ASSET PRICING IN EMERGING MARKETS AN EMPIRICAL INVESTIGATION

Abstract

Emerging financial markets present an important yet challenging context for testing the validity of traditional asset pricing theories. While models such as the Capital Asset Pricing Model (CAPM), the Fama– French Three-Factor Model, and the Arbitrage Pricing Theory (APT) have been widely examined in developed and mature markets, their empirical performance in emerging markets remains comparatively underexplored. These markets differ fundamentally in structure and behavior, exhibiting higher volatility, liquidity constraints, segmented capital flows, and heightened exposure to macroeconomic and political risk. Such characteristics raise questions about whether standard asset pricing frameworks can adequately capture return dynamics in these environments. This study investigates the applicability and performance of mainstream asset pricing models across selected emerging market economies using panel data and crosssectional regression approaches. By incorporating both market-based risk factors and macroeconomic variables, the analysis examines how country-specific characteristics influence asset returns and whether multifactor frameworks outperform single-factor benchmarks. Particular attention is given to inflation, exchange rate movements, interest rate fluctuations, and institutional factors that uniquely shape the risk–return landscape in emerging markets. Empirical findings reveal that while traditional models retain some explanatory power, they often fail to fully account for return variation in these markets, especially during periods of heightened uncertainty or structural change. Multi-factor and macro factor augmentations yield improved performance, suggesting the need for context-specific adaptations. The study contributes to ongoing debates on asset pricing theory by highlighting the limitations of universal model application and advocating for tailored approaches that reflect the heterogeneous and evolving nature of emerging economies. These results carry implications for investors, policymakers, and academics seeking to understand asset behavior in high-growth but complex financial environments.