This system has earned Trades-Own-Strategy (TOS) Certification.
This means that the manager of this system trades his own strategy
in a real-life, funded brokerage account.
Trades-Own-Strategy (TOS) Certification Details
Certification process started
09/21/2020
Most recent certification approved
9/21/20 9:56 ET
Trades at broker
Interactive Brokers (Stocks, Options, Futures)
Scaling percentage used
100%
# trading signals issued by system since certification
725
# trading signals executed in manager's Interactive Brokers (Stocks, Options, Futures) account
724
Percent signals followed since 09/21/2020
99.9%
This information was last updated
8/13/22 7:59 ET
Warning: System trading results are still hypothetical.
Even though the system developer is currently trading his own system in a real-life brokerage account,
the trading results presented on this Web site must still be regarded as purely hypothetical results.
This is because (among other reasons) the system developer may not have traded all signals,
particularly those that occurred before 09/21/2020,
and the system developer's results may not match the system results presented here. In addition,
not all subscribers have received the same trades or prices as the system manager has. For these reasons, and others, it is extremely important you remember the following:
About the results you see on this Web site
Past results are not necessarily indicative of future results.
These results are based on simulated or hypothetical performance results.
Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program.
One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.
You may be interested to learn more technical details about
how Collective2 calculates the hypothetical results you see on this web site.
Patience is a Virtue
(123937705)

This system has earned Trades-Own-Strategy (TOS) Certification. This means that the manager of this system trades his own strategy in a real-life, funded brokerage account.
Trades-Own-Strategy (TOS) Certification Details | |
---|---|
Certification process started | 09/21/2020 |
Most recent certification approved | 9/21/20 9:56 ET |
Trades at broker | Interactive Brokers (Stocks, Options, Futures) |
Scaling percentage used | 100% |
# trading signals issued by system since certification | 725 |
# trading signals executed in manager's Interactive Brokers (Stocks, Options, Futures) account | 724 |
Percent signals followed since 09/21/2020 | 99.9% |
This information was last updated | 8/13/22 7:59 ET |
Warning: System trading results are still hypothetical.
Even though the system developer is currently trading his own system in a real-life brokerage account, the trading results presented on this Web site must still be regarded as purely hypothetical results. This is because (among other reasons) the system developer may not have traded all signals, particularly those that occurred before 09/21/2020, and the system developer's results may not match the system results presented here. In addition, not all subscribers have received the same trades or prices as the system manager has. For these reasons, and others, it is extremely important you remember the following:
About the results you see on this Web site
Past results are not necessarily indicative of future results.
These results are based on simulated or hypothetical performance results. Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program.
One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.
You may be interested to learn more technical details about how Collective2 calculates the hypothetical results you see on this web site.
Subscription terms. Subscriptions to this system cost $125.00 per month.
C2Star
C2Star is a certification program for trading strategies. In order to become "C2Star Certified," a strategy must apply tight risk controls, and must exhibit excellent performance characteristics, including low drawdowns.
You can read more about C2Star certification requirements here.
Note that: all trading strategies are risky, and C2Star Certification does not imply that a strategy is low risk.
Trend-following
Tries to take advantage of long, medium or short-term moves that seem to play out in various markets. Typically, trend-following analysis is backward looking; that is, it attempts to recognize and profit from already-established trends.Sector Rotation
Uses the proceeds from the sale of securities related to a particular investment sector for the purchase of securities in another sector. This strategy is used as a method for capturing returns from market cycles and diversifying holdings over a specified holding period.Rate of Return Calculations
Overview
To comply with NFA regulations, we display Cumulative Rate of Return for strategies with a track record of less than one year. For strategies with longer track records, we display Annualized (Compounded) Rate of Return.
How Annualized (Compounded) Rate of Return is calculated
= ((Ending_equity / Starting_equity) ^ (1 / age_in_years)) - 1
Remember that, following NFA requirements, strategy subscription costs and estimated commissions are included in marked-to-market equity calculations.
All results are hypothetical.
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2019 | +17.0% | (0.7%) | +3.3% | (8%) | +1.5% | +0.7% | +7.2% | +20.7% | |||||
2020 | +9.5% | +9.4% | +30.2% | +8.5% | (0.8%) | +4.3% | +15.4% | +18.4% | (17.7%) | +5.8% | +20.4% | +15.5% | +189.8% |
2021 | (1.1%) | +7.9% | +7.4% | +7.2% | (6.8%) | +2.3% | +2.9% | +9.1% | (12.1%) | +15.3% | (0.3%) | (2.8%) | +29.2% |
2022 | (13.5%) | (4%) | (2.4%) | (14%) | (8.4%) | (2.1%) | (0.4%) | (1.3%) | (38.5%) |
Model Account Details
A trading strategy on Collective2. Follow it in your broker account, or use a free simulated trading account.
