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%  +3.5%  +1.5%  +6.4%  +7.7% 
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  $118,675  
Cash  $1  
Equity  $1  
Cumulative $  $98,675  
Includes dividends and cashsettled expirations:  $22  Itemized 
Total System Equity  $118,675  
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)2245.89

Age75 months ago

What it tradesStocks

# Trades419

# Profitable197

% Profitable47.00%

Avg trade duration1.6 days

Max peaktovalley drawdown24.67%

drawdown periodAug 30, 2018  Feb 12, 2019

Annual Return (Compounded)30.4%

Avg win$1,561

Avg loss$941.02
 Model Account Values (Raw)

Cash$118,675

Margin Used$0

Buying Power$118,675
 Ratios

W:L ratio1.47:1

Sharpe Ratio1.07

Sortino Ratio1.88

Calmar Ratio1.82
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)308.03%

Correlation to SP5000.23930

Return Percent SP500 (cumu) during strategy life105.84%
 Return Statistics

Ann Return (w trading costs)30.4%
 Slump

Current Slump as Pcnt Equity6.00%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.15%
 Return Statistics

Return Pcnt Since TOS Statusn/a
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.304%
 Instruments

Percent Trades Optionsn/a

Percent Trades Stocks1.00%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)33.5%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss40.00%

Chance of 20% account loss7.00%

Chance of 30% account loss1.00%

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)695

Popularity (Last 6 weeks)968
 Trading Style

Any stock shorts? 0/10
 Popularity

C2 Score991

Popularity (7 days, Percentile 1000 scale)930
 TradesOwnSystem Certification

Trades Own System?

TOS percentn/a
 Win / Loss

Avg Loss$941

Avg Win$1,561

Sum Trade PL (losers)$208,907.000
 Age

Num Months filled monthly returns table74
 Win / Loss

Sum Trade PL (winners)$307,560.000

# Winners197

Num Months Winners45
 Dividends

Dividends Received in Model Acct22
 AUM

AUM (AutoTrader live capital)720472
 Win / Loss

# Losers222

% Winners47.0%
 Frequency

Avg Position Time (mins)2292.37

Avg Position Time (hrs)38.21

Avg Trade Length1.6 days

Last Trade Ago3
 Leverage

Daily leverage (average)2.78

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)1.05

MAE:Equity, average, winning trades0.01

MAE:Equity, average, losing trades0.02

Avg(MAE) / Avg(PL)  All trades13.096

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 trades0.292

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

HoldandHope Ratio0.076
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.30435

SD0.23964

Sharpe ratio (Glass type estimate)1.26999

Sharpe ratio (Hedges UMVUE)1.25593

df68.00000

t3.04533

p0.00165

Lowerbound of 95% confidence interval for Sharpe Ratio0.42096

Upperbound of 95% confidence interval for Sharpe Ratio2.11030

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.41175

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.10011
 Statistics related to Sortino ratio

Sortino ratio3.13906

Upside Potential Ratio4.73295

Upside part of mean0.45888

Downside part of mean0.15454

Upside SD0.23434

Downside SD0.09695

N nonnegative terms42.00000

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

N of observations69.00000

Mean of predictor0.11305

Mean of criterion0.30435

SD of predictor0.18835

SD of criterion0.23964

Covariance0.01570

r0.34790

b (slope, estimate of beta)0.44263

a (intercept, estimate of alpha)0.25431

Mean Square Error0.05123

DF error67.00000

t(b)3.03741

p(b)0.00170

t(a)2.65402

p(a)0.00496

Lowerbound of 95% confidence interval for beta0.15176

Upperbound of 95% confidence interval for beta0.73350

Lowerbound of 95% confidence interval for alpha0.06305

Upperbound of 95% confidence interval for alpha0.44556

Treynor index (mean / b)0.68758

Jensen alpha (a)0.25431
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.27394

SD0.22762

Sharpe ratio (Glass type estimate)1.20350

Sharpe ratio (Hedges UMVUE)1.19018

df68.00000

t2.88589

p0.00261

Lowerbound of 95% confidence interval for Sharpe Ratio0.35742

Upperbound of 95% confidence interval for Sharpe Ratio2.04127

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.34870

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.03166
 Statistics related to Sortino ratio

Sortino ratio2.71566

Upside Potential Ratio4.29310

Upside part of mean0.43306

Downside part of mean0.15912

Upside SD0.21711

Downside SD0.10088

N nonnegative terms42.00000

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

N of observations69.00000

Mean of predictor0.09409

Mean of criterion0.27394

SD of predictor0.19528

SD of criterion0.22762

Covariance0.01571

r0.35347

b (slope, estimate of beta)0.41202

a (intercept, estimate of alpha)0.23517

Mean Square Error0.04601

DF error67.00000

t(b)3.09294

p(b)0.00144

t(a)2.60349

p(a)0.00568

Lowerbound of 95% confidence interval for beta0.14613

Upperbound of 95% confidence interval for beta0.67791

Lowerbound of 95% confidence interval for alpha0.05487

Upperbound of 95% confidence interval for alpha0.41548

Treynor index (mean / b)0.66487

Jensen alpha (a)0.23517
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.08172

