100%-300% Annualized Returns Level 1
Over 4000% Annualized Returns Level 3!

The Square

 Quantitative Analysis of Financial Price Structure

By C. N. Plapcianu


NOTE: See Below for the New Non-Beta Excel Results for BOTH Algorithms!


Statistical Performance

Hyperbolic 1 Indicator (Beta Version)


The following section will detail the statistical results produced by the Hyperbolic 1 indicator across a collection of markets and timeframes. We selected a somewhat scattered basket of markets and varied range of time frames to illustrate a wide sampling of performance statistics. The results listed below were derived from the Atomic Trading indicator available on Bloomberg Financial. This indicator has been available on Bloomberg for the past 2 years in varying form, as it has been upgraded over time to produce better results.

The graphic interface shown below displays a full range of selectable trading statistics (not all visible here) available for any market on any time frame that the user would like to backtest or trade. This toolset is available as a stand-alone application through our website, without requiring a Bloomberg subscription to access and use it. We are current developing further software partnerships to deliver this App through different interfaces, such as Market Analyst, allowing different functions to be integrated with our technology, such as automated trading, or further programming capability.

The algorithm presented in this course will produce better results than those displayed below, as some improvements have been made while reprogramming it as a standalone App. It now produces higher returns than the older version available through Bloomberg, tough the statistics below still provide an excellent example of the general functionality and output results produced by Hyperbolic 1 as programmed in our proprietary application. Hyperbolic 1-3 and Circular 1-3 will all be available through the same App.


Statistical Results - Hyperbolic 1 (Beta Version)

Across 15 Markets with Varied Time Frames

6 Equities, 3 Indexes, 3 Currencies, 2 Commodities


       These statistical results are calculated from a NON-LEVERAGED account!

       Each backtest is based upon a starting account value of 100k, trading the full amount, non-leveraged, on each trade, and adding the profit/loss after each trade for the following trade!

       The total number of trades does not always match the sum of winning and losing trades because consecutive trades in the same direction are considered one trade, while in the total trades they are counted separately!


Apple Computer (AAPL) US Equity

15 Minute Scale 2 Month Backtest

Statistical Summary

Average Monthly Return 10.2%

Return as Backtested 20.4%

Annualized Return 122.4%

Bank of America (BAC) US Equity

30 Minute Scale 3 Month Backtest

Statistical Summary

Average Monthly Return: 6.1%
Return as Backtested 18.3%

Annualized Return 73.2%


Dry Ships (DRYS) US Equity

120 Minute Scale 5 Month Backtest

Statistical Summary

Average Monthly Return: 10.1%

Return as Backtested 50.5%

Annualized Return 121.2%


Facebook (FB) US Equity

Daily Scale 23 Month Backtest

Statistical Summary

Average Monthly Return: 9.2%

Return as Backtested 20.4%

Annualized Return 122.4%


Google (GOOG) US Equity

15 Minute Scale 2 Month Backtest

Statistical Summary

Average Monthly Return: 16.2%

Return as Backtested 20.4%

Annualized Return 122.4%

Twitter (TWTR) US Equity

Daily Scale 6 Month Backtest

Statistical Summary

Average Monthly Return: 9.6%

Return as Backtested 20.4%

Annualized Return 122.4%


Italian National Stock Exchange (FTSE MIB) Index

15 Minute Scale 2 Month Backtest

Statistical Summary

Average Monthly Return: 10.7%

Return as Backtested 20.4%

Annualized Return 122.4%


CBOE Volatility Index (VIX) Index

30 Minute Scale 3 Month Backtest

Statistical Summary

Average Monthly Return: 16.2%

Return as Backtested 20.4%

Annualized Return 122.4%


Wheat (W A) Commodity

30 Minute Scale 3 Month Backtest

Statistical Summary

Average Monthly Return: 9.8%

Return as Backtested 20.4%

Annualized Return 122.4%


Excel (non-beta) Results!
Hyperbolic 1 Indicator

Excel Version (Not Beta)

Statistical Results

Following are some of the first test statistics run using an Excel version of the Hyperbolic 1, the first presentation of non-beta results from the new version of the Hyperbolic 1 indicator. This first testing was done only on daily and hourly time frames, but the first results, particular for these higher time frames are excellent!

As expected the Hyperbolic produces about an average of 4-5% per month UNLEVERAGED return! What's interesting is that on the same data set in the same time frame, the Circular 1 and Hyperbolic 1 seem to produce about the same returns. However, the BIG difference is that the Hyperbolic 1 produces the SAME return with only about 1/3 the number of trades! So it saves significantly on the amount of trading effort and commission costs. However, with further testing, this might not be the case in all markets and time frames.

