AI TQQQ SQQQ swing
Trades Own Strategy BrokerTransmit
- hypothetical · Annual Return (Compounded)
- 28.7%
- Max Drawdown
- 66.6%
- Trades
- 731
- Win Trades
- 47.3%
- Profit Factor
- 1.10
- Win Months
- 54.4%
About this strategy
Investment Strategy Overview
This trading strategy is centered around the 3x Long NASDAQ ETF, TQQQ, with the capability to take short positions through SQQQ. This strategy is underpinned by the application of machine learning (Artificial Intelligence) techniques and swing/day trading.
Leveraged ETFs and Risk Mitigation
It is imperative to recognize that leveraged ETFs offer the potential for substantial returns but simultaneously carry a heightened degree of risk, attributable to their 3x leverage. Our approach seeks to mitigate this risk by adopting a dynamic stance that involves holding the long ETF during favorable market conditions while holding the inverse ETF during market downturns. This decision-making process is driven by our machine learning algorithms, ensuring a data-driven and disciplined approach.
Account Requirements and Geographic Considerations
Participants in our strategy should be aware that a margin account is required. We do not employ martingale strategies or margin utilization. In the case of an Individual Retirement Account (IRA), IRA margin is mandatory. Additionally, it's important to note that the ETFs we utilize are not available through Interactive Brokers in Europe.
Account Size and Automation
We recommend a minimum account size of $30,000 to avoid Pattern Day Trader violations. Additionally, we highly recommend using Collective2's autotrading to ensure timely execution and adherence to our algorithmic approach. We emphasize that this strategy should only be implemented with funds designated as risk capital, capital that one is prepared to lose entirely if necessary. Be sure to exercise prudent judgment when setting scaling to align with one's risk tolerance. Our system is entirely algorithmic, devoid of discretionary decision-making.
Suggestion for how to calculate scaling:
1. Find strategy model account value by opening the strategy page.
2. Zoom the chart to the far right, and move mouse over current model account value (e.g., $27,150).
3. Suppose you have $33,000 in your IB account that you want to use in it's entirety.
4. Now divide to get scaling: $33,000 / $27,150 = 1.215, or 121%
5. So you would set your scaling to 121% when setting up autotrading.
6. You may want to choose a lower value to be less aggressive, but we do not recommend a higher value.
7. It is advisable to revisit scaling (yearly is good), and if necessary, update it.
This trading strategy is centered around the 3x Long NASDAQ ETF, TQQQ, with the capability to take short positions through SQQQ. This strategy is underpinned by the application of machine learning (Artificial Intelligence) techniques and swing/day trading.
Leveraged ETFs and Risk Mitigation
It is imperative to recognize that leveraged ETFs offer the potential for substantial returns but simultaneously carry a heightened degree of risk, attributable to their 3x leverage. Our approach seeks to mitigate this risk by adopting a dynamic stance that involves holding the long ETF during favorable market conditions while holding the inverse ETF during market downturns. This decision-making process is driven by our machine learning algorithms, ensuring a data-driven and disciplined approach.
Account Requirements and Geographic Considerations
Participants in our strategy should be aware that a margin account is required. We do not employ martingale strategies or margin utilization. In the case of an Individual Retirement Account (IRA), IRA margin is mandatory. Additionally, it's important to note that the ETFs we utilize are not available through Interactive Brokers in Europe.
Account Size and Automation
We recommend a minimum account size of $30,000 to avoid Pattern Day Trader violations. Additionally, we highly recommend using Collective2's autotrading to ensure timely execution and adherence to our algorithmic approach. We emphasize that this strategy should only be implemented with funds designated as risk capital, capital that one is prepared to lose entirely if necessary. Be sure to exercise prudent judgment when setting scaling to align with one's risk tolerance. Our system is entirely algorithmic, devoid of discretionary decision-making.
