This system has earned TradesOwnStrategy (TOS) Certification.
This means that the manager of this system trades his own strategy
in a reallife, funded brokerage account.
TradesOwnStrategy (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
1,134
# trading signals executed in manager's Interactive Brokers (Stocks, Options, Futures) account
1,133
Percent signals followed since 09/21/2020
99.9%
This information was last updated
6/6/23 2:04 ET
Warning: System trading results are still hypothetical.
Even though the system developer is currently trading his own system in a reallife 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 TradesOwnStrategy (TOS) Certification. This means that the manager of this system trades his own strategy in a reallife, funded brokerage account.
TradesOwnStrategy (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  1,134 
# trading signals executed in manager's Interactive Brokers (Stocks, Options, Futures) account  1,133 
Percent signals followed since 09/21/2020  99.9% 
This information was last updated  6/6/23 2:04 ET 
Warning: System trading results are still hypothetical.
Even though the system developer is currently trading his own system in a reallife 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.
Trendfollowing
Tries to take advantage of long, medium or shortterm moves that seem to play out in various markets. Typically, trendfollowing analysis is backward looking; that is, it attempts to recognize and profit from alreadyestablished 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 markedtomarket equity calculations.
All results are hypothetical.
Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec  YTD  

2019  +17.1%  (0.6%)  +3.4%  (7.9%)  +1.6%  +0.7%  +7.2%  +21.5%  
2020  +9.6%  +9.4%  +30.2%  +8.5%  (0.7%)  +4.3%  +15.3%  +18.3%  (17.6%)  +5.8%  +20.2%  +15.4%  +189.5% 
2021  (1.1%)  +7.9%  +7.4%  +7.1%  (6.8%)  +2.3%  +2.8%  +9.1%  (12%)  +15.2%  (0.3%)  (2.8%)  +29.0% 
2022  (13.4%)  (4%)  (2.4%)  (14%)  (8.4%)  (2.1%)  (0.4%)  (9.2%)  +0.7%  (0.5%)  (0.5%)  (6.3%)  (47.1%) 
2023  +6.9%  (4.7%)  +5.2%  +6.5%  +9.1%  +6.4%  +32.4% 
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  $80,177  
Cash  $1  
Equity  $1  
Cumulative $  $90,678  
Includes dividends and cashsettled expirations:  $1,986  Itemized 
Total System Equity  $128,178  
Margined  $1  
Open P/L  $27,525  
Data has been delayed by 168 hours for nonsubscribers 
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)1462.42

Age49 months ago

What it tradesStocks

# Trades180

# Profitable73

% Profitable40.60%

Avg trade duration36.9 days

Max peaktovalley drawdown53.83%

drawdown periodNov 22, 2021  Dec 22, 2022

Annual Return (Compounded)33.4%

Avg win$3,004

Avg loss$1,221
 Model Account Values (Raw)

Cash$44,316

Margin Used$0

Buying Power$80,177
 Ratios

W:L ratio1.69:1

Sharpe Ratio0.92

Sortino Ratio1.35

Calmar Ratio0.74
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)165.34%

Correlation to SP5000.20800

Return Percent SP500 (cumu) during strategy life52.46%
 Return Statistics

Ann Return (w trading costs)33.4%
 Slump

Current Slump as Pcnt Equity57.10%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.38%
 Return Statistics

Return Pcnt Since TOS Status143.940%
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.334%
 Instruments

Percent Trades Options0.02%

Percent Trades Stocks0.98%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)35.9%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss50.00%

Chance of 20% account loss19.00%

Chance of 30% account loss7.50%

Chance of 40% account loss1.00%

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 (MonteCarlo)

