SP 500 Futures Scalper
Trades Own Strategy BrokerTransmit
- hypothetical · Annual Return (Compounded)
- -5.7%
- Max Drawdown
- 46.7%
- Trades
- 601
- Win Trades
- 62.7%
- Profit Factor
- 1
- Win Months
- 20.0%
About this strategy
ANY CALENDAR MONTH THIS STRATEGY DOES NOT RETURN POSITIVE ROI (as reported by C2) CURRENT SUBSCRIBERS WILL GET THEIR NEXT MONTH FREE.
Strategy details, discussion and updates are here: https://forums.collective2.com/t/sp-500-futures-scalper-2024-new-ath-and-50-off/
SP 500 Futures Scalper opens long and short positions in futures markets trading S&P 500 E-Mini and Micro E-Mini futures contracts. It is designed for account balances of at least USD$60,000. The maximum position is three E-Mini contracts (or thirty Micro E-Mini contracts).
- I trade this strategy live in my own Interactive Brokers account. Every trade is posted using C2 BrokerTransmit, and is a trade I have executed. What you trade, I trade.
- On the backend, this strategy is actually a collection of independent “long only” and “short only” strategies. So C2’s BrokerTransmit system does not break, long positions trade Micro E-Mini contracts, and short positions trade E-Mini contracts.
- This strategy is AI generated and tuned weekly (over the weekend).
- This strategy is 100% automated and run 24x5. I NEVER place a manual order, or override an automated order.
- My tuning and trading servers are beefy dedicated physical servers (not virtual machines) sitting in a data center in New Jersey with <2ms latency to Interactive Brokers. I’m not running this out of my basement or off of my laptop.
- Collective2 is not my full-time gig, but automated algorithmic trading has been my full-time gig for the last six years.
This strategy was generated using genetic algorithm AI and opens a position only when a convergence of technical indicator values result in an acceptable trade setup, and then calculates aggressive take profit exits, ideal for volatile markets with frequent sentiment-driven intraday reversals that destroy most day-trading strategies. The manager has traded this strategy live since May 2022 with their own funds through their broker.
ALL RECORDED TRADES IN TRADE RECORD ARE LIVE TRADES IN THE MANAGER’S OWN ACCOUNT. In other words, I’m trading MY money with this strategy, not just yours. C2 trade signals are generated by mirroring the trades in my live Interactive Brokers account.
Strategy details, discussion and updates are here: https://forums.collective2.com/t/sp-500-futures-scalper-2024-new-ath-and-50-off/
SP 500 Futures Scalper opens long and short positions in futures markets trading S&P 500 E-Mini and Micro E-Mini futures contracts. It is designed for account balances of at least USD$60,000. The maximum position is three E-Mini contracts (or thirty Micro E-Mini contracts).
- I trade this strategy live in my own Interactive Brokers account. Every trade is posted using C2 BrokerTransmit, and is a trade I have executed. What you trade, I trade.
- On the backend, this strategy is actually a collection of independent “long only” and “short only” strategies. So C2’s BrokerTransmit system does not break, long positions trade Micro E-Mini contracts, and short positions trade E-Mini contracts.
- This strategy is AI generated and tuned weekly (over the weekend).
- This strategy is 100% automated and run 24x5. I NEVER place a manual order, or override an automated order.
- My tuning and trading servers are beefy dedicated physical servers (not virtual machines) sitting in a data center in New Jersey with <2ms latency to Interactive Brokers. I’m not running this out of my basement or off of my laptop.
- Collective2 is not my full-time gig, but automated algorithmic trading has been my full-time gig for the last six years.
This strategy was generated using genetic algorithm AI and opens a position only when a convergence of technical indicator values result in an acceptable trade setup, and then calculates aggressive take profit exits, ideal for volatile markets with frequent sentiment-driven intraday reversals that destroy most day-trading strategies. The manager has traded this strategy live since May 2022 with their own funds through their broker.
ALL RECORDED TRADES IN TRADE RECORD ARE LIVE TRADES IN THE MANAGER’S OWN ACCOUNT. In other words, I’m trading MY money with this strategy, not just yours. C2 trade signals are generated by mirroring the trades in my live Interactive Brokers account.
