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%  (5.3%)  (5.2%)  +1.1%  (1.1%) 
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  $111,187  
Cash  $1  
Equity  $1  
Cumulative $  $91,187  
Includes dividends and cashsettled expirations:  $22  Itemized 
Total System Equity  $111,187  
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)2350.25

Age78 months ago

What it tradesStocks

# Trades461

# Profitable218

% Profitable47.30%

Avg trade duration1.5 days

Max peaktovalley drawdown24.67%

drawdown periodAug 30, 2018  Feb 12, 2019

Annual Return (Compounded)27.2%

Avg win$1,494

Avg loss$965.79
 Model Account Values (Raw)

Cash$111,187

Margin Used$0

Buying Power$111,187
 Ratios

W:L ratio1.39:1

Sharpe Ratio0.99

Sortino Ratio1.71

Calmar Ratio1.65
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)255.28%

Correlation to SP5000.23690

Return Percent SP500 (cumu) during strategy life116.63%
 Return Statistics

Ann Return (w trading costs)27.2%
 Slump

Current Slump as Pcnt Equity15.40%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.19%
 Return Statistics

Return Pcnt Since TOS Statusn/a
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.272%
 Instruments

Percent Trades Optionsn/a

Percent Trades Stocks1.00%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)30.5%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss29.00%

Chance of 20% account loss11.00%

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)521

Popularity (Last 6 weeks)933
 Trading Style

Any stock shorts? 0/10
 Popularity

C2 Score469

Popularity (7 days, Percentile 1000 scale)770
 TradesOwnSystem Certification

Trades Own System?

TOS percentn/a
 Win / Loss

Avg Loss$966

Avg Win$1,495

Sum Trade PL (losers)$234,688.000
 Age

Num Months filled monthly returns table78
 Win / Loss

Sum Trade PL (winners)$325,853.000

# Winners218

Num Months Winners47
 Dividends

Dividends Received in Model Acct22
 AUM

AUM (AutoTrader live capital)671910
 Win / Loss

# Losers243

% Winners47.3%
 Frequency

Avg Position Time (mins)2093.62

Avg Position Time (hrs)34.89

Avg Trade Length1.5 days

Last Trade Ago2
 Leverage

Daily leverage (average)2.77

Daily leverage (max)4.28
 Regression

Alpha0.06

Beta0.25

Treynor Index0.26
 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)0.94

MAE:Equity, average, winning trades0.01

MAE:Equity, average, losing trades0.02

Avg(MAE) / Avg(PL)  All trades23.156

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 trades0.310

Avg(MAE) / Avg(PL)  Losing trades1.147

HoldandHope Ratio0.043
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.29192

SD0.23637

Sharpe ratio (Glass type estimate)1.23502

Sharpe ratio (Hedges UMVUE)1.22193

df71.00000

t3.02517

p0.00173

Lowerbound of 95% confidence interval for Sharpe Ratio0.40549

Upperbound of 95% confidence interval for Sharpe Ratio2.05639

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.39692

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.04694
 Statistics related to Sortino ratio

Sortino ratio3.04441

Upside Potential Ratio4.66850

Upside part of mean0.44765

Downside part of mean0.15573

Upside SD0.23022

Downside SD0.09589

N nonnegative terms43.00000

N negative terms29.00000
 Statistics related to linear regression on benchmark

N of observations72.00000

Mean of predictor0.11239

Mean of criterion0.29192

SD of predictor0.18762

SD of criterion0.23637

Covariance0.01530

r0.34496

b (slope, estimate of beta)0.43458

a (intercept, estimate of alpha)0.24308

Mean Square Error0.04992

DF error70.00000

t(b)3.07490

p(b)0.00150

t(a)2.62526

p(a)0.00531

Lowerbound of 95% confidence interval for beta0.15271

Upperbound of 95% confidence interval for beta0.71646

Lowerbound of 95% confidence interval for alpha0.05841

Upperbound of 95% confidence interval for alpha0.42774

Treynor index (mean / b)0.67173

Jensen alpha (a)0.24308
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.26251