Chance of 50% account lossn/a
 Popularity

Popularity (Today)547

Popularity (Last 6 weeks)877
 Trading Style

Any stock shorts? 0/10
 Popularity

C2 Score868

Popularity (7 days, Percentile 1000 scale)812
 TradesOwnSystem Certification

Trades Own System?Yes

TOS percent100%
 Win / Loss

Avg Loss$1,221

Avg Win$3,005

Sum Trade PL (losers)$130,661.000
 Age

Num Months filled monthly returns table49
 Win / Loss

Sum Trade PL (winners)$219,354.000

# Winners73

Num Months Winners28
 Dividends

Dividends Received in Model Acct1987
 AUM

AUM (AutoTrader live capital)204522
 Win / Loss

# Losers107

% Winners40.6%
 Frequency

Avg Position Time (mins)53078.20

Avg Position Time (hrs)884.64

Avg Trade Length36.9 days

Last Trade Ago0
 Leverage

Daily leverage (average)1.47

Daily leverage (max)3.62
 Regression

Alpha0.08

Beta0.25

Treynor Index0.34
 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)0.08

MAE:Equity, average, winning trades0.01

MAE:Equity, average, losing trades0.01

Avg(MAE) / Avg(PL)  All trades3.016

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 strat0.03

Avg(MAE) / Avg(PL)  Winning trades0.247

Avg(MAE) / Avg(PL)  Losing trades1.166

HoldandHope Ratio0.358
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.29781

SD0.30726

Sharpe ratio (Glass type estimate)0.96925

Sharpe ratio (Hedges UMVUE)0.95335

df46.00000

t1.91820

p0.03065

Lowerbound of 95% confidence interval for Sharpe Ratio0.04563

Upperbound of 95% confidence interval for Sharpe Ratio1.97407

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.05598

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation1.96268
 Statistics related to Sortino ratio

Sortino ratio1.98442

Upside Potential Ratio3.71074

Upside part of mean0.55688

Downside part of mean0.25907

Upside SD0.27797

Downside SD0.15007

N nonnegative terms25.00000

N negative terms22.00000
 Statistics related to linear regression on benchmark

N of observations47.00000

Mean of predictor0.08953

Mean of criterion0.29781

SD of predictor0.19685

SD of criterion0.30726

Covariance0.01387

r0.22925

b (slope, estimate of beta)0.35783

a (intercept, estimate of alpha)0.26577

Mean Square Error0.09143

DF error45.00000

t(b)1.57994

p(b)0.06056

t(a)1.72434

p(a)0.04576

Lowerbound of 95% confidence interval for beta0.09833

Upperbound of 95% confidence interval for beta0.81400

Lowerbound of 95% confidence interval for alpha0.04466

Upperbound of 95% confidence interval for alpha0.57620

Treynor index (mean / b)0.83225

Jensen alpha (a)0.26577
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.25022

SD0.29669

Sharpe ratio (Glass type estimate)0.84338

Sharpe ratio (Hedges UMVUE)0.82954

df46.00000

t1.66909

p0.05095

Lowerbound of 95% confidence interval for Sharpe Ratio0.16620

Upperbound of 95% confidence interval for Sharpe Ratio1.84412

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.17522

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation1.83429
 Statistics related to Sortino ratio

Sortino ratio1.57309

Upside Potential Ratio3.27440

Upside part of mean0.52084

Downside part of mean0.27062

Upside SD0.25704

Downside SD0.15907

N nonnegative terms25.00000

N negative terms22.00000
 Statistics related to linear regression on benchmark

N of observations47.00000

Mean of predictor0.06978

Mean of criterion0.25022

SD of predictor0.19991

SD of criterion0.29669

Covariance0.01411

r0.23793

b (slope, estimate of beta)0.35312

a (intercept, estimate of alpha)0.22558

Mean Square Error0.08489

DF error45.00000

t(b)1.64326

p(b)0.05365

t(a)1.52439

p(a)0.06720

Lowerbound of 95% confidence interval for beta0.07969

Upperbound of 95% confidence interval for beta0.78594

Lowerbound of 95% confidence interval for alpha0.07247

Upperbound of 95% confidence interval for alpha0.52363

Treynor index (mean / b)0.70860

Jensen alpha (a)0.22558
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.11310

Expected Shortfall on VaR0.14386
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.04781

Expected Shortfall on VaR0.09346
 ORDER STATISTICS
 Quartiles of return rates

Number of observations47.00000

Minimum0.84267

Quartile 10.97739

Median1.01393

Quartile 31.06977

Maximum1.21850

Mean of quarter 10.92775

Mean of quarter 20.99373

Mean of quarter 31.03742

Mean of quarter 41.15054

Inter Quartile Range0.09238

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high2.00000

Percentage of outliers high0.04255

Mean of outliers high1.21573
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.49600

