The riskiest part of this strategy would definitely be UVXY, which is 1.5x the VIX. Replacing it with SQQQ (3x inverse Nasdaq 100) would reduce the volatility but also reduce returns.
Above the 200-day moving average (bull market), TQQQ (3x Nasdaq-100) is generally a good idea, but be prepared for the value to fluctuate 3.5x compared with the S&P. For example, if the S&P is down 1.5%, TQQQ would be down more than 5%. If that scares you, then you could switch to QLD (2x Nasdaq-100).
Below the 200-day moving average (bear market), the risk would of course be exactly the same as the S&P since the strategy holds SPY.
Yeah, I actually really liked the TQQQ element, seems very simple yet completely logical - buy when market is trending up and sell when overbought. I feel like often enough simple works best (unless you’re a quant).
But as you’ve said, VIX was the bet I was curious about, might consider as you’ve suggested and simply short the market rather than long VIX to reduce beta.
Thanks for the quick response - super informative! Will be looking out for your future posts :)
Thanks for the super article. Couple of questions if I may. Did you use the Simple or Exponential 200 DMA for the S&P 500? Are you using the close level on the S&P 500 (rather than intraday/in session) for the 200 DMA signal? Did you consider tolerance thresholds around the 200 DSMA (e.g. + or - 3% or 4%) to reduce whipsaw trading into and out of TQQQ and SPY? Sorry to ask so many questions, and thanks in advance for your answers. Really enjoyed and appreciated your article.
- Tolerance thresholds are not included in this algo for simplicity's sake, but they can be used.
On tolerance thresholds specifically, there are trade-offs to consider.
On the upside, adding a buffer zone (e.g. +/- 3-4% around the 200 DMA) can reduce whipsaw trades during periods when price is oscillating around the moving average. This means fewer false signals, lower transaction costs, and less slippage from unnecessary round trips. It can also improve signal quality by filtering out noise and only acting on more decisive trend changes.
On the downside, tolerance bands introduce a lag. You're effectively waiting for a larger move before acting, which means delayed entries and exits. In a sharp selloff or rally, that extra 3-4% buffer could erode returns. There's also the issue of parameter sensitivity: the "right" threshold isn't static and what works well in one regime may underperform in another.
Not investment advice, of course. Do your own research.
Thank you for an excellent piece. Thinking in comparison with Michael Gayed's Leverage for the Long Run UPRO 200 DSMA SPY/S&P 500 Leverage Rotation Strategy, why chose SPY as the risk off asset, and not, say, T-Bills or cash (or, for that matter, Intermediate or Long duration Treasuries, or even those and some Gold)? Did SPY give better CAGR and/or Sharpe/Sortino overall? Thanks again for your thought provoking piece.
You're welcome. Yes, SPY produced a better CAGR overall. Snap-back rallies during bear markets can be vicious, and some of the strongest up-days in history have occurred in the midst of drawdowns. By rotating into SPY rather than cash or Treasuries, the strategy captures a portion of that upside without taking on the full downside of leveraged positions.
The "Triple Accelerator" algorithm is an innovative strategy that adjusts investments based on market trends, but it's important to be mindful of the risks involved, including potential drawdowns. While the results are impressive, careful consideration and understanding are key.
Is there anything you’d add to this strategy to improve its accuracy?
It's a decent but volatile strategy as it is.
The riskiest part of this strategy would definitely be UVXY, which is 1.5x the VIX. Replacing it with SQQQ (3x inverse Nasdaq 100) would reduce the volatility but also reduce returns.
Above the 200-day moving average (bull market), TQQQ (3x Nasdaq-100) is generally a good idea, but be prepared for the value to fluctuate 3.5x compared with the S&P. For example, if the S&P is down 1.5%, TQQQ would be down more than 5%. If that scares you, then you could switch to QLD (2x Nasdaq-100).
Below the 200-day moving average (bear market), the risk would of course be exactly the same as the S&P since the strategy holds SPY.
Yeah, I actually really liked the TQQQ element, seems very simple yet completely logical - buy when market is trending up and sell when overbought. I feel like often enough simple works best (unless you’re a quant).
But as you’ve said, VIX was the bet I was curious about, might consider as you’ve suggested and simply short the market rather than long VIX to reduce beta.
Thanks for the quick response - super informative! Will be looking out for your future posts :)
You're welcome! Glad you liked it.
Thanks for the super article. Couple of questions if I may. Did you use the Simple or Exponential 200 DMA for the S&P 500? Are you using the close level on the S&P 500 (rather than intraday/in session) for the 200 DMA signal? Did you consider tolerance thresholds around the 200 DSMA (e.g. + or - 3% or 4%) to reduce whipsaw trading into and out of TQQQ and SPY? Sorry to ask so many questions, and thanks in advance for your answers. Really enjoyed and appreciated your article.
Glad you enjoyed the article.
Happy to answer your questions:
- Simple 200 DMA for the S&P
- Yes, close level on the S&P
- Tolerance thresholds are not included in this algo for simplicity's sake, but they can be used.
On tolerance thresholds specifically, there are trade-offs to consider.
On the upside, adding a buffer zone (e.g. +/- 3-4% around the 200 DMA) can reduce whipsaw trades during periods when price is oscillating around the moving average. This means fewer false signals, lower transaction costs, and less slippage from unnecessary round trips. It can also improve signal quality by filtering out noise and only acting on more decisive trend changes.
On the downside, tolerance bands introduce a lag. You're effectively waiting for a larger move before acting, which means delayed entries and exits. In a sharp selloff or rally, that extra 3-4% buffer could erode returns. There's also the issue of parameter sensitivity: the "right" threshold isn't static and what works well in one regime may underperform in another.
Not investment advice, of course. Do your own research.
Thank you for an excellent piece. Thinking in comparison with Michael Gayed's Leverage for the Long Run UPRO 200 DSMA SPY/S&P 500 Leverage Rotation Strategy, why chose SPY as the risk off asset, and not, say, T-Bills or cash (or, for that matter, Intermediate or Long duration Treasuries, or even those and some Gold)? Did SPY give better CAGR and/or Sharpe/Sortino overall? Thanks again for your thought provoking piece.
You're welcome. Yes, SPY produced a better CAGR overall. Snap-back rallies during bear markets can be vicious, and some of the strongest up-days in history have occurred in the midst of drawdowns. By rotating into SPY rather than cash or Treasuries, the strategy captures a portion of that upside without taking on the full downside of leveraged positions.
The "Triple Accelerator" algorithm is an innovative strategy that adjusts investments based on market trends, but it's important to be mindful of the risks involved, including potential drawdowns. While the results are impressive, careful consideration and understanding are key.
That's correct