Expected Shortfall on VaR0.10633
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.02506

Expected Shortfall on VaR0.05239
 ORDER STATISTICS
 Quartiles of return rates

Number of observations69.00000

Minimum0.87773

Quartile 10.98749

Median1.01120

Quartile 31.05942

Maximum1.24362

Mean of quarter 10.95592

Mean of quarter 21.00182

Mean of quarter 31.03487

Mean of quarter 41.12237

Inter Quartile Range0.07194

Number outliers low1.00000

Percentage of outliers low0.01449

Mean of outliers low0.87773

Number of outliers high3.00000

Percentage of outliers high0.04348

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

Extreme Value Index (moments method)0.07367

VaR(95%) (moments method)0.03509

Expected Shortfall (moments method)0.04752

Extreme Value Index (regression method)0.04189

VaR(95%) (regression method)0.04702

Expected Shortfall (regression method)0.06977
 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)0.81261

Compounded annual return (geometric extrapolation)0.35236

Calmar ratio (compounded annual return / max draw down)1.79728

Compounded annual return / average of 25% largest draw downs2.54392

Compounded annual return / Expected Shortfall lognormal3.31392

0.00000

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

Mean0.29817

SD0.19487

Sharpe ratio (Glass type estimate)1.53003

Sharpe ratio (Hedges UMVUE)1.52927

df1518.00000

t3.68407

p0.45293

Lowerbound of 95% confidence interval for Sharpe Ratio0.71397

Upperbound of 95% confidence interval for Sharpe Ratio2.34559

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.71347

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.34508
 Statistics related to Sortino ratio

Sortino ratio2.72497

Upside Potential Ratio9.98336

Upside part of mean1.09238

Downside part of mean0.79421

Upside SD0.16223

Downside SD0.10942

N nonnegative terms534.00000

N negative terms985.00000
 Statistics related to linear regression on benchmark

N of observations1519.00000

Mean of predictor0.11814

Mean of criterion0.29817

SD of predictor0.20691

SD of criterion0.19487

Covariance0.00916

r0.22715

b (slope, estimate of beta)0.21394

a (intercept, estimate of alpha)0.27300

Mean Square Error0.03604

DF error1517.00000

t(b)9.08485

p(b)0.35664

t(a)3.45900

p(a)0.44376

Lowerbound of 95% confidence interval for beta0.16775

Upperbound of 95% confidence interval for beta0.26014

Lowerbound of 95% confidence interval for alpha0.11814

Upperbound of 95% confidence interval for alpha0.42764

Treynor index (mean / b)1.39367

Jensen alpha (a)0.27289
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.27922

SD0.19324

Sharpe ratio (Glass type estimate)1.44489

Sharpe ratio (Hedges UMVUE)1.44418

df1518.00000

t3.47908

p0.45553

Lowerbound of 95% confidence interval for Sharpe Ratio0.62905

Upperbound of 95% confidence interval for Sharpe Ratio2.26028

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.62857

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.25979
 Statistics related to Sortino ratio

Sortino ratio2.52402

Upside Potential Ratio9.75753

Upside part of mean1.07942

Downside part of mean0.80020

Upside SD0.15931

Downside SD0.11062

N nonnegative terms534.00000

N negative terms985.00000
 Statistics related to linear regression on benchmark

N of observations1519.00000

Mean of predictor0.09661

Mean of criterion0.27922

SD of predictor0.20769

SD of criterion0.19324

Covariance0.00908

r0.22625

b (slope, estimate of beta)0.21051

a (intercept, estimate of alpha)0.25888

Mean Square Error0.03546

DF error1517.00000

t(b)9.04674

p(b)0.35720

t(a)3.30908

p(a)0.44617

Lowerbound of 95% confidence interval for beta0.16487

Upperbound of 95% confidence interval for beta0.25616

Lowerbound of 95% confidence interval for alpha0.10542

Upperbound of 95% confidence interval for alpha0.41234

Treynor index (mean / b)1.32636

Jensen alpha (a)0.25888
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.01840

Expected Shortfall on VaR0.02328
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00816

Expected Shortfall on VaR0.01606
 ORDER STATISTICS
 Quartiles of return rates

Number of observations1519.00000

Minimum0.95459

Quartile 10.99666

Median1.00000

Quartile 31.00403

Maximum1.08753

Mean of quarter 10.98884

Mean of quarter 20.99931

Mean of quarter 31.00087

Mean of quarter 41.01595

Inter Quartile Range0.00738

Number outliers low92.00000

Percentage of outliers low0.06057

Mean of outliers low0.97828

Number of outliers high149.00000

Percentage of outliers high0.09809

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

Extreme Value Index (moments method)0.05812

VaR(95%) (moments method)0.00894

Expected Shortfall (moments method)0.01208

Extreme Value Index (regression method)0.00096

VaR(95%) (regression method)0.01091

Expected Shortfall (regression method)0.01563
 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)0.85094