SD0.22456

Sharpe ratio (Glass type estimate)1.16897

Sharpe ratio (Hedges UMVUE)1.15658

df71.00000

t2.86339

p0.00275

Lowerbound of 95% confidence interval for Sharpe Ratio0.34225

Upperbound of 95% confidence interval for Sharpe Ratio1.98794

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.33413

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation1.97903
 Statistics related to Sortino ratio

Sortino ratio2.63278

Upside Potential Ratio4.23951

Upside part of mean0.42271

Downside part of mean0.16020

Upside SD0.21338

Downside SD0.09971

N nonnegative terms43.00000

N negative terms29.00000
 Statistics related to linear regression on benchmark

N of observations72.00000

Mean of predictor0.09359

Mean of criterion0.26251

SD of predictor0.19433

SD of criterion0.22456

Covariance0.01530

r0.35059

b (slope, estimate of beta)0.40514

a (intercept, estimate of alpha)0.22459

Mean Square Error0.04486

DF error70.00000

t(b)3.13205

p(b)0.00127

t(a)2.57223

p(a)0.00611

Lowerbound of 95% confidence interval for beta0.14715

Upperbound of 95% confidence interval for beta0.66313

Lowerbound of 95% confidence interval for alpha0.05045

Upperbound of 95% confidence interval for alpha0.39873

Treynor index (mean / b)0.64794

Jensen alpha (a)0.22459
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.08126

Expected Shortfall on VaR0.10556
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.02583

Expected Shortfall on VaR0.05329
 ORDER STATISTICS
 Quartiles of return rates

Number of observations72.00000

Minimum0.87773

Quartile 10.98593

Median1.01017

Quartile 31.05381

Maximum1.24362

Mean of quarter 10.95510

Mean of quarter 20.99963

Mean of quarter 31.03301

Mean of quarter 41.11887

Inter Quartile Range0.06788

Number outliers low1.00000

Percentage of outliers low0.01389

Mean of outliers low0.87773

Number of outliers high4.00000

Percentage of outliers high0.05556

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

Extreme Value Index (moments method)0.05809

VaR(95%) (moments method)0.03776

Expected Shortfall (moments method)0.05111

Extreme Value Index (regression method)0.18467

VaR(95%) (regression method)0.04332

Expected Shortfall (regression method)0.06862
 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)0.78525

Compounded annual return (geometric extrapolation)0.33698

Calmar ratio (compounded annual return / max draw down)1.71886

Compounded annual return / average of 25% largest draw downs2.43292

Compounded annual return / Expected Shortfall lognormal3.19241

0.00000

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

Mean0.27254

SD0.19164

Sharpe ratio (Glass type estimate)1.42215

Sharpe ratio (Hedges UMVUE)1.42148

df1592.00000

t3.50674

p0.45622

Lowerbound of 95% confidence interval for Sharpe Ratio0.62556

Upperbound of 95% confidence interval for Sharpe Ratio2.21835

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.62509

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.21788
 Statistics related to Sortino ratio

Sortino ratio2.51702

Upside Potential Ratio9.82447

Upside part of mean1.06376

Downside part of mean0.79123

Upside SD0.15894

Downside SD0.10828

N nonnegative terms564.00000

N negative terms1029.00000
 Statistics related to linear regression on benchmark

N of observations1593.00000

Mean of predictor0.12030

Mean of criterion0.27254

SD of predictor0.20470

SD of criterion0.19164

Covariance0.00883

r0.22509

b (slope, estimate of beta)0.21072

a (intercept, estimate of alpha)0.24700

Mean Square Error0.03489

DF error1591.00000

t(b)9.21463

p(b)0.35792

t(a)3.26116

p(a)0.44818

Lowerbound of 95% confidence interval for beta0.16586

Upperbound of 95% confidence interval for beta0.25557

Lowerbound of 95% confidence interval for alpha0.09851

Upperbound of 95% confidence interval for alpha0.39586

Treynor index (mean / b)1.29336

Jensen alpha (a)0.24719
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.25423