Advanced users may want to use this information to adjust their AutoTrade scaling, or merely to understand the magnitudes of the nearby chart.
Started | $37,500 | |
Buy Power | $54,148 | |
Cash | $1 | |
Equity | $1 | |
Cumulative $ | $74,188 | |
Includes dividends and cash-settled expirations: | $293 | Itemized |
Total System Equity | $111,688 | |
Margined | $1 | |
Open P/L | $270 | |
Data has been delayed by 168 hours for non-subscribers |
System developer has asked us to delay this information by 168 hours.
Trading Record
Statistics
-
Strategy began6/4/2019
-
Suggested Minimum Cap$15,000
-
Strategy Age (days)1165.66
-
Age39 months ago
-
What it tradesStocks
-
# Trades111
-
# Profitable53
-
% Profitable47.70%
-
Avg trade duration50.9 days
-
Max peak-to-valley drawdown45.7%
-
drawdown periodNov 22, 2021 - Aug 05, 2022
-
Annual Return (Compounded)37.6%
-
Avg win$3,293
-
Avg loss$1,735
- Model Account Values (Raw)
-
Cash$52,137
-
Margin Used$0
-
Buying Power$54,148
- Ratios
-
W:L ratio1.74:1
-
Sharpe Ratio0.97
-
Sortino Ratio1.42
-
Calmar Ratio0.977
- CORRELATION STATISTICS
-
Return of Strat Pcnt - Return of SP500 Pcnt (cumu)125.12%
-
Correlation to SP5000.18140
-
Return Percent SP500 (cumu) during strategy life52.68%
- Return Statistics
-
Ann Return (w trading costs)37.6%
- Slump
-
Current Slump as Pcnt Equity79.10%
- Instruments
-
Percent Trades Futuresn/a
- Slump
-
Current Slump, time of slump as pcnt of strategy life0.23%
- Return Statistics
-
Return Pcnt Since TOS Status143.940%
- Instruments
-
Short Options - Percent Covered100.00%
- Return Statistics
-
Return Pcnt (Compound or Annual, age-based, NFA compliant)0.376%
- Instruments
-
Percent Trades Options0.03%
-
Percent Trades Stocks0.97%
-
Percent Trades Forexn/a
- Return Statistics
-
Ann Return (Compnd, No Fees)40.7%
- Risk of Ruin (Monte-Carlo)
-
Chance of 10% account loss47.50%
-
Chance of 20% account loss18.50%
-
Chance of 30% account loss6.00%
-
Chance of 40% account loss1.50%
-
Chance of 60% account loss (Monte Carlo)n/a
-
Chance of 70% account loss (Monte Carlo)n/a
-
Chance of 80% account loss (Monte Carlo)n/a
-
Chance of 90% account loss (Monte Carlo)n/a
- Automation
-
Percentage Signals Automatedn/a
- Risk of Ruin (Monte-Carlo)
-
Chance of 50% account lossn/a
- Popularity
-
Popularity (Today)836
-
Popularity (Last 6 weeks)931
- Trading Style
-
Any stock shorts? 0/10
- Popularity
-
C2 Score880
-
Popularity (7 days, Percentile 1000 scale)856
- Trades-Own-System Certification
-
Trades Own System?Yes
-
TOS percent100%
- Win / Loss
-
Avg Loss$1,735
-
Avg Win$3,293
-
Sum Trade PL (losers)$100,636.000
- Age
-
Num Months filled monthly returns table39
- Win / Loss
-
Sum Trade PL (winners)$174,532.000
-
# Winners53
-
Num Months Winners22
- Dividends
-
Dividends Received in Model Acct293
- AUM
-
AUM (AutoTrader live capital)382878
- Win / Loss
-
# Losers58
-
% Winners47.8%
- Frequency
-
Avg Position Time (mins)73321.50
-
Avg Position Time (hrs)1222.03
-
Avg Trade Length50.9 days
-
Last Trade Ago2
- Leverage
-
Daily leverage (average)1.60
-
Daily leverage (max)3.62
- Regression
-
Alpha0.09
-
Beta0.23
-
Treynor Index0.42
- Maximum Adverse Excursion (MAE)
-
MAE:Equity, average, all trades0.01
-
MAE:PL - worst single value for strategy-
-
MAE:PL (avg, winning trades)-
-
MAE:PL (avg, losing trades)-
-
MAE:PL (avg, all trades)0.27
-
MAE:Equity, average, winning trades0.01
-
MAE:Equity, average, losing trades0.02
-
Avg(MAE) / Avg(PL) - All trades2.757
-
MAE:Equity, losing trades only, 95th Percentile Value for this strat-
-
MAE:Equity, win trades only, 95th Percentile Value for this strat-
-
MAE:Equity, 95th Percentile Value for this strat0.01
-
Avg(MAE) / Avg(PL) - Winning trades0.278
-
Avg(MAE) / Avg(PL) - Losing trades-1.158
-
Hold-and-Hope Ratio0.369
- Analysis based on MONTHLY values, full history
