TSE Jey-StableAlpha
Trades Own Strategy BrokerTransmit
- hypothetical · Cumul. Return
- 2.1%
- Max Drawdown
- 8.2%
- Trades
- 67
- Win Trades
- 56.7%
- Profit Factor
- 1.20
- Win Months
- 42.9%
About this strategy
【Professional Systematic Series – Managed by Jey Hsieh】
Managed by Jey Hsieh, a veteran quantitative trader with over 20 years of research and execution experience. Recognized for his expertise in high-standard international trading benchmarks, Jey is a pioneer in systematic logic, dedicated to the evolution of algorithmic trading and disciplined execution.
【StableAlpha: Systematic Consistency & Intraday Edge】
Specifically engineered for Consistency and Capital Preservation, StableAlpha translates professional-grade quantitative logic into a model refined for the long-term stewardship of a $50k+ portfolio. It leverages the same systematic rigor that defines Jey’s professional career, but is optimized for steady, sustainable equity growth with an ultra-strict approach to risk tolerance.
【Real-Money Execution & Integrity】
This strategy is backed by a 100% TOS (Trade Own Strategy) certification. We provide total transparency by synchronizing this model with Jey’s live brokerage account, ensuring "Skin in the Game." Every signal reflects the same disciplined execution applied to Jey’s own capital.
【Low-Risk Focus & Intraday Execution】
The primary objective of StableAlpha is capital preservation through 100% systematic execution—"No Emotions. Pure Execution."
- Intraday Focus: This model primarily targets intraday opportunities to minimize overnight market exposure and "black swan" risks.
- Institutional Drawdown Control: We prioritize professional risk management, trade only what the data dictates, and maintain a highly defensive profile.
【Capacity Management & Strategic Pricing】
To optimize cost-efficiency for our current scaling phase, we are releasing a limited-capacity incentive specifically designed for accounts synchronizing under a $50k allocation. New subscribers joining during this implementation phase can lock in our specialized rate of $149 USD/month.
*Please note: This promotional pricing is tied to a specific capacity mandate. As total subscription volume fills or the current strategic tracking phase concludes, the subscription fee for all subsequent entrants will be adjusted upward to protect execution quality, liquidity allocation, and slippage control.
[Independent Model Notice]:
StableAlpha is an exclusive, standalone model optimized for the Collective2 platform. It is managed as a distinct mandate with discrete risk-management parameters, ensuring the integrity of this specific strategy’s performance.
Managed by Jey Hsieh, a veteran quantitative trader with over 20 years of research and execution experience. Recognized for his expertise in high-standard international trading benchmarks, Jey is a pioneer in systematic logic, dedicated to the evolution of algorithmic trading and disciplined execution.
【StableAlpha: Systematic Consistency & Intraday Edge】
Specifically engineered for Consistency and Capital Preservation, StableAlpha translates professional-grade quantitative logic into a model refined for the long-term stewardship of a $50k+ portfolio. It leverages the same systematic rigor that defines Jey’s professional career, but is optimized for steady, sustainable equity growth with an ultra-strict approach to risk tolerance.
【Real-Money Execution & Integrity】
This strategy is backed by a 100% TOS (Trade Own Strategy) certification. We provide total transparency by synchronizing this model with Jey’s live brokerage account, ensuring "Skin in the Game." Every signal reflects the same disciplined execution applied to Jey’s own capital.
【Low-Risk Focus & Intraday Execution】
The primary objective of StableAlpha is capital preservation through 100% systematic execution—"No Emotions. Pure Execution."
- Intraday Focus: This model primarily targets intraday opportunities to minimize overnight market exposure and "black swan" risks.
- Institutional Drawdown Control: We prioritize professional risk management, trade only what the data dictates, and maintain a highly defensive profile.
【Capacity Management & Strategic Pricing】
To optimize cost-efficiency for our current scaling phase, we are releasing a limited-capacity incentive specifically designed for accounts synchronizing under a $50k allocation. New subscribers joining during this implementation phase can lock in our specialized rate of $149 USD/month.
*Please note: This promotional pricing is tied to a specific capacity mandate. As total subscription volume fills or the current strategic tracking phase concludes, the subscription fee for all subsequent entrants will be adjusted upward to protect execution quality, liquidity allocation, and slippage control.