Suggestion for how to calculate scaling:
1. Find strategy model account value by opening the strategy page.
2. Zoom the chart to the far right, and move mouse over current model account value (e.g., $27,150).
3. Suppose you have $33,000 in your IB account that you want to use in it's entirety.
4. Now divide to get scaling: $33,000 / $27,150 = 1.215, or 121%
5. So you would set your scaling to 121% when setting up autotrading.
6. You may want to choose a lower value to be less aggressive, but we do not recommend a higher value.
7. It is advisable to revisit scaling (yearly is good), and if necessary, update it.
Trend-following Sector: Technology
Hypothetical Monthly Returns (includes fees/commissions)
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020 | 1.7 | 11.1 | 13.8 | 16.2 | 16.8 | 27.7 | -9.5 | 11.9 | 33.5 | 10.2 | 232.2 | ||
| 2021 | -1.8 | 9.5 | 6.5 | 19.1 | 10.7 | 14.3 | -5.0 | 7.5 | -24.1 | 21.4 | 6.6 | -5.8 | 63.1 |
| 2022 | -11.7 | -25.4 | 11.9 | 15.9 | 2.5 | -3.7 | 21.3 | -4.7 | -12.0 | -11.2 | -11.4 | 17.7 | -20.6 |
| 2023 | 12.5 | -2.6 | 0.2 | -19.0 | 43.4 | 10.7 | 17.8 | 13.6 | -17.5 | -8.7 | 1.4 | 17.7 | 70.1 |
| 2024 | -5.1 | 9.3 | -10.7 | 4.4 | 16.0 | 0.4 | 2.2 | -18.1 | -23.2 | -15.4 | -5.2 | -2.5 | -43.5 |
| 2025 | -5.6 | 8.4 | -13.1 | 30.4 | -8.1 | 5.8 | -0.2 | -1.2 | 17.1 | 12.7 | -12.8 | -1.2 | 26.4 |
| 2026 | 1.1 | -6.5 | -6.2 | 20.0 | 10.6 | -0.8 | -8.1 | -5.7 | -3.3 | -2.2 |
Statistics
Overview
| Strategy began | 3/26/2020 |
|---|---|
| Suggested Minimum Capital | $35,000 |
| Age | 79 months |
| C2 Rank | 307 |
| What it trades | Stocks |
| # Trades | 731 |
| # Profitable | 346 |
| % Profitable | 47.3% |
| Avg trade duration | 3.0 days |
| Max peak-to-valley drawdown | 66.5% |
| drawdown period | July 10, 2024 - April 07, 2025 |
| Annual Return (Compounded) | 28.7% |
| Avg win | $666 |
| Avg loss | $545 |
Ratios
| W:L ratio | 1.11 |
|---|---|
| Sharpe Ratio | 0.62 |
| Sortino Ratio | 0.93 |
| Calmar Ratio | 0.75 |
CORRELATION STATISTICS
| Correlation to SP500 | 0.26 |
|---|---|
| Return Percent SP500 (cumu) during strategy life | 190.5% |
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | 220.0% |
Return Statistics
| Ann Return (w trading costs) | 28.7% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | 0.3% |
| Ann Return (Compnd, No Fees) | 37.9% |
Slump
| Current Slump as Pcnt Equity | 79.7% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 0.3% |
Instruments
| Percent Trades Forex | 0.0% |
|---|---|
| Percent Trades Futures | 0.0% |
| Percent Trades Options | 0.0% |
| Short Options - Percent Covered | 100.0% |
| Percent Trades Stocks | 1.0% |
Risk of Ruin (Monte-Carlo)
| Chance of 10% account loss | 66.5% |
|---|---|
| Chance of 20% account loss | 40.0% |
| Chance of 30% account loss | 20.5% |
| Chance of 40% account loss | 10.5% |
| Chance of 50% account loss | 4.0% |
| Chance of 60% account loss (Monte Carlo) | 2.0% |
| Chance of 70% account loss (Monte Carlo) | 0.0% |
| Chance of 80% account loss (Monte Carlo) | 0.0% |
| Chance of 90% account loss (Monte Carlo) | 0.0% |
| Chance of 100% account loss (Monte Carlo) | 0.0% |
Automation
| Percentage Signals Automated | 0.0% |
|---|
Popularity
| Popularity (Today) | 738 |
|---|---|
| Popularity (Last 6 weeks) | 928 |
| C2 Score | 307 |
| Popularity (7 days, Percentile 1000 scale) | 788 |
Trading Style
| Any stock shorts? 0/1 | 0 |
|---|
Trades-Own-System Certification