- RATIO STATISTICS
- Ratio statistics of excess return rates
- Statistics related to Sharpe ratio
-
Mean0.38875
-
SD0.33542
-
Sharpe ratio (Glass type estimate)1.15899
-
Sharpe ratio (Hedges UMVUE)1.13465
-
df36.00000
-
t2.03512
-
p0.02463
-
Lowerbound of 95% confidence interval for Sharpe Ratio0.00376
-
Upperbound of 95% confidence interval for Sharpe Ratio2.29903
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation-0.01190
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.28119
- Statistics related to Sortino ratio
-
Sortino ratio2.41543
-
Upside Potential Ratio4.12839
-
Upside part of mean0.66443
-
Downside part of mean-0.27569
-
Upside SD0.31009
-
Downside SD0.16094
-
N nonnegative terms21.00000
-
N negative terms16.00000
- Statistics related to linear regression on benchmark
-
N of observations37.00000
-
Mean of predictor0.08862
-
Mean of criterion0.38875
-
SD of predictor0.19048
-
SD of criterion0.33542
-
Covariance0.01605
-
r0.25115
-
b (slope, estimate of beta)0.44225
-
a (intercept, estimate of alpha)0.34955
-
Mean Square Error0.10842
-
DF error35.00000
-
t(b)1.53500
-
p(b)0.06689
-
t(a)1.84705
-
p(a)0.03660
-
Lowerbound of 95% confidence interval for beta-0.14265
-
Upperbound of 95% confidence interval for beta1.02714
-
Lowerbound of 95% confidence interval for alpha-0.03464
-
Upperbound of 95% confidence interval for alpha0.73375
-
Treynor index (mean / b)0.87902
-
Jensen alpha (a)0.34955
- Ratio statistics of excess log return rates
- Statistics related to Sharpe ratio
-
Mean0.33065
-
SD0.32407
-
Sharpe ratio (Glass type estimate)1.02029
-
Sharpe ratio (Hedges UMVUE)0.99886
-
df36.00000
-
t1.79157
-
p0.04081
-
Lowerbound of 95% confidence interval for Sharpe Ratio-0.12710
-
Upperbound of 95% confidence interval for Sharpe Ratio2.15417
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation-0.14092
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.13865
- Statistics related to Sortino ratio
-
Sortino ratio1.93321
-
Upside Potential Ratio3.62333
-
Upside part of mean0.61972
-
Downside part of mean-0.28907
-
Upside SD0.28643
-
Downside SD0.17103
-
N nonnegative terms21.00000
-
N negative terms16.00000
- Statistics related to linear regression on benchmark
-
N of observations37.00000
-
Mean of predictor0.06994
-
Mean of criterion0.33065
-
SD of predictor0.19563
-
SD of criterion0.32407
-
Covariance0.01615
-
r0.25471
-
b (slope, estimate of beta)0.42196
-
a (intercept, estimate of alpha)0.30114
-
Mean Square Error0.10101
-
DF error35.00000
-
t(b)1.55830
-
p(b)0.06408
-
t(a)1.65470
-
p(a)0.05346
-
Lowerbound of 95% confidence interval for beta-0.12776
-
Upperbound of 95% confidence interval for beta0.97166
-
Lowerbound of 95% confidence interval for alpha-0.06832
-
Upperbound of 95% confidence interval for alpha0.67059
-
Treynor index (mean / b)0.78361
-
Jensen alpha (a)0.30114
- Risk estimates for a one-period unit investment (parametric)
- assuming log normal returns and losses (using central moments from Sharpe statistics)
-
VaR(95%)0.11867
-
Expected Shortfall on VaR0.15196
- assuming Pareto losses only (using partial moments from Sortino statistics)
-
VaR(95%)0.04830
-
Expected Shortfall on VaR0.09595
- ORDER STATISTICS
- Quartiles of return rates
-
Number of observations37.00000
-
Minimum0.84267
-
Quartile 10.97575
-
Median1.01812
-
Quartile 31.10593
-
Maximum1.21850
-
Mean of quarter 10.92463
-
Mean of quarter 20.99863
-
Mean of quarter 31.05737
-
Mean of quarter 41.17050
-
Inter Quartile Range0.13018
-
Number outliers low0.00000
-
Percentage of outliers low0.00000
-
Mean of outliers low0.00000
-
Number of outliers high0.00000
-
Percentage of outliers high0.00000
-
Mean of outliers high0.00000
- Risk estimates for a one-period unit investment (based on Ex
-
Extreme Value Index (moments method)-0.56514
-
VaR(95%) (moments method)0.06688
