The "profitability" question for high frequency trading (HFT) in India was decided at the end of fiscal year 2025. Although the rest of the world was debating whether Indian equities were overvalued, the high frequency trading firms (algorithms, etc.) operating in Indian markets made the most money they ever have, as reported in new filings. The best algorithms that executed trades the fastest during times of increasing volatility and higher liquidity generated the highest returns on investment for the year.
As seen in the graph below, the profit after tax (PAT) for the top five players shows a tremendous increase in profitability. Hudson River Trading (HRT) India had the largest increase in PAT, tripling their profits from FY24's 8.6 billion rupees to FY25's 22.1 billion rupees (approximately $240 million USD).
Citadel Securities (the global HFT giant) posted a second place finish, increasing their profits from FY24's 14.6 billion rupees to FY25's 20.6 billion rupees (approximately $220 million USD). Graviton (a well established Indian HFT firm) increased their profits from FY24's 10.1 billion rupees to FY25's 11.8 billion rupees (approximately $130 million USD). AlphaGrep also experienced a large increase in profits, jumping from FY24's 2.7 billion rupees to FY25's 4.7 billion rupees (approximately $50 million USD).
Optiver India had the greatest swing in profits. Optiver India lost approximately 600 million rupees in FY24 but earned 390 million rupees in FY25. These numbers show how sensitive the profitability of HFT firms are. A small tweak to a parameter or a change in strategy could potentially change the profitability of a firm by tens of millions of dollars per day.
The fact that all of these firms experienced increases in profitability is evidence of a structural change in Indian markets. There has been explosive growth in retail volumes in derivative products and a marked increase in liquidity in Indian markets. As the Indian exchanges continue to expand, it appears the "battle for milliseconds" is becoming a "battle for billions."
Source: Data via Tofler, Bloomberg, and Ministry of Corporate Affairs.