In this paper, we employ the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of state-level stock returns in the United States based on monthly metrics of oil price uncertainty (OPU) and the broader energy uncertainty index (EUI). Th...
Stock market volatility is of continuing interest to investors, portfolio managers, corporates and policymakers because it directly influences risk assessment, asset pricing and capital allocation decisions. This paper examines the return-generating and volatility process of the Bombay Stock Exchange Sensitive Index (B...
Based on daily returns of the CSI 300 index and monthly macroeconomic variables from January 2005 to December 2025, this paper examines whether low-frequency macroeconomic information provides incremental value for stock market volatility forecasting. A GARCH-MIDAS model is employed to decompose daily return volatility...
Forecasting stock returns and analyzing market volatility are important aspects of financial research, as they help investors and financial analysts make informed decisions while managing investment risk. This study examines the return and volatility behaviour of five major sectors of the Indian economy: Banking, FMCG,...
Volatility is a fundamental characteristic of financial markets and plays a crucial role in investment decision-making, portfolio management, and financial risk assessment. Understanding the behaviour of stock market volatility is particularly important for frontier markets such as the Nepal Stock Exchange (NEPSE), whe...
This research investigates whether changes in monetary policy (proxied by the interest rate) impact the stock market return, volatility, and liquidity across three key indices of the Pakistan Stock Exchange: the KSE100, KSE30, and KMI30. Utilizing monthly data spanning from 2012 through 2025 and employing regression an...
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