Chimera vs Benchmark

Outperformed S&P 500 – 16 years out of 21 years.

 

We have positive alpha and strong gains during market meltdowns earning us the moniker ‘Crisis Alpha’. During all 10 quarters when U.S equities experienced their largest decline, Quant Savvy posted outperformance 10 out of 10 periods***. Very few investors could endure the dot.com crash & financial crash of 08. Your typical buy and hold investor has always lost money during any market crash period.

Market themes can shift promptly (COVID-19) so we keep our portfolio market neutral. 2020 continues to show why a day trading long and short portfolio is the best strategy for long term performance.

Chimera vs Benchmark

Outperformed S&P 500 – 16 years out of 21 years.

We have positive alpha and strong gains during market meltdowns earning us the moniker ‘Crisis Alpha’. During all 10 quarters when U.S equities experienced their largest decline, Quant Savvy posted outperformance 10 out of 10 periods***. Very few investors could endure the dot.com crash & financial crash of 08. Your typical buy and hold investor has always lost money during any market crash period.

Market themes can shift promptly (COVID-19) so we keep our portfolio market neutral. 2020 continues to show why a day trading long and short portfolio is the best strategy for long term performance.

PROFIT FACTOR

Every $ 1 Invested, Chimera returns $ 1.7

 

Net profit does not accurately define performance. You want to know how much you make for every dollar you risk? A profit factor of less than 1 means a losing system. A profit factor between 1.2 and 1.6 is a system we would never trade. However, a profit factor above 1.6 is considered exceptional and mathematical certainty of long term success. The high-profit factor for each Chimera system** presents reliable evidence of robustness.

CFTC RULE 4.41 – Hypothetical or simulated performance results have certain limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not been executed, the results may have under — or over — compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profit or losses similar to those shown.

Profit Factor

Every $ 1 Invested, Chimera returns $ 1.7

Net profit does not accurately define performance. You want to know how much you make for every dollar you risk? A profit factor of less than 1 means a losing system. A profit factor between 1.2 and 1.6 is a system we would never trade. However, a profit factor above 1.6 is considered exceptional and mathematical certainty of long term success. The high-profit factor for each Chimera system** presents reliable evidence of robustness.

CFTC RULE 4.41 – Hypothetical or simulated performance results have certain limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not been executed, the results may have under — or over — compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profit or losses similar to those shown.

MAXIMUM DRAWDOWN

Chimera max drawdown only 12.53%.

Greatest movement from equity high to a low point is called a drawdown. Small drawdowns allow investors to withstand periods of weak performance with confidence. Quant risk management is critical, no matter how good an automated trading system is, there will be a period where there is a losing streak.

A good quant trading system should break new equity highs every quarter so investors are not stuck in a hole with no profits for extended periods.

See graphs (side) and results table (below) for drawdown metrics for each Chimera system:

Maximum Drawdown

Chimera max drawdown only 12.53%

The greatest movement from equity high to a low point is called a drawdown. Small drawdowns allow investors to withstand periods of weak performance with confidence. Quant risk management is critical, no matter how good an automated trading system is, there will be a period where there is a losing streak.

A good quant trading system should break new equity highs every quarter so investors are not stuck in a hole with no profits for extended periods.

See graphs (side) and results table (below) for drawdown metrics for each Chimera system:

CrudeVirtuosoValueSocratesMomentumFortitudeDanteMisesChimera Totals
Drawdown %-7.93%-3.36%-5.14%-8.68%-9.20%-4.88%-9.51%-6.67%-12.53%
Max Drawdown Date23/07/1312/10/0718/10/0704/01/0704/03/0818/12/0817/09/0204/10/0201/03/07
Drawdown Dollar Value $ $-4,486 $-3,620 $-2,649 $-5,033 $-6,799 $-3,438 $-4,372 $-7,336$-8,211
No. Trades Start - End of Max Drawdown9396285330702625202
Automated Trading Chimera Bot monthly returns from 1999 to 2020

LONG-TERM PERFORMANCE

Don’t buy and hold! Use Chimera for redefining your financial future.

Newbie investors buy and hold – this trading style never has consistent monthly returns and one smart money seldom follows! Chimera Bot is a portfolio of 8 systems, completely individualistic and uncorrelated, leading to long-term performance**.

The table (below) and graph (left) shows very few losing months and monthly returns.

Long-term Performance

Don’t buy and hold! Use Chimera for redefining your financial future.

Newbie investors buy and hold – this trading style never has consistent monthly returns and one smart money seldom follows! Chimera Bot is a portfolio of 8 systems, completely individualistic and uncorrelated, leading to long-term performance**.

The table (below) and graph (left) shows very few losing months and monthly returns.

