TQQQ Aspire
(117734561)
Subscription terms. Subscriptions to this system cost $149.00 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.
Momentum
Aims to capitalize on the continuance of existing trends in the market. Trader takes a long position in an asset in an upward trend, and shortsells a security that has been in a downward trend. While similar to Trendfollowing, tends to be more forwardlooking (predicting oncoming trend), while Momentum is more backwardlooking (observing alreadyestablished price direction).Sector: Technology
Focuses primarily on stocks of technology companies.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  

2018  +4.5%  +7.1%  +5.4%  +12.5%  (10.5%)  (12.5%)    (1.8%)  +2.1%  
2019  (0.9%)  +0.6%  +7.7%  +14.7%  (4.5%)  +25.8%  +5.7%  (12.7%)  (0.7%)  (0.7%)  +3.3%  +8.7%  +51.4% 
2020  (4.1%)  +16.2%  (4.6%)  (8.8%)  +0.5%  +0.1%  (0.9%)  +22.1%  +14.7%  +9.3%  +11.0%  (3.6%)  +58.1% 
2021  +1.0%  +7.0%  +2.6%  +16.9%  (1.6%)  +12.9%  +3.7%  +13.2%  (3.3%)  +14.5%  +6.7%  +1.4%  +102.4% 
2022  +0.5%  (6.5%)  +5.3%  (1%)  +4.3%  (3.4%)  +2.6%  (2.9%)  (1.2%)  +1.6%  +0.5%  (1.8%)  (2.5%) 
2023  +3.9%  +2.2%  (0.1%)  +1.0%  +3.5%  +0.7%  (3%)  +1.3%  (4.4%)  (6.9%)  (0.2%)  +1.5%  (1.1%) 
2024  (3%)  (0.9%)  +0.2%  +3.5%  +1.5%  +1.6%  +5.9%  (5.2%)  +3.3% 
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  $20,000  
Buy Power  $75,979  
Cash  $1  
Equity  $1  
Cumulative $  $95,088  
Includes dividends and cashsettled expirations:  $22  Itemized 
Total System Equity  $115,088  
Margined  $1  
Open P/L  $0  
Data has been delayed by 48 hours for nonsubscribers 
System developer has asked us to delay this information by 48 hours.
Trading Record
Statistics

Strategy began5/1/2018

Suggested Minimum Cap$35,000

Strategy Age (days)2298

Age77 months ago

What it tradesStocks

# Trades442

# Profitable208

% Profitable47.10%

Avg trade duration1.5 days

Max peaktovalley drawdown24.67%

drawdown periodAug 30, 2018  Feb 12, 2019

Annual Return (Compounded)28.8%

Avg win$1,535

Avg loss$958.88
 Model Account Values (Raw)

Cash$75,864

Margin Used$0

Buying Power$75,979
 Ratios

W:L ratio1.42:1

Sharpe Ratio1.03

Sortino Ratio1.79

Calmar Ratio1.739
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)288.36%

Correlation to SP5000.23960

Return Percent SP500 (cumu) during strategy life105.48%
 Return Statistics

Ann Return (w trading costs)28.8%
 Slump

Current Slump as Pcnt Equity10.40%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.17%
 Return Statistics

Return Pcnt Since TOS Statusn/a
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.288%
 Instruments

Percent Trades Optionsn/a

Percent Trades Stocks1.00%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)32.0%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss28.50%

Chance of 20% account loss8.50%

Chance of 30% account loss1.00%

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)847

Popularity (Last 6 weeks)974
 Trading Style

Any stock shorts? 0/10
 Popularity

C2 Score963

Popularity (7 days, Percentile 1000 scale)947
 TradesOwnSystem Certification

Trades Own System?

