Results are based on starting with an initial $100k account (this is standard input for representing performance). All tested performance uses the position sizing bot which will adjust position size automatically to manage risk on every trade.
We assume the drawdown is from the first trade taken. Drawdown figure is based on $100k capital, not the historical cumulative return. Assuming the max drawdown is taken from the initial capital $100k gives users the worst-case scenario. Results show the worst-case scenario; results assume users will experience the worst dollar drawdown on their initial 100k capital.
Every user can adjust their position sizing to suit their risk profile; however, to standardise the performance, we simply base this on $100k initial capital trading. Users can also use the position sizing bot to automatically adjust position sizing based on market price and volatility, and risk management.
Each NQ, YM, and ES system consists of subsystems; we expect days to get correlated trades. The YM, ES, and NQ can go long or short on individual days. There is potential for multiple longs or shorts on individual markets, all at different prices.
If a system report starts with $100k and records an equity peak of 200k and then a drawdown of $50k, that equates to a -25% drawdown (peak to trough). However, for a new User starting with $100k who only started trading at the exact Peak of the Equity curve, then they would still experience a $50k drawdown which equates to 50% of their initial capital. Trade results and position size all based on $100k initial capital.
Days with +3 correlated trades simultaneously are rare and have only occurred a handful of times from 2007 to 2021. However, we expect +3 correlated trades on an individual day to happen a handful of times per year. Because the subsystems have different entry times, stops and targets and trade three different markets, many of these correlated trade days will not have highly correlated daily profit and loss.
Day Trading Strategies generate 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. 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. We are very confident in our systems’ performance – try it yourself.
Market themes can shift promptly (COVID-19) so we keep our portfolio market neutral. 2022 – 2023 has shown why a day trading long and short portfolio is the best strategy for long-term performance. Whilst the Nasdaq has crashed over 30% since Nov 2022 the Chimera Bot has generated gains.
Net profit does not accurately define performance. Traders 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 1.3 is a system we would never trade. However, a profit factor above 1.5 is considered exceptional and gives a high degree of confidence for long-term algorithmic trading success. The high-profit factor for each Chimera Bot system** presents reliable evidence of robustness.
In algorithmic trading, the greatest movement from an 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. The average yearly return of 49.55% is divided by the max drawdown of -29.71% = 1.67 (the average yearly return is one and half times the max ever recorded drawdown).
A good quant trading system should aim to break new equity highs every quarter so investors are not stuck in a hole with no profits for extended periods. Historically, some periods are expected to have longer duration drawdowns. These are Day Trading Strategies only which eliminates considerable overnight market risk.
Newbie investors buy and hold – this trading style never has consistent monthly returns, and smart money seldom follows! Chimera Trading Bot is a portfolio of 5 systems, completely individualistic and uncorrelated, leading to long-term performance**. We are very confident in our auto trading system performance – try it yourself. Chimera Trading Bot is compatible with most algorithmic trading software brokers.
The table (below) and graph (left) show a few losing months and monthly returns.
Producing an algorithmic trading 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 only to take the highest probability trade. The daily trade correlation is low. Day trading has a very low signal-to-noise ratio, so we average only 1 to 2 trades per day.
Our day trading strategies portfolio is market-neutral, meaning 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.
Chimera has over 4600 trades, which, statistically, decreases our chances of not making 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 21 trades per month and 252 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 selective and trades only when the odds are heavily stacked in its favour. Overtrading is a human day trader construct, and one algo bot will never succumb to it. Experience the advantages of algorithmic trading yourself.
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.
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Providing Algo Systems Since 2014
**Commodity Future and Trading Commission Futures has large potential rewards, but also large potential risk. You must be aware of the risks and be willing to accept them in order to invest in the futures markets. Do not trade with money you cannot afford to lose. The past performance posted on quantsavvy.com is not necessarily indicative of future results.
Quant Savvy provides trading algorithms based on a computerized system. All advice is impersonal and not tailored to any specific individual’s unique situation. Quant Savvy, and its principles, are not required to register with the NFA as a CTA and are publicly claiming this exemption. Information posted online or distributed through email has NOT been reviewed by any government agencies — this includes but is not limited to back-tested reports, statements and any other marketing materials. Carefully consider this prior to purchasing our algorithms. For more information on the exemption we are claiming, please visit the NFA website: http://www.nfa.futures.org/nfa-registration/cta/index.html. If you are in need of professional advice unique to your situation, please consult with a licensed broker/CTA.
**DISCLAIMER: Commodity Futures Trading Commission Futures trading has large potential rewards, but also large potential risk. You must be aware of the risks and be willing to accept them in order to invest in the futures markets. Don’t trade with money you can’t afford to lose. This is neither a solicitation nor an offer to Buy/Sell futures. No representation is being made that any account will or is likely to achieve profits or losses similar to those discussed on this website or on any reports. The past performance of any trading system or methodology is not necessarily indicative of future results. ***All returns posted on this site and in our videos is considered Backtested Trading Performance.
Backtested trading results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between backtested trading results and the actual results subsequently achieved by any particular trading program. One of the limitations of backtested trading results is that they are generally prepared with the benefit of hindsight. In addition, backtested trading does not involve financial risk, and no backtested trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of backtested performance results and all of which can adversely affect actual trading results.
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.
Statements posted from our actual customers trading the algorithms (algos) include slippage and commission. Statements posted are not fully audited or verified and should be considered as customer testimonials. Individual results do vary. They are real statements from real people trading our algorithms on auto-pilot and as far as we know, do NOT include any discretionary trades. Tradelists posted on this site also include slippage and commission. All advice and/or suggestions given in Quant Savvy website are intended for running automated software in simulation mode only. Trading futures is not for everyone and does carry a high level of risk. All past performance shown is backtested data only.