Short Term
Hypothetical Monthly Returns (includes fees/commissions)
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023 | -4.0 | -3.2 | 7.1 | 8.4 | 3.8 | 11.4 | 9.7 | 5.6 | -14.9 | -8.7 | 11.4 | 2.4 | 28.0 |
| 2024 | 15.3 | -4.1 | -2.7 | -12.4 | -18.9 | -17.4 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -36.8 |
| 2025 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 2026 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Statistics
Overview
| Strategy began | 1/17/2023 |
|---|---|
| Suggested Minimum Capital | $50,000 |
| Age | 44 months |
| What it trades | Futures |
| # Trades | 601 |
| # Profitable | 377 |
| % Profitable | 62.7% |
| Avg trade duration | 8.6 hours |
| Max peak-to-valley drawdown | 46.7% |
| drawdown period | Jan 29, 2024 - June 30, 2024 |
| Annual Return (Compounded) | -5.7% |
| Avg win | $619 |
| Avg loss | $1,023 |
Ratios
| W:L ratio | 1.02 |
|---|---|
| Sharpe Ratio | -0.24 |
| Sortino Ratio | -0.31 |
| Calmar Ratio | 0.10 |
CORRELATION STATISTICS
| Correlation to SP500 | 0.14 |
|---|---|
| Return Percent SP500 (cumu) during strategy life | 91.5% |
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | -112.6% |
Return Statistics
| Ann Return (w trading costs) | -5.7% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | -0.1% |
| Ann Return (Compnd, No Fees) | 2.3% |
Slump
| Current Slump as Pcnt Equity | 87.7% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 0.7% |
Instruments
| Percent Trades Forex | 0.0% |
|---|---|
| Percent Trades Futures | 1.0% |
| Percent Trades Options | 0.0% |
| Short Options - Percent Covered | 100.0% |
| Percent Trades Stocks | 0.0% |
Risk of Ruin (Monte-Carlo)
| Chance of 10% account loss | 77.0% |
|---|---|
| Chance of 20% account loss | 39.5% |
| Chance of 30% account loss | 13.5% |
| Chance of 40% account loss | 3.0% |
| Chance of 50% account loss | 0.0% |
| Chance of 60% account loss (Monte Carlo) | 0.0% |
| 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% |
Automation
| Percentage Signals Automated | 0.0% |
|---|
Popularity
| Popularity (Today) | 0 |
|---|---|
| Popularity (Last 6 weeks) | 446 |
| Popularity (7 days, Percentile 1000 scale) | 0 |
Trading Style
| Any stock shorts? 0/1 | 0 |
|---|
Trades-Own-System Certification
| Trades Own System? | 186342 |
|---|---|
| TOS percent | 100.0% |
Win / Loss
| Avg Loss | $1,023 |
|---|---|
| Avg Win | $619 |
| # Winners | 377 |
| Sum Trade PL (losers) | $229,084 |
| Sum Trade PL (winners) | $233,343 |
| Num Months Winners | 9 |
| # Losers | 224 |
| % Winners | 62.7% |
Dividends
| Dividends Received in Model Acct | 0 |
|---|
Age
| Num Months filled monthly returns table | 45 |
|---|
Frequency
| Avg Position Time (mins) | 515.40 |
|---|---|
| Avg Position Time (hrs) | 8.59 |
| Avg Trade Length | 0.40 |
| Last Trade Ago | 799 |
Leverage
| Daily leverage (average) | 7.27 |
|---|---|
| Daily leverage (max) | 28.62 |
Regression
| Alpha | -0.02 |
|---|---|
| Beta | 0.19 |
| Treynor Index | -0.08 |
Maximum Adverse Excursion (MAE)
| MAE:Equity, average, all trades | 0.01 |
|---|---|
| MAE:Equity, 95th Percentile Value for this strat | 0.01 |
| MAE:Equity, average, losing trades | 0.02 |
| MAE:Equity, losing trades only, 95th Percentile Value for this strat | — |
| MAE:Equity, average, winning trades | 0.01 |
| MAE:Equity, win trades only, 95th Percentile Value for this strat | — |
| Avg(MAE) / Avg(PL) - All trades | -26.93 |
| MAE:PL (avg, all trades) | 0.32 |
| MAE:PL (avg, losing trades) | — |
| MAE:PL (avg, winning trades) | — |
| MAE:PL - worst single value for strategy | — |
