Drift and Bounce
Trades Own Strategy BrokerTransmit
- hypothetical · Cumul. Return
- 2.4%
- Max Drawdown
- 24.0%
- Trades
- 57
- Win Trades
- 63.2%
- Profit Factor
- 1.50
- Win Months
- 75.0%
About this strategy
A systematic, long-only US-equity strategy running two independent engines side by side:
- Drift — a concentrated momentum rotation in highly liquid large/mid-cap US names, re-ranked on a fixed multi-week schedule. It holds market leaders while they lead, and steps aside to cash when a rules-based regime filter detects a sustained market downtrend.
- Bounce — a short-term mean-reversion engine that buys statistically extreme washouts in healthy, still-uptrending names and sells into the rebound — deliberately throttled so it never loads up into a falling market.
The two engines draw down at different times (trend and reversion rarely break together) and capital is mechanically rebalanced between them.
RISK CHARACTER
- Drawdown control is the primary objective; return is its consequence — the aim is to beat the broad market over full cycles while keeping drawdowns shallower than buy-and-hold. The regime filter (Drift moves to cash in sustained downtrends) is the main drawdown brake.
- A fully-invested long equity strategy — expect equity-level volatility, quiet sideways stretches, and the occasional sharp week. Built to compound across cycles, not to win every month.
- No leverage, no margin, no options, no shorting, no discretionary overrides — only long shares of liquid US stocks.
- Every rule was validated on 27 years of point-in-time data spanning four major bear markets.
ACADEMIC & RESEARCH FOUNDATIONS
Drift — cross-sectional and time-series momentum (among the most replicated effects in finance):
- Jegadeesh & Titman (1993), Returns to Buying Winners and Selling Losers, Journal of Finance.
- Asness, Moskowitz & Pedersen (2013), Value and Momentum Everywhere, Journal of Finance.
- Moskowitz, Ooi & Pedersen (2012), Time Series Momentum, Journal of Financial Economics — trend persistence (the basis of the regime filter).
- Faber (2007), A Quantitative Approach to Tactical Asset Allocation, Journal of Wealth Management — the moving-average regime/trend filter.
Bounce — short-term reversal / overreaction in equities:
- De Bondt & Thaler (1985), Does the Stock Market Overreact?, Journal of Finance.
- Jegadeesh (1990), Evidence of Predictable Behavior of Security Returns, Journal of Finance.
- Lehmann (1990), Fads, Martingales, and Market Efficiency, Quarterly Journal of Economics.
- Lo & MacKinlay (1990), When Are Contrarian Profits Due to Stock Market Overreaction?, Review of Financial Studies.
- Connors & Alvarez (2008), Short Term Trading Strategies That Work — the practitioner short-period-RSI oversold rule inside a trend filter.
Combining them — momentum and short-term reversal are distinct, well-documented effects on opposite horizons (multi-month trend versus days-long reversal), so they diversify each other: Markowitz (1952), Portfolio Selection, Journal of Finance.
- Drift — a concentrated momentum rotation in highly liquid large/mid-cap US names, re-ranked on a fixed multi-week schedule. It holds market leaders while they lead, and steps aside to cash when a rules-based regime filter detects a sustained market downtrend.
- Bounce — a short-term mean-reversion engine that buys statistically extreme washouts in healthy, still-uptrending names and sells into the rebound — deliberately throttled so it never loads up into a falling market.
The two engines draw down at different times (trend and reversion rarely break together) and capital is mechanically rebalanced between them.
RISK CHARACTER
- Drawdown control is the primary objective; return is its consequence — the aim is to beat the broad market over full cycles while keeping drawdowns shallower than buy-and-hold. The regime filter (Drift moves to cash in sustained downtrends) is the main drawdown brake.
- A fully-invested long equity strategy — expect equity-level volatility, quiet sideways stretches, and the occasional sharp week. Built to compound across cycles, not to win every month.
- No leverage, no margin, no options, no shorting, no discretionary overrides — only long shares of liquid US stocks.
- Every rule was validated on 27 years of point-in-time data spanning four major bear markets.
ACADEMIC & RESEARCH FOUNDATIONS
Drift — cross-sectional and time-series momentum (among the most replicated effects in finance):
- Jegadeesh & Titman (1993), Returns to Buying Winners and Selling Losers, Journal of Finance.