Here are the results of the first 5 tests on some popular stocks using only 1 hour or daily time frames:

GE US Daily 1 Month - 11.8% Unleveraged

Leverage 3 - 36%

Leverage 5 - 61%

Leverage 10 - 127%

IBM US 60MIN 3 Months - 11.2% Unleveraged

Leverage 3 - 36.2%

Leverage 5 - 65%

Leverage 10 - 156%

CAT US 60 MIN 3 Weeks - 3.1% Unleveraged

Leverage 3 - 9.4%

Leverage 5 - 15.5%

Leverage 10 - 31%

BAC US 30 MIN 2 Weeks - 1.8% Unleveraged

Leverage 3 - 5.4%

Leverage 5 - 9 %

Leverage 10 - 18%

MSFT US Daily 3 Months - 5%

Leverage 3 - 15.7%

Leverage 5 - 26%

Leverage 10 - 53%

These are almost exactly the results we were expecting, and as you can see, these are normal blue chip stocks, traded in larger scale time frames, so very realistic results. As we've mentioned, with the next level versions of these same tools, we expect the percentage returns to increase exponentially, so Level 2 will produce results double this, and level 3 double Level 2, perhaps even more, but better to be conservative in our expectations. The value of the Circular will also become greater as it advances into the higher levels. Anyway, this gives some first numbers from the (non-beta) Hyperbolic 1.


Excel (non-beta) Results!
Circular 1 Indicator
Excel Version

Statistical Results


The team has also run some first performance tests using an Excel based non-beta Circular 1 indicator. Here they randomly picked the following markets as testers, so these are not cherry-picked results looking for the very best performance.

Also, they have added a new feature to the indicator applications called Risk/Reward (RR) which allows the user to predetermine and set his risk parameters according to his comfort level. What this does is allow the user to dynamically set the stop loss level according to the desired risk exposure. So if one were expecting a 10 point move, he could set a 10% RR and have a 1 point stop. Choosing higher risk/reward values shows that the profits increase, but this is something that the user can play with himself.

So the following statistics show the RR level (i.e. 20% = 1/5) and the total returns for that period first, at the top UNLEVERAGED. Then there are a few iterations listed below using increasing leverage on the same trades.

AAPL DAILY - 1 Yr - RR 20% = 60%

AAPL leverage 3 - 180%

AAPL leverage 5 - 269%

AAPL leverage 10 - 658%

BAC 30MIN - 1.5 Months - RR 20% = 4%

BAC leverage 3 - 12%

BAC leverage 5 - 21%

BAC leverage 10 - 42%

MSFT DAILY - 4 MONTHS - RR 40% = 11%

MSFT leverage 3 - 29%

MSFT leverage 5 - 49%

MSFT leverage 10 - 101%

CAT US 60MIN - 3 MONTHS - RR 40% = 15%

CAT leverage 3 - 42%

CAT leverage 5 - 72%

CAT leverage 10 - 160%

GE DAILY - 6 Months - RR20% = 10%

GE leverage 3 - 30%

GE leverage 5 - 51%

GE leverage 10 - 103%

IBM 60MIN - 1 MONTH - RR20% = 6%

IBM leverage 3 - 21%

IBM leverage 5 - 36%

IBM leverage 10 - 77%

As you can see, the totally unleveraged returns automatedly produced by this indicator equal, at worst, the best performance of most professional managers. Add a little leverage in, and it quickly multiplies far beyond that. And these systems can be diversified across multiple markets, and multiple time frames, so that they can be allocated to large scale investments and trading with 1000's of different options.

These are the first results we've seen from the programmed Circular, since this is the first time it's been automated. At this level Plapcianu thinks that the Hyperbolic 1 will potentially outperform this indicator by 2 to 2.5 times. But the Circular will become more important at higher levels when it can be used for VERY specific and exact forecast trading of a different type than just an automated system as shown here. Still it can be seen that these results are quite good!


Hyperbolic 1 (Beta Version)

Leveraged Returns Study


As mentioned earlier, this course is intended to be accessible to the general public, so we would like to review what may be obvious to professional traders and fund managers, but is not so well understood by less experienced traders or investors. One of the most valuable elements of a highly efficient trading algorithm is the potential to allow for higher leveraging of the trading account, thereby producing greater percentage returns from the base capital.

For these initial Level 1 indicators, we generally do NOT recommend using excessively high leveraging, though we will leave this determination to the level of experience and knowledge of the trader. But we must forewarn all readers to leverage only AT YOUR OWN RISK, as we will not be held responsible for errors in judgement in this regard.