Compounded annual return (geometric extrapolation)0.35951

Calmar ratio (compounded annual return / max draw down)1.82026

Compounded annual return / average of 25% largest draw downs3.36223

Compounded annual return / Expected Shortfall lognormal15.44590

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

Mean0.11513

SD0.08460

Sharpe ratio (Glass type estimate)1.36094

Sharpe ratio (Hedges UMVUE)1.35308

df130.00000

t0.96233

p0.45795

Lowerbound of 95% confidence interval for Sharpe Ratio1.41834

Upperbound of 95% confidence interval for Sharpe Ratio4.13514

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation1.42361

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation4.12976
 Statistics related to Sortino ratio

Sortino ratio2.32043

Upside Potential Ratio10.45720

Upside part of mean0.51886

Downside part of mean0.40372

Upside SD0.06849

Downside SD0.04962

N nonnegative terms51.00000

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

N of observations131.00000

Mean of predictor0.28010

Mean of criterion0.11513

SD of predictor0.10689

SD of criterion0.08460

Covariance0.00161

r0.17818

b (slope, estimate of beta)0.14101

a (intercept, estimate of alpha)0.07564

Mean Square Error0.00698

DF error129.00000

t(b)2.05663

p(b)0.38717

t(a)0.63171

p(a)0.46466

Lowerbound of 95% confidence interval for beta0.00536

Upperbound of 95% confidence interval for beta0.27667

Lowerbound of 95% confidence interval for alpha0.16126

Upperbound of 95% confidence interval for alpha0.31253

Treynor index (mean / b)0.81647

Jensen alpha (a)0.07564
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.11156

SD0.08437

Sharpe ratio (Glass type estimate)1.32227

Sharpe ratio (Hedges UMVUE)1.31463

df130.00000

t0.93499

p0.45914

Lowerbound of 95% confidence interval for Sharpe Ratio1.45661

Upperbound of 95% confidence interval for Sharpe Ratio4.09620

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation1.46178

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation4.09104
 Statistics related to Sortino ratio

Sortino ratio2.23988

Upside Potential Ratio10.36980

Upside part of mean0.51648

Downside part of mean0.40492

Upside SD0.06805

Downside SD0.04981

N nonnegative terms51.00000

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

N of observations131.00000

Mean of predictor0.27426

Mean of criterion0.11156

SD of predictor0.10680

SD of criterion0.08437

Covariance0.00160

r0.17718

b (slope, estimate of beta)0.13997

a (intercept, estimate of alpha)0.07317

Mean Square Error0.00695

DF error129.00000

t(b)2.04472

p(b)0.38780

t(a)0.61299

p(a)0.46571

VAR (95 Confidence Intrvl)0.01800

Lowerbound of 95% confidence interval for beta0.00453

Upperbound of 95% confidence interval for beta0.27541

Lowerbound of 95% confidence interval for alpha0.16300

Upperbound of 95% confidence interval for alpha0.30934

Treynor index (mean / b)0.79702

Jensen alpha (a)0.07317
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.00811

Expected Shortfall on VaR0.01027
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00402

Expected Shortfall on VaR0.00754
 ORDER STATISTICS
 Quartiles of return rates

Number of observations131.00000

Minimum0.98728

Quartile 10.99793

Median1.00000

Quartile 31.00290

Maximum1.02249

Mean of quarter 10.99470

Mean of quarter 20.99944

Mean of quarter 31.00077

Mean of quarter 41.00729

Inter Quartile Range0.00497

Number outliers low2.00000

Percentage of outliers low0.01527

Mean of outliers low0.98831

Number of outliers high6.00000

Percentage of outliers high0.04580

Mean of outliers high1.01491
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.09170

VaR(95%) (moments method)0.00489

Expected Shortfall (moments method)0.00639

Extreme Value Index (regression method)0.12015

VaR(95%) (regression method)0.00516

Expected Shortfall (regression method)0.00671
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations7.00000

Minimum0.00042

Quartile 10.00141

Median0.00912

Quartile 30.01395

Maximum0.04175

Mean of quarter 10.00073

Mean of quarter 20.00545

Mean of quarter 30.01067

Mean of quarter 40.02950

Inter Quartile Range0.01254

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high1.00000

Percentage of outliers high0.14286

Mean of outliers high0.04175
 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 Negativen/a

Expected Shortfall (regression method)0.00000

Strat Max DD how much worse than SP500 max DD during strat life?353248000

Max Equity Drawdown (num days)166
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.14444

Compounded annual return (geometric extrapolation)0.14966

Calmar ratio (compounded annual return / max draw down)3.58434

Compounded annual return / average of 25% largest draw downs5.07374

Compounded annual return / Expected Shortfall lognormal14.57140
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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