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 short-sells a security that has been in a downward trend. While similar to Trend-following, tends to be more forward-looking (predicting oncoming trend), while Momentum is more backward-looking (observing already-established 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 marked-to-market equity calculations.
All results are hypothetical.
Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2018 | +4.5% | +7.1% | +5.4% | +12.5% | (10.5%) | (12.5%) | - | (1.8%) | +2.1% | ||||
2019 | (0.9%) | +0.6% | +7.7% | +14.7% | (4.5%) | +25.8% | +5.7% | (12.7%) | (0.7%) | (0.7%) | +3.3% | +8.7% | +51.4% |
2020 | (4.1%) | +16.2% | (4.6%) | (8.8%) | +0.5% | +0.1% | (0.9%) | +22.1% | +14.7% | +9.3% | +11.0% | (3.6%) | +58.1% |
2021 | +1.0% | +7.0% | +2.6% | +16.9% | (1.6%) | +12.9% | +3.7% | +13.2% | (3.3%) | +14.5% | +6.7% | +1.4% | +102.4% |
2022 | +0.5% | (6.5%) | +5.3% | (1%) | +4.3% | (3.4%) | +2.6% | (2.9%) | (1.2%) | +1.6% | +0.5% | (1.8%) | (2.5%) |
2023 | +3.9% | +2.2% | (0.1%) | +1.0% | +3.5% | +0.7% | (3%) | +1.3% | (4.4%) | (6.9%) | (0.2%) | +1.5% | (1.1%) |
2024 | (3%) | (0.9%) | +0.2% | +3.5% | +1.5% | +1.6% | +5.9% | (5.3%) | (5.2%) | +5.4% | +3.5% | +1.4% | +8.3% |
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 | $47,977 | |
Cash | $1 | |
Equity | $1 | |
Cumulative $ | $100,413 | |
Includes dividends and cash-settled expirations: | $22 | Itemized |
Total System Equity | $120,413 | |
Margined | $1 | |
Open P/L | $0 | |
Data has been delayed by 48 hours for non-subscribers |
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)2408.13
-
Age80 months ago
-
What it tradesStocks
-
# Trades484
-
# Profitable233
-
% Profitable48.10%
-
Avg trade duration1.4 days
-
Max peak-to-valley drawdown24.67%
-
drawdown periodAug 30, 2018 - Feb 12, 2019
-
Annual Return (Compounded)28.2%
-
Avg win$1,465
-
Avg loss$960.73
- Model Account Values (Raw)
-
Cash$48,291
-
Margin Used$0
-
Buying Power$47,977
- Ratios
-
W:L ratio1.42:1
-
Sharpe Ratio1.03
-
Sortino Ratio1.78
-
Calmar Ratio1.69
- CORRELATION STATISTICS
-
Return of Strat Pcnt - Return of SP500 Pcnt (cumu)289.25%
-
Correlation to SP5000.23720
-
Return Percent SP500 (cumu) during strategy life127.78%
- Return Statistics
-
Ann Return (w trading costs)28.2%
- Slump
-
Current Slump as Pcnt Equity5.40%
- Instruments
-
Percent Trades Futuresn/a
- Slump
-
Current Slump, time of slump as pcnt of strategy life0.21%
- Return Statistics
-
Return Pcnt Since TOS Statusn/a
- Instruments
-
Short Options - Percent Covered100.00%
- Return Statistics
-
Return Pcnt (Compound or Annual, age-based, NFA compliant)0.282%
- Instruments
-
Percent Trades Optionsn/a
-
Percent Trades Stocks1.00%
-
Percent Trades Forexn/a
- Return Statistics
-
Ann Return (Compnd, No Fees)31.3%
- Risk of Ruin (Monte-Carlo)
-
Chance of 10% account loss27.00%
-
Chance of 20% account loss6.00%
-
Chance of 30% account loss2.00%
-
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 (Monte-Carlo)
-
Chance of 50% account lossn/a
- Popularity
-
Popularity (Today)742
-
Popularity (Last 6 weeks)924
- Trading Style
-
Any stock shorts? 0/10
- Popularity
-
C2 Score959
-
Popularity (7 days, Percentile 1000 scale)854
- Trades-Own-System Certification
-
Trades Own System?-
-
TOS percentn/a
- Win / Loss
-
Avg Loss$960
-
Avg Win$1,466
-
Sum Trade PL (losers)$240,945.000
- Age
-
Num Months filled monthly returns table80
- Win / Loss
-
Sum Trade PL (winners)$341,536.000
-
# Winners233
-
Num Months Winners49
- Dividends
-
Dividends Received in Model Acct22
- AUM
-
AUM (AutoTrader live capital)607086
- Win / Loss
-
# Losers251
-
% Winners48.1%
- Frequency
-
Avg Position Time (mins)2002.10
-
Avg Position Time (hrs)33.37
-
Avg Trade Length1.4 days
-
Last Trade Ago0
- Leverage
-
Daily leverage (average)2.76
-
Daily leverage (max)4.28
- Regression
-
Alpha0.06
-
Beta0.25
-
Treynor Index0.27