Automated Trading Chimera Bot monthly returns from 1999 to 2020
Chi BotJanFebMarAprMayJunJulAugSepOctNovDecYearAvg Month
20201.500.583.322.517.911.98
20195.290.32-0.291.320.374.121.223.511.12-0.941.680.0817.801.48
2018-0.924.998.771.251.281.82-0.483.850.0316.9510.727.1555.434.62
2017-0.881.191.433.742.181.67-0.374.361.33-2.302.270.0314.631.22
20164.123.942.044.86-0.737.472.643.28-0.761.035.48-1.1032.252.69
20151.45-0.393.76-2.696.152.145.216.834.730.584.191.0232.952.75
20145.374.123.835.431.980.242.831.54-2.364.391.30-0.7027.972.33
20130.953.41-0.592.71-2.020.37-0.472.712.025.142.19-0.6515.761.31
20120.050.782.743.6510.183.84-1.98-2.282.256.030.862.9329.042.42
2011-0.442.21-3.28-1.595.931.834.8610.68-7.206.31-0.253.8922.941.91
20104.850.330.991.431.93-0.300.014.552.584.952.190.7324.252.02
20099.681.7513.3211.171.635.994.965.341.0112.935.25-1.8971.135.93
20080.93-8.596.087.993.101.600.872.580.8911.8116.69-3.2540.703.39
2007-1.30-0.420.40-0.661.292.227.573.52-0.482.6614.712.5332.022.67
20063.771.901.713.121.593.22-0.09-2.79-0.36-3.98-2.961.756.880.57
20052.191.291.534.620.69-2.69-1.21-0.85-1.682.200.811.108.000.67
20040.46-1.095.105.41-1.481.720.321.35-0.540.540.702.1514.621.22
200310.052.924.420.09-0.06-0.265.10-5.902.612.042.805.5629.362.45
2002-0.347.491.699.946.411.945.141.326.811.345.324.9051.964.33
2001-4.2316.316.5613.771.732.388.523.203.370.862.660.2655.414.62
20008.124.0111.0815.3918.080.293.79-5.67-1.819.1913.44-6.3869.515.79
19991.40-0.122.353.342.892.493.143.382.523.643.795.1033.932.83
Chi BotJanFebMarAprMayJunJulAugSepOctNovDecYear
2020 $1,294 $4,975 $5,941 $3,083 $15,294
2019 $6,599 $105 $-566 $2,256 $1,070 $1,990 $2,456 $2,731 $784 $1,017 $1,461 $109 $20,011
2018 $184 $6,877 $8,333 $3,994 $-224 $4,453 $13 $2,006 $-76 $18,076 $9,097 $8,519 $61,250
2017 $-477 $149 $149 $2,543 $665 $2,433 $1,233 $2,758 $1,130 $-921 $530 $43 $10,235
2016 $2,156 $4,998 $-251 $4,104 $-295 $4,025 $-121 $792 $485 $-950 $4,957 $-1,133 $18,765
2015 $1,751 $681 $1,230 $-294 $2,721 $1,340 $2,110 $4,468 $4,718 $-38 $2,934 $917 $22,537
2014 $3,766 $3,045 $2,674 $3,871 $1,808 $214 $2,023 $1,356 $-1,362 $2,727 $1,262 $-711 $20,671
2013 $855 $1,972 $-186 $1,543 $-943 $203 $-321 $1,931 $1,374 $3,421 $1,853 $-570 $11,131
2012 $137 $509 $1,660 $2,086 $5,717 $1,763 $-1,171 $-1,358 $1,320 $3,270 $355 $1,878 $16,165
2011 $-266 $1,033 $-2,026 $-1,015 $3,650 $1,152 $2,776 $5,128 $-3,673 $3,208 $-383 $1,862 $11,443
2010 $2,494 $605 $311 $718 $1,721 $-374 $-23 $2,070 $935 $2,753 $1,200 $362 $12,773
2009 $3,543 $165 $4,040 $4,379 $101 $3,319 $1,913 $2,685 $273 $5,549 $3,035 $-661 $28,339
2008 $346 $-3,256 $2,653 $4,066 $1,598 $877 $1,108 $3,108 $-503 $5,559 $4,258 $-1,306 $18,508
2007 $-656 $-80 $-482 $-168 $1,346 $1,076 $3,464 $2,119 $-349 $2,004 $7,265 $1,017 $16,554
2006 $1,703 $886 $939 $1,765 $668 $764 $790 $-1,081 $-136 $-1,072 $-1,273 $536 $4,488
2005 $750 $418 $981 $1,605 $353 $-1,130 $-380 $-331 $-747 $874 $478 $334 $3,204
2004 $513 $-530 $1,234 $1,834 $-424 $658 $49 $183 $-1 $405 $574 $1,032 $5,527
2003 $3,073 $799 $1,387 $934 $168 $563 $2,090 $-1,875 $704 $901 $1,135 $2,024 $11,902
2002 $-238 $2,535 $1,047 $2,727 $2,008 $295 $938 $-72 $1,861 $380 $1,188 $1,554 $14,223
2001 $-2,139 $8,748 $2,936 $6,177 $1,118 $679 $3,589 $942 $496 $324 $1,383 $-2 $24,250
2000 $6,613 $3,828 $10,412 $13,532 $13,489 $135 $3,255 $-4,394 $-1,325 $6,256 $9,309 $-3,678 $57,433
1999 $933 $-87 $1,668 $2,391 $2,012 $1,788 $1,922 $1,804 $1,474 $2,238 $2,652 $3,959 $22,755
Chi BotJanFebMarAprMayJunJulAugSepOctNovDecYearAvg Month
20201.500.583.322.517.911.98
20195.290.32-0.291.320.374.121.223.511.12-0.941.680.0817.801.48
2018-0.924.998.771.251.281.82-0.483.850.0316.9510.727.1555.434.62
2017-0.881.191.433.742.181.67-0.374.361.33-2.302.270.0314.631.22
20164.123.942.044.86-0.737.472.643.28-0.761.035.48-1.1032.252.69
20151.45-0.393.76-2.696.152.145.216.834.730.584.191.0232.952.75
20145.374.123.835.431.980.242.831.54-2.364.391.30-0.7027.972.33
20130.953.41-0.592.71-2.020.37-0.472.712.025.142.19-0.6515.761.31
20120.050.782.743.6510.183.84-1.98-2.282.256.030.862.9329.042.42
2011-0.442.21-3.28-1.595.931.834.8610.68-7.206.31-0.253.8922.941.91
20104.850.330.991.431.93-0.300.014.552.584.952.190.7324.252.02
20099.681.7513.3211.171.635.994.965.341.0112.935.25-1.8971.135.93
20080.93-8.596.087.993.101.600.872.580.8911.8116.69-3.2540.703.39
2007-1.30-0.420.40-0.661.292.227.573.52-0.482.6614.712.5332.022.67
20063.771.901.713.121.593.22-0.09-2.79-0.36-3.98-2.961.756.880.57
20052.191.291.534.620.69-2.69-1.21-0.85-1.682.200.811.108.000.67
20040.46-1.095.105.41-1.481.720.321.35-0.540.540.702.1514.621.22
200310.052.924.420.09-0.06-0.265.10-5.902.612.042.805.5629.362.45
2002-0.347.491.699.946.411.945.141.326.811.345.324.9051.964.33
2001-4.2316.316.5613.771.732.388.523.203.370.862.660.2655.414.62
20008.124.0111.0815.3918.080.293.79-5.67-1.819.1913.44-6.3869.515.79
19991.40-0.122.353.342.892.493.143.382.523.643.795.1033.932.83
Chi BotJanFebMarAprMayJunJulAugSepOctNovDecYear
2020 $1,294 $4,975 $5,941 $3,083 $15,294
2019 $6,599 $105 $-566 $2,256 $1,070 $1,990 $2,456 $2,731 $784 $1,017 $1,461 $109 $20,011
2018 $184 $6,877 $8,333 $3,994 $-224 $4,453 $13 $2,006 $-76 $18,076 $9,097 $8,519 $61,250
2017 $-477 $149 $149 $2,543 $665 $2,433 $1,233 $2,758 $1,130 $-921 $530 $43 $10,235
2016 $2,156 $4,998 $-251 $4,104 $-295 $4,025 $-121 $792 $485 $-950 $4,957 $-1,133 $18,765
2015 $1,751 $681 $1,230 $-294 $2,721 $1,340 $2,110 $4,468 $4,718 $-38 $2,934 $917 $22,537
2014 $3,766 $3,045 $2,674 $3,871 $1,808 $214 $2,023 $1,356 $-1,362 $2,727 $1,262 $-711 $20,671
2013 $855 $1,972 $-186 $1,543 $-943 $203 $-321 $1,931 $1,374 $3,421 $1,853 $-570 $11,131
2012 $137 $509 $1,660 $2,086 $5,717 $1,763 $-1,171 $-1,358 $1,320 $3,270 $355 $1,878 $16,165
2011 $-266 $1,033 $-2,026 $-1,015 $3,650 $1,152 $2,776 $5,128 $-3,673 $3,208 $-383 $1,862 $11,443
2010 $2,494 $605 $311 $718 $1,721 $-374 $-23 $2,070 $935 $2,753 $1,200 $362 $12,773
2009 $3,543 $165 $4,040 $4,379 $101 $3,319 $1,913 $2,685 $273 $5,549 $3,035 $-661 $28,339
2008 $346 $-3,256 $2,653 $4,066 $1,598 $877 $1,108 $3,108 $-503 $5,559 $4,258 $-1,306 $18,508
2007 $-656 $-80 $-482 $-168 $1,346 $1,076 $3,464 $2,119 $-349 $2,004 $7,265 $1,017 $16,554
2006 $1,703 $886 $939 $1,765 $668 $764 $790 $-1,081 $-136 $-1,072 $-1,273 $536 $4,488
2005 $750 $418 $981 $1,605 $353 $-1,130 $-380 $-331 $-747 $874 $478 $334 $3,204
2004 $513 $-530 $1,234 $1,834 $-424 $658 $49 $183 $-1 $405 $574 $1,032 $5,527
2003 $3,073 $799 $1,387 $934 $168 $563 $2,090 $-1,875 $704 $901 $1,135 $2,024 $11,902
2002 $-238 $2,535 $1,047 $2,727 $2,008 $295 $938 $-72 $1,861 $380 $1,188 $1,554 $14,223
2001 $-2,139 $8,748 $2,936 $6,177 $1,118 $679 $3,589 $942 $496 $324 $1,383 $-2 $24,250
2000 $6,613 $3,828 $10,412 $13,532 $13,489 $135 $3,255 $-4,394 $-1,325 $6,256 $9,309 $-3,678 $57,433
1999 $933 $-87 $1,668 $2,391 $2,012 $1,788 $1,922 $1,804 $1,474 $2,238 $2,652 $3,959 $22,755