[Independent Model Notice]:
StableAlpha is an exclusive, standalone model optimized for the Collective2 platform. It is managed as a distinct mandate with discrete risk-management parameters, ensuring the integrity of this specific strategy’s performance.
Short Term Financials / Indexes
Hypothetical Monthly Returns (includes fees/commissions)
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026 | -0.4 | 4.6 | 1.4 | -1.2 | -4.8 | -1.3 | 4.0 | 2.1 |
Statistics
Overview
| Strategy began | 3/24/2026 |
|---|---|
| Suggested Minimum Capital | $50,000 |
| Age | 167 days |
| C2 Rank | 926 |
| Rank at C2 % | Top 7.4% |
| Rank # | #388 |
| What it trades | Futures |
| # Trades | 67 |
| # Profitable | 38 |
| % Profitable | 56.7% |
| Avg trade duration | 4.5 hours |
| Max peak-to-valley drawdown | 8.2% |
| drawdown period | May 28, 2026 - Aug 24, 2026 |
| Cumul. Return | 2.1% |
| Avg win | $328 |
| Avg loss | $352 |
Ratios
| W:L ratio | 1.22 |
|---|---|
| Sharpe Ratio | 0.38 |
| Sortino Ratio | 0.56 |
| Calmar Ratio | 1.53 |
CORRELATION STATISTICS
| Correlation to SP500 | 0.11 |
|---|---|
| Return Percent SP500 (cumu) during strategy life | 17.7% |
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | -15.6% |
Return Statistics
| Ann Return (w trading costs) | 4.6% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | 0.0% |
| Return Pcnt Since TOS Status | 0.0% |
| Ann Return (Compnd, No Fees) | 10.0% |
Slump
| Current Slump as Pcnt Equity | 4.5% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 0.6% |
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 | 0.0% |
|---|---|
| Chance of 20% account loss | 0.0% |
| Chance of 30% account loss | 0.0% |
| Chance of 40% account loss | 0.0% |
| 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) | 445 |
| C2 Score | 926 |
| Popularity (7 days, Percentile 1000 scale) | 0 |
Trading Style
| Any stock shorts? 0/1 | 0 |
|---|
Trades-Own-System Certification
| Trades Own System? | 187511 |
|---|---|
| TOS percent | 100.0% |
Win / Loss
| Avg Loss | $352 |
|---|---|
| Avg Win | $328 |
| # Winners | 38 |
| Sum Trade PL (losers) | $10,208 |
| Sum Trade PL (winners) | $12,464 |
| Num Months Winners | 3 |
| # Losers | 29 |
| % Winners | 56.7% |
Dividends
| Dividends Received in Model Acct | 0 |
|---|
Age
| Num Months filled monthly returns table | 7 |
|---|
Frequency
| Avg Position Time (mins) | 269.77 |
|---|---|
| Avg Position Time (hrs) | 4.50 |
| Avg Trade Length | 0.20 |
| Last Trade Ago | 5 |
Leverage
| Daily leverage (average) | 1.55 |
|---|---|
| Daily leverage (max) | 3.52 |
Regression
| Alpha | 0 |
|---|---|
| Beta | 0.06 |
| Treynor Index | 0.17 |
Maximum Adverse Excursion (MAE)
| MAE:Equity, average, all trades | 0.01 |
|---|---|
| MAE:Equity, 95th Percentile Value for this strat | 0 |
| MAE:Equity, average, losing trades | 0.01 |
| MAE:Equity, losing trades only, 95th Percentile Value for this strat | — |
| MAE:Equity, average, winning trades | 0 |
| MAE:Equity, win trades only, 95th Percentile Value for this strat | — |
| Avg(MAE) / Avg(PL) - All trades | 13.66 |
| MAE:PL (avg, all trades) | -0.55 |
| MAE:PL (avg, losing trades) | — |
| MAE:PL (avg, winning trades) | — |
| MAE:PL - worst single value for strategy | — |
| Avg(MAE) / Avg(PL) - Winning trades | 0.54 |
| Avg(MAE) / Avg(PL) - Losing trades | -1.39 |