| Trades Own System? | 185199 |
|---|---|
| TOS percent | 100.0% |
Win / Loss
| Avg Loss | $545 |
|---|---|
| Avg Win | $666 |
| # Winners | 346 |
| Sum Trade PL (losers) | $209,867 |
| Sum Trade PL (winners) | $230,481 |
| Num Months Winners | 43 |
| # Losers | 385 |
| % Winners | 47.3% |
Dividends
| Dividends Received in Model Acct | 2140 |
|---|
Age
| Num Months filled monthly returns table | 79 |
|---|
Frequency
| Avg Position Time (mins) | 4385.88 |
|---|---|
| Avg Position Time (hrs) | 73.10 |
| Avg Trade Length | 3 |
| Last Trade Ago | 6 |
Leverage
| Daily leverage (average) | 2.67 |
|---|---|
| Daily leverage (max) | 5.93 |
Regression
| Alpha | 0.06 |
|---|---|
| Beta | 0.69 |
| Treynor Index | 0.14 |
Maximum Adverse Excursion (MAE)
| MAE:Equity, average, all trades | 0.03 |
|---|---|
| MAE:Equity, 95th Percentile Value for this strat | 0.02 |
| MAE:Equity, average, losing trades | 0.04 |
| MAE:Equity, losing trades only, 95th Percentile Value for this strat | — |
| MAE:Equity, average, winning trades | 0.02 |
| MAE:Equity, win trades only, 95th Percentile Value for this strat | — |
| Avg(MAE) / Avg(PL) - All trades | -4.55 |
| MAE:PL (avg, all trades) | 1.04 |
| MAE:PL (avg, losing trades) | — |
| MAE:PL - Winning Trades - this strat Percentile of All Strats | 95.33 |
| MAE:PL (avg, winning trades) | — |
| MAE:PL - worst single value for strategy | — |
| Avg(MAE) / Avg(PL) - Winning trades | 0.53 |
| Avg(MAE) / Avg(PL) - Losing trades | -1.23 |
| Hold-and-Hope Ratio | -0.22 |
RATIO STATISTICS
| Mean | 0.42 |
|---|---|
| SD | 0.47 |
| Sharpe ratio (Glass type estimate) | 0.89 |
| Sharpe ratio (Hedges UMVUE) | 0.88 |
| df | 75 |
| t | 2.24 |
| p | 0.01 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0.10 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.68 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.09 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.67 |
| Sortino ratio | 1.60 |
| Upside Potential Ratio | 3.35 |
| Upside part of mean | 0.87 |
| Downside part of mean | -0.46 |
| Upside SD | 0.40 |
| Downside SD | 0.26 |
| N nonnegative terms | 46 |
| N negative terms | 30 |
| N of observations | 76 |
| Mean of predictor | 0.15 |
| Mean of criterion | 0.42 |
| SD of predictor | 0.15 |
| SD of criterion | 0.47 |
| Covariance | 0.03 |
| r | 0.44 |
| b (slope, estimate of beta) | 1.41 |
| a (intercept, estimate of alpha) | 0.20 |
| Mean Square Error | 0.18 |
| DF error | 74 |
| t(b) | 4.21 |
| p(b) | 0.00 |
| t(a) | 1.14 |
| p(a) | 0.13 |
| Lowerbound of 95% confidence interval for beta | 0.74 |
| Upperbound of 95% confidence interval for beta | 2.08 |
| Lowerbound of 95% confidence interval for alpha | -0.15 |
| Upperbound of 95% confidence interval for alpha | 0.55 |
| Treynor index (mean / b) | 0.29 |
| Jensen alpha (a) | 0.20 |
| Mean | 0.31 |
| SD | 0.46 |
| Sharpe ratio (Glass type estimate) | 0.67 |
| Sharpe ratio (Hedges UMVUE) | 0.66 |
| df | 75 |
| t | 1.69 |
| p | 0.05 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -0.12 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.45 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -0.12 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.45 |
| Sortino ratio | 1.07 |
| Upside Potential Ratio | 2.79 |
| Upside part of mean | 0.80 |
| Downside part of mean | -0.49 |
| Upside SD | 0.36 |
| Downside SD | 0.29 |
| N nonnegative terms | 46 |
| N negative terms | 30 |
