RTS SPY
- hypothetical · Annual Return (Compounded)
- -0.2%
- Max Drawdown
- 22.0%
- Trades
- 157
- Win Trades
- 47.1%
- Profit Factor
- 1.20
- Win Months
- 6.1%
About this strategy
www.RuleTradingSystems.com
(RTS) key staff members combine a knowledge base of over 30 years from within the financial markets with solid international exposure, through which it has created market expertise identifying innovative and systematic solid trading algorithms.
After years of development and market-vibration studies RTS has created alternative cutting-edge strategies in different major indices, providing a systematic approach to trading & a competitive edge on a highly sophisticated financial environment, targeting a low volume system.
RTS provides a quantitative systematic-trading algorithm, implementing artificial intelligence to decision making and a logic focused on risk management with no specific market bias, generating long / short trading signals for the SPY ETF, implementing a cutting-edge innovative algorithm trend filter analyzing different time frames instead of Stochastics RSI, MACD or any other over used conventional indicator.
Each trade is generally kept overnight and the holding period could be from one to several days, by following RTS trading signals, the anxiety of tick by tick screen watching is removed, receiving a disciplined and consistent approach that is free of any long winded explanation. Transparency, ease of use and profitability with low volatility trading are their goals updating weekly their performance page.
RTS considers System Trading the only valid approach to trading, as it is reasonably safe to say that most professional traders will trade using a rule based trading system of some sort (automated or manual). A system, from this perspective, can be any strategy ranging from simple entry and exit criteria, money management rules, the use of stop losses to protect positions or lock-in profits, to the more complex use of mathematical algorithms. A system provides a consistent and logical approach to trading. Whether simple or complex, a trading system will be effective only when implemented consistently, preventing emotional decision-making that ultimately will always hurts the portfolio when trading without a systematic plan (Trading System), automated or not.
Signal frequency and over-trading are a concern at RTS, as such, their algorithms are designed to generate - under normal circumstances - between 2 and 15 signals per month; please note that even with these low frequency some trades could be reversed or closed the same day, therefore the account used to trade RTS
(RTS) key staff members combine a knowledge base of over 30 years from within the financial markets with solid international exposure, through which it has created market expertise identifying innovative and systematic solid trading algorithms.
After years of development and market-vibration studies RTS has created alternative cutting-edge strategies in different major indices, providing a systematic approach to trading & a competitive edge on a highly sophisticated financial environment, targeting a low volume system.
RTS provides a quantitative systematic-trading algorithm, implementing artificial intelligence to decision making and a logic focused on risk management with no specific market bias, generating long / short trading signals for the SPY ETF, implementing a cutting-edge innovative algorithm trend filter analyzing different time frames instead of Stochastics RSI, MACD or any other over used conventional indicator.
Each trade is generally kept overnight and the holding period could be from one to several days, by following RTS trading signals, the anxiety of tick by tick screen watching is removed, receiving a disciplined and consistent approach that is free of any long winded explanation. Transparency, ease of use and profitability with low volatility trading are their goals updating weekly their performance page.
RTS considers System Trading the only valid approach to trading, as it is reasonably safe to say that most professional traders will trade using a rule based trading system of some sort (automated or manual). A system, from this perspective, can be any strategy ranging from simple entry and exit criteria, money management rules, the use of stop losses to protect positions or lock-in profits, to the more complex use of mathematical algorithms. A system provides a consistent and logical approach to trading. Whether simple or complex, a trading system will be effective only when implemented consistently, preventing emotional decision-making that ultimately will always hurts the portfolio when trading without a systematic plan (Trading System), automated or not.