| Hold-and-Hope Ratio | 0.07 |
RATIO STATISTICS
| Mean | -0.00 |
|---|---|
| SD | 0.12 |
| Sharpe ratio (Glass type estimate) | -0.02 |
| Sharpe ratio (Hedges UMVUE) | -0.01 |
| df | 4 |
| t | -0.01 |
| p | 0.50 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -3.05 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 3.02 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -3.05 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 3.02 |
| Sortino ratio | -0.03 |
| Upside Potential Ratio | 2.21 |
| Upside part of mean | 0.15 |
| Downside part of mean | -0.15 |
| Upside SD | 0.08 |
| Downside SD | 0.07 |
| N nonnegative terms | 2 |
| N negative terms | 3 |
| N of observations | 5 |
| Mean of predictor | 0.36 |
| Mean of criterion | -0.00 |
| SD of predictor | 0.13 |
| SD of criterion | 0.12 |
| Covariance | 0.01 |
| r | 0.76 |
| b (slope, estimate of beta) | 0.68 |
| a (intercept, estimate of alpha) | -0.24 |
| Mean Square Error | 0.01 |
| DF error | 3 |
| t(b) | 2.04 |
| p(b) | 0.07 |
| t(a) | -1.34 |
| p(a) | 0.86 |
| Lowerbound of 95% confidence interval for beta | -0.38 |
| Upperbound of 95% confidence interval for beta | 1.73 |
| Lowerbound of 95% confidence interval for alpha | -0.82 |
| Upperbound of 95% confidence interval for alpha | 0.33 |
| Treynor index (mean / b) | -0.00 |
| Jensen alpha (a) | -0.24 |
| Mean | -0.01 |
| SD | 0.12 |
| Sharpe ratio (Glass type estimate) | -0.06 |
| Sharpe ratio (Hedges UMVUE) | -0.05 |
| df | 4 |
| t | -0.04 |
| p | 0.52 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -3.10 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 2.98 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -3.09 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 2.99 |
| Sortino ratio | -0.11 |
| Upside Potential Ratio | 2.13 |
| Upside part of mean | 0.14 |
| Downside part of mean | -0.15 |
| Upside SD | 0.08 |
| Downside SD | 0.07 |
| N nonnegative terms | 2 |
| N negative terms | 3 |
| N of observations | 5 |
| Mean of predictor | 0.34 |
| Mean of criterion | -0.01 |
| SD of predictor | 0.13 |
| SD of criterion | 0.12 |
| Covariance | 0.01 |
| r | 0.75 |
| b (slope, estimate of beta) | 0.68 |
| a (intercept, estimate of alpha) | -0.24 |
| Mean Square Error | 0.01 |
| DF error | 3 |
| t(b) | 1.97 |
| p(b) | 0.07 |
| t(a) | -1.32 |
| p(a) | 0.86 |
| Lowerbound of 95% confidence interval for beta | -0.42 |
| Upperbound of 95% confidence interval for beta | 1.78 |
| Lowerbound of 95% confidence interval for alpha | -0.82 |
| Upperbound of 95% confidence interval for alpha | 0.34 |
| Treynor index (mean / b) | -0.01 |
| Jensen alpha (a) | -0.24 |
| VaR(95%) | 0.05 |
| Expected Shortfall on VaR | 0.07 |
| VaR(95%) | 0.03 |
| Expected Shortfall on VaR | 0.05 |
| Mean | 0.07 |
| SD | 0.08 |
| Sharpe ratio (Glass type estimate) | 0.93 |
| Sharpe ratio (Hedges UMVUE) | 0.93 |
| df | 118 |
| t | 0.63 |
| p | 0.47 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -1.98 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 3.84 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.98 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 3.84 |
| Sortino ratio | 1.43 |
| Upside Potential Ratio | 8.61 |
| Upside part of mean | 0.43 |
| Downside part of mean | -0.36 |
| Upside SD | 0.06 |
| Downside SD | 0.05 |
| N nonnegative terms | 46 |