| N of observations | 76 |
| Mean of predictor | 0.14 |
| Mean of criterion | 0.31 |
| SD of predictor | 0.14 |
| SD of criterion | 0.46 |
| Covariance | 0.03 |
| r | 0.45 |
| b (slope, estimate of beta) | 1.42 |
| a (intercept, estimate of alpha) | 0.11 |
| Mean Square Error | 0.17 |
| DF error | 74 |
| t(b) | 4.31 |
| p(b) | 0.00 |
| t(a) | 0.62 |
| p(a) | 0.27 |
| Lowerbound of 95% confidence interval for beta | 0.76 |
| Upperbound of 95% confidence interval for beta | 2.08 |
| Lowerbound of 95% confidence interval for alpha | -0.23 |
| Upperbound of 95% confidence interval for alpha | 0.44 |
| Treynor index (mean / b) | 0.22 |
| Jensen alpha (a) | 0.11 |
| VaR(95%) | 0.17 |
| Expected Shortfall on VaR | 0.22 |
| VaR(95%) | 0.08 |
| Expected Shortfall on VaR | 0.15 |
| Mean | 0.38 |
| SD | 0.40 |
| Sharpe ratio (Glass type estimate) | 0.95 |
| Sharpe ratio (Hedges UMVUE) | 0.95 |
| df | 1673 |
| t | 2.40 |
| p | 0.46 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0.17 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.72 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.17 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.72 |
| Sortino ratio | 1.44 |
| Upside Potential Ratio | 9.60 |
| Upside part of mean | 2.50 |
| Downside part of mean | -2.13 |
| Upside SD | 0.30 |
| Downside SD | 0.26 |
| N nonnegative terms | 854 |
| N negative terms | 820 |
| N of observations | 1674 |
| Mean of predictor | 0.16 |
| Mean of criterion | 0.38 |
| SD of predictor | 0.18 |
| SD of criterion | 0.40 |
| Covariance | 0.02 |
| r | 0.26 |
| b (slope, estimate of beta) | 0.58 |
| a (intercept, estimate of alpha) | 0.29 |
| Mean Square Error | 0.15 |
| DF error | 1672 |
| t(b) | 10.85 |
| p(b) | 0.37 |
| t(a) | 1.89 |
| p(a) | 0.48 |
| Lowerbound of 95% confidence interval for beta | 0.47 |
| Upperbound of 95% confidence interval for beta | 0.68 |
| Lowerbound of 95% confidence interval for alpha | -0.01 |
| Upperbound of 95% confidence interval for alpha | 0.58 |
| Treynor index (mean / b) | 0.65 |
| Jensen alpha (a) | 0.29 |
| Mean | 0.30 |
| SD | 0.40 |
| Sharpe ratio (Glass type estimate) | 0.75 |
| Sharpe ratio (Hedges UMVUE) | 0.75 |
| df | 1673 |
| t | 1.90 |
| p | 0.47 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -0.02 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.53 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -0.02 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.53 |
| Sortino ratio | 1.11 |
| Upside Potential Ratio | 9.19 |
| Upside part of mean | 2.46 |
| Downside part of mean | -2.16 |
| Upside SD | 0.29 |
| Downside SD | 0.27 |
| N nonnegative terms | 854 |
| N negative terms | 820 |
| N of observations | 1674 |
| Mean of predictor | 0.14 |
| Mean of criterion | 0.30 |
| SD of predictor | 0.18 |
| SD of criterion | 0.40 |
| Covariance | 0.02 |
| r | 0.26 |
| b (slope, estimate of beta) | 0.58 |
| a (intercept, estimate of alpha) | 0.22 |
| Mean Square Error | 0.15 |
| DF error | 1672 |
| t(b) | 10.84 |
| p(b) | 0.37 |
| t(a) | 1.43 |
| p(a) | 0.48 |
| Lowerbound of 95% confidence interval for beta | 0.47 |
| Upperbound of 95% confidence interval for beta | 0.68 |
| Lowerbound of 95% confidence interval for alpha | -0.08 |
| Upperbound of 95% confidence interval for alpha | 0.51 |
| Treynor index (mean / b) | 0.52 |
| Jensen alpha (a) | 0.22 |
| VaR(95%) | 0.04 |
| Expected Shortfall on VaR | 0.05 |
| VaR(95%) | 0.02 |