- Asness, Moskowitz & Pedersen (2013), Value and Momentum Everywhere, Journal of Finance.
- Moskowitz, Ooi & Pedersen (2012), Time Series Momentum, Journal of Financial Economics — trend persistence (the basis of the regime filter).
- Faber (2007), A Quantitative Approach to Tactical Asset Allocation, Journal of Wealth Management — the moving-average regime/trend filter.
Bounce — short-term reversal / overreaction in equities:
- De Bondt & Thaler (1985), Does the Stock Market Overreact?, Journal of Finance.
- Jegadeesh (1990), Evidence of Predictable Behavior of Security Returns, Journal of Finance.
- Lehmann (1990), Fads, Martingales, and Market Efficiency, Quarterly Journal of Economics.
- Lo & MacKinlay (1990), When Are Contrarian Profits Due to Stock Market Overreaction?, Review of Financial Studies.
- Connors & Alvarez (2008), Short Term Trading Strategies That Work — the practitioner short-period-RSI oversold rule inside a trend filter.
Combining them — momentum and short-term reversal are distinct, well-documented effects on opposite horizons (multi-month trend versus days-long reversal), so they diversify each other: Markowitz (1952), Portfolio Selection, Journal of Finance.
Momentum Short-term Reversal
Hypothetical Monthly Returns (includes fees/commissions)
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026 | 12.8 | -15.6 | 3.9 | 3.5 | 2.4 |
Statistics
Overview
| Strategy began | 6/5/2026 |
|---|---|
| Suggested Minimum Capital | $15,000 |
| Age | 93 days |
| C2 Rank | 928 |
| Rank at C2 % | Top 7.2% |
| Rank # | #189 |
| What it trades | Stocks |
| # Trades | 57 |
| # Profitable | 36 |
| % Profitable | 63.2% |
| Avg trade duration | 24.8 days |
| Max peak-to-valley drawdown | 23.9% |
| drawdown period | June 23, 2026 - July 29, 2026 |
| Cumul. Return | 2.4% |
| Avg win | $221 |
| Avg loss | $246 |
Ratios
| W:L ratio | 1.55 |
|---|---|
| Sharpe Ratio | 0.34 |
| Sortino Ratio | 0.49 |
| Calmar Ratio | 0.58 |
CORRELATION STATISTICS
| Correlation to SP500 | 0.51 |
|---|---|
| Return Percent SP500 (cumu) during strategy life | 4.5% |
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | -2.1% |
Return Statistics
| Ann Return (w trading costs) | 9.3% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | 0.0% |
| Return Pcnt Since TOS Status | 0.0% |
| Ann Return (Compnd, No Fees) | 11.4% |
Slump
| Current Slump as Pcnt Equity | 12.1% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 0.8% |
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 | 54.5% |
|---|---|
| Chance of 20% account loss | 15.0% |
| Chance of 30% account loss | 1.5% |
| 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) | 421 |
|---|---|
| Popularity (Last 6 weeks) | 446 |
| C2 Score | 928 |
| Popularity (7 days, Percentile 1000 scale) | 445 |
Trading Style
| Any stock shorts? 0/1 | 0 |
|---|
Trades-Own-System Certification
| Trades Own System? | 187575 |
|---|---|
| TOS percent | 100.0% |
Win / Loss
| Avg Loss | $246 |
|---|---|
| Avg Win | $221 |
| # Winners | 36 |
| Sum Trade PL (losers) | $5,170 |
| Sum Trade PL (winners) | $7,970 |
| Num Months Winners | 3 |
| # Losers | 21 |
| % Winners | 63.2% |
Dividends
| Dividends Received in Model Acct | 33 |
|---|
Age
| Num Months filled monthly returns table | 4 |
|---|
Frequency
| Avg Position Time (mins) | 35716.90 |
|---|---|
| Avg Position Time (hrs) | 595.28 |