VaR(95%) (moments method)0.06418

Expected Shortfall (moments method)0.07570

Extreme Value Index (regression method)0.04754

VaR(95%) (regression method)0.08024

Expected Shortfall (regression method)0.11219
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations6.00000

Minimum0.01571

Quartile 10.04158

Median0.07903

Quartile 30.09905

Maximum0.45093

Mean of quarter 10.02309

Mean of quarter 20.07491

Mean of quarter 30.08315

Mean of quarter 40.27764

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 high0.45093
 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)0.50357

Compounded annual return (geometric extrapolation)0.32066

Calmar ratio (compounded annual return / max draw down)0.71111

Compounded annual return / average of 25% largest draw downs1.15496

Compounded annual return / Expected Shortfall lognormal2.22903

0.00000

0.00000
 Analysis based on DAILY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.31713

SD0.26752

Sharpe ratio (Glass type estimate)1.18544

Sharpe ratio (Hedges UMVUE)1.18459

df1040.00000

t2.36295

p0.46346

Lowerbound of 95% confidence interval for Sharpe Ratio0.20058

Upperbound of 95% confidence interval for Sharpe Ratio2.16976

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.20000

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.16917
 Statistics related to Sortino ratio

Sortino ratio1.73735

Upside Potential Ratio9.07933

Upside part of mean1.65730

Downside part of mean1.34017

Upside SD0.19637

Downside SD0.18254

N nonnegative terms568.00000

N negative terms473.00000
 Statistics related to linear regression on benchmark

N of observations1041.00000

Mean of predictor0.10508

Mean of criterion0.31713

SD of predictor0.23109

SD of criterion0.26752

Covariance0.01325

r0.21426

b (slope, estimate of beta)0.24803

a (intercept, estimate of alpha)0.29100

Mean Square Error0.06835

DF error1039.00000

t(b)7.07047

p(b)0.36465

t(a)2.21837

p(a)0.45632

Lowerbound of 95% confidence interval for beta0.17920

Upperbound of 95% confidence interval for beta0.31687

Lowerbound of 95% confidence interval for alpha0.03360

Upperbound of 95% confidence interval for alpha0.54853

Treynor index (mean / b)1.27858

Jensen alpha (a)0.29107
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.28118

SD0.26760

Sharpe ratio (Glass type estimate)1.05073

Sharpe ratio (Hedges UMVUE)1.04997

df1040.00000

t2.09443

p0.46759

Lowerbound of 95% confidence interval for Sharpe Ratio0.06618

Upperbound of 95% confidence interval for Sharpe Ratio2.03480

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.06567

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.03428
 Statistics related to Sortino ratio

Sortino ratio1.51252

Upside Potential Ratio8.81272

Upside part of mean1.63827

Downside part of mean1.35710

Upside SD0.19309

Downside SD0.18590

N nonnegative terms568.00000

N negative terms473.00000
 Statistics related to linear regression on benchmark

N of observations1041.00000

Mean of predictor0.07823

Mean of criterion0.28118

SD of predictor0.23214

SD of criterion0.26760

Covariance0.01339

r0.21555

b (slope, estimate of beta)0.24847

a (intercept, estimate of alpha)0.26174

Mean Square Error0.06835

DF error1039.00000

t(b)7.11519

p(b)0.36385

t(a)1.99518

p(a)0.46070

Lowerbound of 95% confidence interval for beta0.17995

Upperbound of 95% confidence interval for beta0.31700

Lowerbound of 95% confidence interval for alpha0.00432

Upperbound of 95% confidence interval for alpha0.51916

Treynor index (mean / b)1.13161

Jensen alpha (a)0.26174
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.02578

Expected Shortfall on VaR0.03247
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.01100

Expected Shortfall on VaR0.02258
 ORDER STATISTICS
 Quartiles of return rates

Number of observations1041.00000

Minimum0.93610

Quartile 10.99393

Median1.00094

Quartile 31.00925

Maximum1.09412

Mean of quarter 10.98168

Mean of quarter 20.99820

Mean of quarter 31.00455

Mean of quarter 41.02092

Inter Quartile Range0.01532

Number outliers low44.00000

Percentage of outliers low0.04227

Mean of outliers low0.95793

Number of outliers high38.00000

Percentage of outliers high0.03650

Mean of outliers high1.04259
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.28408

