Discussion Points:
- How decades of government tech and AI experience led to a unique alpha-seeking strategy.
- How the use of curated datasets outperform brute-force modeling.
- How to avoid AI hallucinations and contaminated training data.
Discussion Points:
- How to leverage big data and machine learning to identify market turning points early.
- Emphasis on momentum and trend analysis across different asset groups.
- How high-conviction signals enable quicker, smarter decisions for traders and portfolio managers.
Discussion Points:
- How alternative data such as website visits, search trends, and app usage could be used to seek to predict company performance ahead of Wall Street analysts
- How machine learning turns this data into real trading signals, and
- How to construct portfolios - long, hedged, and market-neutral - based on these insights.
September was tough for the stock market, as often happens. Now that we’re in October, can we learn anything from the ‘Halloween indicator’, aka ‘Sell in May and go away’? Another way to ask the same question - are we witnessing seasonal effects? And if so, do other seasonal phenomena exist? The "Quantpedia.com Explains" trading strategy video series continues with Seasonal/Calendar...
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If I said, “Trend following trading strategy,” which single asset class would you assume that I am talking about? When I learned trend following, I was told, “Equities”, or separately, “Most CTA’s are trend followers” (i.e., “Futures”). Can both be true at the same time? Or, alternately at different times within the same strategy? What about other asset classes too? Enter the concept...
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Have you ever watched a stock’s movements breathlessly during the trading day, from market open to close, only to realize that bigger movements sometimes happen overnight? Have you ever wondered what happens when you combine the effects of market sentiment with the overnight anomaly? Why would you even wonder such a thing? A recent Seeking Alpha article called this phenomenon...
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“The trend is your friend” is a memorable Martin Zweig stock market quote. More instructive aphorisms might be: "The trend is your friend until it bends." (thanks to Investopedia: https://www.investopedia.com/terms/p/pattern.asp), or: “The trend is your friend, until the end when it bends.” (thanks to How The Market Works: https://education.howthemarketworks.com/the-trend-is-your-friend/). But what exactly is a trend, and how is it related...
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In the introduction to the Win/Loss Analysis in FinTech interview series, “It’s Not What You Think!”, we launched a discussion about topics including what is win/loss analysis, who it is for, why FinTech is different, and how to run an effective analysis program in that market. In this interview, Richard Case and I talk about blind interviews, including issues around…
"Whoa! What happened to prices overnight?" -> Have you ever woken up to a shocking market move feeling this way? Did you ever wonder: - if there's really more price movement overnight than during the trading day? - how this phenomenon plays out in continuous markets (like crypto) vs. the equity markets? - what strategies can be used to do...
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In the introduction to the Win/Loss Analysis in FinTech interview series, “It’s Not What You Think!“, we launched a discussion about topics including what is win/loss analysis, who it is for, why FinTech is different, and how to run an effective analysis program in that market. In this interview, Richard Case and I talk about data-driven win/loss analysis, ROI issues,…