INDIVIDUAL ALGO BOTS

Eight System Portfolio

Producing a system with positive yearly performance** demands a portfolio of uncorrelated individual systems each designed uniquely to expose market inefficiencies

The systems in the portfolio communicate to only take the highest probability trade, the daily trades correlation is zero. Never two simultaneous trades in the same direction. Day trading has a very low signal to noise ratio so we average only 1 to 2 trades per day.

Our portfolio is market-neutral, meaning that it has no long term bias and is hedged equally long and short. With day trades only you can sleep soundly with no overnight risk.

Individual Algo Bots

Eight System Portfolio

Producing a system with positive yearly performance** demands a portfolio of uncorrelated individual systems each designed uniquely to expose market inefficiencies

The systems in the portfolio communicate to only take the highest probability trade, the daily trades correlation is zero. Never two simultaneous trades in the same direction. Day trading has a very low signal to noise ratio so we average only 1 to 2 trades per day.

Our portfolio is market-neutral, meaning that it has no long term bias and is hedged equally long and short. With day trades only you can sleep soundly with no overnight risk.

MONTE CARLO ANALYSIS

Shuffling Trades Simulations for Expected Risk

Monte Carlo simulations are used to model the probability of different outcomes in a process that cannot easily be predicted. It is a technique used to understand the impact of risk and uncertainty in automated trading systems. It produces an estimation of expected drawdowns and checks for possible worst-case scenarios.

We applied 1000 Monte Carlo simulations to the Chimera algorithmic system. Shuffling trades over 1000 simulations give us the best and worse case for drawdown and profit factor.

Smallest drawdown -$5,440

Base drawdown -$8,211

Largest drawdown -$16,948

Monte Carlo is a probability test, not a certainty test, and assumes returns of markets follow a Gaussian normal distribution. However, in reality, financial markets might experience huge percentage changes that are outside Guassian curve, which Monte Carlo analysis cannot predict.