VaR(95%) (moments method)0.01735

Expected Shortfall (moments method)0.02955

Extreme Value Index (regression method)0.03419

VaR(95%) (regression method)0.01730

Expected Shortfall (regression method)0.02471
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations50.00000

Minimum0.00005

Quartile 10.00774

Median0.01789

Quartile 30.04462

Maximum0.48952

Mean of quarter 10.00327

Mean of quarter 20.01232

Mean of quarter 30.03243

Mean of quarter 40.13515

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 high0.20324
 Risk estimates based on draw downs (based on Extreme Value T

Extreme Value Index (moments method)0.55486

VaR(95%) (moments method)0.14552

Expected Shortfall (moments method)0.36183

Extreme Value Index (regression method)0.79104

VaR(95%) (regression method)0.12884

Expected Shortfall (regression method)0.56875
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.60772

Compounded annual return (geometric extrapolation)0.36218

Calmar ratio (compounded annual return / max draw down)0.73986

Compounded annual return / average of 25% largest draw downs2.67973

Compounded annual return / Expected Shortfall lognormal11.15390

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

Mean0.42516

SD0.22860

Sharpe ratio (Glass type estimate)1.85984

Sharpe ratio (Hedges UMVUE)1.84909

df130.00000

t1.31511

p0.44271

Lowerbound of 95% confidence interval for Sharpe Ratio0.92468

Upperbound of 95% confidence interval for Sharpe Ratio4.63735

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.93181

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation4.63000
 Statistics related to Sortino ratio

Sortino ratio2.96035

Upside Potential Ratio11.03030

Upside part of mean1.58417

Downside part of mean1.15900

Upside SD0.17867

Downside SD0.14362

N nonnegative terms74.00000

N negative terms57.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.11709

Mean of criterion0.42516

SD of predictor0.15539

SD of criterion0.22860

Covariance0.02081

r0.58576

b (slope, estimate of beta)0.86172

a (intercept, estimate of alpha)0.32426

Mean Square Error0.03459

DF error129.00000

t(b)8.20863

p(b)0.14968

t(a)1.23142

p(a)0.43151

Lowerbound of 95% confidence interval for beta0.65402

Upperbound of 95% confidence interval for beta1.06942

Lowerbound of 95% confidence interval for alpha0.19673

Upperbound of 95% confidence interval for alpha0.84525

Treynor index (mean / b)0.49339

Jensen alpha (a)0.32426
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.39896

SD0.22804

Sharpe ratio (Glass type estimate)1.74952

Sharpe ratio (Hedges UMVUE)1.73940

df130.00000

t1.23710

p0.44607

Lowerbound of 95% confidence interval for Sharpe Ratio1.03370

Upperbound of 95% confidence interval for Sharpe Ratio4.52620

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation1.04045

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation4.51926
 Statistics related to Sortino ratio

Sortino ratio2.74655

Upside Potential Ratio10.79670

Upside part of mean1.56831

Downside part of mean1.16935

Upside SD0.17639

Downside SD0.14526

N nonnegative terms74.00000

N negative terms57.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.10509

Mean of criterion0.39896

SD of predictor0.15532

SD of criterion0.22804

Covariance0.02074

r0.58552

b (slope, estimate of beta)0.85969

a (intercept, estimate of alpha)0.30862

Mean Square Error0.03444

DF error129.00000

t(b)8.20361

p(b)0.14980

t(a)1.17490

p(a)0.43461

VAR (95 Confidence Intrvl)0.02600

Lowerbound of 95% confidence interval for beta0.65235

Upperbound of 95% confidence interval for beta1.06703

Lowerbound of 95% confidence interval for alpha0.21109

Upperbound of 95% confidence interval for alpha0.82833

Treynor index (mean / b)0.46407

Jensen alpha (a)0.30862
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.02142

Expected Shortfall on VaR0.02715
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00935

Expected Shortfall on VaR0.01847
 ORDER STATISTICS
 Quartiles of return rates

Number of observations131.00000

Minimum0.96405

Quartile 10.99294

Median1.00117

Quartile 31.00749

Maximum1.04208

Mean of quarter 10.98438

Mean of quarter 20.99843

Mean of quarter 31.00434

Mean of quarter 41.01985

Inter Quartile Range0.01455

Number outliers low2.00000

Percentage of outliers low0.01527

Mean of outliers low0.96498

Number of outliers high6.00000

Percentage of outliers high0.04580

Mean of outliers high1.03344
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.00208