Signal frequency and over-trading are a concern at RTS, as such, their algorithms are designed to generate - under normal circumstances - between 2 and 15 signals per month; please note that even with these low frequency some trades could be reversed or closed the same day, therefore the account used to trade RTS
Hypothetical Monthly Returns (includes fees/commissions)
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011 | 5.4 | -1.6 | -0.1 | 3.6 | |||||||||
| 2012 | 0.8 | 1.4 | 1.2 | -1.5 | -0.7 | 0.5 | 3.2 | -2.3 | -3.0 | 4.5 | -0.4 | -2.2 | 1.2 |
| 2013 | -4.1 | 0.0 | -5.7 | 4.2 | -3.5 | -5.2 | 6.1 | 1.9 | -1.4 | 1.5 | 0.0 | 0.0 | -6.7 |
| 2014 | 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 |
| 2015 | 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 |
| 2016 | 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 |
| 2017 | 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 |
| 2018 | 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 |
| 2019 | 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 |
| 2020 | 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 |
| 2021 | 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 |
| 2022 | 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 |
| 2023 | 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 |
| 2024 | 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 |
| 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 | 10/12/2011 |
|---|---|
| Suggested Minimum Capital | $25,000 |
| Age | 182 months |
| What it trades | Stocks |
| # Trades | 157 |
| # Profitable | 74 |
| % Profitable | 47.1% |
| Avg trade duration | 1.2 days |
| Max peak-to-valley drawdown | 22.0% |
| drawdown period | April 19, 2012 - June 24, 2013 |
| Annual Return (Compounded) | -0.2% |
| Avg win | $261 |
| Avg loss | $203 |
Ratios
| W:L ratio | 1.16 |
|---|---|
| Sharpe Ratio | -0.47 |
| Sortino Ratio | -0.66 |
| Calmar Ratio | 0.16 |
CORRELATION STATISTICS
| Correlation to SP500 | 0.05 |
|---|---|
| Return Percent SP500 (cumu) during strategy life | 532.4% |
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | -531.0% |
Return Statistics
| Ann Return (w trading costs) | -0.2% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | -0.0% |
| Return Pcnt Since TOS Status | 0.0% |
| Ann Return (Compnd, No Fees) | 0.7% |
Slump
| Current Slump as Pcnt Equity | 12.7% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 1.0% |
Instruments
| Percent Trades Forex | 0.0% |
|---|---|
| Percent Trades Futures | 0.0% |
| Percent Trades Options | 0.0% |
| Percent Trades Stocks | 1.0% |
Risk of Ruin (Monte-Carlo)
| Chance of 10% account loss | 100.0% |
|---|---|
| Chance of 20% account loss | 100.0% |
| 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% |
| Chance of 100% account loss (Monte Carlo) | — |
Automation
| Percentage Signals Automated | 0.0% |
|---|
Popularity
| Popularity (Today) | 0 |
|---|---|
| Popularity (Last 6 weeks) | 0 |
| Popularity (7 days, Percentile 1000 scale) | 0 |
Trading Style
| Any stock shorts? 0/1 | 1 |
|---|
Trades-Own-System Certification
| Trades Own System? | 0 |
|---|---|
| TOS percent | 0.0% |
Win / Loss
| Avg Loss | $203 |
|---|---|
| Avg Win | $261 |
| # Winners | 74 |
| Sum Trade PL (losers) | $16,880 |
| Sum Trade PL (winners) | $19,343 |
| Num Months Winners | 12 |
| # Losers | 83 |
| % Winners | 47.1% |
Dividends
| Dividends Received in Model Acct | 233 |
|---|
Age
| Num Months filled monthly returns table | 180 |
|---|
Frequency
| Avg Position Time (mins) | 1686.90 |
|---|---|
| Avg Position Time (hrs) | 28.11 |
| Avg Trade Length | 1.20 |
| Last Trade Ago | 4718 |
Regression
| Alpha | -0.01 |
|---|---|
| Beta | 0.01 |
| Treynor Index | -0.53 |
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 | 0.01 |
| 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 | 12.55 |
| MAE:PL (avg, all trades) | -0.42 |
