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%)  (0.9%)  +0.2%  +3.8%  0.0 
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  $110,865  
Cash  $1  
Equity  $1  
Cumulative $  $90,865  
Includes dividends and cashsettled expirations:  $22  Itemized 
Total System Equity  $110,865  
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)2184.77

Age73 months ago

What it tradesStocks

# Trades395

# Profitable180

% Profitable45.60%

Avg trade duration1.7 days

Max peaktovalley drawdown24.67%

drawdown periodAug 30, 2018  Feb 12, 2019

Annual Return (Compounded)29.8%

Avg win$1,619

Avg loss$933.33
 Model Account Values (Raw)

Cash$110,865

Margin Used$0

Buying Power$110,865
 Ratios

W:L ratio1.45:1

Sharpe Ratio1.05

Sortino Ratio1.83

Calmar Ratio1.799
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)286.25%

Correlation to SP5000.23800

Return Percent SP500 (cumu) during strategy life91.00%
 Return Statistics

Ann Return (w trading costs)29.8%
 Slump

Current Slump as Pcnt Equity14.10%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.13%
 Return Statistics

Return Pcnt Since TOS Statusn/a
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.298%
 Instruments

Percent Trades Optionsn/a

Percent Trades Stocks1.00%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)33.1%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss27.50%

Chance of 20% account loss7.50%

Chance of 30% account lossn/a

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)828

Popularity (Last 6 weeks)972
 Trading Style

Any stock shorts? 0/10
 Popularity

C2 Score991

Popularity (7 days, Percentile 1000 scale)937
 TradesOwnSystem Certification

Trades Own System?

TOS percentn/a
 Win / Loss

Avg Loss$933

Avg Win$1,619

Sum Trade PL (losers)$200,666.000
 Age

Num Months filled monthly returns table72
 Win / Loss

Sum Trade PL (winners)$291,509.000

# Winners180

Num Months Winners43
 Dividends

Dividends Received in Model Acct22
 AUM

AUM (AutoTrader live capital)1281670
 Win / Loss

# Losers215

% Winners45.6%
 Frequency

Avg Position Time (mins)2420.95

Avg Position Time (hrs)40.35

Avg Trade Length1.7 days

Last Trade Ago1
 Leverage

Daily leverage (average)2.77

Daily leverage (max)4.28
 Regression

Alpha0.07

Beta0.25

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)1.07

MAE:Equity, average, winning trades0.01

MAE:Equity, average, losing trades0.02

Avg(MAE) / Avg(PL)  All trades15.736

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 trades0.274

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

HoldandHope Ratio0.063
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.30855

SD0.24308

Sharpe ratio (Glass type estimate)1.26934

Sharpe ratio (Hedges UMVUE)1.25486

df66.00000

t2.99933

p0.00191

Lowerbound of 95% confidence interval for Sharpe Ratio0.40768

Upperbound of 95% confidence interval for Sharpe Ratio2.12202

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.39821

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.11151
 Statistics related to Sortino ratio

Sortino ratio3.13591

Upside Potential Ratio4.75341

Upside part of mean0.46770

Downside part of mean0.15915

Upside SD0.23761

Downside SD0.09839

N nonnegative terms40.00000

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

N of observations67.00000

Mean of predictor0.11209

Mean of criterion0.30855

SD of predictor0.19088

SD of criterion0.24308

Covariance0.01613

r0.34765

b (slope, estimate of beta)0.44270

a (intercept, estimate of alpha)0.25892

Mean Square Error0.05274

DF error65.00000

t(b)2.98927

p(b)0.00197

t(a)2.62596

p(a)0.00538

Lowerbound of 95% confidence interval for beta0.14693

Upperbound of 95% confidence interval for beta0.73847

Lowerbound of 95% confidence interval for alpha0.06200

Upperbound of 95% confidence interval for alpha0.45585

Treynor index (mean / b)0.69697

Jensen alpha (a)0.25892
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.27729

SD0.23090

Sharpe ratio (Glass type estimate)1.20090

Sharpe ratio (Hedges UMVUE)1.18720

df66.00000

t2.83761

p0.00302

Lowerbound of 95% confidence interval for Sharpe Ratio0.34231

Upperbound of 95% confidence interval for Sharpe Ratio2.05093

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.33336

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.04104
 Statistics related to Sortino ratio

Sortino ratio2.70875

Upside Potential Ratio4.30956

Upside part of mean0.44117

Downside part of mean0.16387

Upside SD0.22011

Downside SD0.10237

N nonnegative terms40.00000

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

N of observations67.00000

Mean of predictor0.09265

Mean of criterion0.27729

SD of predictor0.19792

SD of criterion0.23090

Covariance0.01614

r0.35323

b (slope, estimate of beta)0.41210

a (intercept, estimate of alpha)0.23911

Mean Square Error0.04738

DF error65.00000

t(b)3.04404

p(b)0.00168

t(a)2.57187

p(a)0.00621

Lowerbound of 95% confidence interval for beta0.14173

Upperbound of 95% confidence interval for beta0.68247

Lowerbound of 95% confidence interval for alpha0.05343

Upperbound of 95% confidence interval for alpha0.42479

Treynor index (mean / b)0.67288

Jensen alpha (a)0.23911
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.08289