TOS percentn/a
 Win / Loss

Avg Loss$959

Avg Win$1,543

Sum Trade PL (losers)$224,378.000
 Age

Num Months filled monthly returns table76
 Win / Loss

Sum Trade PL (winners)$319,329.000

# Winners207

Num Months Winners46
 Dividends

Dividends Received in Model Acct22
 AUM

AUM (AutoTrader live capital)724293
 Win / Loss

# Losers234

% Winners46.9%
 Frequency

Avg Position Time (mins)2182.73

Avg Position Time (hrs)36.38

Avg Trade Length1.5 days

Last Trade Ago3
 Leverage

Daily leverage (average)2.78

Daily leverage (max)4.28
 Regression

Alpha0.06

Beta0.26

Treynor Index0.27
 Maximum Adverse Excursion (MAE)

MAE:Equity, average, all trades0.01

MAE:PL  Winning Trades  this strat Percentile of All Strats7.66

MAE:PL  worst single value for strategy

MAE:PL  Losing Trades  this strat Percentile of All Strats54.88

MAE:PL (avg, winning trades)

MAE:PL (avg, losing trades)

MAE:PL (avg, all trades)0.97

MAE:Equity, average, winning trades0.01

MAE:Equity, average, losing trades0.02

Avg(MAE) / Avg(PL)  All trades16.299

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 trades0.297

Avg(MAE) / Avg(PL)  Losing trades1.142

HoldandHope Ratio0.061
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.30088

SD0.23702

Sharpe ratio (Glass type estimate)1.26939

Sharpe ratio (Hedges UMVUE)1.25574

df70.00000

t3.08768

p0.00145

Lowerbound of 95% confidence interval for Sharpe Ratio0.43250

Upperbound of 95% confidence interval for Sharpe Ratio2.09780

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.42356

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.08792
 Statistics related to Sortino ratio

Sortino ratio3.13938

Upside Potential Ratio4.73664

Upside part of mean0.45395

Downside part of mean0.15308

Upside SD0.23184

Downside SD0.09584

N nonnegative terms43.00000

N negative terms28.00000
 Statistics related to linear regression on benchmark

N of observations71.00000

Mean of predictor0.10588

Mean of criterion0.30088

SD of predictor0.18827

SD of criterion0.23702

Covariance0.01587

r0.35568

b (slope, estimate of beta)0.44777

a (intercept, estimate of alpha)0.25347

Mean Square Error0.04978

DF error69.00000

t(b)3.16120

p(b)0.00117

t(a)2.72700

p(a)0.00405

Lowerbound of 95% confidence interval for beta0.16520

Upperbound of 95% confidence interval for beta0.73035

Lowerbound of 95% confidence interval for alpha0.06804

Upperbound of 95% confidence interval for alpha0.43889

Treynor index (mean / b)0.67193

Jensen alpha (a)0.25347
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.27111

SD0.22516

Sharpe ratio (Glass type estimate)1.20404

Sharpe ratio (Hedges UMVUE)1.19110

df70.00000

t2.92874

p0.00230

Lowerbound of 95% confidence interval for Sharpe Ratio0.37001

Upperbound of 95% confidence interval for Sharpe Ratio2.03000

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.36153

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.02067
 Statistics related to Sortino ratio

Sortino ratio2.71932

Upside Potential Ratio4.29969

Upside part of mean0.42866

Downside part of mean0.15756

Upside SD0.21487

Downside SD0.09970

N nonnegative terms43.00000

N negative terms28.00000
 Statistics related to linear regression on benchmark

N of observations71.00000

Mean of predictor0.08702

Mean of criterion0.27111

SD of predictor0.19504

SD of criterion0.22516

Covariance0.01586

r0.36120

b (slope, estimate of beta)0.41699

a (intercept, estimate of alpha)0.23482

Mean Square Error0.04472

DF error69.00000

t(b)3.21756

p(b)0.00099

t(a)2.67848

p(a)0.00462

Lowerbound of 95% confidence interval for beta0.15845

Upperbound of 95% confidence interval for beta0.67554

Lowerbound of 95% confidence interval for alpha0.05992

Upperbound of 95% confidence interval for alpha0.40972

Treynor index (mean / b)0.65015

Jensen alpha (a)0.23482
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.08086