| MAE:PL (avg, losing trades) | — |
| MAE:PL - Losing Trades - this strat Percentile of All Strats | 28.99 |
| MAE:PL - Winning Trades - this strat Percentile of All Strats | 29.16 |
| MAE:PL (avg, winning trades) | — |
| MAE:PL - worst single value for strategy | — |
| Avg(MAE) / Avg(PL) - Winning trades | 0.42 |
| Avg(MAE) / Avg(PL) - Losing trades | -1.11 |
| Hold-and-Hope Ratio | 0.08 |
RATIO STATISTICS
| Mean | -0.00 |
|---|---|
| SD | 0.07 |
| Sharpe ratio (Glass type estimate) | -0.02 |
| Sharpe ratio (Hedges UMVUE) | -0.02 |
| df | 51 |
| t | -0.05 |
| p | 0.52 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -0.97 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 0.92 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -0.97 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.92 |
| Sortino ratio | -0.04 |
| Upside Potential Ratio | 1.66 |
| Upside part of mean | 0.08 |
| Downside part of mean | -0.08 |
| Upside SD | 0.05 |
| Downside SD | 0.05 |
| N nonnegative terms | 12 |
| N negative terms | 40 |
| N of observations | 52 |
| Mean of predictor | 0.44 |
| Mean of criterion | -0.00 |
| SD of predictor | 0.27 |
| SD of criterion | 0.07 |
| Covariance | 0.00 |
| r | 0.00 |
| b (slope, estimate of beta) | 0.00 |
| a (intercept, estimate of alpha) | -0.00 |
| Mean Square Error | 0.01 |
| DF error | 50 |
| t(b) | 0.01 |
| p(b) | 0.50 |
| t(a) | -0.05 |
| p(a) | 0.52 |
| Lowerbound of 95% confidence interval for beta | -0.08 |
| Upperbound of 95% confidence interval for beta | 0.08 |
| Lowerbound of 95% confidence interval for alpha | -0.08 |
| Upperbound of 95% confidence interval for alpha | 0.08 |
| Treynor index (mean / b) | -5.55 |
| Jensen alpha (a) | -0.00 |
| Mean | -0.00 |
| SD | 0.07 |
| Sharpe ratio (Glass type estimate) | -0.06 |
| Sharpe ratio (Hedges UMVUE) | -0.06 |
| df | 51 |
| t | -0.12 |
| p | 0.55 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -1.00 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 0.88 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.00 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.88 |
| Sortino ratio | -0.09 |
| Upside Potential Ratio | 1.60 |
| Upside part of mean | 0.08 |
| Downside part of mean | -0.08 |
| Upside SD | 0.05 |
| Downside SD | 0.05 |
| N nonnegative terms | 12 |
| N negative terms | 40 |
| N of observations | 52 |
| Mean of predictor | 0.39 |
| Mean of criterion | -0.00 |
| SD of predictor | 0.25 |
| SD of criterion | 0.07 |
| Covariance | 0.00 |
| r | 0.01 |
| b (slope, estimate of beta) | 0.00 |
| a (intercept, estimate of alpha) | -0.00 |
| Mean Square Error | 0.01 |
| DF error | 50 |
| t(b) | 0.05 |
| p(b) | 0.48 |
| t(a) | -0.13 |
| p(a) | 0.55 |
| Lowerbound of 95% confidence interval for beta | -0.08 |
| Upperbound of 95% confidence interval for beta | 0.08 |
| Lowerbound of 95% confidence interval for alpha | -0.08 |
| Upperbound of 95% confidence interval for alpha | 0.07 |
| Treynor index (mean / b) | -2.34 |
| Jensen alpha (a) | -0.00 |
| VaR(95%) | 0.03 |
| Expected Shortfall on VaR | 0.04 |
| VaR(95%) | 0.02 |
| Expected Shortfall on VaR | 0.04 |
| Mean | -0.00 |
| SD | 0.06 |
| Sharpe ratio (Glass type estimate) | -0.04 |
| Sharpe ratio (Hedges UMVUE) | -0.04 |
| df | 1138 |
| t | -0.08 |
| p | 0.50 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -0.98 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 0.90 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -0.98 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.90 |
| Sortino ratio | -0.06 |
| Upside Potential Ratio | 4.30 |
| Upside part of mean | 0.19 |
| Downside part of mean | -0.19 |
| Upside SD | 0.04 |
| Downside SD | 0.04 |
| N nonnegative terms | 142 |
| N negative terms | 997 |
| N of observations | 1139 |
| Mean of predictor | 0.43 |
| Mean of criterion | -0.00 |
| SD of predictor | 0.28 |
| SD of criterion | 0.06 |