Monte Carlo Analysis

Shuffling Trades Simulations for Expected Risk

Monte Carlo simulations are used to model the probability of different outcomes in a process that cannot easily be predicted. It is a technique used to understand the impact of risk and uncertainty in automated trading systems. It produces an estimation of expected drawdowns and checks for possible worst-case scenarios.

We applied 1000 Monte Carlo simulations to the Chimera algorithmic system. Shuffling trades over 1000 simulations give us the best and worse case for drawdown and profit factor.

Smallest drawdown -$5,440

Base drawdown -$8,211

Largest drawdown -$16,948

Monte Carlo is a probability test, not a certainty test, and assumes returns of markets follow a Gaussian normal distribution. However, in reality, financial markets might experience huge percentage changes that are outside Guassian curve, which Monte Carlo analysis cannot predict.

MARKET CRASHES

The COVID-19 outbreak caused supply disruptions, leading to the fastest U.S. stock market plunge from record highs into a correction (and subsequently a new bear market). A record drop was seen, and the Dow Jones dropped more than 10% in a single week. Stock markets around the world fell simultaneously amid the turmoil.

Peak to trough: 02/2020 – ongoing Worst Month: 01/02/2020 Weakest Quarter: 1st Quarter 2020 Minimum Year: 2020

The S&P 500 index peaked at 2930 on its September 20 close and dropped 19.73% to 2351 by Christmas Eve. The DJIA falls 18.78% during roughly the same period. Shanghai Composite dropped to a four-year low, escalating their economic downturn since the 2015 recession.

Peak to trough: 09/2018 – 12/2018 Worst Month: 01/12/2018 Weakest Quarter: 4th Quarter 2018 Minimum Year: 2018

The Dow Jones fell 588 points during a two-day period, 1,300 points from August 18–21. On Monday, August 24, world stock markets were down substantially, wiping out all gains made in 2015, with interlinked drops in commodities such as oil, which hit a six-year price low, copper, and most of Asian currencies.

Peak to trough: 05/2015 – 02/2016 Worst Month: 01/01/2016 Weakest Quarter: 3rd Quarter 2015 Minimum Year: 2015

The European debt crisis was a period when several European countries experienced the collapse of financial institutions, high government debt, and rapidly rising bond yield spreads in government securities. During the crisis S&P 500 entered a short-lived bear market between 2 May 2011 and 04 October 2011, experiencing a decline of 21.58%. The stock market rebounded thereafter and ended the year flat.

Peak to trough: 05/2011 – 10/2011 Worst Month: 01/08/2011 Weakest Quarter: 3rd Quarter 2011

The Great Financial Crisis started with a subprime mortgage lending crisis in the US and expanded into a global banking crisis after the failure of investment bank Lehman Brothers in September 2008.

Peak to trough: 10/2007 – 03/2009 Worst Month: 01/09/2008 Weakest Quarter: 4th Quarter 2008 Minimum Year: 2008

The rapid rise in U.S. technology stock equity valutions fueled by investments in internet companies offered revolutionary ideas with no real profits. In 2001 and through 2002 the bubble burst, entering a bear market and ending a period of overhyped investments in technology stocks. During the Dotcom Crash, Chimera Bot outperformed the S&P 500, protecting investors from losing money.

Peak to trough: 03/2000 – 10/2002 Worst Month: 01/09/2002 Weakest Quarter: 3rd Quarter 2001 Minimum Year: 2002

Algorithmic Trading Chimera Bot vs S&P 500 performance during market crashes

Market Crashes

The COVID-19 outbreak caused supply disruptions, leading to the fastest U.S. stock market plunge from record highs into a correction (and subsequently a new bear market). A record drop was seen, and the Dow Jones dropped more than 10% in a single week. Stock markets around the world fell simultaneously amid the turmoil.

Peak to trough: 02/2020 – ongoing Worst Month: 01/02/2020 Weakest Quarter: 1st Quarter 2020 Minimum Year: 2020

The S&P 500 index peaked at 2930 on its September 20 close and dropped 19.73% to 2351 by Christmas Eve. The DJIA falls 18.78% during roughly the same period. Shanghai Composite dropped to a four-year low, escalating their economic downturn since the 2015 recession.

Peak to trough: 09/2018 – 12/2018 Worst Month: 01/12/2018 Weakest Quarter: 4th Quarter 2018 Minimum Year: 2018

The Dow Jones fell 588 points during a two-day period, 1,300 points from August 18–21. On Monday, August 24, world stock markets were down substantially, wiping out all gains made in 2015, with interlinked drops in commodities such as oil, which hit a six-year price low, copper, and most of Asian currencies.

Peak to trough: 05/2015 – 02/2016 Worst Month: 01/01/2016 Weakest Quarter: 3rd Quarter 2015 Minimum Year: 2015

The European debt crisis was a period when several European countries experienced the collapse of financial institutions, high government debt, and rapidly rising bond yield spreads in government securities. During the crisis S&P 500 entered a short-lived bear market between 2 May 2011 and 04 October 2011, experiencing a decline of 21.58%. The stock market rebounded thereafter and ended the year flat.

Peak to trough: 05/2011 – 10/2011 Worst Month: 01/08/2011 Weakest Quarter: 3rd Quarter 2011

The Great Financial Crisis started with a subprime mortgage lending crisis in the US and expanded into a global banking crisis after the failure of investment bank Lehman Brothers in September 2008.

Peak to trough: 10/2007 – 03/2009 Worst Month: 01/09/2008 Weakest Quarter: 4th Quarter 2008 Minimum Year: 2008

The rapid rise in U.S. technology stock equity valutions fueled by investments in internet companies offered revolutionary ideas with no real profits. In 2001 and through 2002 the bubble burst, entering a bear market and ending a period of overhyped investments in technology stocks. During the Dotcom Crash, Chimera Bot outperformed the S&P 500, protecting investors from losing money.