| Avg(MAE) / Avg(PL) - Winning trades | 0.81 |
| Avg(MAE) / Avg(PL) - Losing trades | -1.16 |
| Hold-and-Hope Ratio | -0.04 |
RATIO STATISTICS
| Mean | 0.03 |
|---|---|
| SD | 0.23 |
| Sharpe ratio (Glass type estimate) | 0.14 |
| Sharpe ratio (Hedges UMVUE) | 0.13 |
| df | 28 |
| t | 0.21 |
| p | 0.42 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -1.13 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.40 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.13 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.39 |
| Sortino ratio | 0.19 |
| Upside Potential Ratio | 1.75 |
| Upside part of mean | 0.29 |
| Downside part of mean | -0.25 |
| Upside SD | 0.15 |
| Downside SD | 0.16 |
| N nonnegative terms | 10 |
| N negative terms | 19 |
| N of observations | 29 |
| Mean of predictor | 0.19 |
| Mean of criterion | 0.03 |
| SD of predictor | 0.12 |
| SD of criterion | 0.23 |
| Covariance | 0.01 |
| r | 0.26 |
| b (slope, estimate of beta) | 0.51 |
| a (intercept, estimate of alpha) | -0.07 |
| Mean Square Error | 0.05 |
| DF error | 27 |
| t(b) | 1.43 |
| p(b) | 0.08 |
| t(a) | -0.43 |
| p(a) | 0.66 |
| Lowerbound of 95% confidence interval for beta | -0.23 |
| Upperbound of 95% confidence interval for beta | 1.25 |
| Lowerbound of 95% confidence interval for alpha | -0.39 |
| Upperbound of 95% confidence interval for alpha | 0.26 |
| Treynor index (mean / b) | 0.06 |
| Jensen alpha (a) | -0.07 |
| Mean | 0.01 |
| SD | 0.23 |
| Sharpe ratio (Glass type estimate) | 0.02 |
| Sharpe ratio (Hedges UMVUE) | 0.02 |
| df | 28 |
| t | 0.04 |
| p | 0.48 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -1.24 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.29 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.24 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.28 |
| Sortino ratio | 0.03 |
| Upside Potential Ratio | 1.57 |
| Upside part of mean | 0.27 |
| Downside part of mean | -0.27 |
| Upside SD | 0.14 |
| Downside SD | 0.17 |
| N nonnegative terms | 10 |
| N negative terms | 19 |
| N of observations | 29 |
| Mean of predictor | 0.18 |
| Mean of criterion | 0.01 |
| SD of predictor | 0.12 |
| SD of criterion | 0.23 |
| Covariance | 0.01 |
| r | 0.25 |
| b (slope, estimate of beta) | 0.50 |
| a (intercept, estimate of alpha) | -0.09 |
| Mean Square Error | 0.05 |
| DF error | 27 |
| t(b) | 1.35 |
| p(b) | 0.09 |
| t(a) | -0.54 |
| p(a) | 0.70 |
| Lowerbound of 95% confidence interval for beta | -0.26 |
| Upperbound of 95% confidence interval for beta | 1.26 |
| Lowerbound of 95% confidence interval for alpha | -0.42 |
| Upperbound of 95% confidence interval for alpha | 0.24 |
| Treynor index (mean / b) | 0.01 |
| Jensen alpha (a) | -0.09 |
| VaR(95%) | 0.10 |
| Expected Shortfall on VaR | 0.13 |
| VaR(95%) | 0.06 |
| Expected Shortfall on VaR | 0.11 |
| Mean | 0.03 |
| SD | 0.21 |
| Sharpe ratio (Glass type estimate) | 0.13 |
| Sharpe ratio (Hedges UMVUE) | 0.13 |
| df | 651 |
| t | 0.20 |
| p | 0.42 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -1.11 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.37 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.11 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.37 |
| Sortino ratio | 0.17 |
| Upside Potential Ratio | 5.68 |
| Upside part of mean | 0.91 |
| Downside part of mean | -0.88 |
| Upside SD | 0.13 |
| Downside SD | 0.16 |
| N nonnegative terms | 196 |
| N negative terms | 456 |
| N of observations | 652 |
| Mean of predictor | 0.25 |
| Mean of criterion | 0.03 |
| SD of predictor | 0.17 |
| SD of criterion | 0.21 |
| Covariance | 0.01 |