-
Expected Shortfall (moments method)0.07753
-
Extreme Value Index (regression method)-0.20367
-
VaR(95%) (regression method)0.09972
-
Expected Shortfall (regression method)0.13145
- DRAW DOWN STATISTICS
- Quartiles of draw downs
-
Number of observations6.00000
-
Minimum0.01571
-
Quartile 10.04158
-
Median0.07903
-
Quartile 30.09905
-
Maximum0.38893
-
Mean of quarter 10.02309
-
Mean of quarter 20.07491
-
Mean of quarter 30.08315
-
Mean of quarter 40.24664
-
Inter Quartile Range0.05747
-
Number outliers low0.00000
-
Percentage of outliers low0.00000
-
Mean of outliers low0.00000
-
Number of outliers high1.00000
-
Percentage of outliers high0.16667
-
Mean of outliers high0.38893
- Risk estimates based on draw downs (based on Extreme Value T
-
Extreme Value Index (moments method)0.00000
-
VaR(95%) (moments method)0.00000
-
Expected Shortfall (moments method)0.00000
-
Extreme Value Index (regression method)0.00000
-
VaR(95%) (regression method)0.00000
-
Expected Shortfall (regression method)0.00000
- COMBINED STATISTICS
-
Annualized return (arithmetic extrapolation)0.65541
-
Compounded annual return (geometric extrapolation)0.43126
-
Calmar ratio (compounded annual return / max draw down)1.10883
-
Compounded annual return / average of 25% largest draw downs1.74854
-
Compounded annual return / Expected Shortfall lognormal2.83806
-
0.00000
-
0.00000
- Analysis based on DAILY values, full history
- RATIO STATISTICS
- Ratio statistics of excess return rates
- Statistics related to Sharpe ratio
-
Mean0.35770
-
SD0.28425
-
Sharpe ratio (Glass type estimate)1.25838
-
Sharpe ratio (Hedges UMVUE)1.25724
-
df828.00000
-
t2.23841
-
p0.01273
-
Lowerbound of 95% confidence interval for Sharpe Ratio0.15453
-
Upperbound of 95% confidence interval for Sharpe Ratio2.36155
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.15373
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.36075
- Statistics related to Sortino ratio
-
Sortino ratio1.83511
-
Upside Potential Ratio9.25375
-
Upside part of mean1.80375
-
Downside part of mean-1.44605
-
Upside SD0.20784
-
Downside SD0.19492
-
N nonnegative terms463.00000
-
N negative terms366.00000
- Statistics related to linear regression on benchmark
-
N of observations829.00000
-
Mean of predictor0.13445
-
Mean of criterion0.35770
-
SD of predictor0.23835
-
SD of criterion0.28425
-
Covariance0.01288
-
r0.19014
-
b (slope, estimate of beta)0.22677
-
a (intercept, estimate of alpha)0.32700
-
Mean Square Error0.07797
-
DF error827.00000
-
t(b)5.56962
-
p(b)0.00000
-
t(a)2.08313
-
p(a)0.01877
-
Lowerbound of 95% confidence interval for beta0.14685
-
Upperbound of 95% confidence interval for beta0.30668
-
Lowerbound of 95% confidence interval for alpha0.01890
-
Upperbound of 95% confidence interval for alpha0.63553
-
Treynor index (mean / b)1.57740
-
Jensen alpha (a)0.32721
- Ratio statistics of excess log return rates
- Statistics related to Sharpe ratio
-
Mean0.31708
-
SD0.28443
-
Sharpe ratio (Glass type estimate)1.11478
-
Sharpe ratio (Hedges UMVUE)1.11377
-
df828.00000
-
t1.98296
-
p0.02385
-
Lowerbound of 95% confidence interval for Sharpe Ratio0.01132
-
Upperbound of 95% confidence interval for Sharpe Ratio2.21763
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.01062
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.21692
- Statistics related to Sortino ratio
-
Sortino ratio1.59609
-
Upside Potential Ratio8.97241
-
Upside part of mean1.78246
-
Downside part of mean-1.46538
-
Upside SD0.20426
-
Downside SD0.19866
-
N nonnegative terms463.00000
-
N negative terms366.00000
- Statistics related to linear regression on benchmark
-
N of observations829.00000
-
Mean of predictor0.10584
-
Mean of criterion0.31708
-
SD of predictor0.23970
-
SD of criterion0.28443
-
Covariance0.01307
-
r0.19167
-
b (slope, estimate of beta)0.22743