Peak to trough: 03/2000 – 10/2002 Worst Month: 01/09/2002 Weakest Quarter: 3rd Quarter 2001 Minimum Year: 2002

Algorithmic Trading Chimera Bot vs S&P 500 performance during market crashes
We care about the success of our users - always providing outstanding customer service. No monthly fixed fees! We pay for your server, hardware & software! We pay for 24/7 server maintenance and hardware monitoring!

TOP TEN TRADES, DRAWDOWNS AND SERIES

10 Largest Wins %Date10 Largest Losers %Date
6.88%08/11/2000-2.85%13/08/2019
6.24%10/04/2000-2.80%13/03/2001
5.92%23/03/2009-2.80%23/09/2011
5.82%24/11/2008-2.71%23/01/2009
5.62%13/10/2000-2.71%29/01/2001
5.45%30/05/2000-2.70%10/03/2009
4.77%02/02/2001-2.70%07/09/2001
4.71%03/04/2000-2.70%05/10/2011
4.67%10/07/2001-2.70%07/11/2008
4.60%13/11/2008-2.69%19/09/2000
10 Largest Wins $Date10 Largest Losers $Date
$5,90610/04/2000 $-3,11725/03/2020
$5,72124/10/2018 $-3,08920/03/2020
$5,58625/02/2020 $-2,75408/08/2019
$5,33626/03/2020 $-2,70426/02/2020
$4,96608/11/2000 $-2,67904/05/2018
$4,79627/03/2018 $-2,63426/04/2018
$4,73326/12/2018 $-2,51919/10/2018
$4,56621/12/2018 $-2,46407/04/2000
$4,51603/04/2000 $-2,31415/05/2019
$4,08118/03/2020 $-2,29917/03/2020
Max Drawdown %Max Draw DateStartedRecoveredTradesDays
-12.53%01/03/200722/08/200602/08/2007206248
-11.67%09/01/200113/12/200022/02/20014152
-11.30%05/03/200819/12/200715/04/20087785
-10.74%27/09/200001/08/200017/10/20003956
-10.25%29/09/201123/08/201113/01/201289104
-8.49%13/10/200508/06/200518/01/2006149161
-7.71%15/09/200329/07/200324/11/20036285
-7.33%18/09/200817/07/200801/10/20086055
-6.90%15/04/201128/02/201125/05/20117163
-6.12%25/05/201826/04/201816/07/20184758
Max Drawdown $Max Draw DateStartedRecoveredTradesDays
$-8,16527/09/200001/08/200017/10/20004256
$-6,45209/01/202013/12/200022/02/20014152
$-6,21925/03/202020/03/202026/03/202045
$-5,98825/05/200826/04/201826/06/20183944
$-5,71216/03/201813/02/201823/03/20183329
$-4,96729/09/201123/08/201113/01/201289104
$-4,94415/05/200722/08/200627/07/2007201244
$-4,49204/03/200818/12/200710/04/20087483
$-4,28602/05/201128/01/201125/05/20119284
$-4,11509/03/200016/02/200015/03/20001521
Trade Series1234567891011
Number Winning Series119962232917088502912731
Number Losing Series1198523225112531971

Top 10 Trades, Drawdowns and Series

10 Largest Wins %Date10 Largest Losers %Date
6.88%08/11/2000-2.85%13/08/2019
6.24%10/04/2000-2.80%13/03/2001
5.92%23/03/2009-2.80%23/09/2011
5.82%24/11/2008-2.71%23/01/2009
5.62%13/10/2000-2.71%29/01/2001
5.45%30/05/2000-2.70%10/03/2009
4.77%02/02/2001-2.70%07/09/2001
4.71%03/04/2000-2.70%05/10/2011
4.67%10/07/2001-2.70%07/11/2008
4.60%13/11/2008-2.69%19/09/2000
10 Largest Wins $Date10 Largest Losers $Date
$5,90610/04/2000 $-3,11725/03/2020
$5,72124/10/2018 $-3,08920/03/2020
$5,58625/02/2020 $-2,75408/08/2019
$5,33626/03/2020 $-2,70426/02/2020
$4,96608/11/2000 $-2,67904/05/2018
$4,79627/03/2018 $-2,63426/04/2018
$4,73326/12/2018 $-2,51919/10/2018
$4,56621/12/2018 $-2,46407/04/2000
$4,51603/04/2000 $-2,31415/05/2019
$4,08118/03/2020 $-2,29917/03/2020
Max Drawdown %Max Draw DateStartedRecoveredTradesDays
-12.53%01/03/200722/08/200602/08/2007206248
-11.67%09/01/200113/12/200022/02/20014152
-11.30%05/03/200819/12/200715/04/20087785
-10.74%27/09/200001/08/200017/10/20003956
-10.25%29/09/201123/08/201113/01/201289104
-8.49%13/10/200508/06/200518/01/2006149161
-7.71%15/09/200329/07/200324/11/20036285
-7.33%18/09/200817/07/200801/10/20086055
-6.90%15/04/201128/02/201125/05/20117163
-6.12%25/05/201826/04/201816/07/20184758
Max Drawdown $Max Draw DateStartedRecoveredTradesDays
$-8,16527/09/200001/08/200017/10/20004256
$-6,45209/01/202013/12/200022/02/20014152
$-6,21925/03/202020/03/202026/03/202045
$-5,98825/05/200826/04/201826/06/20183944
$-5,71216/03/201813/02/201823/03/20183329
$-4,96729/09/201123/08/201113/01/201289104
$-4,94415/05/200722/08/200627/07/2007201244
$-4,49204/03/200818/12/200710/04/20087483
$-4,28602/05/201128/01/201125/05/20119284
$-4,11509/03/200016/02/200015/03/20001521
Trade Series1234567891011
Number Winning Series119962232917088502912731
Number Losing Series1198523225112531971

TRADE ANALYSIS

Yearly # Trades, Monthly # Trades

Chimera has over 4600 trades, which, statistically, decreases our chances not to make money**. Algorithmic system trades should be Long and Short otherwise there will be a long bias and the algorithmic trading bot will fail every time the market plunges. Chimera Bot is balanced long and short and market neutral.