- Maximum Adverse Excursion (MAE)
-
MAE:Equity, average, all trades0.01
-
MAE:PL - Winning Trades - this strat Percentile of All Strats7.66
-
MAE:PL - worst single value for strategy-
-
MAE:PL - Losing Trades - this strat Percentile of All Strats54.88
-
MAE:PL (avg, winning trades)-
-
MAE:PL (avg, losing trades)-
-
MAE:PL (avg, all trades)0.92
-
MAE:Equity, average, winning trades0.01
-
MAE:Equity, average, losing trades0.02
-
Avg(MAE) / Avg(PL) - All trades14.827
-
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 strat0.02
-
Avg(MAE) / Avg(PL) - Winning trades0.312
-
Avg(MAE) / Avg(PL) - Losing trades-1.155
-
Hold-and-Hope Ratio0.068
- Analysis based on MONTHLY values, full history
- RATIO STATISTICS
- Ratio statistics of excess return rates
- Statistics related to Sharpe ratio
-
Mean0.28641
-
SD0.23423
-
Sharpe ratio (Glass type estimate)1.22273
-
Sharpe ratio (Hedges UMVUE)1.21012
-
df73.00000
-
t3.03637
-
p0.00166
-
Lowerbound of 95% confidence interval for Sharpe Ratio0.40508
-
Upperbound of 95% confidence interval for Sharpe Ratio2.03252
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.39681
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.02343
- Statistics related to Sortino ratio
-
Sortino ratio3.00526
-
Upside Potential Ratio4.64452
-
Upside part of mean0.44263
-
Downside part of mean-0.15622
-
Upside SD0.22777
-
Downside SD0.09530
-
N nonnegative terms44.00000
-
N negative terms30.00000
- Statistics related to linear regression on benchmark
-
N of observations74.00000
-
Mean of predictor0.12091
-
Mean of criterion0.28641
-
SD of predictor0.18564
-
SD of criterion0.23423
-
Covariance0.01477
-
r0.33972
-
b (slope, estimate of beta)0.42865
-
a (intercept, estimate of alpha)0.23458
-
Mean Square Error0.04921
-
DF error72.00000
-
t(b)3.06488
-
p(b)0.00153
-
t(a)2.58016
-
p(a)0.00596
-
Lowerbound of 95% confidence interval for beta0.14985
-
Upperbound of 95% confidence interval for beta0.70745
-
Lowerbound of 95% confidence interval for alpha0.05334
-
Upperbound of 95% confidence interval for alpha0.41581
-
Treynor index (mean / b)0.66816
-
Jensen alpha (a)0.23458
- Ratio statistics of excess log return rates
- Statistics related to Sharpe ratio
-
Mean0.25756
-
SD0.22259
-
Sharpe ratio (Glass type estimate)1.15711
-
Sharpe ratio (Hedges UMVUE)1.14518
-
df73.00000
-
t2.87342
-
p0.00266
-
Lowerbound of 95% confidence interval for Sharpe Ratio0.34217
-
Upperbound of 95% confidence interval for Sharpe Ratio1.96455
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.33435
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation1.95601
- Statistics related to Sortino ratio
-
Sortino ratio2.60009
-
Upside Potential Ratio4.22170
-
Upside part of mean0.41820
-
Downside part of mean-0.16064
-
Upside SD0.21117
-
Downside SD0.09906
-
N nonnegative terms44.00000
-
N negative terms30.00000
- Statistics related to linear regression on benchmark
-
N of observations74.00000
-
Mean of predictor0.10239
-
Mean of criterion0.25756
-
SD of predictor0.19227
-
SD of criterion0.22259
-
Covariance0.01478
-
r0.34539
-
b (slope, estimate of beta)0.39987
-
a (intercept, estimate of alpha)0.21662
-
Mean Square Error0.04424
-
DF error72.00000
-
t(b)3.12294
-
p(b)0.00129
-
t(a)2.52734
-
p(a)0.00684
-
Lowerbound of 95% confidence interval for beta0.14462
-
Upperbound of 95% confidence interval for beta0.65512
-
Lowerbound of 95% confidence interval for alpha0.04576
-
Upperbound of 95% confidence interval for alpha0.38748
-
Treynor index (mean / b)0.64412
-
Jensen alpha (a)0.21662
- Risk estimates for a one-period unit investment (parametric)
- assuming log normal returns and losses (using central moments from Sharpe statistics)
-
VaR(95%)0.08078
-
Expected Shortfall on VaR0.10488
- assuming Pareto losses only (using partial moments from Sortino statistics)
-
VaR(95%)0.02606
-
Expected Shortfall on VaR0.05347
- ORDER STATISTICS