SD0.19005

Sharpe ratio (Glass type estimate)1.33770

Sharpe ratio (Hedges UMVUE)1.33707

df1592.00000

t3.29849

p0.45881

Lowerbound of 95% confidence interval for Sharpe Ratio0.54128

Upperbound of 95% confidence interval for Sharpe Ratio2.13372

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.54085

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.13328
 Statistics related to Sortino ratio

Sortino ratio2.32270

Upside Potential Ratio9.60505

Upside part of mean1.05132

Downside part of mean0.79709

Upside SD0.15609

Downside SD0.10945

N nonnegative terms564.00000

N negative terms1029.00000
 Statistics related to linear regression on benchmark

N of observations1593.00000

Mean of predictor0.09923

Mean of criterion0.25423

SD of predictor0.20547

SD of criterion0.19005

Covariance0.00876

r0.22421

b (slope, estimate of beta)0.20739

a (intercept, estimate of alpha)0.23365

Mean Square Error0.03433

DF error1591.00000

t(b)9.17672

p(b)0.35847

t(a)3.10833

p(a)0.45059

Lowerbound of 95% confidence interval for beta0.16306

Upperbound of 95% confidence interval for beta0.25171

Lowerbound of 95% confidence interval for alpha0.08621

Upperbound of 95% confidence interval for alpha0.38110

Treynor index (mean / b)1.22589

Jensen alpha (a)0.23365
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.01818

Expected Shortfall on VaR0.02297
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00811

Expected Shortfall on VaR0.01593
 ORDER STATISTICS
 Quartiles of return rates

Number of observations1593.00000

Minimum0.95459

Quartile 10.99652

Median1.00000

Quartile 31.00396

Maximum1.08753

Mean of quarter 10.98895

Mean of quarter 20.99926

Mean of quarter 31.00087

Mean of quarter 41.01553

Inter Quartile Range0.00744

Number outliers low92.00000

Percentage of outliers low0.05775

Mean of outliers low0.97819

Number of outliers high149.00000

Percentage of outliers high0.09353

Mean of outliers high1.02700
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.04246

VaR(95%) (moments method)0.00905

Expected Shortfall (moments method)0.01225

Extreme Value Index (regression method)0.03560

VaR(95%) (regression method)0.01064

Expected Shortfall (regression method)0.01539
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations55.00000

Minimum0.00035

Quartile 10.00942

Median0.03314

Quartile 30.06820

Maximum0.19750

Mean of quarter 10.00409

Mean of quarter 20.02124

Mean of quarter 30.05045

Mean of quarter 40.10937

Inter Quartile Range0.05877

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)0.01102

VaR(95%) (moments method)0.11592

Expected Shortfall (moments method)0.14685

Extreme Value Index (regression method)0.05757

VaR(95%) (regression method)0.12607

Expected Shortfall (regression method)0.16560
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.74984

Compounded annual return (geometric extrapolation)0.32596

Calmar ratio (compounded annual return / max draw down)1.65041

Compounded annual return / average of 25% largest draw downs2.98030

Compounded annual return / Expected Shortfall lognormal14.18990

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

Mean0.01207

SD0.10092

Sharpe ratio (Glass type estimate)0.11964

Sharpe ratio (Hedges UMVUE)0.11894

df130.00000

t0.08460

p0.49629

Lowerbound of 95% confidence interval for Sharpe Ratio2.65233

Upperbound of 95% confidence interval for Sharpe Ratio2.89136

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation2.65290

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.89079
 Statistics related to Sortino ratio

