Nasdaq TQQQ Quant Fund
(138858521)
Subscription terms. Subscriptions to this system cost $159.00 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.
Trend-following
Tries to take advantage of long, medium or short-term moves that seem to play out in various markets. Typically, trend-following analysis is backward looking; that is, it attempts to recognize and profit from already-established trends.Short-term Reversal
Exploits the tendency of stocks with strong gains and stocks with strong losses to reverse in a short-term time frame (up to one month).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 Cumulative Rate of Return is calculated
= (Ending_equity - Starting_equity) / Starting_equity
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 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022 | (4.6%) | - | - | - | - | - | - | - | - | - | - | - | (4.6%) |
| 2023 | - | - | - | - | - | - | - | - | - | - | - | - | 0.0 |
| 2024 | - | - | - | - | 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 | $50,000 | |
| Buy Power | $47,886 | |
| Cash | $1 | |
| Equity | $1 | |
| Cumulative $ | ($2,113) | |
| Total System Equity | $47,886 | |
| Margined | $1 | |
| Open P/L | $0 | |
| Data has been delayed by 168 hours for non-subscribers | ||
System developer has asked us to delay this information by 168 hours.
Trading Record
symbol.
Statistics
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Strategy began1/6/2022
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Suggested Minimum Cap$50,000
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Strategy Age (days)838.64
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Age28 months ago
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What it tradesStocks
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# Trades1
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# Profitable0
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% Profitablen/a
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Avg trade duration2.1 days
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Max peak-to-valley drawdown7.16%
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drawdown periodJan 12, 2022 - Jan 13, 2022
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Cumul. Return-4.6%
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Avg win$0.00
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Avg loss$2,113
- Model Account Values (Raw)
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Cash$47,886
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Margin Used$0
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Buying Power$47,886
- Ratios
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W:L ratio0.00:1
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Sharpe Ratio-0.97
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Sortino Ratio-1
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Calmar Ratio-2.087
- CORRELATION STATISTICS
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Return of Strat Pcnt - Return of SP500 Pcnt (cumu)-3.91%
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Correlation to SP5000.02290
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Return Percent SP500 (cumu) during strategy life8.60%
- Return Statistics
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Ann Return (w trading costs)-71.8%
- Slump
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Current Slump as Pcnt Equity7.70%
- Return Statistics
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Return Pcnt (Compound or Annual, age-based, NFA compliant)-0.046%
- Instruments
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Percent Trades Optionsn/a
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Percent Trades Futuresn/a
- Slump
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Current Slump, time of slump as pcnt of strategy life0.99%
- Instruments
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Percent Trades Stocks1.00%
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Short Options - Percent Covered100.00%
- Return Statistics
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Return Pcnt Since TOS Statusn/a
- Instruments
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Percent Trades Forexn/a
- Return Statistics
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Ann Return (Compnd, No Fees)-1.8%
- Risk of Ruin (Monte-Carlo)
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Chance of 10% account lossn/a
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Chance of 20% account lossn/a
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Chance of 30% account lossn/a
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Chance of 40% account lossn/a
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Chance of 60% account loss (Monte Carlo)n/a
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Chance of 70% account loss (Monte Carlo)n/a
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Chance of 80% account loss (Monte Carlo)n/a
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Chance of 90% account loss (Monte Carlo)n/a
- Automation
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Percentage Signals Automatedn/a
- Risk of Ruin (Monte-Carlo)
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Chance of 50% account lossn/a
- Popularity
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Popularity (Today)843
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Popularity (Last 6 weeks)849
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Popularity (7 days, Percentile 1000 scale)913
- Trading Style
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Any stock shorts? 0/10
- Trades-Own-System Certification
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Trades Own System?-
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TOS percentn/a
- Win / Loss
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Avg Win$0
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Avg Loss$2,113
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Sum Trade PL (losers)$2,113.000
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# Winners0
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Num Months Winners0
- Age
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Num Months filled monthly returns table28
- Win / Loss
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Sum Trade PL (winners)$0.000
- Dividends
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Dividends Received in Model Acct0
- Win / Loss
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# Losers1
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% Winnersn/a
- Frequency
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Avg Position Time (mins)3071.57
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Avg Position Time (hrs)51.19
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Avg Trade Length2.1 days
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Last Trade Ago832
- Leverage
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Daily leverage (average)2.79
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Daily leverage (max)2.82
- Regression
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Alpha-0.01
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Beta0.00
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Treynor Index-2.43
- Maximum Adverse Excursion (MAE)
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MAE:Equity, average, all trades0.04
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MAE:Equity, losing trades only, 95th Percentile Value for this strat-
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MAE:Equity, win trades only, 95th Percentile Value for this strat-
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MAE:PL (avg, winning trades)-
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MAE:PL - worst single value for strategy-
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MAE:PL (avg, losing trades)-
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MAE:PL (avg, all trades)-1.01
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Avg(MAE) / Avg(PL) - All trades-1.014
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MAE:Equity, 95th Percentile Value for this strat0.04
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MAE:Equity, average, winning trades-
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MAE:Equity, average, losing trades0.04
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Avg(MAE) / Avg(PL) - Winning trades-
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Avg(MAE) / Avg(PL) - Losing trades-1.014
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Hold-and-Hope Ratio-0.987
- Analysis based on DAILY values, full history
- RATIO STATISTICS
- Ratio statistics of excess return rates
- Statistics related to linear regression on benchmark
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a (intercept, estimate of alpha)-0.15900
- Analysis based on DAILY values, last 6 months only
- Ratio statistics of excess log return rates
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VAR (95 Confidence Intrvl)0.01000
- DRAW DOWN STATISTICS
- Risk estimates based on draw downs (based on Extreme Value T
- assuming Pareto losses only (using partial moments from Sortino statistics)
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Strat Max DD how much worse than SP500 max DD during strat life?-39386300
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Max Equity Drawdown (num days)1
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Last 4 Months - Pcnt Negativen/a
Strategy Description
What this strategy does:
This strategy uses a proprietary combination of statistics, algebra, code, trends and custom-built technical indicators to identify and enter into trend-following and mean-reversion trades. This is not a strategy that you will find in any technical analysis library and is the results of hundreds of hours of development time.
