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  +3.6%  +8.0%  +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%)  (0.4%)  (3.4%) 
Model Account Details
A trading strategy on Collective2. Follow it in your broker account, or use a free simulated trading account.
Advanced users may want to use this information to adjust their AutoTrade scaling, or merely to understand the magnitudes of the nearby chart.
Started  $20,000  
Buy Power  $42,061  
Cash  $1  
Equity  $1  
Cumulative $  $87,886  
Includes dividends and cashsettled expirations:  $22  Itemized 
Total System Equity  $107,886  
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)2123.1

Age71 months ago

What it tradesStocks

# Trades375

# Profitable170

% Profitable45.30%

Avg trade duration1.8 days

Max peaktovalley drawdown24.67%

drawdown periodAug 30, 2018  Feb 12, 2019

Annual Return (Compounded)30.0%

Avg win$1,641

Avg loss$932.56
 Model Account Values (Raw)

Cash$41,904

Margin Used$0

Buying Power$42,061
 Ratios

W:L ratio1.46:1

Sharpe Ratio1.05

Sortino Ratio1.83

Calmar Ratio1.825
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)273.42%

Correlation to SP5000.24000

Return Percent SP500 (cumu) during strategy life87.65%
 Return Statistics

Ann Return (w trading costs)30.0%
 Slump

Current Slump as Pcnt Equity18.10%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.10%
 Return Statistics

Return Pcnt Since TOS Statusn/a
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.300%
 Instruments

Percent Trades Optionsn/a

Percent Trades Stocks1.00%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)33.4%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss30.50%

Chance of 20% account loss6.00%

Chance of 30% account loss0.50%

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)672

Popularity (Last 6 weeks)984
 Trading Style

Any stock shorts? 0/10
 Popularity

C2 Score966

Popularity (7 days, Percentile 1000 scale)935
 TradesOwnSystem Certification

Trades Own System?

TOS percentn/a
 Win / Loss

Avg Loss$931

Avg Win$1,650

Sum Trade PL (losers)$191,751.000
 Age

Num Months filled monthly returns table70
 Win / Loss

Sum Trade PL (winners)$278,890.000

# Winners169

Num Months Winners41
 Dividends

Dividends Received in Model Acct22
 AUM

AUM (AutoTrader live capital)1396950
 Win / Loss

# Losers206

% Winners45.1%
 Frequency

Avg Position Time (mins)2542.88

Avg Position Time (hrs)42.38

Avg Trade Length1.8 days

Last Trade Ago0
 Leverage

Daily leverage (average)2.77

Daily leverage (max)4.28
 Regression

Alpha0.07

Beta0.26

Treynor Index0.29
 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)1.15

MAE:Equity, average, winning trades0.01

MAE:Equity, average, losing trades0.02

Avg(MAE) / Avg(PL)  All trades16.630

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 trades0.267

Avg(MAE) / Avg(PL)  Losing trades1.146

HoldandHope Ratio0.062
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.31591

SD0.24653

Sharpe ratio (Glass type estimate)1.28140

Sharpe ratio (Hedges UMVUE)1.26633

df64.00000

t2.98230

p0.00202

Lowerbound of 95% confidence interval for Sharpe Ratio0.40595

Upperbound of 95% confidence interval for Sharpe Ratio2.14752

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.39609

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.13657
 Statistics related to Sortino ratio

Sortino ratio3.16245

Upside Potential Ratio4.80465

Upside part of mean0.47995

Downside part of mean0.16404

Upside SD0.24121

Downside SD0.09989

N nonnegative terms38.00000

N negative terms27.00000
 Statistics related to linear regression on benchmark

N of observations65.00000

Mean of predictor0.10675

Mean of criterion0.31591

SD of predictor0.19359

SD of criterion0.24653

Covariance0.01674

r0.35083

b (slope, estimate of beta)0.44677

a (intercept, estimate of alpha)0.26822

Mean Square Error0.05414

DF error63.00000

t(b)2.97366

p(b)0.00208

t(a)2.64887

p(a)0.00510

Lowerbound of 95% confidence interval for beta0.14653

Upperbound of 95% confidence interval for beta0.74701

Lowerbound of 95% confidence interval for alpha0.06587

Upperbound of 95% confidence interval for alpha0.47056

Treynor index (mean / b)0.70709

Jensen alpha (a)0.26822
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.28370