- Quartiles of return rates
-
Number of observations74.00000
-
Minimum0.87773
-
Quartile 10.98543
-
Median1.01017
-
Quartile 31.05149
-
Maximum1.24362
-
Mean of quarter 10.95606
-
Mean of quarter 20.99963
-
Mean of quarter 31.03268
-
Mean of quarter 41.11535
-
Inter Quartile Range0.06606
-
Number outliers low1.00000
-
Percentage of outliers low0.01351
-
Mean of outliers low0.87773
-
Number of outliers high4.00000
-
Percentage of outliers high0.05405
-
Mean of outliers high1.20873
- Risk estimates for a one-period unit investment (based on Ex
-
Extreme Value Index (moments method)-0.05608
-
VaR(95%) (moments method)0.03765
-
Expected Shortfall (moments method)0.05072
-
Extreme Value Index (regression method)0.27562
-
VaR(95%) (regression method)0.04018
-
Expected Shortfall (regression method)0.06694
- 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)0.78077
-
Compounded annual return (geometric extrapolation)0.33039
-
Calmar ratio (compounded annual return / max draw down)1.68522
-
Compounded annual return / average of 25% largest draw downs2.38530
-
Compounded annual return / Expected Shortfall lognormal3.15013
-
0.00000
-
0.00000
- Analysis based on DAILY values, full history
- RATIO STATISTICS
- Ratio statistics of excess return rates
- Statistics related to Sharpe ratio
-
Mean0.27806
-
SD0.18967
-
Sharpe ratio (Glass type estimate)1.46604
-
Sharpe ratio (Hedges UMVUE)1.46537
-
df1634.00000
-
t3.66230
-
p0.45488
-
Lowerbound of 95% confidence interval for Sharpe Ratio0.67963
-
Upperbound of 95% confidence interval for Sharpe Ratio2.25202
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.67917
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.25156
- Statistics related to Sortino ratio
-
Sortino ratio2.59650
-
Upside Potential Ratio9.86354
-
Upside part of mean1.05627
-
Downside part of mean-0.77822
-
Upside SD0.15741
-
Downside SD0.10709
-
N nonnegative terms586.00000
-
N negative terms1049.00000
- Statistics related to linear regression on benchmark
-
N of observations1635.00000
-
Mean of predictor0.12445
-
Mean of criterion0.27806
-
SD of predictor0.20290
-
SD of criterion0.18967
-
Covariance0.00868
-
r0.22543
-
b (slope, estimate of beta)0.21073
-
a (intercept, estimate of alpha)0.25200
-
Mean Square Error0.03417
-
DF error1633.00000
-
t(b)9.35052
-
p(b)0.35771
-
t(a)3.40102
-
p(a)0.44667
-
Lowerbound of 95% confidence interval for beta0.16653
-
Upperbound of 95% confidence interval for beta0.25494
-
Lowerbound of 95% confidence interval for alpha0.10660
-
Upperbound of 95% confidence interval for alpha0.39706
-
Treynor index (mean / b)1.31948
-
Jensen alpha (a)0.25183
- Ratio statistics of excess log return rates
- Statistics related to Sharpe ratio
-
Mean0.26012
-
SD0.18810
-
Sharpe ratio (Glass type estimate)1.38283
-
Sharpe ratio (Hedges UMVUE)1.38219
-
df1634.00000
-
t3.45443
-
p0.45743
-
Lowerbound of 95% confidence interval for Sharpe Ratio0.59662
-
Upperbound of 95% confidence interval for Sharpe Ratio2.16865
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation0.59618
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.16821
- Statistics related to Sortino ratio
-
Sortino ratio2.40290
-
Upside Potential Ratio9.64489
-
Upside part of mean1.04407
-
Downside part of mean-0.78395
-
Upside SD0.15460
-
Downside SD0.10825
-
N nonnegative terms586.00000
-
N negative terms1049.00000
- Statistics related to linear regression on benchmark
-
N of observations1635.00000
-
Mean of predictor0.10375
-
Mean of criterion0.26012
-
SD of predictor0.20365
-
SD of criterion0.18810
-
Covariance0.00860
-
r0.22456
-
b (slope, estimate of beta)0.20742
-
a (intercept, estimate of alpha)0.23860
-
Mean Square Error0.03362
-
DF error1633.00000
-
t(b)9.31237
-
p(b)0.35825
-
t(a)3.24908
-
p(a)0.44903
-
Lowerbound of 95% confidence interval for beta0.16373
-
Upperbound of 95% confidence interval for beta0.25111
-