| N negative terms | 73 |
| N of observations | 119 |
| Mean of predictor | 0.34 |
| Mean of criterion | 0.07 |
| SD of predictor | 0.14 |
| SD of criterion | 0.08 |
| Covariance | 0.00 |
| r | 0.08 |
| b (slope, estimate of beta) | 0.05 |
| a (intercept, estimate of alpha) | 0.06 |
| Mean Square Error | 0.01 |
| DF error | 117 |
| t(b) | 0.92 |
| p(b) | 0.45 |
| t(a) | 0.48 |
| p(a) | 0.47 |
| Lowerbound of 95% confidence interval for beta | -0.06 |
| Upperbound of 95% confidence interval for beta | 0.15 |
| Lowerbound of 95% confidence interval for alpha | -0.17 |
| Upperbound of 95% confidence interval for alpha | 0.28 |
| Treynor index (mean / b) | 1.51 |
| Jensen alpha (a) | 0.06 |
| Mean | 0.07 |
| SD | 0.08 |
| Sharpe ratio (Glass type estimate) | 0.90 |
| Sharpe ratio (Hedges UMVUE) | 0.89 |
| df | 118 |
| t | 0.60 |
| p | 0.47 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -2.01 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 3.81 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -2.02 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 3.80 |
| Sortino ratio | 1.36 |
| Upside Potential Ratio | 8.54 |
| Upside part of mean | 0.43 |
| Downside part of mean | -0.36 |
| Upside SD | 0.06 |
| Downside SD | 0.05 |
| N nonnegative terms | 46 |
| N negative terms | 73 |
| N of observations | 119 |
| Mean of predictor | 0.33 |
| Mean of criterion | 0.07 |
| SD of predictor | 0.14 |
| SD of criterion | 0.08 |
| Covariance | 0.00 |
| r | 0.08 |
| b (slope, estimate of beta) | 0.05 |
| a (intercept, estimate of alpha) | 0.05 |
| Mean Square Error | 0.01 |
| DF error | 117 |
| t(b) | 0.92 |
| p(b) | 0.45 |
| t(a) | 0.46 |
| p(a) | 0.47 |
| Lowerbound of 95% confidence interval for beta | -0.06 |
| Upperbound of 95% confidence interval for beta | 0.15 |
| Lowerbound of 95% confidence interval for alpha | -0.18 |
| Upperbound of 95% confidence interval for alpha | 0.28 |
| Treynor index (mean / b) | 1.45 |
| Jensen alpha (a) | 0.05 |
| VaR(95%) | 0.01 |
| Expected Shortfall on VaR | 0.01 |
| VaR(95%) | 0.00 |
| Expected Shortfall on VaR | 0.01 |
| VAR (95 Confidence Intrvl) | 0.01 |
ORDER STATISTICS
| Number of observations | 5 |
|---|---|
| Minimum | 0.97 |
| Quartile 1 | 0.98 |
| Median | 1.00 |
| Quartile 3 | 1.01 |
| Maximum | 1.06 |
| Mean of quarter 1 | 0.97 |
| Mean of quarter 2 | 1.00 |
| Mean of quarter 3 | 1.01 |
| Mean of quarter 4 | 1.06 |
| Inter Quartile Range | 0.03 |
| 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 | 119 |
| Minimum | 0.99 |
| Quartile 1 | 1.00 |
| Median | 1 |
| Quartile 3 | 1.00 |
| Maximum | 1.02 |
| Mean of quarter 1 | 0.99 |
| Mean of quarter 2 | 1.00 |
| Mean of quarter 3 | 1.00 |
| Mean of quarter 4 | 1.01 |
| Inter Quartile Range | 0.00 |
| Number outliers low | 17 |
| Percentage of outliers low | 0.14 |
| Mean of outliers low | 0.99 |
| Number of outliers high | 14 |
| Percentage of outliers high | 0.12 |
| Mean of outliers high | 1.01 |
| Extreme Value Index (moments method) | -2.18 |
| VaR(95%) (moments method) | 0.00 |
| Expected Shortfall (moments method) | 0.00 |
| Extreme Value Index (regression method) | -0.63 |
| VaR(95%) (regression method) | 0.00 |
| Expected Shortfall (regression method) | 0.01 |
DRAW DOWN STATISTICS
| Number of observations | 1 |
|---|---|
| Minimum | 0.05 |