SD0.23424

Sharpe ratio (Glass type estimate)1.21119

Sharpe ratio (Hedges UMVUE)1.19695

df64.00000

t2.81890

p0.00320

Lowerbound of 95% confidence interval for Sharpe Ratio0.33897

Upperbound of 95% confidence interval for Sharpe Ratio2.07452

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.32966

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.06423
 Statistics related to Sortino ratio

Sortino ratio2.72971

Upside Potential Ratio4.35496

Upside part of mean0.45262

Downside part of mean0.16892

Upside SD0.22345

Downside SD0.10393

N nonnegative terms38.00000

N negative terms27.00000
 Statistics related to linear regression on benchmark

N of observations65.00000

Mean of predictor0.08684

Mean of criterion0.28370

SD of predictor0.20071

SD of criterion0.23424

Covariance0.01675

r0.35630

b (slope, estimate of beta)0.41581

a (intercept, estimate of alpha)0.24760

Mean Square Error0.04866

DF error63.00000

t(b)3.02665

p(b)0.00179

t(a)2.59180

p(a)0.00593

Lowerbound of 95% confidence interval for beta0.14127

Upperbound of 95% confidence interval for beta0.69035

Lowerbound of 95% confidence interval for alpha0.05669

Upperbound of 95% confidence interval for alpha0.43850

Treynor index (mean / b)0.68230

Jensen alpha (a)0.24760
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.08385

Expected Shortfall on VaR0.10910
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.02783

Expected Shortfall on VaR0.05682
 ORDER STATISTICS
 Quartiles of return rates

Number of observations65.00000

Minimum0.87773

Quartile 10.98618

Median1.01388

Quartile 31.06454

Maximum1.24362

Mean of quarter 10.95406

Mean of quarter 21.00060

Mean of quarter 31.03863

Mean of quarter 41.12599

Inter Quartile Range0.07835

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high3.00000

Percentage of outliers high0.04615

Mean of outliers high1.22265
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.22784

VaR(95%) (moments method)0.03834

Expected Shortfall (moments method)0.04873

Extreme Value Index (regression method)0.04997

VaR(95%) (regression method)0.04824

Expected Shortfall (regression method)0.07126
 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)0.81380

Compounded annual return (geometric extrapolation)0.36562

Calmar ratio (compounded annual return / max draw down)1.86496

Compounded annual return / average of 25% largest draw downs2.63971

Compounded annual return / Expected Shortfall lognormal3.35129

0.00000

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

Mean0.29970

SD0.19943

Sharpe ratio (Glass type estimate)1.50279

Sharpe ratio (Hedges UMVUE)1.50200

df1431.00000

t3.51332

p0.44121

Lowerbound of 95% confidence interval for Sharpe Ratio0.66238

Upperbound of 95% confidence interval for Sharpe Ratio2.34270

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.66184

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.34216
 Statistics related to Sortino ratio

Sortino ratio2.67352

Upside Potential Ratio9.98735

Upside part of mean1.11958

Downside part of mean0.81988

Upside SD0.16589

Downside SD0.11210

N nonnegative terms498.00000

N negative terms934.00000
 Statistics related to linear regression on benchmark

N of observations1432.00000

Mean of predictor0.10972

Mean of criterion0.29970

SD of predictor0.21143

SD of criterion0.19943

Covariance0.00959

r0.22735

b (slope, estimate of beta)0.21445

a (intercept, estimate of alpha)0.27600

Mean Square Error0.03774

DF error1430.00000

t(b)8.82862

p(b)0.38632

t(a)3.32168

p(a)0.45625

Lowerbound of 95% confidence interval for beta0.16680

Upperbound of 95% confidence interval for beta0.26210

Lowerbound of 95% confidence interval for alpha0.11308

Upperbound of 95% confidence interval for alpha0.43927

Treynor index (mean / b)1.39752

Jensen alpha (a)0.27617
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.27987