-
a (intercept, estimate of alpha)0.29301
-
Mean Square Error0.07802
-
DF error827.00000
-
t(b)5.61593
-
p(b)0.00000
-
t(a)1.86521
-
p(a)0.03125
-
Lowerbound of 95% confidence interval for beta0.14794
-
Upperbound of 95% confidence interval for beta0.30693
-
Lowerbound of 95% confidence interval for alpha-0.01534
-
Upperbound of 95% confidence interval for alpha0.60135
-
Treynor index (mean / b)1.39416
-
Jensen alpha (a)0.29301
- Risk estimates for a one-period unit investment (parametric)
- assuming log normal returns and losses (using central moments from Sharpe statistics)
-
VaR(95%)0.02731
-
Expected Shortfall on VaR0.03441
- assuming Pareto losses only (using partial moments from Sortino statistics)
-
VaR(95%)0.01165
-
Expected Shortfall on VaR0.02393
- ORDER STATISTICS
- Quartiles of return rates
-
Number of observations829.00000
-
Minimum0.93610
-
Quartile 10.99354
-
Median1.00153
-
Quartile 31.00995
-
Maximum1.09412
-
Mean of quarter 10.98037
-
Mean of quarter 20.99799
-
Mean of quarter 31.00549
-
Mean of quarter 41.02214
-
Inter Quartile Range0.01641
-
Number outliers low37.00000
-
Percentage of outliers low0.04463
-
Mean of outliers low0.95593
-
Number of outliers high29.00000
-
Percentage of outliers high0.03498
-
Mean of outliers high1.04517
- Risk estimates for a one-period unit investment (based on Ex
-
Extreme Value Index (moments method)0.29206
-
VaR(95%) (moments method)0.01863
-
Expected Shortfall (moments method)0.03202
-
Extreme Value Index (regression method)-0.04624
-
VaR(95%) (regression method)0.01909
-
Expected Shortfall (regression method)0.02630
- DRAW DOWN STATISTICS
- Quartiles of draw downs
-
Number of observations50.00000
-
Minimum0.00005
-
Quartile 10.00774
-
Median0.01789
-
Quartile 30.04462
-
Maximum0.42158
-
Mean of quarter 10.00327
-
Mean of quarter 20.01232
-
Mean of quarter 30.03243
-
Mean of quarter 40.12993
-
Inter Quartile Range0.03688
-
Number outliers low0.00000
-
Percentage of outliers low0.00000
-
Mean of outliers low0.00000
-
Number of outliers high7.00000
-
Percentage of outliers high0.14000
-
Mean of outliers high0.19353
- Risk estimates based on draw downs (based on Extreme Value T
-
Extreme Value Index (moments method)0.50000
-
VaR(95%) (moments method)0.13939
-
Expected Shortfall (moments method)0.31364
-
Extreme Value Index (regression method)0.70668
-
VaR(95%) (regression method)0.12611
-
Expected Shortfall (regression method)0.41308
- COMBINED STATISTICS
-
Annualized return (arithmetic extrapolation)0.62544
-
Compounded annual return (geometric extrapolation)0.41197
-
Calmar ratio (compounded annual return / max draw down)0.97720
-
Compounded annual return / average of 25% largest draw downs3.17077
-
Compounded annual return / Expected Shortfall lognormal11.97270
-
0.00000
-
0.00000
- Analysis based on DAILY values, last 6 months only
- RATIO STATISTICS
- Ratio statistics of excess return rates
- Statistics related to Sharpe ratio
-
Mean-0.62649
-
SD0.20443
-
Sharpe ratio (Glass type estimate)-3.06452
-
Sharpe ratio (Hedges UMVUE)-3.04681
-
df130.00000
-
t-2.16694
-
p0.59336
-
Lowerbound of 95% confidence interval for Sharpe Ratio-5.85552
-
Upperbound of 95% confidence interval for Sharpe Ratio-0.26207
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation-5.84324
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation-0.25037
- Statistics related to Sortino ratio
-
Sortino ratio-3.64781
-
Upside Potential Ratio4.26684
-
Upside part of mean0.73280
-
Downside part of mean-1.35929
-
Upside SD0.11608
-
Downside SD0.17174
-
N nonnegative terms55.00000
-
N negative terms76.00000
- Statistics related to linear regression on benchmark
-
N of observations131.00000
-
Mean of predictor-0.09858
-
Mean of criterion-0.62649
-
SD of predictor0.25070
-
SD of criterion0.20443
-
Covariance0.01708
-