| Covariance | 0.00 |
| r | 0.05 |
| b (slope, estimate of beta) | 0.01 |
| a (intercept, estimate of alpha) | -0.01 |
| Mean Square Error | 0.00 |
| DF error | 1137 |
| t(b) | 1.79 |
| p(b) | 0.47 |
| t(a) | -0.25 |
| p(a) | 0.50 |
| Lowerbound of 95% confidence interval for beta | -0.00 |
| Upperbound of 95% confidence interval for beta | 0.02 |
| Lowerbound of 95% confidence interval for alpha | -0.07 |
| Upperbound of 95% confidence interval for alpha | 0.05 |
| Treynor index (mean / b) | -0.20 |
| Jensen alpha (a) | -0.01 |
| Mean | -0.00 |
| SD | 0.06 |
| Sharpe ratio (Glass type estimate) | -0.07 |
| Sharpe ratio (Hedges UMVUE) | -0.07 |
| df | 1138 |
| t | -0.15 |
| p | 0.50 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -1.01 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 0.87 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -1.01 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.87 |
| Sortino ratio | -0.10 |
| Upside Potential Ratio | 4.24 |
| Upside part of mean | 0.19 |
| Downside part of mean | -0.19 |
| Upside SD | 0.04 |
| Downside SD | 0.04 |
| N nonnegative terms | 142 |
| N negative terms | 997 |
| N of observations | 1139 |
| Mean of predictor | 0.40 |
| Mean of criterion | -0.00 |
| SD of predictor | 0.28 |
| SD of criterion | 0.06 |
| Covariance | 0.00 |
| r | 0.05 |
| b (slope, estimate of beta) | 0.01 |
| a (intercept, estimate of alpha) | -0.01 |
| Mean Square Error | 0.00 |
| DF error | 1137 |
| t(b) | 1.76 |
| p(b) | 0.47 |
| t(a) | -0.30 |
| p(a) | 0.51 |
| Lowerbound of 95% confidence interval for beta | -0.00 |
| Upperbound of 95% confidence interval for beta | 0.02 |
| Lowerbound of 95% confidence interval for alpha | -0.07 |
| Upperbound of 95% confidence interval for alpha | 0.05 |
| Treynor index (mean / b) | -0.37 |
| Jensen alpha (a) | -0.01 |
| VaR(95%) | 0.01 |
| Expected Shortfall on VaR | 0.01 |
| VaR(95%) | 0.00 |
| Expected Shortfall on VaR | 0.01 |
| 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 | 1.02 |
| Mean of criterion | -0.03 |
| SD of predictor | 0.50 |
| 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 | 0.90 |
| Mean of criterion | -0.03 |
| SD of predictor | 0.50 |
| 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) | -6824147371950080 |
| p(a) | 1 |
| Lowerbound of 95% confidence interval for beta | 0 |
| VAR (95 Confidence Intrvl) | 0.01 |
| 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) | -1.90478680966304e+32 |
| 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 | 52 |
|---|---|
| Minimum | 0.95 |
| Quartile 1 | 1 |
| Median | 1 |
| Quartile 3 | 1 |
| Maximum | 1.05 |
| Mean of quarter 1 | 0.98 |
| Mean of quarter 2 | 1 |
| Mean of quarter 3 | 1 |
| Mean of quarter 4 | 1.03 |
| Inter Quartile Range | 0 |
| Number outliers low | 11 |
| Percentage of outliers low | 0.21 |
| Mean of outliers low | 0.98 |
| Number of outliers high | 12 |
| Percentage of outliers high | 0.23 |
| Mean of outliers high | 1.03 |
| Extreme Value Index (moments method) | 0 |
| VaR(95%) (moments method) | 0 |
| Expected Shortfall (moments method) | 0 |
| Extreme Value Index (regression method) | -0.79 |
| VaR(95%) (regression method) | 0.02 |
| Expected Shortfall (regression method) | 0.03 |
| Number of observations | 1139 |
| Minimum | 0.97 |
| Quartile 1 | 1 |
| Median | 1 |
| Quartile 3 | 1 |
| Maximum | 1.03 |
| Mean of quarter 1 | 1.00 |
| Mean of quarter 2 | 1 |
| Mean of quarter 3 | 1 |
| Mean of quarter 4 | 1.00 |
| Inter Quartile Range | 0 |
| Number outliers low | 131 |
| Percentage of outliers low | 0.12 |
| Mean of outliers low | 0.99 |
| Number of outliers high | 146 |
| Percentage of outliers high | 0.13 |
| Mean of outliers high | 1.01 |
| Extreme Value Index (moments method) | 0.17 |
| VaR(95%) (moments method) | 0.00 |
| Expected Shortfall (moments method) | 0.00 |