Chimera Bot averages 19 trades per month and 229 trades per year. Our research shows that day trading markets are 90% random, only failed human day traders think they can pick every minor wave. Chimera is very selective and trades only when the odds are heavily stacked in its favour. Overtrading is a human day trader construct and one algo bots will never succumb to.

Trade Analysis

Yearly # Trades, Monthly # Trades

Chimera has over 4600 trades, which, statistically, decreases our chances not to make money**. Algorithmic system trades should be Long and Short otherwise there will be a long bias and the algorithmic trading bot will fail every time the market plunges. Chimera Bot is balanced long and short and market neutral.

Chimera Bot averages 19 trades per month and 229 trades per year. Our research shows that day trading markets are 90% random, only failed human day traders think they can pick every minor wave. Chimera is very selective and trades only when the odds are heavily stacked in its favour. Overtrading is a human day trader construct and one algo bots will never succumb to.

SCATTER PLOTS

Highly Performing Investment

The % scatterplot highlights that very few trades on the downside exceed -2% and none less than -3%. On the upside, we have many trades exceeding 3% gains. The risk to reward on each trade is positive as is the overall trades winning percentage of 54%.

The $ scatterplot shows very few trades exceed losses of -$1k on the downside but numerous trades are greater than +$1k on the upside. Keep in mind the dollar value will increase relative to an increase in market price: see normalised trade data.

Scatter Plots

Highly Performing Invesment

The % scatterplot highlights that very few trades on the downside exceed -2% and none less than -3%. On the upside, we have many trades exceeding 3% gains. The risk to reward on each trade is positive as is the overall trades winning percentage of 54%.

The $ scatterplot shows very few trades exceed losses of -$1k on the downside but numerous trades are greater than +$1k on the upside. Keep in mind the dollar value will increase relative to an increase in market price: see normalised trade data.

Normalising trades for expected dollar values

Drawdown metrics can be misleading when analysing system performance. Every investor wants to know what they can potentially lose or what a system has lost in the past, this way the investor has some expectation going forwards. This is a measure of risk and survivability, especially when you consider margins (futures are traded heavily on margin).

Drawdown percentage depends entirely on the starting capital. Most systems backtest reports are run with the assumption of starting $100k capital trading 1 contract with no compounding of returns. However, some developers will then inform investors that the system can be run with as little as $10k and still have the same performance.

Let’s assume the backtest report stated a 10% drawdown on $100k right of the start of trading = $10k drawdown.

Traders starting this with $35k the dollar value drawdown will be -$8211 trading 1 futures contract. Percentage drawdown is  23.46%. 

Futures are traded only in 1 contract increments. Markets move in percentages and price has risen remarkably over the last decade. It is better to normalise the trade data to the current market price to get a more accurate figure for a trades expected dollar value.

After adjusting and normalising the data for historical trades we achieve expected dollar performance at today’s market prices. The same trades would be made but after adjusting for a much higher current market price we get greater dollar values per trade. 

Process normalising past trades to current market price

14
1. Convert dollars to points

Each trades profit/loss dollar value will be converted to points for their respective markets e.g. $50 = 1 Point ES Market, $20 = 1 Point NQ, $5 = 1 Point YM

13
2. Convert points to percentage

Convert points to a percentage at that current time and market price e.g NQ trade in March 2007 (market trading at 1763.75 price) with $175.98 profitable trade = 8.8 Nasdaq points = 0.5% market move.

Asset 1
3. Normalise to market price

The 0.5% move is now normalised to this year's market price, NQ trading at 7711, this now equates to a $769.37 dollar value.

Normalising trades for expected dollar values

 

Drawdown metrics can be misleading when analysing system performance. Every investor wants to know what they can potentially lose or what a system has lost in the past, this way the investor has some expectation going forwards. This is a measure of risk and survivability, especially when you consider margins (futures are traded heavily on margin).

Drawdown percentage depends entirely on the starting capital. Most systems backtest reports are run with the assumption of starting $100k capital trading 1 contract with no compounding of returns. However, some developers will then inform investors that the system can be run with as little as $10k and still have the same performance.

Let’s assume the backtest report stated a 10% drawdown on $100k right of the start of trading = $10k drawdown.

Traders starting this with $35k the dollar value drawdown will be -$8211 trading 1 futures contract. Percentage drawdown is  23.46%. 

Futures are traded only in 1 contract increments. Markets move in percentages and price has risen remarkably over the last decade. It is better to normalise the trade data to the current market price to get a more accurate figure for a trades expected dollar value.

After adjusting and normalising the data for historical trades we achieve expected dollar performance at today’s market prices. The same trades would be made but after adjusting for a much higher current market price we get greater dollar values per trade. 

Process normalising past trades to current market price

14
1. Convert dollars to points

Each trades profit/loss dollar value will be converted to points for their respective markets e.g. $50 = 1 Point ES Market, $20 = 1 Point NQ, $5 = 1 Point YM

13
2. Convert points to percentage

Convert points to a percentage at that current time and market price e.g NQ trade in March 2007 (market trading at 1763.75 price) with $175.98 profitable trade = 8.8 Nasdaq points = 0.5% market move.

Asset 1
3. Normalise to market price

The 0.5% move is now normalised to this year's market price, NQ trading at 7711, this now equates to a $769.37 dollar value.