| Quartile 1 | 0.05 |
| Median | 0.05 |
| Quartile 3 | 0.05 |
| Maximum | 0.05 |
| 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 |
| Number of observations | 4 |
| Minimum | 0.01 |
| Quartile 1 | 0.01 |
| Median | 0.02 |
| Quartile 3 | 0.03 |
| Maximum | 0.07 |
| Mean of quarter 1 | 0.01 |
| Mean of quarter 2 | 0.01 |
| Mean of quarter 3 | 0.02 |
| Mean of quarter 4 | 0.07 |
| Inter Quartile Range | 0.02 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 1 |
| Percentage of outliers high | 0.25 |
| Mean of outliers high | 0.07 |
| 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? | -395720960 |
| Max Equity Drawdown (num days) | 88 |
| Last 4 Months - Pcnt Negative | 0.8% |
COMBINED STATISTICS
| Annualized return (arithmetic extrapolation) | 0.02 |
|---|---|
| Compounded annual return (geometric extrapolation) | 0.02 |
| Calmar ratio (compounded annual return / max draw down) | 0.38 |
| Compounded annual return / average of 25% largest draw downs | 0 |
| Compounded annual return / Expected Shortfall lognormal | 0.30 |
| j156mfCOMBRisPar | 0 |
| j157mfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 0.10 |
| Compounded annual return (geometric extrapolation) | 0.10 |
| Calmar ratio (compounded annual return / max draw down) | 1.53 |
| Compounded annual return / average of 25% largest draw downs | 1.53 |
| Compounded annual return / Expected Shortfall lognormal | 10.73 |
Trading record
Placed 154 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| MNQ U6 | short | 1 | Sep 3, 2026 | Sep 3, 2026 | $6 |
| MNQ U6 | long | 4 | Sep 3, 2026 | Sep 3, 2026 | $1,196 |
| MNQ U6 | short | 3 | Sep 1, 2026 | Sep 1, 2026 | $278 |
| MNQ U6 | long | 1 | Sep 1, 2026 | Sep 1, 2026 | $250 |
| MNQ U6 | short | 1 | Sep 1, 2026 | Sep 1, 2026 | $249 |
| MNQ U6 | short | 2 | Aug 24, 2026 | Aug 24, 2026 | ($441) |
| MNQ U6 | long | 1 | Aug 20, 2026 | Aug 20, 2026 | ($97) |
| MNQ U6 | short | 1 | Aug 19, 2026 | Aug 19, 2026 | $181 |
| MNQ U6 | long | 2 | Aug 10, 2026 | Aug 11, 2026 | ($616) |
| MNQ U6 | long | 1 | Aug 5, 2026 | Aug 6, 2026 | ($141) |
| MNQ U6 | long | 2 | Aug 5, 2026 | Aug 5, 2026 | $4 |
| MNQ U6 | long | 2 | Aug 3, 2026 | Aug 4, 2026 | $649 |
| MNQ U6 | long | 1 | Jul 31, 2026 | Jul 31, 2026 | ($1,001) |
| MNQ U6 | long | 2 | Jul 30, 2026 | Jul 31, 2026 | $128 |
| MNQ U6 | long | 1 | Jul 24, 2026 | Jul 24, 2026 | ($460) |
| MNQ U6 | long | 1 | Jul 23, 2026 | Jul 23, 2026 | ($486) |
| MNQ U6 | short | 2 | Jul 17, 2026 | Jul 17, 2026 | ($141) |
| MNQ U6 | long | 1 | Jul 14, 2026 | Jul 14, 2026 | ($30) |
| MNQ U6 | short | 1 | Jul 13, 2026 | Jul 13, 2026 | $161 |
| MNQ U6 | long | 2 | Jul 13, 2026 | Jul 13, 2026 | ($745) |
| MNQ U6 | short | 1 | Jul 13, 2026 | Jul 13, 2026 | ($260) |
| MNQ U6 | long | 3 | Jul 10, 2026 | Jul 10, 2026 | $495 |
| MNQ U6 | short | 1 | Jul 7, 2026 | Jul 7, 2026 | $51 |
| MNQ U6 | short | 1 | Jul 7, 2026 | Jul 7, 2026 | $325 |
| MNQ U6 | short | 2 | Jul 3, 2026 | Jul 3, 2026 | $44 |
| MNQ U6 | long | 1 | Jul 1, 2026 | Jul 1, 2026 | ($396) |
| MNQ U6 | long | 2 | Jun 29, 2026 | Jun 30, 2026 | $491 |
| MNQ U6 | long | 1 | Jun 29, 2026 | Jun 29, 2026 | $304 |
| MNQ U6 | long | 1 | Jun 16, 2026 | Jun 16, 2026 | ($237) |
| MNQ M6 | long | 2 | Jun 16, 2026 | Jun 16, 2026 | ($517) |
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.