Expected Shortfall on VaR0.10523
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.02497

Expected Shortfall on VaR0.05208
 ORDER STATISTICS
 Quartiles of return rates

Number of observations71.00000

Minimum0.87773

Quartile 10.98684

Median1.01120

Quartile 31.05568

Maximum1.24362

Mean of quarter 10.95579

Mean of quarter 21.00102

Mean of quarter 31.03430

Mean of quarter 41.11887

Inter Quartile Range0.06885

Number outliers low1.00000

Percentage of outliers low0.01408

Mean of outliers low0.87773

Number of outliers high4.00000

Percentage of outliers high0.05634

Mean of outliers high1.20873
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.07487

VaR(95%) (moments method)0.03728

Expected Shortfall (moments method)0.05445

Extreme Value Index (regression method)0.09793

VaR(95%) (regression method)0.04618

Expected Shortfall (regression method)0.07028
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations11.00000

Minimum0.00695

Quartile 10.02053

Median0.03575

Quartile 30.10403

Maximum0.19605

Mean of quarter 10.01319

Mean of quarter 20.02789

Mean of quarter 30.08435

Mean of quarter 40.13851

Inter Quartile Range0.08349

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)0.03909

VaR(95%) (moments method)0.15408

Expected Shortfall (moments method)0.19406

Extreme Value Index (regression method)2.35181

VaR(95%) (regression method)0.21938

Expected Shortfall (regression method)0.00000
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.82241

Compounded annual return (geometric extrapolation)0.34853

Calmar ratio (compounded annual return / max draw down)1.77776

Compounded annual return / average of 25% largest draw downs2.51628

Compounded annual return / Expected Shortfall lognormal3.31191

0.00000

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

Mean0.28602

SD0.19353

Sharpe ratio (Glass type estimate)1.47793

Sharpe ratio (Hedges UMVUE)1.47722

df1554.00000

t3.60054

p0.45452

Lowerbound of 95% confidence interval for Sharpe Ratio0.67151

Upperbound of 95% confidence interval for Sharpe Ratio2.28389

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.67103

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.28340
 Statistics related to Sortino ratio

Sortino ratio2.62077

Upside Potential Ratio9.91147

Upside part of mean1.08171

Downside part of mean0.79569

Upside SD0.16072

Downside SD0.10914

N nonnegative terms549.00000

N negative terms1006.00000
 Statistics related to linear regression on benchmark

N of observations1555.00000

Mean of predictor0.11418

Mean of criterion0.28602

SD of predictor0.20624

SD of criterion0.19353

Covariance0.00908

r0.22752

b (slope, estimate of beta)0.21350

a (intercept, estimate of alpha)0.26200

Mean Square Error0.03554

DF error1553.00000

t(b)9.20763

p(b)0.35642

t(a)3.37932

p(a)0.44567

Lowerbound of 95% confidence interval for beta0.16802

Upperbound of 95% confidence interval for beta0.25898

Lowerbound of 95% confidence interval for alpha0.10978

Upperbound of 95% confidence interval for alpha0.41352

Treynor index (mean / b)1.33968

Jensen alpha (a)0.26165
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.26735

SD0.19193

Sharpe ratio (Glass type estimate)1.39295

Sharpe ratio (Hedges UMVUE)1.39228

df1554.00000

t3.39353

p0.45712

Lowerbound of 95% confidence interval for Sharpe Ratio0.58675

Upperbound of 95% confidence interval for Sharpe Ratio2.19875

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.58628

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.19828
 Statistics related to Sortino ratio

