpackBOT Software Trading Platform V2.0 Second major release: Strategy Marketplace and Back-testing
September 2019 New trading features such as new exchanges, strategy options or indicators
October 2019 WolfpackBOT Software Trading Platform V3.0 Third major release: Signals Marketplace (Supporting 3rd Party App Signals) Mobile Application for WolfpackBOT Software and Trading Platform
November 2019 New trading features such as new exchanges, strategy options or indicator
December 2019 WolfpackBOT Software Trading Platform V4.0
January 2020 WolfpackBOT Software Trading Platform V5.0 Fourth major release: Machine Learning Strategy Optimization

THE AMAZING TEAM

Philip Longhurst Chief Executive Officer The leader of our pack and the man behind the WolfpackBOT trading bot, Philip Longhurst is a mathematical genius, engineer, day trader, and animal rescuer. As an account manager for J.P. Morgan and MBNA Bank, Phil managed the accounts of several high-profile clients and businesses. He has been successfully trading stocks for over twenty-five years and has successfully applied his trading expertise and mathematical acumen to the cryptocurrency market since 2013.
Philip holds bachelor's degrees in mechanical engineering and business administration and is a loving husband, father, and family man who has been rescuing dogs since 1995. His driving desire is to use the success of Wolfpack Group to create a brighter future for humanity. He currently resides in the United States of America with his wife, daughter, and dogs.
Rogier Pointl Chief Financial Officer Rogier Pointl is a successful entrepreneur with nearly twenty-five years of experience in business management, marketing, financial administration, economics, and fintech. Rogier holds bachelor's degrees in Business Communications and Financial Administration. He is a pioneer in the field of virtual reality, having served as CEO and owner of Simworld, the first virtual reality racing center in Europe, where he oversaw the development of advanced simulator and virtual reality hardware and software.
Rogier is an experienced trader and has been trading stocks since 2007. He began applying his expertise to the cryptocurrency market in 2010, gaining experience as a Bitcoin miner along the way. Rogier is a loving husband and father and currently resides in the Netherlands with his wife and two daughters.
Jason Cormier Chief Technical Officer Jason Cormier is a humble -but extraordinary- individual who is blessed with a Mensa IQ of 151, he is continually driven by a desire for knowledge and self-growth. He is self-taught in Visual Basics, C#, C++, HTML, and CSS and began developing programs and applications at the age of 14, including the TCB Wallet, which was the first ever wallet program that held its users' log in names and passwords. Jason is a cryptocurrency guru whose expertise includes cryptocurrency mining farms, proof-of-stake, masternodes, and cryptocurrency trading.
Jason holds Associate degrees in Computer Science and Psychology, and currently resides in the United States of America with his wife and son.
Jay McKinney Chief Web Development and Design Officer Jay is a veteran of the Iraq War who put his life on the line in combat to protect our freedoms. To center himself while stationed in the Iraqi warzone, he taught himself C# as he knew honing his Web Development skills would help him provide a better future for himself and his family. Upon returning home safely, he worked his way through college and holds bachelor's degrees in Computer Programming and Web Development & Design.
Jay has worked for the Kentucky Housing Corporation, serving as a software engineer and web developer. He is a loving family man who currently resides in the United States of America with his wife and two children.
David Johnson Chief Software Development Officer David holds a Master of Science degree in Information Systems and a Bachelor's degree in Business Administration with a specialization in Information Systems, graduating with Magna Cum Laude status. He has worked for the Kentucky Housing Corporation, serving as a network analyst and software engineer. As an entrepreneur, he has owned his own web and software development company since 2009, creating and maintaining several websites in C# and PHP, and has been operating the crypto-oriented YouTube channel BigBits since 2017, where he discusses automated Cryptocurrency trading strategies.
David is a proud father of two and resides in the United States of America with his wife and children. Like any good Kentuckian, he is a huge fan of the University of Kentucky's college sports teams.
Gabriel Condrea Software and Web Development Officer Gabriel Condrea holds a bachelor's degree in electrical and computer engineering and has worked as a software developer and senior systems engineer in both the United States and the United Kingdom, working with a variety of programming languages and IDEs. He has used his expertise to create Manufacturing and SCADA systems in industrial applications.
Gabriel also applies his engineering skills to cryptocurrency day trading, seeking to automate the process. He loves to travel and currently resides in the United States with his girlfriend.
Igor Otorepec Chief Hardware Development Officer Igor is an engineer with twenty years of experience specializing in advanced PLC programming and industrial robotics. He is also an IT security expert and a CEC Certified Ethical Cracker who uses his skills to expose and patch security vulnerabilities in blockchain codes.
Igor is an advanced cryptocurrency trader and Kung Fu master who uses bio-hacking as a way of life to keep his 'chi' constantly centered. He currently resides in Austria with his loving wife.
Manik Ehhsan Director of Marketing and Public Relations Manik holds a Bachelor's degree in Computer Science and has over five years of experience in Web Development, Digital Marketing and Graphics Design. He has also managed the marketing for more than 30 successful Cryptocurrency start-ups and projects, and specializes in SEO and ASO. Manik is also a Cryptocurrency project promotion expert with an emphasis on Masternodes and building Social Media Communities.
Manik has focused his life on Cryptocurrency and currently resides in Bangladesh with his loving family.
Rance Garrison Chief Marketing Officer Rance Garrison holds a bachelor's degree in Business Administration and specialized in Seminary Studies for his Master's degree. He served as an AmeriCorps VISTA at WMMT-FM, the radio station owned by Appalshop, an arts and education center in Kentucky, and has also specialized in local cable television advertising. Rance is also a musician who has released several albums independently over the last decade.
Rance is very dedicated to his local community and is most excited by the potential implications of cryptocurrencies and blockchain technology for rural and remote economies. He currently resides in the United States of America with his wife, dog, and cats.
Paul Gabens Chief Public Relations Officer A master negotiator with a penchant for strategy, Paul Gabens brings more than twenty years of marketing and promotional experience in the automotive, hospitality, and entertainment industries to the Wolfpack. He is also an avid stock and cryptocurrency trader, having first entered into the cryptocurrency market two years ago, embracing his passion for crypto with the same vigor as his love for travel, classic cars, extreme roller coasters, and surfing.
Paul holds degrees in business management, marketing, and automotive aftermarket. He currently resides in the United States with his fiancé and two cats.
Blake Stanley Marketing and Social Media Officer Blake Stanley is a cryptocurrency enthusiast who also has over six years of experience managing both government and private sector client and customer relations. A strategic thinker and expert in the field of social media-based advertising, Blake also owns and manages his own online marketing company where he has been successfully curating and implementing online marketing and advertising strategies for his clients for the past three years.
Blake is a proud father and family man and currently lives in the United States with his daughter and fiancé.
Martin Kilgore Market and Trading Analyst Martin Kilgore holds bachelor’s degrees in both accounting and mathematics, having researched Knot Theory and the Jones Polynomial during his undergraduate studies, giving him a firm edge when analyzing market conditions. He has worked as a staff accountant for several governmental organizations.
Martin lives in the United States with his fiancé.
Jonathan McDonald Chief Trading Strategy Officer Jonathan has honed his trading skills over the past five years by studying and implementing economics, financial strategy, Forex trading analysis and trading bots. Through his constant learning, he discovered Cryptocurrency after seeing the difference in market volatility and high yield trading. His fine-tuned trading strategies complement Crypto markets perfectly, and he has been implementing trading strategies to the Cryptocurrency market for over a year with phenomenal results. Jonathan is constantly improving his trading skills with an emphasis on scalping techniques. He has applied his trading skillset to the WolfpackBOT and enjoys working alongside the Wolfpack in creating the fastest trading bot on the market.
Jonathan currently resides in Canada with his supportive girlfriend and family.
Web site: https://www.wolfpackbot.com/
Technical document: https://www.wolfpackbot.com/Pdf/whitepaper_en.pdf
Bounty0x username: idrixoxo
submitted by idrixoxo2015 to u/idrixoxo2015 [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