| r | 0.16 |
| b (slope, estimate of beta) | 0.20 |
| a (intercept, estimate of alpha) | -0.02 |
| Mean Square Error | 0.04 |
| DF error | 650 |
| t(b) | 4.00 |
| p(b) | 0.00 |
| t(a) | -0.17 |
| p(a) | 0.57 |
| Lowerbound of 95% confidence interval for beta | 0.10 |
| Upperbound of 95% confidence interval for beta | 0.29 |
| Lowerbound of 95% confidence interval for alpha | -0.28 |
| Upperbound of 95% confidence interval for alpha | 0.24 |
| Treynor index (mean / b) | 0.14 |
| Jensen alpha (a) | -0.02 |
| Mean | 0.00 |
| SD | 0.21 |
| Sharpe ratio (Glass type estimate) | 0.02 |
| Sharpe ratio (Hedges UMVUE) | 0.02 |
| df | 651 |
| t | 0.04 |
| p | 0.49 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -1.22 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.26 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.22 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.26 |
| Sortino ratio | 0.03 |
| Upside Potential Ratio | 5.45 |
| Upside part of mean | 0.90 |
| Downside part of mean | -0.90 |
| Upside SD | 0.13 |
| Downside SD | 0.17 |
| N nonnegative terms | 196 |
| N negative terms | 456 |
| N of observations | 652 |
| Mean of predictor | 0.24 |
| Mean of criterion | 0.00 |
| SD of predictor | 0.16 |
| SD of criterion | 0.21 |
| Covariance | 0.01 |
| r | 0.15 |
| b (slope, estimate of beta) | 0.20 |
| a (intercept, estimate of alpha) | -0.04 |
| Mean Square Error | 0.04 |
| DF error | 650 |
| t(b) | 3.93 |
| p(b) | 0.00 |
| t(a) | -0.32 |
| p(a) | 0.62 |
| Lowerbound of 95% confidence interval for beta | 0.10 |
| Upperbound of 95% confidence interval for beta | 0.29 |
| Lowerbound of 95% confidence interval for alpha | -0.30 |
| Upperbound of 95% confidence interval for alpha | 0.22 |
| Treynor index (mean / b) | 0.02 |
| Jensen alpha (a) | -0.04 |
| VaR(95%) | 0.02 |
| Expected Shortfall on VaR | 0.03 |
| VaR(95%) | 0.01 |
| Expected Shortfall on VaR | 0.02 |
| Mean | -0.03 |
| SD | 0 |
| Sharpe ratio (Glass type estimate) | 0 |
| Sharpe ratio (Hedges UMVUE) | 0 |
| df | 0 |
| t | 0 |
| p | 0 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 0 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0 |
| Sortino ratio | -16.19 |
| Upside Potential Ratio | 0 |
| Upside part of mean | 0 |
| Downside part of mean | -0.03 |
| Upside SD | 0 |
| Downside SD | 0.00 |
| N nonnegative terms | 0 |
| N negative terms | 131 |
| N of observations | 131 |
| Mean of predictor | 0.62 |
| Mean of criterion | -0.03 |
| SD of predictor | 0.26 |
| SD of criterion | 0 |
| Covariance | 0 |
| r | 0 |
| b (slope, estimate of beta) | 0 |
| a (intercept, estimate of alpha) | 0 |
| Mean Square Error | 0 |
| DF error | 0 |
| t(b) | 0 |
| p(b) | 0 |
| t(a) | 0 |
| p(a) | 0 |
| Lowerbound of 95% confidence interval for beta | 0 |
| Upperbound of 95% confidence interval for beta | 0 |
| Lowerbound of 95% confidence interval for alpha | 0 |
| Upperbound of 95% confidence interval for alpha | 0 |
| Treynor index (mean / b) | 0 |
| Jensen alpha (a) | 0 |
| Mean | -0.03 |
| SD | 0 |
| Sharpe ratio (Glass type estimate) | -9.74841826823373e+15 |
| Sharpe ratio (Hedges UMVUE) | -9.69206937105203e+15 |
| df | 130 |
| t | -6893172865105920 |
| p | 1 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 0 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.08701574255084e+16 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | -8513981316595712 |
| Sortino ratio | -16.19 |
| Upside Potential Ratio | 0 |
| Upside part of mean | 0 |
| Downside part of mean | -0.03 |
| Upside SD | 0 |
| Downside SD | 0.00 |
| N nonnegative terms | 0 |
