Buffalo Q
- hypothetical · Annual Return (Compounded)
- -3.5%
- Max Drawdown
- 42.9%
- Trades
- 30
- Win Trades
- 53.3%
- Profit Factor
- 0.70
- Win Months
- 4.9%
About this strategy
****It is FREE to add this strategy to your Watch List or to start Simulate.
If you have questions about my strategy, feel free to reach me out by email buffaloasset@gmail.com.
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Main difference between our two strategies
………………..............…………...Buffalo………….........……Buffalo Q...............
Focus:…………...........…………US large-cap stocks…..US tech stocks.....
Equity holding:………….......10 to 20…………......……5 to 10...................
Average trade per month:9..…………..........………….5.............................
Average holding time:…....1.5 month……….....…….1.5 month.............
Average leverage:………......1.3…………………..........…1.4..........................
Return:....…………………….....Moderate……….....……..High.......................
Risk:....……………….........…….Moderate……….....……..High.......................
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****Description of strategy "Buffalo Q" ****
Although this strategy only deployed on Colletive2 in August 2021, I have been back-testing, optimising, and tracking real-time performance of this model for years. I saw promising results. I know it is weak to say how good our strategy is without having a Collective2 solid tracking record. You may want to wait for six months or more before subscription. However, if you are reading, add this strategy to your Watch List or start Simulate, it is free to do so. Track it for six months and see the result.
1. Summary
This strategy focuses on technology section and holds companies that have the most upward momentum.
2. Objective
To achieve an outsized return higher than SPX500 over the long term, with a lower maximum drawback.
3. System description
The theory behind this model is momentum. Stocks that have risen in the past tend to keep rising. Stocks that have done poorly tend to keep falling. Stocks that have the most upward momentum beat the market.
This strategy is fully algorithm based. It uses a diverse set of factors and multiple performance windows to rank assets from an asset pool. It only holds the top best-performing assets. The performance of each asset will be reviewed monthly. Generally, changes in asset allocation happen once a month especially on the last trading day of each month. At the time when there is no asset meeting its criteria, it simply holds cash.
To ensure best performance and avoid lack of liquidity, our asset pool is composed of carefully selected medium-large US stocks, index ETFs and Bond ETFs.
4. Key Features:
Fully algorithm based
Designed to scale up
Average 1.5 months holding time
Average 6 trades each month
Medium-large stocks and ETFs only strategy
Long-only strategy
AutoTrade (recommended, hassle-free) or manual.
Sophisticated risk management
5. Risk management
The following defensive strategy is used to protecting profits.
a. Hold and be patient. Keep a close eye on the market.
b. Close risky positions.
c. Reduce leverage
d. Add hedges to the portfolio, including Inverse ETFs and Bond ETFs.
Stop Loss is used and will be updated regularly as well.
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FAQs
1. Should I copy open trades?
Yes
2. What is the minimum amount I should copy?
For AutoTraders, the recommended minimum amount is $20000 otherwise you may not 100% copy all my trades. Why? First, some stocks are not cheap. e.g. AMZN $3300/share, GOOGL $2800/share. Second, C2 AutoTrade rounds down fractions.
For manual traders, if your broker has fractional trading available, a minimum amount of $1000 will do, otherwise recommended minimum amount is $20000.
3. When is the best time to start copying?
The best time is now. You have to enter the market, in order to beat the market. As a long-term investor, the daily movements in markets will ultimately have a marginal effect on your returns.
4. Does this system need to be AutoTraded?
AutoTrade is recommended, hassle-free.
Manual trading also works.
As we know that AutoTrade is not supported by all brokers, you can copy my positions manually. Signals will be sent by C2 system-generated emails at the same time when I enter/close positions. You could simply copy my trade at market price. It is been back-tested that there is not much difference in returns between trading by using end of day price and trading by using the next day open price. Manual trading may have a little advantage which is you could 100% copy my portfolio if your broker has fractional trading available. Why? Because C2 AutoTrade rounds down fractions.