Sortino ratio2.42311

Upside Potential Ratio9.68889

Upside part of mean1.06899

Downside part of mean0.80165

Upside SD0.15784

Downside SD0.11033

N nonnegative terms549.00000

N negative terms1006.00000
 Statistics related to linear regression on benchmark

N of observations1555.00000

Mean of predictor0.09280

Mean of criterion0.26735

SD of predictor0.20701

SD of criterion0.19193

Covariance0.00901

r0.22665

b (slope, estimate of beta)0.21013

a (intercept, estimate of alpha)0.24785

Mean Square Error0.03497

DF error1553.00000

t(b)9.17048

p(b)0.35696

t(a)3.22779

p(a)0.44809

Lowerbound of 95% confidence interval for beta0.16519

Upperbound of 95% confidence interval for beta0.25508

Lowerbound of 95% confidence interval for alpha0.09723

Upperbound of 95% confidence interval for alpha0.39846

Treynor index (mean / b)1.27227

Jensen alpha (a)0.24785
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.01831

Expected Shortfall on VaR0.02316
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00816

Expected Shortfall on VaR0.01605
 ORDER STATISTICS
 Quartiles of return rates

Number of observations1555.00000

Minimum0.95459

Quartile 10.99659

Median1.00000

Quartile 31.00403

Maximum1.08753

Mean of quarter 10.98886

Mean of quarter 20.99928

Mean of quarter 31.00089

Mean of quarter 41.01577

Inter Quartile Range0.00745

Number outliers low92.00000

Percentage of outliers low0.05916

Mean of outliers low0.97819

Number of outliers high148.00000

Percentage of outliers high0.09518

Mean of outliers high1.02708
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.04536

VaR(95%) (moments method)0.00902

Expected Shortfall (moments method)0.01223

Extreme Value Index (regression method)0.01305

VaR(95%) (regression method)0.01092

Expected Shortfall (regression method)0.01568
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations55.00000

Minimum0.00035

Quartile 10.00942

Median0.03314

Quartile 30.06500

Maximum0.19750

Mean of quarter 10.00409

Mean of quarter 20.02124

Mean of quarter 30.04982

Mean of quarter 40.10693

Inter Quartile Range0.05557

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high3.00000

Percentage of outliers high0.05455

Mean of outliers high0.17816
 Risk estimates based on draw downs (based on Extreme Value T

Extreme Value Index (moments method)0.15104

VaR(95%) (moments method)0.11785

Expected Shortfall (moments method)0.16062

Extreme Value Index (regression method)0.18584

VaR(95%) (regression method)0.12097

Expected Shortfall (regression method)0.16811
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.80339

Compounded annual return (geometric extrapolation)0.34347

Calmar ratio (compounded annual return / max draw down)1.73903

Compounded annual return / average of 25% largest draw downs3.21220

Compounded annual return / Expected Shortfall lognormal14.83280

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

Mean0.09652

SD0.09995

Sharpe ratio (Glass type estimate)0.96572

Sharpe ratio (Hedges UMVUE)0.96014

df130.00000

t0.68287

p0.47011

Lowerbound of 95% confidence interval for Sharpe Ratio1.81038

Upperbound of 95% confidence interval for Sharpe Ratio3.73821

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation1.81412

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation3.73440
 Statistics related to Sortino ratio

Sortino ratio1.49504

Upside Potential Ratio9.31979

Upside part of mean0.60170

Downside part of mean0.50518

Upside SD0.07603

Downside SD0.06456

N nonnegative terms51.00000

N negative terms80.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.13859

Mean of criterion0.09652

SD of predictor0.13099

SD of criterion0.09995

Covariance0.00331

r0.25312

b (slope, estimate of beta)0.19314

a (intercept, estimate of alpha)0.06976

Mean Square Error0.00942

DF error129.00000

t(b)2.97169

p(b)0.34059

t(a)0.50706

p(a)0.47162

Lowerbound of 95% confidence interval for beta0.06455

Upperbound of 95% confidence interval for beta0.32173

Lowerbound of 95% confidence interval for alpha0.20243

Upperbound of 95% confidence interval for alpha0.34194

Treynor index (mean / b)0.49975

Jensen alpha (a)0.06976
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.09155