VaR(95%) (moments method)0.01516

Expected Shortfall (moments method)0.02012

Extreme Value Index (regression method)0.12157

VaR(95%) (regression method)0.01608

Expected Shortfall (regression method)0.02048
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations9.00000

Minimum0.00012

Quartile 10.00837

Median0.04485

Quartile 30.05367

Maximum0.09651

Mean of quarter 10.00296

Mean of quarter 20.03605

Mean of quarter 30.05314

Mean of quarter 40.08094

Inter Quartile Range0.04530

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)1.13484

VaR(95%) (moments method)0.08597

Expected Shortfall (moments method)0.08984

Extreme Value Index (regression method)0.41083

VaR(95%) (regression method)0.10616

Last 4 Months  Pcnt Negativen/a

Expected Shortfall (regression method)0.17640

Strat Max DD how much worse than SP500 max DD during strat life?346551000

Max Equity Drawdown (num days)395
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.47584

Compounded annual return (geometric extrapolation)0.53245

Calmar ratio (compounded annual return / max draw down)5.51720

Compounded annual return / average of 25% largest draw downs6.57820

Compounded annual return / Expected Shortfall lognormal19.61240
Strategy Description
I believe the logic behind this strategy is very sound. In short, invest in a diversified basket of historically appreciating assets with leverage and use various algorithmic trading signals to reduce leverage at various times in an effort to reduce drawdowns.
I use a mix of short, medium, and longterm signals to algorithmically determine entries and exits. I mostly buy things that have a longterm history of going up in value. On rare occasions like March of 2020, there are certain metrics that can trigger bets on inverse volatility. For example, in March of 2020 I did buy TVIX which has a longterm history of going down in value but does great in times of turmoil.
To be very clear, I expect to have high drawdowns when compared to investing in something like a balanced mutual fund. However, I do not expect to have drawdowns nearly as big as just buying and holding leveraged funds.
I have a Roth IRA at Interactive Brokers and this strategy reads the trades I make in it. For context, I have about 30 years before I plan to use the money in this Roth IRA. Like any REASONABLE investor, I know I won't make money every day, week, month, or year  especially if I want to target HIGH longterm growth  patience is needed! 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.
Stops are generally not the primary way the system is designed to exit trades. However, the algorithm places stops with each position. I do this because you just never know what will happen. If price changes way faster than the signals can capture it, I donâ€™t want to hold on to a 3X leveraged ETF during a day where the overall market drops 20% in a single day like it did in 1987! Because I use BrokerTransmit (AKA my strategy literally just copies my real brokerage account) you are not able to see stop orders until they trigger. On your end a stop triggered would just look like a market sell order. If it makes you feel more secure you could certainly instruct C2 to place stops on each position for you. I would not put them too tight though. For example, if you were to use a 1% stop you would probably experience too much whipsaw on these investments. Leveraged ETFs need more space to move when swing trading. Perhaps 10% would work well.
While I hope you follow, please consider the risks and your willingness to remain consistent. By jumping in and out I believe you will decrease your odds of success dramatically. Therefore, I suggest you only follow with money that you will feel comfortable remaining consistent with.
Good luck!
patiencetoinvest.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 underor overcompensated 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 rescaled downward to make current goforward 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 pertrade 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.
Not available
This feature isn't available under your current Trade Leader Plan.
Strategy is now visible
This strategy is now visible to the public. New subscribers will be able to follow it.
If you designate your strategy as Private, it will no longer be visible to the public.
No subscribers and simulations will be allowed. If you have subscribers, the strategy will still be visible to them.
If you have simulations, they will be stopped.
Continue to designate your strategy as Private?
Strategy is no longer visible
This strategy is no longer visible to anyone except current subscribers.
(Current subscribers will remain subscribed. You can see who is subscribed, and control their subscriptions, on your Subscriber Management screen.)
Finally, please note that you can restore public visibility at any time.
This strategy is no longer visible to the public. No subscribers will be allowed.
You can restore public visibility at any time.
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.