For manual traders, make sure you have C2 signal alerts turned on. Refer to https://support.collective2.com/hc/en-us/articles/115013734467-Can-I-receive-real-time-signal-alerts-
5. Do you short stocks?
No.
6. Do you use leverage?
Yes, average 1.5 leverage
7. Do you use Stops?
Yes, our strategy has a 20% Stop Loss at portfolio level, and will be updated regularly.
8. How do I set up Auto Stop Loss?
Choose "No custom stop loss. Follow strategy rules." (Recommended)
If you want to set up a custom stop loss, make it as more than 30% of every position. A stop-loss that is too small pretty much guarantees you to sell at the worst time possible. We use inverse ETFs and bond ETFs to protect our positions when necessary. Follow our strategy rules. Don't panic sell. The last thing you want is for your positions to be sold when the market crashes.
9. Which account type should I have?
Your account must have permission to trade stocks (Long) and ETF(Long). We may buy inverse ETFs (e.g. SH, PSQ) to hedge against market crashes but we DO NOT short stocks.
1). Margin account is recommended. (Recommend 100% AutoTrade Scaling)
2). Non-margin account including Cash account, Individual Retirement Account (IRA) or Self-Managed Superannuation Fund account (SMSF) also works. HOWEVER, as we know, these accounts don't allow you to borrow funds. As my strategy uses an average 1.5X leverage, please set your AutoTrade Scaling as 60% or under, otherwise, you may not copy all my positions or you may exceed your account limit.
10. How much scaling should I use?
1). For margin account holders, recommended Scaling= (the amount you wish to allocate / my model account equity)*100%.
Example:
Strategy’s current Model Account equity is $50,000.
You wish to allocate $40,000 to my strategy.
You might consider doing the following: set your AutoTrade Scaling to 80% = 40000/50000*100%.
2). For non-margin account holders, recommended Scaling= (the amount you wish to allocate / my model account equity)*100%*60%.
Our strategy uses 1.5x leverage, you cannot borrow funds and you do not want to exceed your account limit.
Example:
Strategy’s current Model Account equity is $50,000.
You wish to allocate $40,000 to my strategy.
You might consider doing the following: set your AutoTrade Scaling to 48% = (40000/50000)*100%*60%.
About Scaling, refer to https://support.collective2.com/hc/en-us/articles/115008510008-AutoTrade-Setting-Scaling-How-big-or-small-should-I-make-my-scaling-
Trend-following
Hypothetical Monthly Returns (includes fees/commissions)
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021 | 14.7 | -10.3 | 28.0 | 5.6 | -0.2 | 38.8 | |||||||
| 2022 | -23.9 | -6.9 | -15.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -39.9 |
| 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 |
Statistics
Overview
| Strategy began | 8/9/2021 |
|---|---|
| Suggested Minimum Capital | $50,000 |
| Age | 62 months |
| What it trades | Stocks |
| # Trades | 30 |
| # Profitable | 16 |
| % Profitable | 53.3% |
| Avg trade duration | 42.9 days |
| Max peak-to-valley drawdown | 42.9% |
| drawdown period | Jan 04, 2022 - March 10, 2022 |
| Annual Return (Compounded) | -3.5% |
| Avg win | $1,273 |
| Avg loss | $2,008 |
Ratios
| W:L ratio | 0.73 |
|---|---|
| Sharpe Ratio | -0.29 |
| Sortino Ratio | -0.40 |