r0.33335
-
b (slope, estimate of beta)0.27183
-
a (intercept, estimate of alpha)-0.59969
-
Mean Square Error0.03744
-
DF error129.00000
-
t(b)4.01579
-
p(b)0.29178
-
t(a)-2.19096
-
p(a)0.61986
-
Lowerbound of 95% confidence interval for beta0.13790
-
Upperbound of 95% confidence interval for beta0.40576
-
Lowerbound of 95% confidence interval for alpha-1.14123
-
Upperbound of 95% confidence interval for alpha-0.05815
-
Treynor index (mean / b)-2.30469
-
Jensen alpha (a)-0.59969
- Ratio statistics of excess log return rates
- Statistics related to Sharpe ratio
-
Mean-0.64812
-
SD0.20578
-
Sharpe ratio (Glass type estimate)-3.14956
-
Sharpe ratio (Hedges UMVUE)-3.13136
-
df130.00000
-
t-2.22708
-
p0.59585
-
Lowerbound of 95% confidence interval for Sharpe Ratio-5.94172
-
Upperbound of 95% confidence interval for Sharpe Ratio-0.34560
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation-5.92918
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation-0.33354
- Statistics related to Sortino ratio
-
Sortino ratio-3.70868
-
Upside Potential Ratio4.15500
-
Upside part of mean0.72612
-
Downside part of mean-1.37424
-
Upside SD0.11439
-
Downside SD0.17476
-
N nonnegative terms55.00000
-
N negative terms76.00000
- Statistics related to linear regression on benchmark
-
N of observations131.00000
-
Mean of predictor-0.12990
-
Mean of criterion-0.64812
-
SD of predictor0.25140
-
SD of criterion0.20578
-
Covariance0.01727
-
r0.33376
-
b (slope, estimate of beta)0.27320
-
a (intercept, estimate of alpha)-0.61263
-
Mean Square Error0.03792
-
DF error129.00000
-
t(b)4.02138
-
p(b)0.29153
-
t(a)-2.22344
-
p(a)0.62155
-
VAR (95 Confidence Intrvl)0.02700
-
Lowerbound of 95% confidence interval for beta0.13878
-
Upperbound of 95% confidence interval for beta0.40761
-
Lowerbound of 95% confidence interval for alpha-1.15778
-
Upperbound of 95% confidence interval for alpha-0.06748
-
Treynor index (mean / b)-2.37236
-
Jensen alpha (a)-0.61263
- Risk estimates for a one-period unit investment (parametric)
- assuming log normal returns and losses (using central moments from Sharpe statistics)
-
VaR(95%)0.02311
-
Expected Shortfall on VaR0.02828
- assuming Pareto losses only (using partial moments from Sortino statistics)
-
VaR(95%)0.01310
-
Expected Shortfall on VaR0.02512
- ORDER STATISTICS
- Quartiles of return rates
-
Number of observations131.00000
-
Minimum0.94054
-
Quartile 10.99317
-
Median0.99890
-
Quartile 31.00213
-
Maximum1.05039
-
Mean of quarter 10.98308
-
Mean of quarter 20.99673
-
Mean of quarter 31.00043
-
Mean of quarter 41.01070
-
Inter Quartile Range0.00896
-
Number outliers low9.00000
-
Percentage of outliers low0.06870
-
Mean of outliers low0.96641
-
Number of outliers high9.00000
-
Percentage of outliers high0.06870
-
Mean of outliers high1.02271
- Risk estimates for a one-period unit investment (based on Ex
-
Extreme Value Index (moments method)0.43460
-
VaR(95%) (moments method)0.01840
-
Expected Shortfall (moments method)0.03611
-
Extreme Value Index (regression method)0.39072
-
VaR(95%) (regression method)0.01795
-
Expected Shortfall (regression method)0.03311
- DRAW DOWN STATISTICS
- Quartiles of draw downs
-
Number of observations1.00000
-
Minimum0.28087
-
Quartile 10.28087
-
Median0.28087
-
Quartile 30.28087
-
Maximum0.28087
-
Mean of quarter 10.00000
-
Mean of quarter 20.00000
-
Mean of quarter 30.00000
-
Mean of quarter 40.00000
-
Inter Quartile Range0.00000
-
Number outliers low0.00000
-
Percentage of outliers low0.00000
-
Mean of outliers low0.00000
-
Number of outliers high0.00000
-
Percentage of outliers high0.00000
-
Mean of outliers high0.00000
- Risk estimates based on draw downs (based on Extreme Value T
-
Extreme Value Index (moments method)0.00000
-
VaR(95%) (moments method)0.00000
-
Expected Shortfall (moments method)0.00000
-
