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I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

The purpose of this study is to investigate how changes in the firm's information disclosure practices impact the way investors process macroeconomic news. Specifically, the authors examine the role of derivative instruments and hedging activities disclosure, as required by SFAS 133, in shaping invertors response to good and bad interest rate news. In addition, the authors examine whether the effect of SFAS 133 on investors' response to good and bad interest rate news varies between firms with higher and lower earnings volatility.

This study uses data on all US public firms over the period from 1990 to 2019. The authors mainly apply multivariate regression and a difference-in-difference approach to test their hypotheses.

The results show a significant decrease in the asymmetry of responses to good and bad interest rate news for users of interest rate derivatives following the adoption of SFAS 133. However, in contrast to this finding, the authors also find that the adoption of SFAS 133 has no impact on the asymmetry of responses to good and bad interest rate news for nonusers of interest rate derivatives. Consistent with the ambiguity theory, the finding suggests that SFAS 133 indeed decreases investors’ uncertainty (ambiguity) about the cash flow implications of changes in the interest rate. The authors also find that the decrease in the asymmetry of response to good and bad interest rate news after the adoption of SFAS 133 is greater for users of interest rate derivatives with higher than lower earnings volatility. This implies that derivatives and hedging activities disclosure, as required by SFAS 133, are more important for firms with higher than lower earnings volatility. The finding is consistent with the idea that investors demand more accounting information when underlying earnings volatility is higher. In a set of additional analyses, the authors find that the effect of SFAS 133 on investors' response to good and bad interest rate news varies depending on the level of analyst coverage and interest rate exposure. Specifically, the authors find that the decrease in the asymmetry of response to good and bad interest rate news after the adoption of SFAS 133 is greater for users of interest rate derivatives with higher interest rate exposure and lower analyst coverage.

The findings of this study help market participants including regulators and standard setters to understand the impact of mandatory disclosure practices on investors' reaction to macroeconomic news. Moreover, the findings of the study help managers to understand the influence firm-specific characteristics (e.g. earnings volatility, analyst coverage and interest rates exposure) on the effectiveness of mandatory derivative instruments and hedging activities disclosure.

To the best of the authors' knowledge, this is the first paper to explore how firm-specific information environment affects the way investors process macroeconomic news. This study contributes to the literature by providing the empirical evidence that derivatives instruments and hedging activities, as required by SFAS 133, affect investors' response to good and bad interest rate news. In doing so, the results provide insights about how firm-specific information environment affects the way investors process macroeconomic news. This study shows that the cross-sectional variation in earnings volatility, analysts’ coverage and interest rate exposure affects the impact of SFAS 133 on investors' response to good and bad interest rate news. The findings are not only the notable addition to the existing literature on the topic but also can aid to market participants including policy makers, regulators, standard setters and managers to understand the influence of firm-specific characteristics on the effectiveness of mandatory derivative instruments and hedging activities disclosure. Finally, the findings contribute to the general debate about the effectiveness of SFAS 133 by showing that the adoption of SFAS 133 indeed decreases information ambiguity.

The authors aim to understand the driving forces behind the idiosyncratic volatility puzzle in the Korean stock market. The authors study the Korean stock market because previous works report a strong idiosyncratic volatility puzzle in Korea, and the market for the exchange-traded funds (ETFs) including low volatility ETFs has experienced drastic growth in Korea.

Using common stocks listed either on KOSPI or KOSDAQ over the period 1997–2016, the authors estimate idiosyncratic volatility using the Fama–French three-factor model. In addition, based on prior literature, the authors use turnover as a proxy for overvaluation. The authors then study the role of turnover in understanding the idiosyncratic volatility puzzle in Korea.

The authors find that turnover is highly associated with idiosyncratic volatility. Turnover is extremely large among firms with high idiosyncratic volatility and the puzzle disappears after we control for turnover, meaning that turnover subsumes the explanatory power of idiosyncratic volatility for equity returns. The authors also find underperformance of stocks with high turnover and high idiosyncratic volatility exclusively during earnings announcement periods. Overall, our finding implies that the puzzle arises since high idiosyncratic volatility stocks due to high turnover are overvalued and experience correction afterwards.

Literature has suggested explanations based on lottery preferences of investors and market frictions behind the idiosyncratic volatility puzzle. What makes our study distinct from previous work is that we find the role of turnover in understanding the idiosyncratic volatility puzzle using turnover measure as a proxy for overvaluation in the Korean stock market.