| Expected Shortfall on VaR | 0.04 |
| Mean | 0.06 |
| SD | 0.27 |
| Sharpe ratio (Glass type estimate) | 0.20 |
| Sharpe ratio (Hedges UMVUE) | 0.20 |
| df | 130 |
| t | 0.14 |
| p | 0.49 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -2.57 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 2.98 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -2.57 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 2.98 |
| Sortino ratio | 0.31 |
| Upside Potential Ratio | 9.52 |
| Upside part of mean | 1.70 |
| Downside part of mean | -1.65 |
| Upside SD | 0.20 |
| Downside SD | 0.18 |
| N nonnegative terms | 66 |
| N negative terms | 65 |
| N of observations | 131 |
| Mean of predictor | 0.23 |
| Mean of criterion | 0.06 |
| SD of predictor | 0.14 |
| SD of criterion | 0.27 |
| Covariance | 0.02 |
| r | 0.44 |
| b (slope, estimate of beta) | 0.86 |
| a (intercept, estimate of alpha) | -0.14 |
| Mean Square Error | 0.06 |
| DF error | 129 |
| t(b) | 5.49 |
| p(b) | 0.23 |
| t(a) | -0.40 |
| p(a) | 0.52 |
| Lowerbound of 95% confidence interval for beta | 0.55 |
| Upperbound of 95% confidence interval for beta | 1.17 |
| Lowerbound of 95% confidence interval for alpha | -0.83 |
| Upperbound of 95% confidence interval for alpha | 0.55 |
| Treynor index (mean / b) | 0.06 |
| Jensen alpha (a) | -0.14 |
| Mean | 0.02 |
| SD | 0.27 |
| Sharpe ratio (Glass type estimate) | 0.07 |
| Sharpe ratio (Hedges UMVUE) | 0.07 |
| df | 130 |
| t | 0.05 |
| p | 0.50 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -2.70 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 2.84 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -2.70 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 2.84 |
| Sortino ratio | 0.11 |
| Upside Potential Ratio | 9.28 |
| Upside part of mean | 1.68 |
| Downside part of mean | -1.66 |
| Upside SD | 0.20 |
| Downside SD | 0.18 |
| N nonnegative terms | 66 |
| N negative terms | 65 |
| N of observations | 131 |
| Mean of predictor | 0.22 |
| Mean of criterion | 0.02 |
| SD of predictor | 0.14 |
| SD of criterion | 0.27 |
| Covariance | 0.02 |
| r | 0.44 |
| b (slope, estimate of beta) | 0.86 |
| a (intercept, estimate of alpha) | -0.17 |
| Mean Square Error | 0.06 |
| DF error | 129 |
| t(b) | 5.52 |
| p(b) | 0.23 |
| t(a) | -0.49 |
| p(a) | 0.53 |
| Lowerbound of 95% confidence interval for beta | 0.55 |
| VAR (95 Confidence Intrvl) | 0.04 |
| Upperbound of 95% confidence interval for beta | 1.17 |
| Lowerbound of 95% confidence interval for alpha | -0.86 |
| Upperbound of 95% confidence interval for alpha | 0.52 |
| Treynor index (mean / b) | 0.02 |
| Jensen alpha (a) | -0.17 |
| VaR(95%) | 0.03 |
| Expected Shortfall on VaR | 0.03 |
| VaR(95%) | 0.01 |
| Expected Shortfall on VaR | 0.03 |
ORDER STATISTICS
| Number of observations | 76 |
|---|---|
| Minimum | 0.74 |
| Quartile 1 | 0.95 |
| Median | 1.03 |
| Quartile 3 | 1.13 |
| Maximum | 1.33 |
| Mean of quarter 1 | 0.86 |
| Mean of quarter 2 | 0.99 |
| Mean of quarter 3 | 1.07 |
| Mean of quarter 4 | 1.22 |
| Inter Quartile Range | 0.18 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 0 |
| Percentage of outliers high | 0 |
| Mean of outliers high | 0 |
| Extreme Value Index (moments method) | -1.71 |
| VaR(95%) (moments method) | 0.12 |
| Expected Shortfall (moments method) | 0.12 |
| Extreme Value Index (regression method) | -0.52 |
| VaR(95%) (regression method) | 0.15 |