Expected Shortfall on VaR0.10781
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.02639

Expected Shortfall on VaR0.05454
 ORDER STATISTICS
 Quartiles of return rates

Number of observations67.00000

Minimum0.87773

Quartile 10.98684

Median1.01120

Quartile 31.06198

Maximum1.24362

Mean of quarter 10.95406

Mean of quarter 21.00070

Mean of quarter 31.03546

Mean of quarter 41.12237

Inter Quartile Range0.07515

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high3.00000

Percentage of outliers high0.04478

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)0.03795

Expected Shortfall (moments method)0.04842

Extreme Value Index (regression method)0.04997

VaR(95%) (regression method)0.04759

Expected Shortfall (regression method)0.07057
 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)0.80527

Compounded annual return (geometric extrapolation)0.35690

Calmar ratio (compounded annual return / max draw down)1.82044

Compounded annual return / average of 25% largest draw downs2.57670

Compounded annual return / Expected Shortfall lognormal3.31025

0.00000

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

Mean0.29541

SD0.19688

Sharpe ratio (Glass type estimate)1.50046

Sharpe ratio (Hedges UMVUE)1.49970

df1475.00000

t3.56138

p0.44130

Lowerbound of 95% confidence interval for Sharpe Ratio0.67269

Upperbound of 95% confidence interval for Sharpe Ratio2.32776

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.67217

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.32724
 Statistics related to Sortino ratio

Sortino ratio2.66958

Upside Potential Ratio9.96223

Upside part of mean1.10242

Downside part of mean0.80700

Upside SD0.16378

Downside SD0.11066

N nonnegative terms513.00000

N negative terms963.00000
 Statistics related to linear regression on benchmark

N of observations1476.00000

Mean of predictor0.10897

Mean of criterion0.29541

SD of predictor0.20929

SD of criterion0.19688

Covariance0.00931

r0.22595

b (slope, estimate of beta)0.21256

a (intercept, estimate of alpha)0.27200

Mean Square Error0.03681

DF error1474.00000

t(b)8.90521

p(b)0.38702

t(a)3.36639

p(a)0.45633

Lowerbound of 95% confidence interval for beta0.16574

Upperbound of 95% confidence interval for beta0.25938

Lowerbound of 95% confidence interval for alpha0.11361

Upperbound of 95% confidence interval for alpha0.43089

Treynor index (mean / b)1.38981

Jensen alpha (a)0.27225
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.27608

SD0.19523

Sharpe ratio (Glass type estimate)1.41417

Sharpe ratio (Hedges UMVUE)1.41345

df1475.00000

t3.35655

p0.44464

Lowerbound of 95% confidence interval for Sharpe Ratio0.58661

Upperbound of 95% confidence interval for Sharpe Ratio2.24129

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.58611

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.24078
 Statistics related to Sortino ratio

Sortino ratio2.46763

Upside Potential Ratio9.73536

Upside part of mean1.08921

Downside part of mean0.81313

Upside SD0.16081

Downside SD0.11188

N nonnegative terms513.00000

N negative terms963.00000
 Statistics related to linear regression on benchmark

N of observations1476.00000

Mean of predictor0.08695

Mean of criterion0.27608

SD of predictor0.21008

SD of criterion0.19523

Covariance0.00923

r0.22503

b (slope, estimate of beta)0.20912

a (intercept, estimate of alpha)0.25790

Mean Square Error0.03621

DF error1474.00000

t(b)8.86705

p(b)0.38748

t(a)3.21587

p(a)0.45826

Lowerbound of 95% confidence interval for beta0.16286

Upperbound of 95% confidence interval for beta0.25538

Lowerbound of 95% confidence interval for alpha0.10059

Upperbound of 95% confidence interval for alpha0.41521

Treynor index (mean / b)1.32020

Jensen alpha (a)0.25790
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.01861

Expected Shortfall on VaR0.02353
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00832

Expected Shortfall on VaR0.01634
 ORDER STATISTICS
 Quartiles of return rates

Number of observations1476.00000

Minimum0.95459

Quartile 10.99657

Median1.00000

Quartile 31.00409

Maximum1.08753

Mean of quarter 10.98868

Mean of quarter 20.99928

Mean of quarter 31.00086

Mean of quarter 41.01612

Inter Quartile Range0.00753

Number outliers low90.00000

Percentage of outliers low0.06098

Mean of outliers low0.97812

Number of outliers high144.00000

Percentage of outliers high0.09756

Mean of outliers high1.02734
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.06651