| Avg Trade Length | 24.80 |
| Last Trade Ago | 3 |
Leverage
| Daily leverage (average) | 0.69 |
|---|---|
| Daily leverage (max) | 0.85 |
Regression
| Alpha | -0.03 |
|---|---|
| Beta | 1.55 |
| Treynor Index | 0.03 |
Maximum Adverse Excursion (MAE)
| MAE:Equity, average, all trades | 0 |
|---|---|
| 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 | -108.06 |
| MAE:PL (avg, all trades) | -0.94 |
| MAE:PL (avg, losing trades) | — |
| MAE:PL (avg, winning trades) | — |
| MAE:PL - worst single value for strategy | — |
| Avg(MAE) / Avg(PL) - Winning trades | 1.47 |
| Avg(MAE) / Avg(PL) - Losing trades | -2.56 |
| Hold-and-Hope Ratio | 0.12 |
RATIO STATISTICS
| Mean | 0.10 |
|---|---|
| SD | 0.14 |
| Sharpe ratio (Glass type estimate) | 0.71 |
| Sharpe ratio (Hedges UMVUE) | 0.40 |
| df | 2 |
| t | 0.35 |
| p | 0.38 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -3.34 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 4.60 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -3.54 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 4.34 |
| Sortino ratio | 1.36 |
| Upside Potential Ratio | 3.36 |
| Upside part of mean | 0.24 |
| Downside part of mean | -0.15 |
| Upside SD | 0.09 |
| Downside SD | 0.07 |
| N nonnegative terms | 2 |
| N negative terms | 1 |
| N of observations | 3 |
| Mean of predictor | 0.15 |
| Mean of criterion | 0.10 |
| SD of predictor | 0.05 |
| SD of criterion | 0.14 |
| Covariance | -0.01 |
| r | -0.95 |
| b (slope, estimate of beta) | -2.92 |
| a (intercept, estimate of alpha) | 0.54 |
| Mean Square Error | 0.00 |
| DF error | 1 |
| t(b) | -3.15 |
| p(b) | 0.90 |
| t(a) | 2.93 |
| p(a) | 0.10 |
| Lowerbound of 95% confidence interval for beta | -14.70 |
| Upperbound of 95% confidence interval for beta | 8.86 |
| Lowerbound of 95% confidence interval for alpha | -1.81 |
| Upperbound of 95% confidence interval for alpha | 2.89 |
| Treynor index (mean / b) | -0.03 |
| Jensen alpha (a) | 0.54 |
| Mean | 0.09 |
| SD | 0.14 |
| Sharpe ratio (Glass type estimate) | 0.66 |
| Sharpe ratio (Hedges UMVUE) | 0.37 |
| df | 2 |
| t | 0.33 |
| p | 0.39 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -3.38 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 4.55 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -3.57 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 4.31 |
| Sortino ratio | 1.24 |
| Upside Potential Ratio | 3.24 |
| Upside part of mean | 0.24 |
| Downside part of mean | -0.15 |
| Upside SD | 0.09 |
| Downside SD | 0.07 |
| N nonnegative terms | 2 |
| N negative terms | 1 |
| N of observations | 3 |
| Mean of predictor | 0.15 |
| Mean of criterion | 0.09 |
| SD of predictor | 0.05 |
| SD of criterion | 0.14 |
| Covariance | -0.01 |
| r | -0.95 |
| b (slope, estimate of beta) | -2.94 |
| a (intercept, estimate of alpha) | 0.53 |
| Mean Square Error | 0.00 |
| DF error | 1 |
| t(b) | -3.01 |
| p(b) | 0.90 |
| t(a) | 2.77 |
| p(a) | 0.11 |
| Lowerbound of 95% confidence interval for beta | -15.32 |
| Upperbound of 95% confidence interval for beta | 9.45 |
| Lowerbound of 95% confidence interval for alpha | -1.90 |
| Upperbound of 95% confidence interval for alpha | 2.97 |
| Treynor index (mean / b) | -0.03 |
| Jensen alpha (a) | 0.53 |
| VaR(95%) | 0.06 |
| Expected Shortfall on VaR | 0.07 |
| VaR(95%) | 0.02 |
| Expected Shortfall on VaR | 0.04 |