SD0.09985

Sharpe ratio (Glass type estimate)0.91682

Sharpe ratio (Hedges UMVUE)0.91152

df130.00000

t0.64829

p0.47162

Lowerbound of 95% confidence interval for Sharpe Ratio1.85892

Upperbound of 95% confidence interval for Sharpe Ratio3.68918

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation1.86250

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation3.68554
 Statistics related to Sortino ratio

Sortino ratio1.40945

Upside Potential Ratio9.21879

Upside part of mean0.59877

Downside part of mean0.50722

Upside SD0.07555

Downside SD0.06495

N nonnegative terms51.00000

N negative terms80.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.13001

Mean of criterion0.09155

SD of predictor0.13116

SD of criterion0.09985

Covariance0.00332

r0.25359

b (slope, estimate of beta)0.19306

a (intercept, estimate of alpha)0.06645

Mean Square Error0.00940

DF error129.00000

t(b)2.97754

p(b)0.34031

t(a)0.48366

p(a)0.47292

VAR (95 Confidence Intrvl)0.01800

Lowerbound of 95% confidence interval for beta0.06477

Upperbound of 95% confidence interval for beta0.32134

Lowerbound of 95% confidence interval for alpha0.20537

Upperbound of 95% confidence interval for alpha0.33826

Treynor index (mean / b)0.47418

Jensen alpha (a)0.06645
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.00975

Expected Shortfall on VaR0.01230
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00502

Expected Shortfall on VaR0.00962
 ORDER STATISTICS
 Quartiles of return rates

Number of observations131.00000

Minimum0.97725

Quartile 10.99729

Median1.00000

Quartile 31.00367

Maximum1.02249

Mean of quarter 10.99331

Mean of quarter 20.99930

Mean of quarter 31.00092

Mean of quarter 41.00839

Inter Quartile Range0.00638

Number outliers low3.00000

Percentage of outliers low0.02290

Mean of outliers low0.98391

Number of outliers high4.00000

Percentage of outliers high0.03053

Mean of outliers high1.01708
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.10992

VaR(95%) (moments method)0.00624

Expected Shortfall (moments method)0.00806

Extreme Value Index (regression method)0.14510

VaR(95%) (regression method)0.00702

Expected Shortfall (regression method)0.00907
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations11.00000

Minimum0.00042

Quartile 10.00545

Median0.01272

Quartile 30.02206

Maximum0.05934

Mean of quarter 10.00108

Mean of quarter 20.01116

Mean of quarter 30.01757

Mean of quarter 40.04078

Inter Quartile Range0.01661

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high1.00000

Percentage of outliers high0.09091

Mean of outliers high0.05934
 Risk estimates based on draw downs (based on Extreme Value T

Extreme Value Index (moments method)1.83507

VaR(95%) (moments method)0.04743

Expected Shortfall (moments method)0.04884

Extreme Value Index (regression method)0.09674

VaR(95%) (regression method)0.06156

Last 4 Months  Pcnt Negative0.25%

Expected Shortfall (regression method)0.08781

Strat Max DD how much worse than SP500 max DD during strat life?350612000

Max Equity Drawdown (num days)166
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.12309