| Expected Shortfall (regression method) | 0.18 |
| Number of observations | 1674 |
| Minimum | 0.87 |
| Quartile 1 | 0.99 |
| Median | 1.00 |
| Quartile 3 | 1.01 |
| Maximum | 1.14 |
| Mean of quarter 1 | 0.97 |
| Mean of quarter 2 | 0.99 |
| Mean of quarter 3 | 1.01 |
| Mean of quarter 4 | 1.03 |
| Inter Quartile Range | 0.03 |
| Number outliers low | 32 |
| Percentage of outliers low | 0.02 |
| Mean of outliers low | 0.93 |
| Number of outliers high | 51 |
| Percentage of outliers high | 0.03 |
| Mean of outliers high | 1.07 |
| Extreme Value Index (moments method) | 0.14 |
| VaR(95%) (moments method) | 0.03 |
| Expected Shortfall (moments method) | 0.04 |
| Extreme Value Index (regression method) | 0.07 |
| VaR(95%) (regression method) | 0.03 |
| Expected Shortfall (regression method) | 0.03 |
| Number of observations | 131 |
| Minimum | 0.96 |
| Quartile 1 | 0.99 |
| Median | 1.00 |
| Quartile 3 | 1.01 |
| Maximum | 1.05 |
| Mean of quarter 1 | 0.98 |
| Mean of quarter 2 | 0.99 |
| Mean of quarter 3 | 1.00 |
| Mean of quarter 4 | 1.02 |
| Inter Quartile Range | 0.02 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 3 |
| Percentage of outliers high | 0.02 |
| Mean of outliers high | 1.05 |
| Extreme Value Index (moments method) | 0.04 |
| VaR(95%) (moments method) | 0.02 |
| Expected Shortfall (moments method) | 0.03 |
| Extreme Value Index (regression method) | 0.16 |
| VaR(95%) (regression method) | 0.02 |
| Expected Shortfall (regression method) | 0.03 |
DRAW DOWN STATISTICS
| Number of observations | 7 |
|---|---|
| Minimum | 0.02 |
| Quartile 1 | 0.07 |
| Median | 0.28 |
| Quartile 3 | 0.38 |
| Maximum | 0.43 |
| Mean of quarter 1 | 0.04 |
| Mean of quarter 2 | 0.18 |
| Mean of quarter 3 | 0.37 |
| Mean of quarter 4 | 0.41 |
| Inter Quartile Range | 0.32 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 0 |
| Percentage of outliers high | 0 |
| Mean of outliers high | 0 |
| Extreme Value Index (moments method) | 0 |
| VaR(95%) (moments method) | 0 |
| Expected Shortfall (moments method) | 0 |
| Extreme Value Index (regression method) | 0 |
| VaR(95%) (regression method) | 0 |
| Expected Shortfall (regression method) | 0 |
| Number of observations | 63 |
| Minimum | 0.00 |
| Quartile 1 | 0.01 |
| Median | 0.04 |
| Quartile 3 | 0.09 |
| Maximum | 0.51 |
| Mean of quarter 1 | 0.00 |
| Mean of quarter 2 | 0.02 |
| Mean of quarter 3 | 0.07 |
| Mean of quarter 4 | 0.21 |
| Inter Quartile Range | 0.08 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 5 |
| Percentage of outliers high | 0.08 |
| Mean of outliers high | 0.39 |
| Extreme Value Index (moments method) | 0.46 |
| VaR(95%) (moments method) | 0.23 |
| Expected Shortfall (moments method) | 0.47 |
| Extreme Value Index (regression method) | 0.47 |
| VaR(95%) (regression method) | 0.19 |
| Expected Shortfall (regression method) | 0.35 |
| Number of observations | 7 |
| Minimum | 0.02 |
| Quartile 1 | 0.03 |
| Median | 0.04 |
| Quartile 3 | 0.09 |
| Maximum | 0.20 |
| Mean of quarter 1 | 0.02 |
| Mean of quarter 2 | 0.04 |
| Mean of quarter 3 | 0.05 |
| Mean of quarter 4 | 0.17 |
| Inter Quartile Range | 0.06 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 1 |
| Percentage of outliers high | 0.14 |
| Mean of outliers high | 0.20 |
| Extreme Value Index (moments method) | 0 |
| VaR(95%) (moments method) | 0 |
| Expected Shortfall (moments method) | 0 |
| Extreme Value Index (regression method) | 0 |