| Extreme Value Index (regression method) | 0.03 |
| VaR(95%) (regression method) | 0.00 |
| Expected Shortfall (regression method) | 0.01 |
| 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 | 5 |
|---|---|
| Minimum | 0.01 |
| Quartile 1 | 0.01 |
| Median | 0.02 |
| Quartile 3 | 0.04 |
| Maximum | 0.10 |
| Mean of quarter 1 | 0.01 |
| Mean of quarter 2 | 0.02 |
| Mean of quarter 3 | 0.04 |
| Mean of quarter 4 | 0.10 |
| Inter Quartile Range | 0.03 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 1 |
| Percentage of outliers high | 0.20 |
| Mean of outliers high | 0.10 |
| 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 | 8 |
| Minimum | 0.01 |
| Quartile 1 | 0.01 |
| Median | 0.03 |
| Quartile 3 | 0.05 |
| Maximum | 0.15 |
| Mean of quarter 1 | 0.01 |
| Mean of quarter 2 | 0.01 |
| Mean of quarter 3 | 0.04 |
| Mean of quarter 4 | 0.10 |
| Inter Quartile Range | 0.04 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 1 |
| Percentage of outliers high | 0.12 |
| Mean of outliers high | 0.15 |
| 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 | 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? | -403786496 |
| Max Equity Drawdown (num days) | 431 |
| Last 4 Months - Pcnt Negative | 0.0% |
COMBINED STATISTICS
| Annualized return (arithmetic extrapolation) | 0.02 |
|---|---|
| Compounded annual return (geometric extrapolation) | 0.02 |
| Calmar ratio (compounded annual return / max draw down) | 0.23 |
| Compounded annual return / average of 25% largest draw downs | 0.23 |
| Compounded annual return / Expected Shortfall lognormal | 0.57 |
| j156mfCOMBRisPar | 0 |
| j157mfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 0.02 |
| Compounded annual return (geometric extrapolation) | 0.02 |
| Calmar ratio (compounded annual return / max draw down) | 0.16 |
| Compounded annual return / average of 25% largest draw downs | 0.23 |
| Compounded annual return / Expected Shortfall lognormal | 3.03 |
| 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 38 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| SPY | long | 276 | Oct 10, 2013 | Oct 10, 2013 | $367 |
| SPY | short | 276 | Oct 7, 2013 | Oct 8, 2013 | $419 |
| SPY | long | 274 | Oct 4, 2013 | Oct 7, 2013 | ($421) |
| SPY | short | 171 | Sep 20, 2013 | Sep 24, 2013 | $173 |
| SPY | short | 280 | Sep 6, 2013 | Sep 6, 2013 | ($415) |
| SPY | long | 280 | Sep 4, 2013 | Sep 5, 2013 | $226 |
| SPY | short | 262 | Sep 3, 2013 | Sep 4, 2013 | ($233) |
| SPY | short | 248 | Aug 26, 2013 | Aug 27, 2013 | $431 |
| SPY | long | 233 | Aug 23, 2013 | Aug 23, 2013 | ($157) |
| SPY | short | 273 | Aug 14, 2013 | Aug 15, 2013 | $678 |
| SPY | long | 273 | Aug 13, 2013 | Aug 14, 2013 | ($169) |
| SPY | long | 544 | Aug 13, 2013 | Aug 13, 2013 | $57 |
| SPY | short | 274 | Aug 7, 2013 | Aug 13, 2013 | ($199) |
| SPY | long | 273 | Aug 6, 2013 | Aug 7, 2013 | ($166) |
| SPY | long | 272 | Aug 1, 2013 | Aug 2, 2013 | $85 |
| SPY | short | 275 | Jul 30, 2013 | Jul 31, 2013 | ($314) |
| SPY | long | 275 | Jul 29, 2013 | Jul 30, 2013 | ($100) |
| SPY | short | 254 | Jul 26, 2013 | Jul 26, 2013 | ($295) |
| SPY | long | 182 | Jul 24, 2013 | Jul 26, 2013 | ($95) |
| SPY | short | 182 | Jul 24, 2013 | Jul 24, 2013 | ($22) |
| SPY | long | 278 | May 30, 2013 | Jul 16, 2013 | $494 |
| SPY | short | 280 | May 29, 2013 | May 29, 2013 | ($56) |
| SPY | long | 277 | May 28, 2013 | May 28, 2013 | ($543) |
| SPY | short | 194 | May 22, 2013 | May 23, 2013 | ($14) |
| SPY | long | 291 | May 2, 2013 | May 2, 2013 | $262 |
| SPY | long | 296 | Apr 22, 2013 | Apr 23, 2013 | $106 |
| SPY | short | 297 | Apr 17, 2013 | Apr 17, 2013 | $172 |
| SPY | long | 294 | Apr 16, 2013 | Apr 17, 2013 | ($350) |
| SPY | short | 294 | Apr 15, 2013 | Apr 15, 2013 | $182 |
| SPY | long | 297 | Apr 8, 2013 | Apr 9, 2013 | $383 |
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.