Lowerbound of 95% confidence interval for alpha0.09456
-
Upperbound of 95% confidence interval for alpha0.38263
-
Treynor index (mean / b)1.25405
-
Jensen alpha (a)0.23860
- Risk estimates for a one-period unit investment (parametric)
- assuming log normal returns and losses (using central moments from Sharpe statistics)
-
VaR(95%)0.01796
-
Expected Shortfall on VaR0.02271
- assuming Pareto losses only (using partial moments from Sortino statistics)
-
VaR(95%)0.00794
-
Expected Shortfall on VaR0.01565
- ORDER STATISTICS
- Quartiles of return rates
-
Number of observations1635.00000
-
Minimum0.95459
-
Quartile 10.99663
-
Median1.00000
-
Quartile 31.00400
-
Maximum1.08753
-
Mean of quarter 10.98910
-
Mean of quarter 20.99930
-
Mean of quarter 31.00092
-
Mean of quarter 41.01535
-
Inter Quartile Range0.00737
-
Number outliers low93.00000
-
Percentage of outliers low0.05688
-
Mean of outliers low0.97827
-
Number of outliers high150.00000
-
Percentage of outliers high0.09174
-
Mean of outliers high1.02692
- Risk estimates for a one-period unit investment (based on Ex
-
Extreme Value Index (moments method)-0.03140
-
VaR(95%) (moments method)0.00885
-
Expected Shortfall (moments method)0.01206
-
Extreme Value Index (regression method)0.04625
-
VaR(95%) (regression method)0.01043
-
Expected Shortfall (regression method)0.01519
- DRAW DOWN STATISTICS
- Quartiles of draw downs
-
Number of observations55.00000
-
Minimum0.00035
-
Quartile 10.00942
-
Median0.03314
-
Quartile 30.06820
-
Maximum0.19750
-
Mean of quarter 10.00409
-
Mean of quarter 20.02124
-
Mean of quarter 30.05045
-
Mean of quarter 40.10937
-
Inter Quartile Range0.05877
-
Number outliers low0.00000
-
Percentage of outliers low0.00000
-
Mean of outliers low0.00000
-
Number of outliers high3.00000
-
Percentage of outliers high0.05455
-
Mean of outliers high0.17816
- Risk estimates based on draw downs (based on Extreme Value T
-
Extreme Value Index (moments method)0.01102
-
VaR(95%) (moments method)0.11592
-
Expected Shortfall (moments method)0.14685
-
Extreme Value Index (regression method)0.05757
-
VaR(95%) (regression method)0.12607
-
Expected Shortfall (regression method)0.16560
- COMBINED STATISTICS
-
Annualized return (arithmetic extrapolation)0.80666
-
Compounded annual return (geometric extrapolation)0.33379
-
Calmar ratio (compounded annual return / max draw down)1.69003
-
Compounded annual return / average of 25% largest draw downs3.05185
-
Compounded annual return / Expected Shortfall lognormal14.69970
-
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
-
Mean0.11801
-
SD0.10066
-
Sharpe ratio (Glass type estimate)1.17241
-
Sharpe ratio (Hedges UMVUE)1.16564
-
df130.00000
-
t0.82902
-
p0.46374
-
Lowerbound of 95% confidence interval for Sharpe Ratio-1.60523
-
Upperbound of 95% confidence interval for Sharpe Ratio3.94571
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation-1.60979
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation3.94106
- Statistics related to Sortino ratio
-
Sortino ratio1.77697
-
Upside Potential Ratio9.72859
-
Upside part of mean0.64611
-
Downside part of mean-0.52810
-
Upside SD0.07548
-
Downside SD0.06641
-
N nonnegative terms58.00000
-
N negative terms73.00000
- Statistics related to linear regression on benchmark
-
N of observations131.00000
-
Mean of predictor0.24801
-
Mean of criterion0.11801
-
SD of predictor0.13425
-
SD of criterion0.10066
-
Covariance0.00283
-
r0.20910
-
b (slope, estimate of beta)0.15679
-
a (intercept, estimate of alpha)0.07913
-
Mean Square Error0.00976
-
DF error129.00000
-
t(b)2.42861
-
p(b)0.36786
-
t(a)0.56256
-
p(a)0.46852
-
Lowerbound of 95% confidence interval for beta0.02906
-
Upperbound of 95% confidence interval for beta0.28452
-
Lowerbound of 95% confidence interval for alpha-0.19917
-
Upperbound of 95% confidence interval for alpha0.35743
-
Treynor index (mean / b)0.75270
-
Jensen alpha (a)0.07913