| Calmar Ratio | -0.33 |
CORRELATION STATISTICS
| Correlation to SP500 | 0.09 |
|---|---|
| Return Percent SP500 (cumu) during strategy life | 72.3% |
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | -90.5% |
Return Statistics
| Ann Return (w trading costs) | -3.5% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | -0.0% |
| Return Pcnt Since TOS Status | 0.0% |
| Ann Return (Compnd, No Fees) | -3.2% |
Slump
| Current Slump as Pcnt Equity | 74.8% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 0.9% |
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 | 100.0% |
|---|---|
| Chance of 20% account loss | 80.0% |
| Chance of 30% account loss | 29.5% |
| Chance of 40% account loss | 4.5% |
| Chance of 50% account loss | 0.5% |
| 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) | 0 |
| Popularity (7 days, Percentile 1000 scale) | 0 |
Trading Style
| Any stock shorts? 0/1 | 0 |
|---|
Trades-Own-System Certification
| Trades Own System? | 0 |
|---|---|
| TOS percent | 0.0% |
Win / Loss
| Avg Loss | $2,008 |
|---|---|
| Avg Win | $1,272 |
| # Winners | 16 |
| Sum Trade PL (losers) | $28,118 |
| Sum Trade PL (winners) | $20,360 |
| Num Months Winners | 3 |
| # Losers | 14 |
| % Winners | 53.3% |
Dividends
| Dividends Received in Model Acct | 182 |
|---|
Age
| Num Months filled monthly returns table | 61 |
|---|
Frequency
| Avg Position Time (mins) | 61725 |
|---|---|
| Avg Position Time (hrs) | 1028.75 |
| Avg Trade Length | 42.90 |
| Last Trade Ago | 1632 |
Leverage
| Daily leverage (average) | 1.83 |
|---|---|
| Daily leverage (max) | 4.29 |
Regression
| Alpha | -0.01 |
|---|---|
| Beta | 0.07 |
| Treynor Index | -0.18 |
Maximum Adverse Excursion (MAE)
| MAE:Equity, average, all trades | 0.03 |
|---|---|
| MAE:Equity, 95th Percentile Value for this strat | 0.05 |
| MAE:Equity, average, losing trades | 0.04 |
| 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 | -4.93 |
| MAE:PL (avg, all trades) | -0.07 |
| MAE:PL (avg, losing trades) | — |
| MAE:PL (avg, winning trades) | — |
| MAE:PL - worst single value for strategy | — |
| Avg(MAE) / Avg(PL) - Winning trades | 0.41 |
| Avg(MAE) / Avg(PL) - Losing trades | -1.06 |
| Hold-and-Hope Ratio | -0.20 |
RATIO STATISTICS
| Mean | -0.07 |
|---|---|
| SD | 0.49 |
| Sharpe ratio (Glass type estimate) | -0.14 |
| Sharpe ratio (Hedges UMVUE) | -0.14 |
| df | 12 |
| t | -0.15 |
| p | 0.52 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -2.03 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.74 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -2.02 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.75 |
| Sortino ratio | -0.23 |
| Upside Potential Ratio | 1.55 |
| Upside part of mean | 0.48 |
| Downside part of mean | -0.55 |
| Upside SD | 0.35 |
| Downside SD | 0.31 |
| N nonnegative terms | 3 |
| N negative terms | 10 |
| N of observations | 13 |
| Mean of predictor | 0.50 |
| Mean of criterion | -0.07 |
| SD of predictor | 0.33 |
| SD of criterion | 0.49 |
| Covariance | 0.05 |
| r | 0.29 |
| b (slope, estimate of beta) | 0.42 |
| a (intercept, estimate of alpha) | -0.28 |
| Mean Square Error | 0.24 |
| DF error | 11 |
| t(b) | 1.00 |
| p(b) | 0.17 |
| t(a) | -0.55 |
| p(a) | 0.70 |
| Lowerbound of 95% confidence interval for beta | -0.51 |
| Upperbound of 95% confidence interval for beta | 1.36 |
