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%)  +5.4%  +1.0%  +4.2% 
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  $116,456  
Cash  $1  
Equity  $1  
Cumulative $  $96,456  
Includes dividends and cashsettled expirations:  $22  Itemized 
Total System Equity  $116,456  
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)2378.26

Age79 months ago

What it tradesStocks

# Trades472

# Profitable226

% Profitable47.90%

Avg trade duration1.4 days

Max peaktovalley drawdown24.67%

drawdown periodAug 30, 2018  Feb 12, 2019

Annual Return (Compounded)27.9%

Avg win$1,476

Avg loss$964.65
 Model Account Values (Raw)

Cash$116,456

Margin Used$0

Buying Power$116,456
 Ratios

W:L ratio1.41:1

Sharpe Ratio1.01

Sortino Ratio1.75

Calmar Ratio1.673
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)281.29%

Correlation to SP5000.23700

Return Percent SP500 (cumu) during strategy life115.79%
 Return Statistics

Ann Return (w trading costs)27.9%
 Slump

Current Slump as Pcnt Equity9.60%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.20%
 Return Statistics

Return Pcnt Since TOS Statusn/a
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.279%
 Instruments

Percent Trades Optionsn/a

Percent Trades Stocks1.00%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)31.0%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss30.50%

Chance of 20% account loss9.50%

Chance of 30% account loss1.50%

Chance of 40% account lossn/a

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)472

Popularity (Last 6 weeks)920
 Trading Style

Any stock shorts? 0/10
 Popularity

C2 Score963

Popularity (7 days, Percentile 1000 scale)831
 TradesOwnSystem Certification

Trades Own System?

TOS percentn/a
 Win / Loss

Avg Loss$965

Avg Win$1,477

Sum Trade PL (losers)$237,305.000
 Age

Num Months filled monthly returns table79
 Win / Loss

Sum Trade PL (winners)$333,739.000

# Winners226

Num Months Winners48
 Dividends

Dividends Received in Model Acct22
 AUM

AUM (AutoTrader live capital)672269
 Win / Loss

# Losers246

% Winners47.9%
 Frequency

Avg Position Time (mins)2048.42

Avg Position Time (hrs)34.14

Avg Trade Length1.4 days

Last Trade Ago2
 Leverage

Daily leverage (average)2.77

Daily leverage (max)4.28
 Regression

Alpha0.06

Beta0.25

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 trades17.391

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 strat0.00

Avg(MAE) / Avg(PL)  Winning trades0.309

Avg(MAE) / Avg(PL)  Losing trades1.149

HoldandHope Ratio0.057
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.28315

SD0.23572

Sharpe ratio (Glass type estimate)1.20125

Sharpe ratio (Hedges UMVUE)1.18869

df72.00000

t2.96282

p0.00206

Lowerbound of 95% confidence interval for Sharpe Ratio0.37889

Upperbound of 95% confidence interval for Sharpe Ratio2.01576

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.37067

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.00672
 Statistics related to Sortino ratio

Sortino ratio2.95099

Upside Potential Ratio4.60145

Upside part of mean0.44152

Downside part of mean0.15837

Upside SD0.22864

Downside SD0.09595

N nonnegative terms43.00000

N negative terms30.00000
 Statistics related to linear regression on benchmark

N of observations73.00000

Mean of predictor0.11622

Mean of criterion0.28315

SD of predictor0.18656

SD of criterion0.23572

Covariance0.01488

r0.33842

b (slope, estimate of beta)0.42760

a (intercept, estimate of alpha)0.23346

Mean Square Error0.04989

DF error71.00000

t(b)3.03042

p(b)0.00170

t(a)2.53663

p(a)0.00670

Lowerbound of 95% confidence interval for beta0.14625

Upperbound of 95% confidence interval for beta0.70896

Lowerbound of 95% confidence interval for alpha0.04995

Upperbound of 95% confidence interval for alpha0.41697

Treynor index (mean / b)0.66219

Jensen alpha (a)0.23346
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.25408

SD0.22396

Sharpe ratio (Glass type estimate)1.13449

Sharpe ratio (Hedges UMVUE)1.12263

df72.00000

t2.79815

p0.00329

Lowerbound of 95% confidence interval for Sharpe Ratio0.31485

Upperbound of 95% confidence interval for Sharpe Ratio1.94665

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.30710

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation1.93816
 Statistics related to Sortino ratio

Sortino ratio2.54759

Upside Potential Ratio4.18026

Upside part of mean0.41692

Downside part of mean0.16284

Upside SD0.21191

Downside SD0.09974

N nonnegative terms43.00000

N negative terms30.00000
 Statistics related to linear regression on benchmark

N of observations73.00000

Mean of predictor0.09758

Mean of criterion0.25408

SD of predictor0.19322

SD of criterion0.22396

Covariance0.01488

r0.34390

b (slope, estimate of beta)0.39862

a (intercept, estimate of alpha)0.21519

Mean Square Error0.04485

DF error71.00000

t(b)3.08602

p(b)0.00145

t(a)2.47956

p(a)0.00776

Lowerbound of 95% confidence interval for beta0.14106

Upperbound of 95% confidence interval for beta0.65617

Lowerbound of 95% confidence interval for alpha0.04214

Upperbound of 95% confidence interval for alpha0.38823

Treynor index (mean / b)0.63741

Jensen alpha (a)0.21519
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.08164