- Ratio statistics of excess log return rates
- Statistics related to Sharpe ratio
-
Mean0.11295
-
SD0.10062
-
Sharpe ratio (Glass type estimate)1.12259
-
Sharpe ratio (Hedges UMVUE)1.11610
-
df130.00000
-
t0.79379
-
p0.46527
-
Lowerbound of 95% confidence interval for Sharpe Ratio-1.65463
-
Upperbound of 95% confidence interval for Sharpe Ratio3.89570
-
Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation-1.65902
-
Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation3.89123
- Statistics related to Sortino ratio
-
Sortino ratio1.69095
-
Upside Potential Ratio9.62913
-
Upside part of mean0.64321
-
Downside part of mean-0.53026
-
Upside SD0.07506
-
Downside SD0.06680
-
N nonnegative terms58.00000
-
N negative terms73.00000
- Statistics related to linear regression on benchmark
-
N of observations131.00000
-
Mean of predictor0.23891
-
Mean of criterion0.11295
-
SD of predictor0.13443
-
SD of criterion0.10062
-
Covariance0.00283
-
r0.20919
-
b (slope, estimate of beta)0.15657
-
a (intercept, estimate of alpha)0.07555
-
Mean Square Error0.00976
-
DF error129.00000
-
t(b)2.42968
-
p(b)0.36780
-
t(a)0.53758
-
p(a)0.46991
-
VAR (95 Confidence Intrvl)0.01800
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Lowerbound of 95% confidence interval for beta0.02907
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Upperbound of 95% confidence interval for beta0.28407
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Lowerbound of 95% confidence interval for alpha-0.20250
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Upperbound of 95% confidence interval for alpha0.35359
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Treynor index (mean / b)0.72141
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Jensen alpha (a)0.07555
- Risk estimates for a one-period unit investment (parametric)
- assuming log normal returns and losses (using central moments from Sharpe statistics)
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VaR(95%)0.00975
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Expected Shortfall on VaR0.01231
- assuming Pareto losses only (using partial moments from Sortino statistics)
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VaR(95%)0.00497
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Expected Shortfall on VaR0.00955
- ORDER STATISTICS
- Quartiles of return rates
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Number of observations131.00000
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Minimum0.97725
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Quartile 10.99654
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Median1.00000
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Quartile 31.00408
-
Maximum1.01713
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Mean of quarter 10.99286
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Mean of quarter 20.99937
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Mean of quarter 31.00171
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Mean of quarter 41.00832
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Inter Quartile Range0.00754
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Number outliers low1.00000
-
Percentage of outliers low0.00763
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Mean of outliers low0.97725
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Number of outliers high1.00000
-
Percentage of outliers high0.00763
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Mean of outliers high1.01713
- Risk estimates for a one-period unit investment (based on Ex
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Extreme Value Index (moments method)-0.13090
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VaR(95%) (moments method)0.00719
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Expected Shortfall (moments method)0.00899