What this strategy doesn’t do:
This strategy does not use martingale, dollar cost averaging, or any other gambling technique. It isn’t a black-box AI that makes decisions that can’t be explained by a human or math. It also doesn’t predict the future (no strategy actually does this). The performance of the strategy will depend on the price action of the underlying asset, and how similar that behavior is to the past several years of behavior. It does not currently use any leverage (other the leverage of the underlying ETF asset). However, when more live trading history is available, I may decide to use a small amount of leverage to increase returns.
Can I trade leveraged ETFs if I’m in Europe?
There are some articles about this online. I would start with this one: https://europoor.com/how-to-buy-leveraged-etfs-from-europe/
When has it performed good/bad in back-testing?
In back-testing, the strategy has historically performed well during times the market is trending, and during short/medium-term market pullbacks. This has been the vast majority of the behavior of TQQQ over the past decade. It has also avoided realizing the drawdown of some black swan events. This strategy has performed the poorest when the market is ranging sideways and/or is unusually choppy. During these times, the strategy may under-perform buy and hold because it repeatedly looks like a trend is forming that reverses on the position. Since there is no way to identify if that trend formation will turn into a reversal until it is over, this ends up being a cost of doing business. The mean reversion part of the strategy does better in this environment.
Should I trade this?
Consider talking to a financial adviser. Trading leveraged ETFs is risky and can be volatile. TQQQ makes regular swings up and down to the tune of 20%+. Do not trade with money you cannot afford to lose. This is a high risk/reward strategy. If you cannot handle this type of volatility, or cannot handle a pullback to a 200 day moving average, then you should consider a strategy that does not trade leveraged ETFs.
Will you change the strategy because it has some bad trades?
It is unlikely. The strategy entry and exit criteria has been optimized using a decade of historical data. Over-fitting the model to one-off events can lead to the model performing worse in the long run. In the event there is a change that makes the model perform better over a decade of historical data on multiple assets, I would consider implementing it.
Should I enter into existing positions?
This is up to you. In general, I’ve found that positions are more likely to reverse at highs than at lows.
Should I set my own stop?
This is up to you. The current entry/exit criteria is optimized for this highest strategy return over a decade of historical data. Additional stop levels have made the strategy perform significantly worse in backtesting. If you want to place your own stops, be aware that it could make the strategy perform worse than the model.
What is the minimum account size needed to follow this strategy?
The Collective2 recommended account size is generated automatically. A minimum account size of $35k is likely necessary. The algorithm could place more trades in a week than is allowed by the FINRA pattern day trader (PDT) rule. The PDT rule says that you must have minimum $25k equity in your account if your account makes more than 4 trades in a week. $35k allows you to have a buffer over that in case you have the misfortune of joining during a drawdown. You can read more about the PDT rule here: https://www.finra.org/investors/learn-to-invest/advanced-investing/day-trading-margin-requirements-know-rules
This just bought a dip and it is still dipping! Are you crazy?!?
The mean reversion part of this algorithm will buy dips at a level that it has determined to be statistically probable to mean revert within 3-5 days. They can dip further before they revert, or they could not revert. It leads to some volatility/drawdowns at times. However, this part of the strategy has a 72%+ win rate over the past 3 years of historical data, and significantly increases the overall return of the strategy over the past decade of historical testing. Watching these trades can sometimes be psychologically difficult (me included!). However, I will not interfere with the model unless there is overwhelming consensus that we are in a black swan event.
Why aren’t you trying to sell me on this?!?
If I did not believe in this strategy, I would not be trading it. I designed it for my level of risk tolerance seeking maximum gains while attempting to avoid the full drawdowns that are realized by the underlying asset. With that said, I want anyone following the strategy to have a basic understanding of what it does, and the risks involved, so they can make the best decision to follow strategies within their comfort level.
Disclaimer: Nothing in this description is to be treated as financial advice. Before investing in any strategy, you should consider talking to a financial adviser.
Latest Activity
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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Suggested Minimum Capital
This is our estimate of the minimum amount of capital to follow a strategy, assuming you use the smallest reasonable AutoTrade Scaling % for the strategy.