| VaR(95%) (regression method) | 0 |
| Expected Shortfall (regression method) | 0 |
| Strat Max DD how much worse than SP500 max DD during strat life? | -404702592 |
| Max Equity Drawdown (num days) | 271 |
| Last 4 Months - Pcnt Negative | 1.0% |
COMBINED STATISTICS
| Annualized return (arithmetic extrapolation) | 1.16 |
|---|---|
| Compounded annual return (geometric extrapolation) | 0.40 |
| Calmar ratio (compounded annual return / max draw down) | 0.93 |
| Compounded annual return / average of 25% largest draw downs | 0.97 |
| Compounded annual return / Expected Shortfall lognormal | 1.82 |
| j156mfCOMBRisPar | 0 |
| j157mfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 1.10 |
| Compounded annual return (geometric extrapolation) | 0.39 |
| Calmar ratio (compounded annual return / max draw down) | 0.75 |
| Compounded annual return / average of 25% largest draw downs | 1.86 |
| Compounded annual return / Expected Shortfall lognormal | 8.01 |
| j313dfCOMBRisPar | 0 |
| j314dfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 0.05 |
| Compounded annual return (geometric extrapolation) | 0.05 |
| Calmar ratio (compounded annual return / max draw down) | 0.24 |
| Compounded annual return / average of 25% largest draw downs | 0.29 |
| Compounded annual return / Expected Shortfall lognormal | 1.42 |
Trading record
Placed 1665 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| TQQQ | long | 225 | Sep 1, 2026 | Sep 2, 2026 | $118 |
| TQQQ | long | 225 | Aug 27, 2026 | Sep 1, 2026 | ($982) |
| SQQQ | long | 436 | Aug 27, 2026 | Aug 27, 2026 | ($265) |
| TQQQ | long | 232 | Aug 19, 2026 | Aug 27, 2026 | $72 |
| TQQQ | long | 234 | Aug 12, 2026 | Aug 19, 2026 | ($782) |
| SQQQ | long | 458 | Aug 10, 2026 | Aug 11, 2026 | $314 |
| TQQQ | long | 230 | Aug 4, 2026 | Aug 10, 2026 | ($88) |
| SQQQ | long | 451 | Aug 4, 2026 | Aug 4, 2026 | ($770) |
| TQQQ | long | 266 | Aug 3, 2026 | Aug 3, 2026 | $865 |
| SQQQ | long | 386 | Jul 30, 2026 | Jul 30, 2026 | ($775) |
| TQQQ | long | 293 | Jul 29, 2026 | Jul 30, 2026 | $955 |
| TQQQ | long | 286 | Jul 27, 2026 | Jul 29, 2026 | ($1,177) |
| TQQQ | long | 293 | Jul 24, 2026 | Jul 27, 2026 | ($329) |
| SQQQ | long | 433 | Jul 22, 2026 | Jul 23, 2026 | $1,072 |
| TQQQ | long | 251 | Jul 22, 2026 | Jul 22, 2026 | $133 |
| TQQQ | long | 245 | Jul 16, 2026 | Jul 21, 2026 | $230 |
| TQQQ | long | 235 | Jul 9, 2026 | Jul 15, 2026 | ($628) |
| SQQQ | long | 471 | Jul 9, 2026 | Jul 9, 2026 | ($472) |
| TQQQ | long | 246 | Jul 8, 2026 | Jul 9, 2026 | $409 |
| TQQQ | long | 252 | Jul 7, 2026 | Jul 8, 2026 | ($246) |
| TQQQ | long | 263 | Jul 2, 2026 | Jul 7, 2026 | $113 |
| TQQQ | long | 248 | Jun 30, 2026 | Jul 1, 2026 | ($997) |
| SQQQ | long | 556 | Jun 30, 2026 | Jun 30, 2026 | ($1,007) |
| TQQQ | long | 273 | Jun 29, 2026 | Jun 30, 2026 | $52 |
| TQQQ | long | 294 | Jun 25, 2026 | Jun 29, 2026 | ($755) |
| SQQQ | long | 557 | Jun 25, 2026 | Jun 25, 2026 | $981 |
| TQQQ | long | 291 | Jun 23, 2026 | Jun 24, 2026 | ($752) |
| TQQQ | long | 291 | Jun 18, 2026 | Jun 23, 2026 | ($2,549) |
| SQQQ | long | 663 | Jun 18, 2026 | Jun 18, 2026 | ($396) |
| TQQQ | long | 301 | Jun 17, 2026 | Jun 18, 2026 | $1,430 |
Past results are not necessarily indicative of future results.
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical 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 profits or losses similar to these being shown.