Modeling and Estimating Long-Term Volatility of Stock Markets in Romania, Poland, Greece, and USA

Modeling and Estimating Long-Term Volatility of Stock Markets in Romania, Poland, Greece, and USA

Copyright: © 2019 |Pages: 17
DOI: 10.4018/978-1-5225-9269-3.ch009

Abstract

The main purpose of this chapter is to examine long-term volatility of stock markets in Romania, Poland, Greece, and USA using asymmetric GARCH class models. The selected financial databases include daily log-returns of sample stock market major indices during the period from January 2000 until January 2014. The empirical results provide an additional contribution to existing literature regarding volatility estimations and international portfolio investment strategies. Moreover, this book chapter provides a useful empirical approach for a better understanding of volatility behavioral patterns, similar reaction to external shocks, international contagion, the impact of new information on the market and risk management optimal strategies, investor risk aversion and international portfolio diversification benefits.
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Approaches To Literature

Financial literature on capital market volatility is extremely vast. The empirical results of each research have provided certain directions for investors, decision makers and financial researchers. As additional empirical contribution, each research study regarding this issue gives equal chance to learn and understand the unforeseeable behavior of stock markets. According to Engle (1982) traditional econometric models assume a constant one-period forecast variance and therefore in order to generalize this implausible assumption, it was implemented a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes.

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