Extreme Value Index (regression method)0.00000
-
VaR(95%) (regression method)0.00000
-
Last 4 Months - Pcnt Negative1.00%
-
Expected Shortfall (regression method)0.00000
-
Strat Max DD how much worse than SP500 max DD during strat life?-384596000
-
Max Equity Drawdown (num days)256
- COMBINED STATISTICS
-
Annualized return (arithmetic extrapolation)-0.53326
-
Compounded annual return (geometric extrapolation)-0.46217
-
Calmar ratio (compounded annual return / max draw down)-1.64551
-
Compounded annual return / average of 25% largest draw downs0.00000
-
Compounded annual return / Expected Shortfall lognormal-16.34340
Strategy Description
Subscribe at PatienceToInvest.com
Like any reasonable investor, I know I won't make money every day, week, month, or year. Patience and consistency are crucial to success. I want to encourage patience and consistency, so please consider subscribing to my blog at PatienceToInvest.com. You can also ask me questions there anytime.
I put my own money into the same trades as my subscribers – as shown by my TOS badge! In fact I put more than what is shown here into the same trades. However, you should consider that this strategy is very risky and volatile especially on a daily time frame. For example, September 3rd, 2020 it dropped by almost 11% in a single day.
I use an IRA to run the strategy but it works fine for taxable or margin accounts too.
The strategy uses many different indicators and timing methods. I believe it is well suited to do very well in the long-term. While some components of this strategy are things I have been personally doing since 2017, it wasn't until February 2019 that I had an algorithm close to what I do now. I did backtesting from 2004 to Feb 2019 and had very promising results. As we all know backtests can easily be misleading or wrong. So, in February 2019 I took a small sum of money and started forward testing it. Then in June 2019 I re-ran my backtests to cover the period of 2004 through early June 2019. For the time period of February 2019 to early June 2019 I now had backtest and real results to compare. I found them to be very similar.
Then in June 2019 I started investing much more of my money using this strategy. From June 2019 until November 2020 I did live trading as you can see from my track record. If I do backtests over the same period of June 2019 to November 2020 the real results and backtest results are remarkably similar. Because the real results and the backtest results for that period seem to match, I believe my longer-term backtests have merit.
Of course, the future could be vastly different, but I believe my system is based on long-term market tendencies that are unlikely to end without a truly seismic shift in the way people invest. A few of the indicators have been tested back as far as the Great Depression and they seem to have worked in most years since. Unfortunately, only some of my indicators can be tested that far back. Most can only be backtested over the last couple decades. Please know that backtests don't guarantee good results in the future even if the backtests were done correctly. My most recent backtest results can be found here, but please take them in context:
https://forums.collective2.com/t/backtest-results-for-patience-is-a-virtue/14518
I use a mix of short, medium, and long-term signals to algorithmically determine entries and exits. I mostly buy things that have a long-term history of going up in value. That way even if the algorithm is doesn't do well the odds are in my favor because I am focusing on assets that historically have appreciated. On rare occasions like March of 2020, I do buy some things that are depreciating assets. For example, in March of 2020 I did buy TVIX which has a long-term history of going down in value but does great in times of turmoil.