SD0.19775

Sharpe ratio (Glass type estimate)1.41527

Sharpe ratio (Hedges UMVUE)1.41452

df1431.00000

t3.30871

p0.44460

Lowerbound of 95% confidence interval for Sharpe Ratio0.57509

Upperbound of 95% confidence interval for Sharpe Ratio2.25500

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.57457

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.25448
 Statistics related to Sortino ratio

Sortino ratio2.46922

Upside Potential Ratio9.75836

Upside part of mean1.10604

Downside part of mean0.82617

Upside SD0.16288

Downside SD0.11334

N nonnegative terms498.00000

N negative terms934.00000
 Statistics related to linear regression on benchmark

N of observations1432.00000

Mean of predictor0.08725

Mean of criterion0.27987

SD of predictor0.21224

SD of criterion0.19775

Covariance0.00950

r0.22644

b (slope, estimate of beta)0.21098

a (intercept, estimate of alpha)0.26146

Mean Square Error0.03713

DF error1430.00000

t(b)8.79130

p(b)0.38678

t(a)3.17137

p(a)0.45821

Lowerbound of 95% confidence interval for beta0.16391

Upperbound of 95% confidence interval for beta0.25806

Lowerbound of 95% confidence interval for alpha0.09974

Upperbound of 95% confidence interval for alpha0.42318

Treynor index (mean / b)1.32649

Jensen alpha (a)0.26146
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.01885

Expected Shortfall on VaR0.02383
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00845

Expected Shortfall on VaR0.01658
 ORDER STATISTICS
 Quartiles of return rates

Number of observations1432.00000

Minimum0.95459

Quartile 10.99651

Median1.00000

Quartile 31.00402

Maximum1.08753

Mean of quarter 10.98848

Mean of quarter 20.99928

Mean of quarter 31.00085

Mean of quarter 41.01639

Inter Quartile Range0.00751

Number outliers low90.00000

Percentage of outliers low0.06285

Mean of outliers low0.97812

Number of outliers high146.00000

Percentage of outliers high0.10196

Mean of outliers high1.02718
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.11157

VaR(95%) (moments method)0.00938

Expected Shortfall (moments method)0.01238

Extreme Value Index (regression method)0.00081

VaR(95%) (regression method)0.01113

Expected Shortfall (regression method)0.01586
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations54.00000

Minimum0.00035

Quartile 10.00921

Median0.03303

Quartile 30.06628

Maximum0.19750

Mean of quarter 10.00409

Mean of quarter 20.02033

Mean of quarter 30.04781

Mean of quarter 40.10693

Inter Quartile Range0.05708

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high3.00000

Percentage of outliers high0.05556

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)0.11852

Expected Shortfall (moments method)0.16141

Extreme Value Index (regression method)0.18584

VaR(95%) (regression method)0.12166

Expected Shortfall (regression method)0.16897
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.80088

Compounded annual return (geometric extrapolation)0.36039

Calmar ratio (compounded annual return / max draw down)1.82474

Compounded annual return / average of 25% largest draw downs3.37051

Compounded annual return / Expected Shortfall lognormal15.12160

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

Mean0.18024

SD0.07662

Sharpe ratio (Glass type estimate)2.35225

Sharpe ratio (Hedges UMVUE)2.33865

df130.00000

t1.66329

p0.57218

Lowerbound of 95% confidence interval for Sharpe Ratio5.13427

Upperbound of 95% confidence interval for Sharpe Ratio0.43864

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation5.12499

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation0.44770
 Statistics related to Sortino ratio