NORMALISED TRADES $
Quant Savvy normalised trades data
Normalised Annual and Cumulative Profits $
Quant Savvy Normalised Drawdown $ Equity Curve and Annual Returns
Normalised Drawdown $
Quant Savvy Normalised Drawdown $
NORMALISED TRADES $
Quant Savvy normalised trades data
Normalised Annual and Cumulative Profits $
Quant Savvy Normalised Drawdown $ Equity Curve and Annual Returns
Normalised Drawdown $
Quant Savvy Normalised Drawdown $

TOP TEN NORMALISED

Biggest winners and losers, ten Largest drawdowns

The data tables show Chimera trades normalised to the current market price, this highlights that dollar drawdown on the tested period will be larger if normalised to the current market price. This is close to close drawdown so intraday dollar drawdown value will be higher.

Monte Carlo analysis will show drawdown values can be exceeded without impacting the statistical expectancy of the system. Users should trade a position size relative to the worst-case Monte Carlo analysis – this is currently $16,948 per contract.

10 Big Wins $Date10 Big Losers $Date
$9,638.6708/11/2000 $-3,914.3213/03/2001
$8,733.8910/04/2000 $-3,797.5623/01/2009
$7,861.7713/10/2000 $-3,794.2629/01/2001
$7,632.8430/05/2000 $-3,784.4410/03/2009
$6,673.1002/02/2001 $-3,781.8007/09/2001
$6,595.4203/04/2000 $-3,776.9505/10/2011
$6,533.2610/07/2001 $-3,775.2707/11/2008
$6,445.9713/11/2008 $-3,762.7619/09/2000
$6,230.4226/04/2002 $-3,758.6219/12/2000
$6,171.0808/05/2002 $-3,757.1516/08/2001
Max Drawdown $Max Draw DateStartedRecoveredTradesDays
$-17,36101/03/200728/06/200621/08/2007255300
$-16,44531/01/200113/12/200022/02/20014152
$-15,45105/03/200819/12/200715/04/20087785
$-13,48627/09/200001/08/200012/10/20003953
$-11,83015/09/200817/07/200801/10/20086155
$-10,22313/10/200508/06/200518/01/2006149161
$-10,07215/09/200329/07/200324/11/20036285
$-8,46819/02/200922/01/200902/03/20092528
$-7,99305/10/201123/08/201108/12/20117178
$-7,68402/07/201010/05/201027/08/20107980

Top 10 Normalized

Biggest winners and losers, ten Largest drawdowns

The data tables show Chimera trades normalised to the current market price, this highlights that dollar drawdown on the tested period will be larger if normalised to the current market price. This is close to close drawdown so intraday dollar drawdown value will be higher.

Monte Carlo analysis will show drawdown values can be exceeded without impacting the statistical expectancy of the system. Users should trade a position size relative to the worst-case Monte Carlo analysis – this is currently $16,948 per contract.

10 Big Wins $Date10 Big Losers $Date
$9,638.6708/11/2000 $-3,914.3213/03/2001
$8,733.8910/04/2000 $-3,797.5623/01/2009
$7,861.7713/10/2000 $-3,794.2629/01/2001
$7,632.8430/05/2000 $-3,784.4410/03/2009
$6,673.1002/02/2001 $-3,781.8007/09/2001
$6,595.4203/04/2000 $-3,776.9505/10/2011
$6,533.2610/07/2001 $-3,775.2707/11/2008
$6,445.9713/11/2008 $-3,762.7619/09/2000
$6,230.4226/04/2002 $-3,758.6219/12/2000
$6,171.0808/05/2002 $-3,757.1516/08/2001
Max Drawdown $Max Draw DateStartedRecoveredTradesDays
$-17,36101/03/200728/06/200621/08/2007255300
$-16,44531/01/200113/12/200022/02/20014152
$-15,45105/03/200819/12/200715/04/20087785
$-13,48627/09/200001/08/200012/10/20003953
$-11,83015/09/200817/07/200801/10/20086155
$-10,22313/10/200508/06/200518/01/2006149161
$-10,07215/09/200329/07/200324/11/20036285
$-8,46819/02/200922/01/200902/03/20092528
$-7,99305/10/201123/08/201108/12/20117178
$-7,68402/07/201010/05/201027/08/20107980

INITIAL CAPITAL RISK PROFILES

See expectations based on different risk profiles – each investor has different risk tolerance and profiles should be adjusted relative to market price and volatility.

Results based on Intial Capital $14,000 $24,500 $35,000 $70,000 $140,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage55555
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain6.61%6.61%6.61%6.61%6.61%
% Avg Annual Gain79.34%79.34%79.34%79.34%79.34%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-49.60%-49.60%-49.60%-49.60%-49.60%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-23.46%-23.46%-23.46%-23.46%-23.46%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $17,000 $30,625 $43,000 $87,000 $175,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage44444
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain5.44%5.29%5.38%5.32%5.29%
% Avg Annual Gain65.33%63.47%64.58%63.83%63.47%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-40.85%-39.68%-40.37%-39.91%-39.68%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-19.32%-18.77%-19.10%-18.88%-18.77%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $23,000 $40,833 $58,000 $116,000 $233,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage33333
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain4.02%3.97%3.99%3.99%3.97%
% Avg Annual Gain48.29%47.60%47.87%47.87%47.67%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-30.19%-29.76%-29.93%-29.93%-29.80%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-14.28%-14.08%-14.16%-14.16%-14.10%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $35,000 $61,250 $87,000 $175,000 $350,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage22222
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain2.64%2.64%2.66%2.64%2.64%
% Avg Annual Gain31.73%31.73%31.92%31.73%31.73%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-19.84%-19.84%-19.96%-19.84%-19.84%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-9.38%-9.38%-9.44%-9.38%-9.38%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $70,000 $122,500 $175,000 $350,000 $700,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage11111
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain1.32%1.32%1.32%1.32%1.32%
% Avg Annual Gain15.87%15.87%15.87%15.87%15.87%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-9.92%-9.92%-9.92%-9.92%-9.92%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-4.69%-4.69%-4.69%-4.69%-4.69%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM

Initial Capital Profiles

See expectations based on different risk profiles – each investor has different risk tolerance and profiles should be adjusted relative to market price and volatility. Futures Trading has large potential reward but also large potential risk.

