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1 – 10 of over 53000I 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…
Abstract
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.
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This paper aims to explore the effects of illiquidity on portfolio weight and return dynamics.
Abstract
Purpose
This paper aims to explore the effects of illiquidity on portfolio weight and return dynamics.
Design/methodology/approach
Using a novel continuous-time framework, the paper makes two key contributions to the literature on asset pricing and illiquidity. The first is to study the effects of illiquidity on portfolio weight dynamics. The second contribution is to analyze how illiquidity affects the risk/return dynamics of a portfolio.
Findings
The numerical results highlight that investors should be prepared for potentially large and skewed variations in portfolio weights and can be away from optimal diversification for a long time when adding illiquid assets to a portfolio. Additionally, the paper shows that illiquidity increases portfolio risk. Interestingly, this effect gets more pronounced when the return correlation between the illiquid and liquid asset is low. Thus, there is a correlation effect in the sense that illiquidity costs, as measured by the increase in overall portfolio risk, are inversely related to the return correlation of the assets.
Originality/value
This is the first paper that highlights that the increase in portfolio risk caused by illiquidity is inversely related to the return correlation between the liquid and illiquid assets. This important economic result contrasts with the widely used argument that the benefit of adding illiquid (alternative) assets to a portfolio is their low correlation with (traditional) traded assets. The results imply that the benefits of adding illiquid assets to a portfolio can be much lower than typically perceived.
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Elizabeth A. Maharaj, Don U.A. Galagedera and Jonathan Dark
The purpose of this paper is to examine the volatility of daily returns in a sample of developed and emerging equity markets at different time scales through wavelet…
Abstract
Purpose
The purpose of this paper is to examine the volatility of daily returns in a sample of developed and emerging equity markets at different time scales through wavelet decomposition. Such information is vital for international investors who have different time horizons for their investment decisions and trading strategies.
Design/methodology/approach
The wavelet technique used here allows the return series to be viewed at different frequency by decomposing the series into different time horizons known as time scales. The decomposed return series enable investigation of return variability at different return intervals.
Findings
In an analysis at different time scales, there is no evidence to suggest that the return dynamics of developed and emerging markets are different. In both types of markets, return variance is time scale dependent, satisfying a pure power law process, and the variability in returns is more likely to be due to the dynamics at the lower time scales. While emerging markets generally exhibit a higher level of volatility, the relative contribution from each time scale is quite similar to that of the developed markets.
Originality/value
The difference in the return dynamics between emerging and developed markets is observed at the lowest time scale. This is an indication that differences in the return dynamics between the two types of markets may be more likely in the short term (high frequency) rather than in the long term. A plausible reason for this is speculative trading. Such information is vital for international investors who have different time horizons for their investment decisions and trading strategies.
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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…
Abstract
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.
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James Giannarelli and Piyush Tiwari
This paper examines the extent of the short-run relationship between Australian real estate investment trusts (A-REITs) and direct real estate returns on both a commercial…
Abstract
Purpose
This paper examines the extent of the short-run relationship between Australian real estate investment trusts (A-REITs) and direct real estate returns on both a commercial property sector and a prime and secondary grade basis, i.e. a subsector basis.
Design/methodology/approach
Two-step methodology is used. First, we identify the dynamic interdependencies between A-REITs and each commercial property subsector to determine whether the returns of A-REITs lead each subsector or vice versa. Second, short-run deviations between these asset returns are estimated by measuring their individual response behaviours to changes in key economic and financial market factors that are expected to influence these returns.
Findings
Results suggest that each subsector shares a unique relationship to A-REITs, given each prime and secondary grade commercial property return series varies in behaviour. Some property subsector returns can be predicted by movements in A-REIT returns, whereas returns for others move independent to changes in A-REITs. Similarly, some subsectors commove with A-REITs in response to changes in certain market factors, whereas others diverge. As such, these findings have practical significance to fund managers and portfolio selection, as each commercial subsector embodies its own exposure to A-REITs and vulnerabilities to market forces. Subsectors that commove with A-REITs in response to certain market forces may be used as substitutes in a portfolio. Alternatively, subsectors that diverge from A-REITs in response to market forces may offer diversification benefits when combined.