Compounded annual return (geometric extrapolation)0.12688

Calmar ratio (compounded annual return / max draw down)2.13805

Compounded annual return / average of 25% largest draw downs3.11133

Compounded annual return / Expected Shortfall lognormal10.31860
Strategy Description
The TQQQ Aspire Strategy is based on a statistical computer model whose signals are designed to be efficiently traded utilizing C2’s AutoTrading technology. This Strategy uses the leveraged ETF TQQQ which is highly correlated to the Nasdaq 100 Index (NDX). This is one of the Top Ten popular ETFs for traders with a substantial trading volume on a daily basis.
White Papers and Video
If you would like to review a white paper that compares TQQQ Aspire relative to other Strategies using the C2 Grid as an evaluation tool, please copy this link into your browser:
https://docsend.com/view/5nd6v3w85wc2xiem
In addition to the White Paper, here is a link to the Collective2 video interview of the Strategy Leader for “TQQQ Aspire”.
https://www.youtube.com/watch?v=tN6bNJwc1EA
Strategy Philosophy
1. Alternative Investment Strategy – As an Alternative Investment Strategy, TQQQ Aspire is built to be a small portion of your investable assets. Due to the inherent leveraged price movement (3X the Nasdaq price movement), We encourage investors to limit this to less than 10% of their portfolio.
2. Substantial Returns  The intent of this Strategy is to provide substantial returns as part of a larger investor portfolio. In other words, diversification is the responsibility of the investor subscribing to this Strategy.
3. “Windows of Momentum” – TQQQ Aspire seeks to limit exposure to brief periods of time as the Strategy constantly seeks momentum. During low volatility periods, a swing strategy is applied and our algorithm may signal positions can be held overnight. The StopLoss calculation on Day 1 of a swing trade and all subsequent days in the trade is part of the “Secret Sauce” and is calculated on a daily basis for each day’s trading. However, when volatility is high, like 2022 and intraday 2023, our algorithm has been modified where entries and exits are likely to occur in the same day.
4. Lost Crystal Ball – We still haven’t seen a Strategy with a Crystal Ball for predicting when to close a position at the peak. Believe us, if someone had a reliable method of making this decision, we would all be living in luxury. Depending on volatility levels, exits occur either in the same day (high volatility) or positions can be held overnight when volatility is low and our algorithm calculates a statistical probability for doing so.
5. Risk Mitigation – TQQQ Aspire never leaves a trade position “exposed.” This means there is a StopLoss in effect at the point of the trade entry and there is one in place until the closing of the trade.
6. Trading Adjustment  Prior to 2022, the swing trade strategy often held positions overnight. During low volatility and when higher probability calculations to hold overnight occur, the average length of a position is 5+ days according to backtesting. Some trades have lasted as long as in excess of 20 days...it simply depends on the strength of the momentum. A trade to enter a position can also occur with a StopLoss on the same day should the market turn downward. At higher volatility levels, we adjusted our algorithm to accommodate this volatility by exiting a trade typically on the same day as the entry utilizes a "Profit Taker" or limit order to sell should a calculated profit be reached. However, when volatility is low and a calculated decision occurs to hold overnight, a trade to enter and a trade to close a position can occur on separate days.
7. Trade Entry – Recently, we have adjusted our entries to occur shortly after the open. Subsequently, we may adjust our StopLoss and ProfitTaker sell orders based on mathematical adjustments during the trading day. This is why we recommend AutoTrading so you do not miss the trading signals early in the day or the order adjustments throughout the day.
8. Pursuit of Simplicity – This Strategy in its earliest form was more complex than today’s Strategy. We put a great deal of energy into simplifying the Strategy and through exhaustive backtesting. The “Secret Sauce” for this Strategy is partly due to identifying a unique advantage and then using simplicity to make the Strategy more efficient.
9. Strategy Leader Discretion  This Strategy, albeit based mostly on a quantitative strategy is not 100% mechanical. If market circumstances or geopolitical conditions arise that could impact performance of a trade in the opinion of the strategy leader, discretion may be exercised by overriding the calculated signal.
On November 1, 2019, we enhanced this model to improve the entry decision and StopLoss calculation. The performance during rising and falling markets has made a substantial improvement during this timeperiod. The current C2 Max Drawdown reported on this Strategy occurred prior to this model update.
On January 1, 2023, we added adjustments to our algorithm that accommodate increased trading volatility. While 2022 was a difficult year, the "silver lining" to this extended downturn was the market's provision of substantial data for similar volatile periods in the future.
In December 2023 we executed additional adjustments to the algorithm to accommodate the market volatility of 2022 and intraday volatility in 2023.
The main inventor of this Strategy has been building statistical models for many years. His initial work was for the Department of Defense during the 1980's. We have been working on the key elements of this financial model's technique for over 8 years. v.1152024 linkv.1152024
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.
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