We investigate the link between firm volatility and risk-taking (RT) among 4232 institutions across 11 countries during the period of 2000–2017 and find RT is negatively correlated with volatility measures. Second, a decomposition of the primary risk measure, the Z score and Merton distance-to-default, reveals that high RT contributed to lower stock return volatility mainly through better corporate governance, firm size, higher information efficiency, and strong BOD. Third, Australia firms engage in more RT compared to other countries. Finally, majority of the selected countries show the negative impact of RT in firm volatility in the pre-crises period (2002–2006) and during the crises period (2007–2009) but not in the post-crises period (2010–2014).

The purpose of this paper is to test whether investors take flight to safety when sentiment is low. In other words, do safe firms perform better than risky firms following periods of low sentiment.

Using cash flow volatility and the percent of bullish investors as proxies for risk and investor sentiment the paper tests the relationship between sentiment and returns conditional on risk this performance. Second, a cross-sectional analysis is conducted based on individual firm characteristics and sentiment to explain annual returns.

The paper finds that there is a negative relationship between investor sentiment and the return of risky companies, which is contrary to prior studies. All told, risky companies perform worse following periods of high investor sentiment.

This paper presents evidence contrary to extant literature and that there is no concerted flight to safety. Investor sentiment has little influence on safe stocks.

This paper aims to examine the dynamic of volatility of Malaysian listed property companies within pan-Asian public property markets based on different volatility perspective over the past 18 years, especially during the global financial crisis (GFC).

This study uses several statistical methods and formulas for analysing the dynamic of volatility of Malaysian listed property companies such as exponential generalised autoregressive conditional heteroscedasticity (EGARCH) and Markov-switching (MS) EGARCH. The MS-EGARCH model provides new insights on the volatility dynamics of Malaysian listed property companies compared to conventional volatility modelling techniques, particularly EGARCH. Additionally, this paper will analyse the volatility movement based on three different sub-periods such as pre-GFC, GFC and post-GFC.

The findings reveal that the markets perform differently under different volatility conditions. Moreover, the application of MS-EGARCH provides a different view on the volatility dynamics compared to the conventional EGARCH model, as MS-EGARCH provides more comprehensive findings, especially during extreme market conditions.

This study contributes to the literature on the dynamics of Malaysian listed property companies within pan-Asian countries, as the approach for assessing the volatility performance based on different volatility conditions is less explored by previous researchers.

Intraday volatility characteristics throughout the trading week are examined at the emerging Borsa Istanbul (BIST) stock exchange. Using five-minute (and 15-minute) intervals, accentuated intraday volatility patterns at the microstructure level are examined during the stock market open and close in the morning and in the afternoon sessions. Volatility is highest when markets open in the morning. The second highest is during the afternoon open. The third highest is before the market closes for the day. Volatility before the market close has increased in recent years. These characteristics are seen every trading day. There are also differences: Monday returns are lowest, Friday returns are highest, and Monday morning volatility is highest of the entire trading week. Day-of-the-week and intraday accentuated volatility smile anomalies are jointly investigated using the longest intraday sample period in the emerging country stock exchange literature. Investment companies and professionals can utilize the results for risk management and hedging by avoiding highly volatile opening and closing periods. Arbitrageurs, speculators, and risk takers should trade during these highly volatile periods. Heightened volatility is increased difficulty in price discovery, thus inefficiency. Market participants, exchanges, and public prefer efficient markets. The research presents evidence of trading days, and periods during the trading day, when the exchange becomes more efficient. This is the first research that explores day-of-the-week effect from intraday volatility perspective in an emerging market, and provides useful recommendations in designing risk management strategies at market microstructure level.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

The purpose of this paper is to find the impact of food price volatility on child health and education attainment in urban areas of Pakistan. This research also compares the two variables among the two time periods: the period of low volatile food prices (2014‒2015) and the period of high volatile food prices (2013‒2014). The rate of child immunization and the rate of child school attendance are used as proxies for child health and child education, respectively.

This study employs propensity score matching (PSM) technique introduced by Rosenbaum and Rubin (1983), to overcome the selection bias problem in the observational studies.

The closing part of the paper concludes that both the rate of child immunization and the rate of child school attendance are significantly poorer for the households of Pakistan in the control period (of high food price volatility) as compared to the treated period (of low food price volatility). After controlling the problem of selection bias through PSM technique, it is found that there is a further increase in the rate of child immunization and the rate of child school attendance. It proves that the data were biased before applying the matching technique.

This study lengthens the literature by identifying the impact of food price volatility on child health and education of urban households of Pakistan, using high frequency data of PSLM/HIES, with the help of semi-parametric technique of matching. This type of micro-level research has not been conducted (nationally or internationally) so far; therefore, it would possibly open a sphere for policy makers to implement the suitable policies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2019-0275.