It is not appropriate for all investors – do not trade with money you cannot afford to lose.

Results based on Intial Capital $14,000 $24,500 $35,000 $70,000 $140,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage55555
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain6.61%6.61%6.61%6.61%6.61%
% Avg Annual Gain79.34%79.34%79.34%79.34%79.34%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-49.60%-49.60%-49.60%-49.60%-49.60%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-23.46%-23.46%-23.46%-23.46%-23.46%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $17,000 $30,625 $43,000 $87,000 $175,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage44444
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain5.44%5.29%5.38%5.32%5.29%
% Avg Annual Gain65.33%63.47%64.58%63.83%63.47%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-40.85%-39.68%-40.37%-39.91%-39.68%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-19.32%-18.77%-19.10%-18.88%-18.77%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $23,000 $40,833 $58,000 $116,000 $233,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage33333
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain4.02%3.97%3.99%3.99%3.97%
% Avg Annual Gain48.29%47.60%47.87%47.87%47.67%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-30.19%-29.76%-29.93%-29.93%-29.80%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-14.28%-14.08%-14.16%-14.16%-14.10%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $35,000 $61,250 $87,000 $175,000 $350,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage22222
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain2.64%2.64%2.66%2.64%2.64%
% Avg Annual Gain31.73%31.73%31.92%31.73%31.73%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-19.84%-19.84%-19.96%-19.84%-19.84%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-9.38%-9.38%-9.44%-9.38%-9.38%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM
Results based on Intial Capital $70,000 $122,500 $175,000 $350,000 $700,000
Futures Contracts4 Micro7 Micro1 Emini2 Emini4 Emini
Leverage11111
2015 $9,015 $15,776 $22,537 $45,074 $90,148
2016 $7,506 $13,135 $18,765 $37,530 $75,060
2017 $4,094 $7,165 $10,235 $20,471 $40,942
2018 $24,500 $42,875 $61,250 $122,500 $245,001
2019 $8,004 $14,008 $20,011 $40,022 $80,045
2020 $6,117 $10,705 $15,294 $30,587 $61,174
Net Gain $59,237 $103,665 $148,092 $296,185 $592,370
$ Avg Monthly Gain $926 $1,620 $2,314 $4,628 $9,256
% Avg Monthly Gain1.32%1.32%1.32%1.32%1.32%
% Avg Annual Gain15.87%15.87%15.87%15.87%15.87%
Avg Trade $49.95 $87.41 $124.87 $249.73 $499.47
Max Normalised Drawdown $-6,944 $-12,153 $-17,361 $-34,722 $-69,444
Max Normalised Drawdown %-9.92%-9.92%-9.92%-9.92%-9.92%
Total All Systems Trades1,1861,1861,1861,1861,186
Total All Systems Trades Per Month1818181818
Max Drawown 1999 - 2020 $-3,284 $-5,748-8,211 $-16,422 $-32,844
If Max Drawdown from 1st Trade-4.69%-4.69%-4.69%-4.69%-4.69%
Markets: Micro/Emini Based on Initial CapitalMES,MNQ,MYM,QMMES,MNQ,MYM,QMES,NQ,YM,CL/QMES,NQ,YM,CL/QMES,NQ,YM,CL/QM

ACCOUNT INFORMATION

Minimum account size required: $15,000 (no maximum account size), Capital per unit traded should track the current market price and volatility. Allocation: One contract traded on each algorithm (1/1/1/1/1/1/1/1 = 8 total). Account types allowed: Cash, IRA, Roth IRA. We accept users worldwide you just need a compatible broker.

Only 1 trade in the same direction per day (zero correlation so never 2 trades in the same direction). The number of algorithms traded: 8 systems. Systems are independent and uncorrelated, portfolio equally weighted Long & Short. You will trade the entire Chimera Bot portfolio. No margin issues as only one trade in the same direction at the same time.

Markets based on Initial Capital. Small accounts: Micro Markets (MES,MNQ,MYM,QM) & large accounts Emini (ES,NQ,YM,QM/CL). Licenses Available: Yes – contact us quickly as we limit the number of users who can trade the portfolio due to scaleability and future liquidity concerns. Past portfolios have reached the max size and are closed off to new users.

We recommend TradeStation or Interactive Brokers. There are many other compatible brokers and they can be used with Multicharts. We will set up your selected platform on your server and we will pay for all software and hardware fees, you have zero cost. Open a futures account with a compatible broker and subscribe to CME,CBOT and Nymex futures data.

We provide high spec server located close proximity to your broker, latency less than 1 millisecond in many cases. Systems fire orders at high-speed ensuring slippage costs are limited. Users can access their server 24/7 via PC/Smartphone. Log in to view live trades & charts in real-time. No server costs, no hardware costs, no monthly fixed fees, no support costs.

Contact for Pricing Now

We will email you pricing and more information about algorithmic trading. Our CEO will contact you personally.

Office

Kemp House, City Road
London,
United Kingdom, EC1V 2NX

 

Contact Us

Email: info@quantsavvy.com

US/Canada Toll Free: 1-800-820-3275

Rest of World: 0203 005 5238


    Contact for Pricing Now

    We will email you pricing and more information about algorithmic trading. Our CEO will contact you personally.


      Office

      Kemp House, City Road
      London,
      United Kingdom, EC1V 2NX

       

      Contact Us

      Email: info@quantsavvy.com

      US/Canada Toll Free: 1-800-820-3275

      Rest of World: 0203 005 5238