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How to analyse Forex trading charts - Technical Analysis ...

A brief technical analysis tutorial (introduction for beginners). This video covers all the basics when it comes to learning about technical analysis Hi I'm ... This video shows how simple it is to analyse a Forex chart, with a USDJPY example we execute a top down analysis using strictly tools and price action. This ... Checkout MyFxBook to learn how we trade 👇🏼👇🏼👇🏼👇🏼👇🏼👇🏼👇🏼👇🏼 https://www.myfxbook.com/members/Tumelo0073/fx-goat/3562881 ... This guide is aimed at beginners who would like to know how to use Technical analysis in MetaTrader 4. Metatrader 4 is one of the most popular trading platfo... NEW COURSE: https://chartguys.com/courses/entries-exits/ Introduction to Technical Analysis for Beginners Technical Analysis Basics Technical Analysis for Be... Secrets of the best technical traders revealed! I'm going to share with you give things profitable traders do when it comes to technical analysis trading. Su... Published on 27 Sep 2018 Muuqaalkaan waxa uu la socdaa midkii isaga ka horeeyay waxa uuna sharaxaad toos ah iyo hoga-tusaalayn kaa siinayaa sidii aad ku fahm... Discover the truth about Technical Analysis — when to use it, when NOT to use it, and how it really works. Here’s the deal: Technical Analysis is not what yo... In part 2 of our Forex beginner course, we talk about technical analysis and chart analysis. I introduce the most important concepts of technical analysis. ... HOW I DO TECHNICAL ANALYSIS WHEN TRADING **LIVE FOREX** What Broker Do I recommend? https://bit.ly/2QCWYTD Disclaimer Our content is intended to be used and ...

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