| Lowerbound of 95% confidence interval for alpha | -1.41 |
| Upperbound of 95% confidence interval for alpha | 0.85 |
| Treynor index (mean / b) | -0.17 |
| Jensen alpha (a) | -0.28 |
| Mean | -0.18 |
| SD | 0.48 |
| Sharpe ratio (Glass type estimate) | -0.37 |
| Sharpe ratio (Hedges UMVUE) | -0.35 |
| df | 12 |
| t | -0.39 |
| p | 0.56 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -2.25 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.53 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -2.23 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.54 |
| Sortino ratio | -0.51 |
| Upside Potential Ratio | 1.22 |
| Upside part of mean | 0.42 |
| Downside part of mean | -0.60 |
| Upside SD | 0.31 |
| Downside SD | 0.35 |
| N nonnegative terms | 3 |
| N negative terms | 10 |
| N of observations | 13 |
| Mean of predictor | 0.44 |
| Mean of criterion | -0.18 |
| SD of predictor | 0.31 |
| SD of criterion | 0.48 |
| Covariance | 0.05 |
| r | 0.33 |
| b (slope, estimate of beta) | 0.52 |
| a (intercept, estimate of alpha) | -0.41 |
| Mean Square Error | 0.23 |
| DF error | 11 |
| t(b) | 1.17 |
| p(b) | 0.13 |
| t(a) | -0.82 |
| p(a) | 0.79 |
| Lowerbound of 95% confidence interval for beta | -0.45 |
| Upperbound of 95% confidence interval for beta | 1.49 |
| Lowerbound of 95% confidence interval for alpha | -1.50 |
| Upperbound of 95% confidence interval for alpha | 0.68 |
| Treynor index (mean / b) | -0.35 |
| Jensen alpha (a) | -0.41 |
| VaR(95%) | 0.22 |
| Expected Shortfall on VaR | 0.26 |
| VaR(95%) | 0.14 |
| Expected Shortfall on VaR | 0.25 |
| Mean | -0.14 |
| SD | 0.27 |
| Sharpe ratio (Glass type estimate) | -0.51 |
| Sharpe ratio (Hedges UMVUE) | -0.50 |
| df | 287 |
| t | -0.53 |
| p | 0.70 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -2.37 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.36 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -2.37 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.37 |
| Sortino ratio | -0.70 |
| Upside Potential Ratio | 6.10 |
| Upside part of mean | 1.21 |
| Downside part of mean | -1.35 |
| Upside SD | 0.19 |
| Downside SD | 0.20 |
| N nonnegative terms | 72 |
| N negative terms | 216 |
| N of observations | 288 |
| Mean of predictor | 0.54 |
| Mean of criterion | -0.14 |
| SD of predictor | 0.32 |
| SD of criterion | 0.27 |
| Covariance | 0.01 |
| r | 0.10 |
| b (slope, estimate of beta) | 0.09 |
| a (intercept, estimate of alpha) | -0.19 |
| Mean Square Error | 0.07 |
| DF error | 286 |
| t(b) | 1.77 |
| p(b) | 0.04 |
| t(a) | -0.71 |
| p(a) | 0.76 |
| Lowerbound of 95% confidence interval for beta | -0.01 |
| Upperbound of 95% confidence interval for beta | 0.19 |
| Lowerbound of 95% confidence interval for alpha | -0.70 |
| Upperbound of 95% confidence interval for alpha | 0.33 |
| Treynor index (mean / b) | -1.54 |
| Jensen alpha (a) | -0.19 |
| Mean | -0.18 |
| SD | 0.27 |
| Sharpe ratio (Glass type estimate) | -0.64 |
| Sharpe ratio (Hedges UMVUE) | -0.64 |
| df | 287 |
| t | -0.67 |
| p | 0.75 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -2.51 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.23 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -2.51 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.23 |
| Sortino ratio | -0.87 |