I don't ever plan to short appreciating assets in this portfolio because the unlimited risk that comes with shorting. However, I do use stock replacement via puts to simulate short or long positions while still keeping the risk defined and limited. For example, buying a put helps you bet against a stock without exposing yourself to the unlimited losses due to shorting. It also prevents the short position being called away during the middle of a trade. Finally, using puts instead of shorting enables it to be done in cash and IRA accounts.
One of the main ways I try to reduce drawdowns is by being diversified. This forum post has some good information about the different assets I trade and how my strategy has done compared to them.
https://forums.collective2.com/t/diversification-of-patience-is-a-virtue/14609/2
The algorithm places stops with each position. Some stops are as tight as 2% while others are as far off as 35% of the capital invested. It depends on the asset type and indicators. Because I use BrokerTransmit (AKA my strategy literally just copies my real brokerage account) you are not able to see orders until they become active. So, you cannot see a stop order until it gets triggered and becomes a live market sell order.
If you can open long option trades and positions in leveraged ETFs like UPRO you should have the permissions you need to trade the strategy.
This strategy is fantastic but far from perfect and will require a great deal of patience and grit. Please be wise and don't invest more than is appropriate for you.
While I hope you follow, please consider the risks and your willingness to remain consistent. By jumping in and out you decrease your odds of success dramatically. I have seen many people join at peaks then leave after a drawdown, then repeat the process over and over. Therefore, I suggest you only follow with money that you will feel comfortable remaining consistent with. Please see this forum post about the need to remain consistent. https://forums.collective2.com/t/patience-is-required/14586
I recommend AutoTrading and starting with $25,000 or more. I would join all trades in progress at anytime. If my algorithm thought it was statistically ideal to not hold a position it would have already exited it. If you have any questions about how I would set up AutoTrading please visit this post, in the forums: https://forums.collective2.com/t/how-should-i-scale-patience-is-a-virtue/14636?u=interactiveassets
Good luck!
patiencetoinvest.wordpress.com
Most values on this page (including the Strategy Equity Chart, above) have been adjusted by estimated trading commissions and subscription costs.
Some advanced users find it useful to see "raw" Model Account values. These numbers do not include any commissions, fees, subscription costs, or dividend actions.
Strategy developers can "archive" strategies at any time. This means the strategy Model Account is reset to its initial level and the trade list cleared. However, all archived track records are permanently preserved for evaluation by potential subscribers.
About the results you see on this Web site
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.
In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program, which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.
Material assumptions and methods used when calculating results
The following are material assumptions used when calculating any hypothetical monthly results that appear on our web site.
- Profits are reinvested. We assume profits (when there are profits) are reinvested in the trading strategy.
- Starting investment size. For any trading strategy on our site, hypothetical results are based on the assumption that you invested the starting amount shown on the strategy's performance chart. In some cases, nominal dollar amounts on the equity chart have been re-scaled downward to make current go-forward trading sizes more manageable. In these cases, it may not have been possible to trade the strategy historically at the equity levels shown on the chart, and a higher minimum capital was required in the past.
- All fees are included. When calculating cumulative returns, we try to estimate and include all the fees a typical trader incurs when AutoTrading using AutoTrade technology. This includes the subscription cost of the strategy, plus any per-trade AutoTrade fees, plus estimated broker commissions if any.
- "Max Drawdown" Calculation Method. We calculate the Max Drawdown statistic as follows. Our computer software looks at the equity chart of the system in question and finds the largest percentage amount that the equity chart ever declines from a local "peak" to a subsequent point in time (thus this is formally called "Maximum Peak to Valley Drawdown.") While this is useful information when evaluating trading systems, you should keep in mind that past performance does not guarantee future results. Therefore, future drawdowns may be larger than the historical maximum drawdowns you see here.
Trading is risky
There is a substantial risk of loss in futures and forex trading. Online trading of stocks and options is extremely risky. Assume you will lose money. Don't trade with money you cannot afford to lose.
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Suggested Minimum Capital
This is our estimate of the minimum amount of capital to follow a strategy, assuming you use the smallest reasonable AutoTrade Scaling % for the strategy.