Expected Shortfall on VaR0.10587
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.02669

Expected Shortfall on VaR0.05446
 ORDER STATISTICS
 Quartiles of return rates

Number of observations73.00000

Minimum0.87773

Quartile 10.98518

Median1.00915

Quartile 31.05194

Maximum1.24362

Mean of quarter 10.95606

Mean of quarter 20.99963

Mean of quarter 31.03301

Mean of quarter 41.11887

Inter Quartile Range0.06676

Number outliers low1.00000

Percentage of outliers low0.01370

Mean of outliers low0.87773

Number of outliers high4.00000

Percentage of outliers high0.05479

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

Extreme Value Index (moments method)0.05608

VaR(95%) (moments method)0.03784

Expected Shortfall (moments method)0.05090

Extreme Value Index (regression method)0.27562

VaR(95%) (regression method)0.04044

Expected Shortfall (regression method)0.06730
 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)0.74945

Compounded annual return (geometric extrapolation)0.32577

Calmar ratio (compounded annual return / max draw down)1.66166

Compounded annual return / average of 25% largest draw downs2.35195

Compounded annual return / Expected Shortfall lognormal3.07713

0.00000

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

Mean0.27570

SD0.19066

Sharpe ratio (Glass type estimate)1.44601

Sharpe ratio (Hedges UMVUE)1.44534

df1612.00000

t3.58789

p0.45550

Lowerbound of 95% confidence interval for Sharpe Ratio0.65432

Upperbound of 95% confidence interval for Sharpe Ratio2.23731

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.65385

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.23683
 Statistics related to Sortino ratio

Sortino ratio2.56020

Upside Potential Ratio9.84501

Upside part of mean1.06018

Downside part of mean0.78448

Upside SD0.15819

Downside SD0.10769

N nonnegative terms575.00000

N negative terms1038.00000
 Statistics related to linear regression on benchmark

N of observations1613.00000

Mean of predictor0.11791

Mean of criterion0.27570

SD of predictor0.20380

SD of criterion0.19066

Covariance0.00876

r0.22535

b (slope, estimate of beta)0.21083

a (intercept, estimate of alpha)0.25100

Mean Square Error0.03453

DF error1611.00000

t(b)9.28378

p(b)0.35776

t(a)3.34740

p(a)0.44715

Lowerbound of 95% confidence interval for beta0.16628

Upperbound of 95% confidence interval for beta0.25537

Lowerbound of 95% confidence interval for alpha0.10386

Upperbound of 95% confidence interval for alpha0.39782

Treynor index (mean / b)1.30771

Jensen alpha (a)0.25084
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.25758

SD0.18909

Sharpe ratio (Glass type estimate)1.36219

Sharpe ratio (Hedges UMVUE)1.36156

df1612.00000

t3.37991

p0.45806

Lowerbound of 95% confidence interval for Sharpe Ratio0.57068

Upperbound of 95% confidence interval for Sharpe Ratio2.15331

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.57024

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.15287
 Statistics related to Sortino ratio

Sortino ratio2.36618

Upside Potential Ratio9.62593

Upside part of mean1.04785

Downside part of mean0.79028

Upside SD0.15536

Downside SD0.10886

N nonnegative terms575.00000

N negative terms1038.00000
 Statistics related to linear regression on benchmark

N of observations1613.00000

Mean of predictor0.09702

Mean of criterion0.25758

SD of predictor0.20456

SD of criterion0.18909

Covariance0.00868

r0.22447

b (slope, estimate of beta)0.20750

a (intercept, estimate of alpha)0.23744

Mean Square Error0.03397

DF error1611.00000

t(b)9.24571

p(b)0.35830

t(a)3.19496

p(a)0.44954

Lowerbound of 95% confidence interval for beta0.16348

Upperbound of 95% confidence interval for beta0.25152

Lowerbound of 95% confidence interval for alpha0.09167

Upperbound of 95% confidence interval for alpha0.38321

Treynor index (mean / b)1.24134

Jensen alpha (a)0.23744
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.01807

Expected Shortfall on VaR0.02284
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00802

Expected Shortfall on VaR0.01579
 ORDER STATISTICS
 Quartiles of return rates

Number of observations1613.00000

Minimum0.95459

Quartile 10.99657

Median1.00000

Quartile 31.00400

Maximum1.08753

Mean of quarter 10.98903

Mean of quarter 20.99929

Mean of quarter 31.00090

Mean of quarter 41.01545

Inter Quartile Range0.00742

Number outliers low92.00000

Percentage of outliers low0.05704

Mean of outliers low0.97819

Number of outliers high150.00000

Percentage of outliers high0.09299

Mean of outliers high1.02692
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.03839