| Upside Potential Ratio | 5.89 |
| Upside part of mean | 1.19 |
| Downside part of mean | -1.37 |
| Upside SD | 0.19 |
| Downside SD | 0.20 |
| N nonnegative terms | 72 |
| N negative terms | 216 |
| N of observations | 288 |
| Mean of predictor | 0.48 |
| Mean of criterion | -0.18 |
| SD of predictor | 0.32 |
| SD of criterion | 0.27 |
| Covariance | 0.01 |
| r | 0.11 |
| b (slope, estimate of beta) | 0.09 |
| a (intercept, estimate of alpha) | -0.22 |
| Mean Square Error | 0.07 |
| DF error | 286 |
| t(b) | 1.80 |
| p(b) | 0.04 |
| t(a) | -0.84 |
| p(a) | 0.80 |
| Lowerbound of 95% confidence interval for beta | -0.01 |
| Upperbound of 95% confidence interval for beta | 0.19 |
| Lowerbound of 95% confidence interval for alpha | -0.74 |
| Upperbound of 95% confidence interval for alpha | 0.30 |
| Treynor index (mean / b) | -1.92 |
| Jensen alpha (a) | -0.22 |
| VaR(95%) | 0.03 |
| Expected Shortfall on VaR | 0.04 |
| VaR(95%) | 0.02 |
| Expected Shortfall on VaR | 0.03 |
| 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 | 1.17 |
| Mean of criterion | -0.03 |
| SD of predictor | 0.41 |
| 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 | 1.08 |
| Mean of criterion | -0.03 |
| SD of predictor | 0.42 |
| 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) | -6779752442494976 |
| p(a) | 1 |
| Lowerbound of 95% confidence interval for beta | 0 |
| VAR (95 Confidence Intrvl) | 0.03 |
| 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) | -5.89608112906218e+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 | 13 |
|---|---|
| Minimum | 0.73 |
| Quartile 1 | 0.92 |
| Median | 1 |
| Quartile 3 | 1 |
| Maximum | 1.33 |
| Mean of quarter 1 | 0.86 |
| Mean of quarter 2 | 0.99 |
| Mean of quarter 3 | 1 |
| Mean of quarter 4 | 1.17 |
| Inter Quartile Range | 0.08 |
| Number outliers low | 1 |
| Percentage of outliers low | 0.08 |
| Mean of outliers low | 0.73 |
| Number of outliers high | 2 |
| Percentage of outliers high | 0.15 |
| Mean of outliers high | 1.25 |
| Extreme Value Index (moments method) | 0.41 |
| VaR(95%) (moments method) | 0.17 |
| Expected Shortfall (moments method) | 0.31 |
| Extreme Value Index (regression method) | 1.58 |
| VaR(95%) (regression method) | 0.22 |
| Expected Shortfall (regression method) | 0 |
| Number of observations | 288 |
| Minimum | 0.93 |
| Quartile 1 | 1.00 |
| Median | 1 |
| Quartile 3 | 1.00 |
| Maximum | 1.06 |
| Mean of quarter 1 | 0.98 |
| Mean of quarter 2 | 1.00 |
| Mean of quarter 3 | 1 |
| Mean of quarter 4 | 1.02 |
| Inter Quartile Range | 0.00 |
| Number outliers low | 59 |
| Percentage of outliers low | 0.20 |
| Mean of outliers low | 0.98 |
| Number of outliers high | 60 |
| Percentage of outliers high | 0.21 |
| Mean of outliers high | 1.02 |
| Extreme Value Index (moments method) | -0.68 |
| VaR(95%) (moments method) | 0.01 |
| Expected Shortfall (moments method) | 0.01 |
| Extreme Value Index (regression method) | -0.13 |
| VaR(95%) (regression method) | 0.02 |
| Expected Shortfall (regression method) | 0.03 |
| 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 | 2 |
|---|---|
| Minimum | 0.09 |
| Quartile 1 | 0.17 |
| Median | 0.25 |
| Quartile 3 | 0.33 |
| Maximum | 0.41 |
| Mean of quarter 1 | 0.09 |
| Mean of quarter 2 | 0 |
| Mean of quarter 3 | 0 |
| Mean of quarter 4 | 0.41 |