Practical implications
These findings extend beyond existing research to offer critical decision-making guidance at the acquisition level, as fund managers may more closely consider the impact that prime or secondary grade properties within a given commercial sector may have on a portfolio that consists of public and private Australian real estate. Ultimately, a more informed acquisition may be carried out as consideration of a property's asset grade allows for a deeper insight into the property's risk profile and its anticipated short-run impact on a portfolio.
Originality/value
This paper extends previous studies that focus mostly on aggregate or sector-level returns by measuring REIT and real estate dynamics at the subsector level, allowing for practical significance at not only the portfolio level but crucially at the acquisition level, a pivotal decision-making stage for fund managers. This is also the first paper to study REIT and real estate causality and response patterns to changes in market factors at the Australian sector level.
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Yousra Trichilli, Mouna Boujelbène Abbes and Afif Masmoudi
The purpose of this paper is to evaluate the capability of the hidden Markov model using Googling investors’ sentiments to predict the dynamics of Islamic indexes’ returns in the…
Abstract
Purpose
The purpose of this paper is to evaluate the capability of the hidden Markov model using Googling investors’ sentiments to predict the dynamics of Islamic indexes’ returns in the Middle East and North Africa (MENA) financial markets from 2004 to 2018.
Design/methodology/approach
The authors propose a hidden Markov model based on the transition matrix to apprehend the relationship between investor’s sentiment and Islamic index returns. The proposed model facilitates capturing the uncertainties in Islamic market indexes and the possible effects of the dynamics of Islamic market on the persistence of these regimes or States.
Findings
The bearish state is the most persistent sentiment with the longest duration for all the MENA Islamic markets except for Jordan, Morocco and Qatar. In addition, the obtained results indicate that the effect of sentiment on predicting the future Islamic index returns is conditional on the MENA States. Besides, the estimated mean returns for each state indicates that the bullish and calm states are ideal for investing in Islamic indexes of Bahrain, Oman, Morocco, Kuwait, Saudi Arabia and United Arab Emirates. However, only the bullish state is ideal for investing Islamic indexes of Jordan, Egypt and Qatar.
Research limitations/implications
This paper has used data at a monthly frequency that can explain only short-term dynamics between Googling investor’s sentiment and the MENA Islamic stock market returns. Moreover, this work can be done on the stock markets while taking into account the specificity of each activity sector.
Practical implications
In fact, the findings of this paper are helpful for academics, analysts and practitioners, and more specifically for the Islamic MENA financial investors. Moreover, this study provides useful insights not only into the duration of the relationship between the indexes’ returns and the investors’ sentiments in the five states but also into the transition probabilities which have implications for how investors could be guided in their choice of future investment in a portfolio with Islamic indexes. Findings of this paper are important and valuable for policy-makers and investors. Thus, predicting the effect of Googling investors’ sentiment on the MENA Islamic stock market dynamics is important for portfolio diversification by domestic and international investors. Moreover, the results of this paper gave new insights into financial analysts about the dynamic relationship between Googling investors’ sentiment and Islamic stock market returns across market regimes. Therefore, the findings of this study might be useful for investors as they help them capture the unobservable dynamics of the changes in the investors’ sentiment regimes in the MENA financial markets to make successful investment decisions.
Originality/value
To the best of the authors’ knowledge, this paper is the first to use the hidden Markov model to examine changes in the Islamic index return dynamics across five market sentiment states, namely the depressed sentiment (S1), the bullish sentiment (S2), the bearish sentiment (S3), the calm sentiment (S4) and the bubble sentiment (S5).
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David G McMillan and Pornsawan Evans
The purpose of this paper is to examine the nature of equity ownership of state-owned enterprises (SOEs) for over 2,000 listed firms in China. The paper examines both the pattern…
Abstract
Purpose
The purpose of this paper is to examine the nature of equity ownership of state-owned enterprises (SOEs) for over 2,000 listed firms in China. The paper examines both the pattern of state ownership and the dynamics of stock returns and volatility. Firms under the control of SOEs dominate the Chinese stock markets and currently account for over three-quarters of total market capitalisation. Central SOEs are focused in strategic industries, while Local SOEs concentrate on pillar industries relating to consumer goods and services.
Design/methodology/approach
The authors obtain firm-level data from the Shanghai and Shenzhen stock markets and using panel estimation techniques examine the dynamics of returns, volatility and their relationship.