| N negative terms | 131 |
| N of observations | 131 |
| Mean of predictor | 0.59 |
| Mean of criterion | -0.03 |
| SD of predictor | 0.26 |
| SD of criterion | 0 |
| Covariance | 0 |
| r | 0 |
| b (slope, estimate of beta) | 0 |
| a (intercept, estimate of alpha) | -0.03 |
| Mean Square Error | 0 |
| DF error | 129 |
| t(b) | 0 |
| p(b) | 0.50 |
| t(a) | -6796814200078336 |
| p(a) | 1 |
| Lowerbound of 95% confidence interval for beta | 0 |
| VAR (95 Confidence Intrvl) | 0.02 |
| Upperbound of 95% confidence interval for beta | 0 |
| Lowerbound of 95% confidence interval for alpha | -0.03 |
| Upperbound of 95% confidence interval for alpha | -0.03 |
| Treynor index (mean / b) | 4.60478829193524e+31 |
| Jensen alpha (a) | -0.03 |
| VaR(95%) | 0.00 |
| Expected Shortfall on VaR | 0.00 |
| VaR(95%) | 0 |
| Expected Shortfall on VaR | 0 |
ORDER STATISTICS
| Number of observations | 29 |
|---|---|
| Minimum | 0.85 |
| Quartile 1 | 0.98 |
| Median | 1 |
| Quartile 3 | 1.05 |
| Maximum | 1.11 |
| Mean of quarter 1 | 0.93 |
| Mean of quarter 2 | 1 |
| Mean of quarter 3 | 1.02 |
| Mean of quarter 4 | 1.08 |
| Inter Quartile Range | 0.07 |
| Number outliers low | 2 |
| Percentage of outliers low | 0.07 |
| Mean of outliers low | 0.86 |
| Number of outliers high | 0 |
| Percentage of outliers high | 0 |
| Mean of outliers high | 0 |
| Extreme Value Index (moments method) | 0.62 |
| VaR(95%) (moments method) | 0.08 |
| Expected Shortfall (moments method) | 0.23 |
| Extreme Value Index (regression method) | 0.14 |
| VaR(95%) (regression method) | 0.08 |
| Expected Shortfall (regression method) | 0.13 |
| Number of observations | 652 |
| Minimum | 0.86 |
| Quartile 1 | 1.00 |
| Median | 1 |
| Quartile 3 | 1.00 |
| Maximum | 1.06 |
| Mean of quarter 1 | 0.99 |
| Mean of quarter 2 | 1 |
| Mean of quarter 3 | 1.00 |
| Mean of quarter 4 | 1.01 |
| Inter Quartile Range | 0.00 |
| Number outliers low | 114 |
| Percentage of outliers low | 0.17 |
| Mean of outliers low | 0.98 |
| Number of outliers high | 110 |
| Percentage of outliers high | 0.17 |
| Mean of outliers high | 1.02 |
| Extreme Value Index (moments method) | -0.13 |
| VaR(95%) (moments method) | 0.00 |
| Expected Shortfall (moments method) | 0.01 |
| Extreme Value Index (regression method) | -0.02 |
| VaR(95%) (regression method) | 0.01 |
| Expected Shortfall (regression method) | 0.02 |
| Number of observations | 131 |
| Minimum | 1 |
| Quartile 1 | 1 |
| Median | 1 |
| Quartile 3 | 1 |
| Maximum | 1 |
| Mean of quarter 1 | 1 |
| Mean of quarter 2 | 1 |
| Mean of quarter 3 | 1 |
| Mean of quarter 4 | 1 |
| Inter Quartile Range | 0 |
| 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 |
DRAW DOWN STATISTICS
| Number of observations | 4 |
|---|---|
| Minimum | 0.02 |
| Quartile 1 | 0.03 |
| Median | 0.08 |
| Quartile 3 | 0.18 |
| Maximum | 0.34 |
| Mean of quarter 1 | 0.02 |
| Mean of quarter 2 | 0.03 |
| Mean of quarter 3 | 0.13 |
| Mean of quarter 4 | 0.34 |
| Inter Quartile Range | 0.15 |
| 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 | 19 |
| Minimum | 0.00 |
| Quartile 1 | 0.00 |
| Median | 0.03 |
| Quartile 3 | 0.07 |
| Maximum | 0.35 |
| Mean of quarter 1 | 0.00 |
| Mean of quarter 2 | 0.01 |
| Mean of quarter 3 | 0.06 |
| 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 | 2 |
| Percentage of outliers high | 0.11 |
| Mean of outliers high | 0.28 |
| Extreme Value Index (moments method) | -0.03 |
| VaR(95%) (moments method) | 0.16 |
| Expected Shortfall (moments method) | 0.21 |
| Extreme Value Index (regression method) | 0.46 |