Sortino ratio3.09537

Upside Potential Ratio5.93393

Upside part of mean0.34552

Downside part of mean0.52576

Upside SD0.05060

Downside SD0.05823

N nonnegative terms43.00000

N negative terms88.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.22777

Mean of criterion0.18024

SD of predictor0.11949

SD of criterion0.07662

Covariance0.00187

r0.20370

b (slope, estimate of beta)0.13063

a (intercept, estimate of alpha)0.20999

Mean Square Error0.00567

DF error129.00000

t(b)2.36320

p(b)0.37122

t(a)1.95811

p(a)0.60764

Lowerbound of 95% confidence interval for beta0.02126

Upperbound of 95% confidence interval for beta0.24000

Lowerbound of 95% confidence interval for alpha0.42218

Upperbound of 95% confidence interval for alpha0.00219

Treynor index (mean / b)1.37975

Jensen alpha (a)0.20999
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.18319

SD0.07660

Sharpe ratio (Glass type estimate)2.39159

Sharpe ratio (Hedges UMVUE)2.37777

df130.00000

t1.69111

p0.57336

Lowerbound of 95% confidence interval for Sharpe Ratio5.17412

Upperbound of 95% confidence interval for Sharpe Ratio0.39991

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation5.16460

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation0.40906
 Statistics related to Sortino ratio

Sortino ratio3.13345

Upside Potential Ratio5.88764

Upside part of mean0.34422

Downside part of mean0.52741

Upside SD0.05033

Downside SD0.05846

N nonnegative terms43.00000

N negative terms88.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.22057

Mean of criterion0.18319

SD of predictor0.11947

SD of criterion0.07660

Covariance0.00186

r0.20326

b (slope, estimate of beta)0.13033

a (intercept, estimate of alpha)0.21194

Mean Square Error0.00567

DF error129.00000

t(b)2.35785

p(b)0.37150

t(a)1.97757

p(a)0.60867

VAR (95 Confidence Intrvl)0.01900

Lowerbound of 95% confidence interval for beta0.02097

Upperbound of 95% confidence interval for beta0.23969

Lowerbound of 95% confidence interval for alpha0.42398

Upperbound of 95% confidence interval for alpha0.00010

Treynor index (mean / b)1.40563

Jensen alpha (a)0.21194
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.00845

Expected Shortfall on VaR0.01040
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00552

Expected Shortfall on VaR0.00961
 ORDER STATISTICS
 Quartiles of return rates

Number of observations131.00000

Minimum0.98443

Quartile 10.99691

Median1.00000

Quartile 31.00130

Maximum1.01714

Mean of quarter 10.99365

Mean of quarter 20.99867

Mean of quarter 31.00025

Mean of quarter 41.00513

Inter Quartile Range0.00440

Number outliers low2.00000

Percentage of outliers low0.01527

Mean of outliers low0.98688

Number of outliers high6.00000

Percentage of outliers high0.04580

Mean of outliers high1.01192
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.63923

VaR(95%) (moments method)0.00649

Expected Shortfall (moments method)0.00724

Extreme Value Index (regression method)0.00921

VaR(95%) (regression method)0.00583

Expected Shortfall (regression method)0.00749
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations1.00000

Minimum0.10594

Quartile 10.10594

Median0.10594

Quartile 30.10594

Maximum0.10594

Mean of quarter 10.00000

Mean of quarter 20.00000

Mean of quarter 30.00000

Mean of quarter 40.00000

Inter Quartile Range0.00000

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high0.00000

Percentage of outliers high0.00000

Mean of outliers high0.00000
 Risk estimates based on draw downs (based on Extreme Value T

Extreme Value Index (moments method)0.00000

VaR(95%) (moments method)0.00000

Expected Shortfall (moments method)0.00000

Extreme Value Index (regression method)0.00000

VaR(95%) (regression method)0.00000

Last 4 Months  Pcnt Negative0.75%

Expected Shortfall (regression method)0.00000

Strat Max DD how much worse than SP500 max DD during strat life?386964000

Max Equity Drawdown (num days)166
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.14941

Compounded annual return (geometric extrapolation)0.14383

Calmar ratio (compounded annual return / max draw down)1.35765

Compounded annual return / average of 25% largest draw downs0.00000

Compounded annual return / Expected Shortfall lognormal13.82380
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
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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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