Sortino ratio0.17627

Upside Potential Ratio8.38966

Upside part of mean0.57466

Downside part of mean0.56259

Upside SD0.07360

Downside SD0.06850

N nonnegative terms55.00000

N negative terms76.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.20307

Mean of criterion0.01207

SD of predictor0.13467

SD of criterion0.10092

Covariance0.00274

r0.20156

b (slope, estimate of beta)0.15105

a (intercept, estimate of alpha)0.01860

Mean Square Error0.00985

DF error129.00000

t(b)2.33718

p(b)0.37256

t(a)0.13196

p(a)0.50740

Lowerbound of 95% confidence interval for beta0.02318

Upperbound of 95% confidence interval for beta0.27891

Lowerbound of 95% confidence interval for alpha0.29747

Upperbound of 95% confidence interval for alpha0.26027

Treynor index (mean / b)0.07994

Jensen alpha (a)0.01860
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.00702

SD0.10085

Sharpe ratio (Glass type estimate)0.06965

Sharpe ratio (Hedges UMVUE)0.06924

df130.00000

t0.04925

p0.49784

Lowerbound of 95% confidence interval for Sharpe Ratio2.70230

Upperbound of 95% confidence interval for Sharpe Ratio2.84135

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation2.70257

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.84106
 Statistics related to Sortino ratio

Sortino ratio0.10195

Upside Potential Ratio8.30125

Upside part of mean0.57191

Downside part of mean0.56489

Upside SD0.07312

Downside SD0.06889

N nonnegative terms55.00000

N negative terms76.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.19395

Mean of criterion0.00702

SD of predictor0.13492

SD of criterion0.10085

Covariance0.00275

r0.20196

b (slope, estimate of beta)0.15097

a (intercept, estimate of alpha)0.02226

Mean Square Error0.00983

DF error129.00000

t(b)2.34207

p(b)0.37231

t(a)0.15809

p(a)0.50886

VAR (95 Confidence Intrvl)0.01800

Lowerbound of 95% confidence interval for beta0.02343

Upperbound of 95% confidence interval for beta0.27850

Lowerbound of 95% confidence interval for alpha0.30080

Upperbound of 95% confidence interval for alpha0.25628

Treynor index (mean / b)0.04653

Jensen alpha (a)0.02226
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.01017

Expected Shortfall on VaR0.01274
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00543

Expected Shortfall on VaR0.01021
 ORDER STATISTICS
 Quartiles of return rates

Number of observations131.00000

Minimum0.97725

Quartile 10.99686

Median1.00000

Quartile 31.00308

Maximum1.02249

Mean of quarter 10.99267

Mean of quarter 20.99905

Mean of quarter 31.00100

Mean of quarter 41.00791

Inter Quartile Range0.00623

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)0.60968

VaR(95%) (moments method)0.00717

Expected Shortfall (moments method)0.00810

Extreme Value Index (regression method)0.22018

VaR(95%) (regression method)0.00684

Expected Shortfall (regression method)0.00839
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations9.00000

Minimum0.00042

Quartile 10.00178

Median0.01166

Quartile 30.01724

Maximum0.10182

Mean of quarter 10.00108

Mean of quarter 20.01039

Mean of quarter 30.01498

Mean of quarter 40.06930

Inter Quartile Range0.01546

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high1.00000

Percentage of outliers high0.11111

Mean of outliers high0.10182
 Risk estimates based on draw downs (based on Extreme Value T

Extreme Value Index (moments method)1.32745

VaR(95%) (moments method)0.05025

Expected Shortfall (moments method)0.05326

Extreme Value Index (regression method)0.73556

VaR(95%) (regression method)0.12507

Last 4 Months  Pcnt Negative0.50%

Expected Shortfall (regression method)0.53467

Strat Max DD how much worse than SP500 max DD during strat life?375052000

Max Equity Drawdown (num days)166
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.03524

Compounded annual return (geometric extrapolation)0.03555

Calmar ratio (compounded annual return / max draw down)0.34911

Compounded annual return / average of 25% largest draw downs0.51296

Compounded annual return / Expected Shortfall lognormal2.79014
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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