| VaR(95%) (regression method) | 0.26 |
| Expected Shortfall (regression method) | 0.58 |
| Number of observations | 0 |
| Minimum | 0 |
| Quartile 1 | 0 |
| Median | 0 |
| Quartile 3 | 0 |
| Maximum | 0 |
| Mean of quarter 1 | 0 |
| Mean of quarter 2 | 0 |
| Mean of quarter 3 | 0 |
| Mean of quarter 4 | 0 |
| Inter Quartile Range | 0 |
| 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 |
| Strat Max DD how much worse than SP500 max DD during strat life? | -438765408 |
| Max Equity Drawdown (num days) | 153 |
| Last 4 Months - Pcnt Negative | 0.0% |
COMBINED STATISTICS
| Annualized return (arithmetic extrapolation) | 0.04 |
|---|---|
| Compounded annual return (geometric extrapolation) | 0.03 |
| Calmar ratio (compounded annual return / max draw down) | 0.10 |
| Compounded annual return / average of 25% largest draw downs | 0.10 |
| Compounded annual return / Expected Shortfall lognormal | 0.27 |
| j156mfCOMBRisPar | 0 |
| j157mfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 0.03 |
| Compounded annual return (geometric extrapolation) | 0.03 |
| Calmar ratio (compounded annual return / max draw down) | 0.10 |
| Compounded annual return / average of 25% largest draw downs | 0.20 |
| Compounded annual return / Expected Shortfall lognormal | 1.25 |
| j313dfCOMBRisPar | 0 |
| j314dfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 0 |
| Compounded annual return (geometric extrapolation) | 0 |
| Calmar ratio (compounded annual return / max draw down) | 0 |
| Compounded annual return / average of 25% largest draw downs | 0 |
| Compounded annual return / Expected Shortfall lognormal | 0 |
Trading record
Placed 1948 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| ES U4 | short | 3 | Jun 28, 2024 | Jun 28, 2024 | $2,151 |
| MES U4 | long | 4 | Jun 28, 2024 | Jun 28, 2024 | ($425) |
| MES U4 | long | 6 | Jun 28, 2024 | Jun 28, 2024 | ($307) |
| MES U4 | long | 8 | Jun 27, 2024 | Jun 28, 2024 | ($140) |
| MES U4 | long | 12 | Jun 27, 2024 | Jun 27, 2024 | ($292) |
| MES U4 | long | 4 | Jun 27, 2024 | Jun 27, 2024 | $80 |
| ES U4 | short | 4 | Jun 26, 2024 | Jun 27, 2024 | ($620) |
| MES U4 | long | 22 | Jun 26, 2024 | Jun 26, 2024 | ($606) |
| MES U4 | long | 8 | Jun 26, 2024 | Jun 26, 2024 | ($485) |
| MES U4 | long | 18 | Jun 25, 2024 | Jun 26, 2024 | $1,299 |
| ES U4 | short | 3 | Jun 25, 2024 | Jun 25, 2024 | ($2,687) |
| MES U4 | long | 6 | Jun 25, 2024 | Jun 25, 2024 | ($307) |
| MES U4 | long | 8 | Jun 24, 2024 | Jun 24, 2024 | ($190) |
| MES U4 | long | 4 | Jun 24, 2024 | Jun 24, 2024 | ($205) |
| ES U4 | short | 3 | Jun 21, 2024 | Jun 21, 2024 | $1,314 |
| MES U4 | long | 4 | Jun 20, 2024 | Jun 21, 2024 | ($165) |
| ES U4 | short | 3 | Jun 20, 2024 | Jun 21, 2024 | ($2,637) |
| MES U4 | long | 8 | Jun 20, 2024 | Jun 20, 2024 | ($480) |
| MES U4 | long | 4 | Jun 20, 2024 | Jun 20, 2024 | $175 |
| MES U4 | long | 8 | Jun 20, 2024 | Jun 20, 2024 | ($385) |
| MES U4 | long | 28 | Jun 18, 2024 | Jun 20, 2024 | $676 |
| ES U4 | short | 3 | Jun 18, 2024 | Jun 20, 2024 | ($2,212) |
| MES U4 | long | 4 | Jun 18, 2024 | Jun 18, 2024 | $115 |
| MES U4 | long | 14 | Jun 17, 2024 | Jun 17, 2024 | ($777) |
| MES U4 | long | 4 | Jun 17, 2024 | Jun 17, 2024 | $165 |
| MES U4 | long | 4 | Jun 17, 2024 | Jun 17, 2024 | $150 |
| MES U4 | long | 4 | Jun 17, 2024 | Jun 17, 2024 | $175 |
| MES U4 | long | 8 | Jun 17, 2024 | Jun 17, 2024 | $810 |
| MES M4 | long | 16 | Jun 13, 2024 | Jun 14, 2024 | $82 |
| MES M4 | long | 4 | Jun 13, 2024 | Jun 13, 2024 | $175 |
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.