VaR(95%) (moments method)0.00894

Expected Shortfall (moments method)0.01214

Extreme Value Index (regression method)0.04270

VaR(95%) (regression method)0.01052

Expected Shortfall (regression method)0.01529
 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)0.77940

Compounded annual return (geometric extrapolation)0.33041

Calmar ratio (compounded annual return / max draw down)1.67290

Compounded annual return / average of 25% largest draw downs3.02092

Compounded annual return / Expected Shortfall lognormal14.46660

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

Mean0.07329

SD0.09689

Sharpe ratio (Glass type estimate)0.75643

Sharpe ratio (Hedges UMVUE)0.75206

df130.00000

t0.53488

p0.47657

Lowerbound of 95% confidence interval for Sharpe Ratio2.01835

Upperbound of 95% confidence interval for Sharpe Ratio3.52831

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation2.02126

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation3.52537
 Statistics related to Sortino ratio

Sortino ratio1.10890

Upside Potential Ratio9.01848

Upside part of mean0.59603

Downside part of mean0.52274

Upside SD0.07048

Downside SD0.06609

N nonnegative terms59.00000

N negative terms72.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.22729

Mean of criterion0.07329

SD of predictor0.13044

SD of criterion0.09689

Covariance0.00238

r0.18829

b (slope, estimate of beta)0.13986

a (intercept, estimate of alpha)0.04150

Mean Square Error0.00912

DF error129.00000

t(b)2.17755

p(b)0.38084

t(a)0.30542

p(a)0.48289

Lowerbound of 95% confidence interval for beta0.01278

Upperbound of 95% confidence interval for beta0.26694

Lowerbound of 95% confidence interval for alpha0.22733

Upperbound of 95% confidence interval for alpha0.31033

Treynor index (mean / b)0.52401

Jensen alpha (a)0.04150
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.06861

SD0.09688

Sharpe ratio (Glass type estimate)0.70821

Sharpe ratio (Hedges UMVUE)0.70411

df130.00000

t0.50078

p0.47806

Lowerbound of 95% confidence interval for Sharpe Ratio2.06627

Upperbound of 95% confidence interval for Sharpe Ratio3.48002

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation2.06902

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation3.47724
 Statistics related to Sortino ratio

Sortino ratio1.03218

Upside Potential Ratio8.92834

Upside part of mean0.59350

Downside part of mean0.52489

Upside SD0.07010

Downside SD0.06647

N nonnegative terms59.00000

N negative terms72.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.21871

Mean of criterion0.06861

SD of predictor0.13071

SD of criterion0.09688

Covariance0.00239

r0.18889

b (slope, estimate of beta)0.14001

a (intercept, estimate of alpha)0.03799

Mean Square Error0.00912

DF error129.00000

t(b)2.18470

p(b)0.38047

t(a)0.27978

p(a)0.48433

VAR (95 Confidence Intrvl)0.01800

Lowerbound of 95% confidence interval for beta0.01321

Upperbound of 95% confidence interval for beta0.26680

Lowerbound of 95% confidence interval for alpha0.23068

Upperbound of 95% confidence interval for alpha0.30666

Treynor index (mean / b)0.49007

Jensen alpha (a)0.03799
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.00954

Expected Shortfall on VaR0.01201
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00487

Expected Shortfall on VaR0.00942
 ORDER STATISTICS
 Quartiles of return rates

Number of observations131.00000

Minimum0.97725

Quartile 10.99697

Median1.00000

Quartile 31.00380

Maximum1.01713

Mean of quarter 10.99289

Mean of quarter 20.99942

Mean of quarter 31.00154

Mean of quarter 41.00773

Inter Quartile Range0.00683

Number outliers low1.00000

Percentage of outliers low0.00763

Mean of outliers low0.97725

Number of outliers high3.00000

Percentage of outliers high0.02290

Mean of outliers high1.01572
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.68260

VaR(95%) (moments method)0.00695

Expected Shortfall (moments method)0.00775

Extreme Value Index (regression method)0.11065

VaR(95%) (regression method)0.00601

Expected Shortfall (regression method)0.00824
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations8.00000

Minimum0.00042

Quartile 10.00090

Median0.00545

Quartile 30.02099

Maximum0.10182

Mean of quarter 10.00044

Mean of quarter 20.00141

Mean of quarter 30.01242

Mean of quarter 40.06930

Inter Quartile Range0.02009

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high1.00000

Percentage of outliers high0.12500

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

Extreme Value Index (moments method)0.00000

VaR(95%) (moments method)0.00000

Expected Shortfall (moments method)0.00000

Extreme Value Index (regression method)0.00000

VaR(95%) (regression method)0.00000

Last 4 Months  Pcnt Negative0.50%

Expected Shortfall (regression method)0.00000

Strat Max DD how much worse than SP500 max DD during strat life?337763000

Max Equity Drawdown (num days)166
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.09889

Compounded annual return (geometric extrapolation)0.10133

Calmar ratio (compounded annual return / max draw down)0.99516

Compounded annual return / average of 25% largest draw downs1.46223

Compounded annual return / Expected Shortfall lognormal8.43782
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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