Frustration Drives Innovation

There have been two bouts of significant trading performance frustration that has driven major breakthroughs in strategy and math models. First, in August of 2019 we suffered our worst month as the market gyrated up and down and we were caught in vicious whip-saws resulting in a 10.7% loss for the month and a 21.0% intraday peak-to-trough drawdown. When the volatility spiked, we kept on trading as usual leading to these poor numbers. This reality led to a lot of R&D effort in September and a new math model structure launched in early October that made volatility calculations a central component of entry and exit decisions. This worked well using daily interval data (meaning that the market closes, we run the math and make a decision to buy, sell, adjust a stop-loss or do nothing when the market opens tomorrow). The new approach generated a profit every month through January 2020 for a net gain of 12.4%. Then, the epic pandemic bear market of 2020 began. Once again, the volatility-centric models worked well only losing 2.1% in February and March versus 19.9% loss in the SP500 during these two months. We started the month of April quite pleased with our September 2019 R&D efforts based on these numbers and the decisive beat of the market indexes.

Then, the historic V-shape recovery began complete with high volatility which shut-down our daily models as it did in late February and March, so we have missed the 24.4% market gain in April through July. The missed opportunity was caused by the high volatility and the slow-roll of daily data to adjust.

As we covered last week, it is important to trade in multiple time-frames so we performed portfolio analysis to blend in a new model based on 15-min data that we had been working on for a number of months which updates data more quickly and has less sensitive volatility settings. This model worked well to both avoid the large sell-off and quickly capture the gains available starting in April (theoretically with retrospective analysis).

The other big frustration we’ve had is that we traded the volatility ETFs (UVXY and TVIX) extensively in 2018-19 up until September 2019 when we stopped in the aftermath of the August 2019 frustrations. These symbols likely would have performed well during the big sell-off as they were up over 950% during a five-week period starting in late February. (To greater clarity, 950% is not a typo – UVXY closed at 10.57 on February 12 and at 111.02 on March 18.) So, we have developed both daily and 15-min interval UVXY models to serve as a hedge for our predominate TQQQ long trades and hopefully generate profits during the next sell-off (which, regardless of the global central bankers, another sell-off will eventually emerge).

For transparency, we both have full-time corporate positions so we’ll employ professional traders and continue to work on greater automation to fully and consistently execute the 15-min models. So far, our execution of these 15-min models has been sporadic. We execute daily models overnight, so there is no complication with catching these trades; although the performance is not as strong as the 15-min models.

Forte Strategy Update

We executed eleven trades last week in our Forte (ETF) Strategy using the Nasdaq 3X leveraged ETF (TQQQ) and the 1.5X Leveraged VIX index ETF (UVXY) for a net gain of 1.0% compared to a loss of 0.3% by the S&P 500. Our YTD net results so far are a 0.6% loss compared to a 0.5% YTD loss for the S&P 500. Our YTD max drawdown is 9.5% vs 33.9% for the market and the correlation between the two data sets is 0.155 – so little to no correlation.

Forte Futures Update

In May, we made the decision to start a second strategy, Forte Futures, largely in an effort to diversify approaches. As mentioned above and in previous blogs, strategic use of multiple timeframes and symbols when trading can present more opportunities to profit especially given the unpredictable conditions in nearly every market. Like a pool shark studies the billiard table, playing out multiple scenarios in her/his head prior to making the shot, we study 2-, 5-, 15- and 60-minute charts across several futures contracts (both mini and micro) to find the highest probability trades. The result has been a 5.7% return since May inception and 4.1% in July with a 4.6% drawdown. Although we’re confident that we can sustain and even further improve the performance, it’s currently a manual process, so we continue to research and explore ways to automate. Stay tuned.

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