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Extreme Value Index (regression method)0.19459
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VaR(95%) (regression method)0.00608
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Expected Shortfall (regression method)0.00829
- DRAW DOWN STATISTICS
- Quartiles of draw downs
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Number of observations5.00000
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Minimum0.00042
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Quartile 10.00178
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Median0.00912
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Quartile 30.03677
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Maximum0.10182
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Mean of quarter 10.00110
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Mean of quarter 20.00912
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Mean of quarter 30.03677
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Mean of quarter 40.10182
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Inter Quartile Range0.03499
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Number outliers low0.00000
-
Percentage of outliers low0.00000
-
Mean of outliers low0.00000
-
Number of outliers high1.00000
-
Percentage of outliers high0.20000
-
Mean of outliers high0.10182
- Risk estimates based on draw downs (based on Extreme Value T
-
Extreme Value Index (moments method)0.00000
-
VaR(95%) (moments method)0.00000
-
Expected Shortfall (moments method)0.00000
-
Extreme Value Index (regression method)0.00000
-
VaR(95%) (regression method)0.00000
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Last 4 Months - Pcnt Negative0.25%
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Expected Shortfall (regression method)0.00000
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Strat Max DD how much worse than SP500 max DD during strat life?-427828000
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Max Equity Drawdown (num days)166
- COMBINED STATISTICS
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Annualized return (arithmetic extrapolation)0.14594
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Compounded annual return (geometric extrapolation)0.15126
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Calmar ratio (compounded annual return / max draw down)1.48553
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Compounded annual return / average of 25% largest draw downs1.48553
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Compounded annual return / Expected Shortfall lognormal12.28580
Strategy Description
The TQQQ Aspire Strategy is based on a statistical computer model whose signals are designed to be efficiently traded utilizing C2’s Auto-Trading 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 Stop-Loss 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 Stop-Loss 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 Stop-Loss 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 Stop-Loss and Profit-Taker sell orders based on mathematical adjustments during the trading day. This is why we recommend Auto-Trading 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 geo-political 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 Stop-Loss calculation. The performance during rising and falling markets has made a substantial improvement during this time-period. 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.1-15-2024 linkv.1-15-2024
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 under-or over-compensated 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 re-scaled downward to make current go-forward 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 per-trade 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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