Estimation of the idiosyncratic and systemic volatilities of asset returns using factor stochastic volatility model - Dela Cruz, Melissa E. (Quezon City University of the Philippines, 2023)
ABSTRACT

Volatilities are fluctuations of asset prices over time that signifies risks in the market. Accurately estimating volatilities help portfolio managers mitigate market risks especially for highly volatile assets such as shares of publicly traded stocks. Covariation among the stocks is commonly observed in practice. In this study, stock price return volatility of four conglomerates in the Philippines (AC, DMC, JGS and SMPH) will be decomposed into systemic and idiosyncratic volatilities to identify the volatilities that are common to all companies and determine the volatilities experienced only by a particular company. The decomposition will use the factor stochastic volatility model, estimated using Bayesian MCMC, to take into consideration the existence of a latent factor that drives the systemic volatilities in the financial market. The two factor stochastic volatility models are considered: (i) extension of the single-equation stochastic volatility and (ii) factor stochastic volatility model applied to a portfolio of four publicly traded holding companies in the Philippines. The results show that systematic and idiosyncratic volatilities can be decomposed where high fluctuations of the systemic volatility coincide with documented crises periods. The extracted systemic and idiosyncratic volatilities ca be used to fine tune value at risk (VaR) analyses in portfolio optimization.
Keywords: Factor stochastic volatility model