| Mean | 0.16 |
| SD | 0.38 |
| Sharpe ratio (Glass type estimate) | 0.43 |
| Sharpe ratio (Hedges UMVUE) | 0.42 |
| df | 65 |
| t | 0.21 |
| p | 0.42 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -3.48 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 4.33 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -3.48 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 4.33 |
| Sortino ratio | 0.62 |
| Upside Potential Ratio | 9.75 |
| Upside part of mean | 2.59 |
| Downside part of mean | -2.43 |
| Upside SD | 0.27 |
| Downside SD | 0.27 |
| N nonnegative terms | 33 |
| N negative terms | 33 |
| N of observations | 66 |
| Mean of predictor | 0.16 |
| Mean of criterion | 0.16 |
| SD of predictor | 0.12 |
| SD of criterion | 0.38 |
| Covariance | 0.02 |
| r | 0.49 |
| b (slope, estimate of beta) | 1.52 |
| a (intercept, estimate of alpha) | -0.07 |
| Mean Square Error | 0.11 |
| DF error | 64 |
| t(b) | 4.55 |
| p(b) | 0.00 |
| t(a) | -0.11 |
| p(a) | 0.54 |
| Lowerbound of 95% confidence interval for beta | 0.85 |
| Upperbound of 95% confidence interval for beta | 2.19 |
| Lowerbound of 95% confidence interval for alpha | -1.42 |
| Upperbound of 95% confidence interval for alpha | 1.27 |
| Treynor index (mean / b) | 0.11 |
| Jensen alpha (a) | -0.07 |
| Mean | 0.09 |
| SD | 0.38 |
| Sharpe ratio (Glass type estimate) | 0.24 |
| Sharpe ratio (Hedges UMVUE) | 0.23 |
| df | 65 |
| t | 0.12 |
| p | 0.45 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -3.67 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 4.14 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -3.67 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 4.14 |
| Sortino ratio | 0.34 |
| Upside Potential Ratio | 9.44 |
| Upside part of mean | 2.56 |
| Downside part of mean | -2.46 |
| Upside SD | 0.27 |
| Downside SD | 0.27 |
| N nonnegative terms | 33 |
| N negative terms | 33 |
| N of observations | 66 |
| Mean of predictor | 0.15 |
| Mean of criterion | 0.09 |
| SD of predictor | 0.12 |
| SD of criterion | 0.38 |
| Covariance | 0.02 |
| r | 0.49 |
| b (slope, estimate of beta) | 1.51 |
| a (intercept, estimate of alpha) | -0.13 |
| Mean Square Error | 0.11 |
| DF error | 64 |
| t(b) | 4.49 |
| p(b) | 0.00 |
| t(a) | -0.20 |
| p(a) | 0.58 |
| Lowerbound of 95% confidence interval for beta | 0.84 |
| Upperbound of 95% confidence interval for beta | 2.18 |
| Lowerbound of 95% confidence interval for alpha | -1.48 |
| Upperbound of 95% confidence interval for alpha | 1.21 |
| Treynor index (mean / b) | 0.06 |
| Jensen alpha (a) | -0.13 |
| VaR(95%) | 0.04 |
| Expected Shortfall on VaR | 0.05 |
| VaR(95%) | 0.02 |
| Expected Shortfall on VaR | 0.04 |
| VAR (95 Confidence Intrvl) | 0.04 |
ORDER STATISTICS
| Number of observations | 3 |
|---|---|
| Minimum | 0.97 |
| Quartile 1 | 0.99 |
| Median | 1.02 |
| Quartile 3 | 1.03 |
| Maximum | 1.04 |
| Mean of quarter 1 | 0.97 |
| Mean of quarter 2 | 1.02 |
| Mean of quarter 3 | 0 |
| Mean of quarter 4 | 1.04 |
| Inter Quartile Range | 0.04 |
| 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 | 66 |
| Minimum | 0.95 |
| Quartile 1 | 0.98 |
| Median | 1.00 |
| Quartile 3 | 1.02 |
| Maximum | 1.05 |
| 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 | 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) | -0.80 |
| VaR(95%) (moments method) | 0.03 |
