Emerging market quant strategies face unique data challenges — but also unique alpha opportunities. We examine how to build robust quantitative models for Indian and ASEAN markets.
Quantitative investing in emerging markets is both harder and more rewarding than in developed markets. The data challenges are significant: shorter time series, less frequent reporting, more frequent corporate actions, and regulatory environments that change without much notice. But these same challenges create alpha opportunities for investors who can overcome them.
India, in particular, offers compelling opportunities for quantitative strategies. The market is deep — over $3 trillion in market capitalisation across listed equities — but less efficient than developed markets. The institutional investor base is growing, creating predictable flow patterns. The regulatory environment is improving, with increasing disclosure requirements and market infrastructure investment.
Building robust models
The key to successful quant strategies in emerging markets is robustness. Models built on noisy data with short histories are prone to overfitting. At IIG, we use a combination of fundamental and quantitative approaches, using quant models to identify opportunities and fundamental research to validate them. The combination has produced consistent returns across market cycles.
The best quant strategies in emerging markets are not purely quantitative — they are fundamentally-informed, quantitatively-executed, and disciplined in their risk management.