VaR(95%) (moments method)0.00916

Expected Shortfall (moments method)0.01232

Extreme Value Index (regression method)0.00399

VaR(95%) (regression method)0.01102

Expected Shortfall (regression method)0.01576
 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)0.80643

Compounded annual return (geometric extrapolation)0.35525

Calmar ratio (compounded annual return / max draw down)1.79873

Compounded annual return / average of 25% largest draw downs3.32245

Compounded annual return / Expected Shortfall lognormal15.09570

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

Mean0.02377

SD0.07969

Sharpe ratio (Glass type estimate)0.29830

Sharpe ratio (Hedges UMVUE)0.29657

df130.00000

t0.21093

p0.50925

Lowerbound of 95% confidence interval for Sharpe Ratio3.06986

Upperbound of 95% confidence interval for Sharpe Ratio2.47423

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation3.06861

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.47547
 Statistics related to Sortino ratio

Sortino ratio0.44868

Upside Potential Ratio8.73036

Upside part of mean0.46252

Downside part of mean0.48629

Upside SD0.05914

Downside SD0.05298

N nonnegative terms48.00000

N negative terms83.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.34428

Mean of criterion0.02377

SD of predictor0.11604

SD of criterion0.07969

Covariance0.00093

r0.10050

b (slope, estimate of beta)0.06902

a (intercept, estimate of alpha)0.04753

Mean Square Error0.00633

DF error129.00000

t(b)1.14728

p(b)0.43613

t(a)0.41531

p(a)0.52326

Lowerbound of 95% confidence interval for beta0.05000

Upperbound of 95% confidence interval for beta0.18804

Lowerbound of 95% confidence interval for alpha0.27397

Upperbound of 95% confidence interval for alpha0.17891

Treynor index (mean / b)0.34442

Jensen alpha (a)0.04753
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.02691

SD0.07958

Sharpe ratio (Glass type estimate)0.33819

Sharpe ratio (Hedges UMVUE)0.33623

df130.00000

t0.23913

p0.51048

Lowerbound of 95% confidence interval for Sharpe Ratio3.10970

Upperbound of 95% confidence interval for Sharpe Ratio2.43453

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation3.10834

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.43587
 Statistics related to Sortino ratio

Sortino ratio0.50629

Upside Potential Ratio8.66699

Upside part of mean0.46074

Downside part of mean0.48765

Upside SD0.05884

Downside SD0.05316

N nonnegative terms48.00000

N negative terms83.00000
 Statistics related to linear regression on benchmark

N of observations131.00000

Mean of predictor0.33735

Mean of criterion0.02691

SD of predictor0.11588

SD of criterion0.07958

Covariance0.00092

r0.09960

b (slope, estimate of beta)0.06841

a (intercept, estimate of alpha)0.04999

Mean Square Error0.00632

DF error129.00000

t(b)1.13695

p(b)0.43669

t(a)0.43761

p(a)0.52450

VAR (95 Confidence Intrvl)0.01900

Lowerbound of 95% confidence interval for beta0.05064

Upperbound of 95% confidence interval for beta0.18746

Lowerbound of 95% confidence interval for alpha0.27602

Upperbound of 95% confidence interval for alpha0.17604

Treynor index (mean / b)0.39343

Jensen alpha (a)0.04999
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.00816

Expected Shortfall on VaR0.01019
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00494

Expected Shortfall on VaR0.00856
 ORDER STATISTICS
 Quartiles of return rates

Number of observations131.00000

Minimum0.98933

Quartile 10.99706

Median1.00000

Quartile 31.00291

Maximum1.01714

Mean of quarter 10.99417

Mean of quarter 20.99873

Mean of quarter 31.00069

Mean of quarter 41.00650

Inter Quartile Range0.00585

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high3.00000

Percentage of outliers high0.02290

Mean of outliers high1.01428
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.36425

VaR(95%) (moments method)0.00602

Expected Shortfall (moments method)0.00706

Extreme Value Index (regression method)0.32494

VaR(95%) (regression method)0.00597

Expected Shortfall (regression method)0.00705
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations3.00000

Minimum0.02540

Quartile 10.02679

Median0.02819

Quartile 30.03750

Maximum0.04681

Mean of quarter 10.02540

Mean of quarter 20.02819

Mean of quarter 30.00000

Mean of quarter 40.04681

Inter Quartile Range0.01071

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 Negative0.50%

Expected Shortfall (regression method)0.00000

Strat Max DD how much worse than SP500 max DD during strat life?355780000

Max Equity Drawdown (num days)166
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.00099

Compounded annual return (geometric extrapolation)0.00099

Calmar ratio (compounded annual return / max draw down)0.02121

Compounded annual return / average of 25% largest draw downs0.02121

Compounded annual return / Expected Shortfall lognormal0.09744
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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