| Expected Shortfall (moments method) | 0.03 |
| Extreme Value Index (regression method) | -0.48 |
| VaR(95%) (regression method) | 0.03 |
| Expected Shortfall (regression method) | 0.03 |
DRAW DOWN STATISTICS
| Number of observations | 1 |
|---|---|
| Minimum | 0.03 |
| Quartile 1 | 0.03 |
| Median | 0.03 |
| Quartile 3 | 0.03 |
| Maximum | 0.03 |
| 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 | 3 |
| Minimum | 0.00 |
| Quartile 1 | 0.01 |
| Median | 0.02 |
| Quartile 3 | 0.12 |
| Maximum | 0.22 |
| Mean of quarter 1 | 0.00 |
| Mean of quarter 2 | 0.02 |
| Mean of quarter 3 | 0 |
| Mean of quarter 4 | 0.22 |
| Inter Quartile Range | 0.11 |
| 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? | -370660512 |
| Max Equity Drawdown (num days) | 36 |
| Last 4 Months - Pcnt Negative | 0.2% |
COMBINED STATISTICS
| Annualized return (arithmetic extrapolation) | 0.12 |
|---|---|
| Compounded annual return (geometric extrapolation) | 0.13 |
| Calmar ratio (compounded annual return / max draw down) | 3.74 |
| Compounded annual return / average of 25% largest draw downs | 0 |
| Compounded annual return / Expected Shortfall lognormal | 1.75 |
| j156mfCOMBRisPar | 0 |
| j157mfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 0.12 |
| Compounded annual return (geometric extrapolation) | 0.13 |
| Calmar ratio (compounded annual return / max draw down) | 0.58 |
| Compounded annual return / average of 25% largest draw downs | 0.58 |
| Compounded annual return / Expected Shortfall lognormal | 2.66 |
Trading record
Placed 135 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| CAT | long | 4 | Aug 31, 2026 | Sep 4, 2026 | $52 |
| MRVL | long | 15 | Aug 28, 2026 | Sep 4, 2026 | $90 |
| KLAC | long | 18 | Aug 21, 2026 | Sep 4, 2026 | $26 |
| GEV | long | 3 | Aug 24, 2026 | Sep 2, 2026 | ($55) |
| XOM | long | 21 | Aug 27, 2026 | Aug 31, 2026 | $79 |
| AVGO | long | 8 | Aug 14, 2026 | Aug 28, 2026 | ($163) |
| NVDA | long | 15 | Aug 18, 2026 | Aug 27, 2026 | $138 |
| TXN | long | 5 | Aug 3, 2026 | Aug 24, 2026 | ($66) |
| UNH | long | 8 | Aug 19, 2026 | Aug 24, 2026 | $82 |
| AMZN | long | 12 | Aug 17, 2026 | Aug 19, 2026 | $68 |
| AAPL | long | 11 | Jul 31, 2026 | Aug 18, 2026 | $29 |
| V | long | 9 | Aug 10, 2026 | Aug 13, 2026 | $47 |
| XOM | long | 21 | Aug 5, 2026 | Aug 10, 2026 | $167 |
| LLY | long | 2 | Aug 3, 2026 | Aug 5, 2026 | $101 |
| CAT | long | 4 | Jul 28, 2026 | Aug 3, 2026 | ($24) |
| COHR | long | 2 | Jul 23, 2026 | Aug 3, 2026 | ($122) |
| GEV | long | 3 | Jul 22, 2026 | Jul 31, 2026 | $11 |
| NVDA | long | 17 | Jul 27, 2026 | Jul 31, 2026 | $75 |
| MRVL | long | 20 | Jul 29, 2026 | Jul 31, 2026 | $411 |
| V | long | 10 | Jul 23, 2026 | Jul 27, 2026 | $107 |
| BRK.B | long | 7 | Jul 9, 2026 | Jul 24, 2026 | ($13) |
| CSCO | long | 31 | Jul 15, 2026 | Jul 23, 2026 | $25 |
| CAT | long | 4 | Jul 16, 2026 | Jul 22, 2026 | $66 |
| TXN | long | 12 | Jul 17, 2026 | Jul 21, 2026 | $90 |
| LLY | long | 3 | Jul 14, 2026 | Jul 17, 2026 | $57 |
| GOOGL | long | 10 | Jul 13, 2026 | Jul 15, 2026 | $186 |
| CSCO | long | 33 | Jul 6, 2026 | Jul 10, 2026 | $144 |
| QCOM | long | 19 | Jun 25, 2026 | Jul 10, 2026 | ($553) |
| AAPL | long | 13 | Jun 26, 2026 | Jul 1, 2026 | $212 |
| GOOGL | long | 11 | Jun 29, 2026 | Jun 30, 2026 | $59 |
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.