In the U.S. equity market, European financial markets, and major Asian capital markets, algorithmic trading accounts for about 60-75 percent of the overall trading volume. Algo trading has been on the rise in the U.S. equity markets since the turn of the century but seems to have plateaued around 70-80 percent in the last 5 to 10 years.

In this episode of the Asia Tech Podcast, we spoke with Nirav Shah, Founding Partner of Versor Investments, about systematic investing and how technology is reshaping the financial landscape. Nirav explained how quantitative trading models use data to identify patterns and opportunities in global markets, allowing for trades at scale across various asset classes.

Some of the topics that Nirav covered in detail include:

• Quantitative models operate at scale, meaning they can apply algorithms across various asset classes and geographies, from equity markets to commodities, currencies, and futures. This ability to scale is a key advantage for systematic firms.
• While systematic investing might seem purely data-driven, Shah highlighted that every algorithm starts with economic intuition. Before a model is built, there needs to be a reasoned hypothesis—an understanding of why a specific signal should correlate with future market behavior.
• Nirav believes that Versor’s edge lies in its use of alternative data—non-traditional datasets that aren’t created specifically for finance but can be harnessed to generate investment insights. This alternative data include news sentiment, social media sentiment, regulatory filings, credit card data, and app or web traffic.
• Even with advanced algorithms, there are times when human intervention can occur. Nirav explained that Versor typically lets models run without interference. However, in rare situations their investment committee steps in to adjust strategies.
• While alternative data provides a significant advantage, Nirav points out that it is operationally challenging to work with. Quant firms like Versor have developed a unique ability to handle large datasets, process information quickly, and connect with multiple data vendors.
• Nirav is optimistic about the future of systematic investing. He believes that we are at the cusp of an AI revolution, where technology will touch every part of the investment process. The increasing availability of alternative datasets, combined with the rapid advancement of AI tools, is creating a new landscape for investment firms.