| Inter Quartile Range | 0.16 |
| 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 | 7 |
| Minimum | 0.00 |
| Quartile 1 | 0.00 |
| Median | 0.03 |
| Quartile 3 | 0.09 |
| Maximum | 0.42 |
| Mean of quarter 1 | 0.00 |
| Mean of quarter 2 | 0.02 |
| Mean of quarter 3 | 0.03 |
| Mean of quarter 4 | 0.29 |
| Inter Quartile Range | 0.09 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 1 |
| Percentage of outliers high | 0.14 |
| Mean of outliers high | 0.42 |
| 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? | -375928544 |
| Max Equity Drawdown (num days) | 65 |
| Last 4 Months - Pcnt Negative | 0.0% |
COMBINED STATISTICS
| Annualized return (arithmetic extrapolation) | -0.14 |
|---|---|
| Compounded annual return (geometric extrapolation) | -0.14 |
| Calmar ratio (compounded annual return / max draw down) | -0.34 |
| Compounded annual return / average of 25% largest draw downs | -0.34 |
| Compounded annual return / Expected Shortfall lognormal | -0.54 |
| j156mfCOMBRisPar | 0 |
| j157mfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | -0.14 |
| Compounded annual return (geometric extrapolation) | -0.14 |
| Calmar ratio (compounded annual return / max draw down) | -0.33 |
| Compounded annual return / average of 25% largest draw downs | -0.48 |
| Compounded annual return / Expected Shortfall lognormal | -3.94 |
| 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 47 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| UBT | long | 1839 | Jan 28, 2022 | Mar 10, 2022 | ($10,395) |
| AMAT | long | 72 | Jan 13, 2022 | Jan 28, 2022 | ($2,502) |
| KLAC | long | 28 | Jan 10, 2022 | Jan 28, 2022 | ($1,891) |
| MU | long | 124 | Jan 10, 2022 | Jan 28, 2022 | ($1,886) |
| TSLA | long | 11 | Dec 31, 2021 | Jan 28, 2022 | ($2,488) |
| AAPL | long | 65 | Dec 13, 2021 | Jan 28, 2022 | ($847) |
| MRVL | long | 162 | Nov 30, 2021 | Jan 21, 2022 | $720 |
| QCOM | long | 67 | Nov 15, 2021 | Jan 20, 2022 | $173 |
| AVGO | long | 18 | Dec 13, 2021 | Jan 18, 2022 | ($734) |
| COST | long | 22 | Nov 15, 2021 | Jan 10, 2022 | $42 |
| NVDA | long | 52 | Aug 31, 2021 | Jan 10, 2022 | $2,500 |
| AMD | long | 107 | Oct 1, 2021 | Jan 10, 2022 | $3,094 |
| INTU | long | 18 | Aug 31, 2021 | Dec 17, 2021 | $898 |
| LULU | long | 25 | Nov 30, 2021 | Dec 13, 2021 | ($1,173) |
| KLAC | long | 28 | Nov 24, 2021 | Dec 13, 2021 | ($218) |
| MSFT | long | 34 | Oct 29, 2021 | Nov 30, 2021 | $140 |
| TEAM | long | 27 | Aug 31, 2021 | Nov 30, 2021 | $375 |
| NFLX | long | 16 | Oct 1, 2021 | Nov 23, 2021 | $803 |
| TSLA | long | 13 | Oct 1, 2021 | Nov 15, 2021 | $3,155 |
| CRWD | long | 39 | Oct 29, 2021 | Nov 15, 2021 | ($613) |
| COST | long | 22 | Oct 1, 2021 | Oct 29, 2021 | $921 |
| ISRG | long | 30 | Aug 31, 2021 | Oct 29, 2021 | $158 |
| DOCU | long | 34 | Aug 31, 2021 | Oct 1, 2021 | ($1,298) |
| ASML | long | 12 | Aug 31, 2021 | Oct 1, 2021 | ($1,092) |
| ADBE | long | 15 | Aug 31, 2021 | Oct 1, 2021 | ($1,316) |
| REGN | long | 15 | Aug 31, 2021 | Oct 1, 2021 | ($1,679) |
| ASML | long | 31 | Aug 9, 2021 | Aug 31, 2021 | $1,243 |
| NVDA | long | 122 | Aug 9, 2021 | Aug 31, 2021 | $2,222 |
| INTU | long | 47 | Aug 9, 2021 | Aug 31, 2021 | $1,341 |
| TEAM | long | 75 | Aug 9, 2021 | Aug 31, 2021 | $2,560 |
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.