As this series progresses, the Hyperbolic and Circular indicators on Level 2 and Level 3 will become more precise and efficient, allowing more highly leveraged positions to be safely taken with these more advanced indicators. However, even with the Level 1 indicators, in many cases leveraging 2x will work fine without significantly increasing risk, while producing double the returns. And in some cases, even higher leverage can be relatively safely used, according to the statistical results provided by the backtesting.

The following analysis and study of these variations is provided to help traders better understand the results of using different degrees of leverage when trading the Hyperbolic 1 algorithm.

The primary factors required to determine the viability and degree of leveraging are the number of consecutive losses, or Loss Run, and the Maximum % Drawdown variables shown in the far right columns of the statistical table on Page 102. As will be seen below, the smaller the Maximum % Drawdown, the higher the leverage possible, and the larger the % Drawdown, the less desirable it is to leverage the system. With this in mind, it is prudent to backtest longer data sets in order to determine probable drawdowns over extended periods.

We will give examples of three of cases below, the first showing a small maximum % drawdown (0.84%) in the USDJPY, then a mid-range drawdown (3.99%) with Google, and an extremely high drawdown (25.64%) in Facebook. It will be seen with the Facebook example that leveraging the account above 2x wiped out the entire account, exactly the situation we most want to avoid.

The table shows a sample of 5 markets from Appendix 1, along with the results of trading them for the defined backtest period using a 2x, 5x, and 10x leverage factor. We will illustrate the 3 cases mentioned above just to show the potential positive and negative results which can occur using these various levels of leverage with the Hyperbolic 1 algorithm. A final point is that there are other ways to take advantage of leverage besides using a margin account, such as using various options strategies which can serve to leverage returns while limiting risk to pre-defined levels.

JPYUSD Leverage Study Chart 1 2x Leverage = 14.6%

JPYUSD Leverage Study Chart 2 5x Leverage = 39.4%

JPYUSD Leverage Study Chart 3 10x Leverage = 89%

Google Leverage Study Chart 1 2x Leverage = 73.3%

Google Leverage Study Chart 2 5x Leverage = 264.4%



Google Leverage Study Chart 3 10x Leverage = 944.6%

Facebook Leverage Study Chart 1 2x Leverage = 538.3%


Facebook Leverage Study Chart 2 5x Leverage = -$57,326 LOSS

This example shows how using leverage can be HIGHLY RISKY!

The 23.75% drawdown caused the total loss of -$57,326 beneath the initial account value!


Facebook Leverage Study Chart 3 10x Leverage = -$648,826 LOSS!

This example shows how using leverage can be HIGHLY RISKY!

The 23.75% drawdown caused the total loss of -$648,826 beneath the initial account value!



 DISCLAIMER: The Institute of Cosmological Economics & Sacred Science Institute are economic research and educational companies. The information contained herein is for general education purposes and is not intended as specific advice or recommendations to any person or entity. Any reference to a transaction, trade, position, holding, security, market, or level is purely meant to educate readers about possible risks and opportunities in the marketplace and are not meant to imply that any person or entity should take any action whatsoever without first evaluating such action(s) in light of their own situation either on their own or through a professional advisor. The methods presented are not solicitations of any order to buy or sell. If a person or entity does not believe they are qualified to make such decisions, they should seek professional advice. The prices listed are for reference only and are in no way intended to represent an actual trade, entry price or exit price conducted by the Institute of Cosmological Economics, portfolios managed by any entity affiliated with the Institute of Cosmological Economics, or any principal or employee of the Institute of Cosmological Economics, or any of its affiliates. This information is not a substitute for professional advice of any nature, including tax, legal, and financial. While we believe the information contained herein to be accurate, all numbers should be verified by the reader through independent sources. It should not be assumed that the methods, techniques, or indicators presented in these products will be profitable or that they will not result in losses. There is no assurance that the strategies and methods presented in this book will be successful for you. Past results are not necessarily indicative of future performance. Trading securities, options, futures, or any other security involves risk and can result in the immediate and substantial loss of the capital invested. The author, publisher, distributors and all affiliates assume no responsibility for your trading or investment results, and will not be liable for any loss, damage or liability directly or indirectly caused by the usage of this material. There is considerable risk of loss in Futures, Stock and Options trading. You should only use risk capital in all such endeavors. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. Every reader/recipient is responsible for his or her own investment decisions. The information contained in this report or in any update does not necessarily mean that the Institute of Cosmological Economics, or any portfolio managed by any affiliates of the Institute of Cosmological Economics, or that any employees of the Institute of Cosmological Economics, or its affiliates holds the positions or has conducted the actual trade. At various times the Institute of Cosmological Economics, portfolios managed by affiliates of the Institute of Cosmological Economics, or any other principal or employee of the Institute of Cosmological Economics may own, buy or sell the securities discussed for the purposes of investment or trading.

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