Our Algos Trades Their Algos
We oversee an algorithm that reduces drawdowns in AI-enabled equity ETFs. We track institutional money flows, market sentiment, advanced volatility indicators, and keep a close on the economic calendar.
Algorithmic trading systems – whether they are executed by computer programs or used as decision support tools by disciplined individuals – have been shown to significantly outperform traditional methods of investing. (1,2) Take, for example, that algorithmic trading programs do not hold onto losing trades nor do they hold winning trades until they move adversely. When trading volatile markets, intra-day, computers have a decided advantage in response time. But in the realm of algorithmic investing and longer horizons, it will be knowledge-based investors whose decisions are supported by machine algorithms that possess the key to superior returns. (3)
The “Wisdom of the Crowds”
Insights for Machine-based Alpha
⋅ Target the highest performing and liquid AI-enabled equity ETFs (AI-ETFs)
⋅ Screen for hidden information in options volume, gamma, and implied volatility in major index ETFs with highest correlation to the AI-ETF trading instrument
⋅ Trade predictive analytics, sentiment, and event risk against an auction market backdrop
Insights for Human Decision Making
⋅ Eat a whole food, plant-based diet
⋅ Exercise daily
⋅ Meditate daily
- Cartea, Álvaro and Jaimungal, Sebastian and Ricci, Jason, Buy Low Sell High: A High Frequency Trading Perspective (April 15, 2014). SIAM Journal of Financial Mathematics.
- Dietvorst, Berkeley J. and Simmons, Joseph P. and Massey, Cade, Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err (July 6, 2014). Journal of Experimental Psychology.
- Lin, Tom C. W., The New Investor. 60 UCLA Law Review 678 (2013); 60 UCLA Law Review 678 (2013); Temple University Legal Studies Research Paper No. 2013-45.