Findings
The authors report an increase in state control among listed firms compared to earlier reported figures. This is contradictory to the expectation of a lower state influence following China joining of the World Trade Organisation in 2001. In examining the behaviour of stock returns the authors find evidence of daily and monthly autocorrelations that are larger and of a different sign to that reported for western markets. The authors also report evidence of volatility persistence but little evidence of volatility asymmetry, again in contrast to that often reported for other markets. Finally, the authors find evidence of either no or a negative relationship between returns and volatility (risk) that differs from our usual view of risk aversion.
Originality/value
It is hoped, knowledge of these dynamics will increase the understanding of the Chinese equity market, which in turn is important for those engaged in international portfolio management and micro-structure modelling.
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Takato Hiraki and Edwin D. Maberly
This paper investigates Japanese stock returns for the Friday, Monday and Tuesday surrounding U.S. Monday holiday closures. The empirical results show that U.S. Monday closures…
Abstract
This paper investigates Japanese stock returns for the Friday, Monday and Tuesday surrounding U.S. Monday holiday closures. The empirical results show that U.S. Monday closures have a statistically significant impact on Japanese stock return dynamics for surrounding trading days, but do not support the hypothesis that the U.S. Monday and Japanese Tuesday effects are related. Potential explanations for the occurrence and then disappearance of the Japanese Tuesday effect rely on market microstructure properties unique to the Tokyo market. The spillover effects from New York to Tokyo have been increased in density over time, which is attributed to market structural changes represented by the introduction of Nikkei 225 index futures on the SIMEX in 1986.
Nader Naifar and Sohale Altamimi
This paper investigates the impact of global sentiment and various coronavirus disease 2019 (COVID-19)-related media coverage news (Media-Hype index; Panic Index; Media Coverage…
Abstract
Purpose
This paper investigates the impact of global sentiment and various coronavirus disease 2019 (COVID-19)-related media coverage news (Media-Hype index; Panic Index; Media Coverage Index, infodemic index and coronavirus statistics) on the dynamics of bitcoin returns during the COVID-19 pandemic using an asymmetric framework.
Design/methodology/approach
The authors use an asymmetric framework based on quantile regression (QR) and quantile-on-quantile regression.
Findings
QR results show that COVID-19 panic news negatively affects bitcoin market returns at times of extreme bearish. However, COVID-19 bullish sentiment negatively impacts bitcoin market returns during bullish market conditions. Quantile-on-quantile approach's (QQA) empirical results show that the effects of COVID-19-related news on bitcoin returns were heterogeneous, mainly negative and varied across quantiles.
Research limitations/implications
The authors find some significant differences regarding the impact of news on bitcoin return dynamics compared to stock markets, suggesting the safe-haven role of bitcoin against stock during the ongoing epidemic.
Practical implications
The authors find some significant differences regarding the impact of news on bitcoin return dynamics compared to stock markets, suggesting the safe-haven role of bitcoin against stock during the ongoing epidemic.
Originality/value
This study contributes to understanding the dynamics of bitcoin returns using various COVID-19 media news.
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Opeoluwa Adeniyi Adeosun, Suhaib Anagreh, Mosab I. Tabash and Xuan Vinh Vo
This paper aims to examine the return and volatility transmission among economic policy uncertainty (EPU), geopolitical risk (GPR), their interaction (EPGR) and five tradable…
Abstract
Purpose
This paper aims to examine the return and volatility transmission among economic policy uncertainty (EPU), geopolitical risk (GPR), their interaction (EPGR) and five tradable precious metals: gold, silver, platinum, palladium and rhodium.
Design/methodology/approach
Applying time-varying parameter vector autoregression (TVP-VAR) frequency-based connectedness approach to a data set spanning from January 1997 to February 2023, the study analyzes return and volatility connectedness separately, providing insights into how the data, in return and volatility forms, differ across time and frequency.
Findings
The results of the return connectedness show that gold, palladium and silver are affected more by EPU in the short term, while all precious metals are influenced by GPR in the short term. EPGR exhibits strong contributions to the system due to its elevated levels of policy uncertainty and extreme global risks. Palladium shows the highest reaction to EPGR, while silver shows the lowest. Return spillovers are generally time-varying and spike during critical global events. The volatility connectedness is long-term driven, suggesting that uncertainty and risk factors influence market participants’ long-term expectations. Notable peaks in total connectedness occurred during the Global Financial Crisis and the COVID-19 pandemic, with the latter being the highest.
Originality/value
Using the recently updated news-based uncertainty indicators, the study examines the time and frequency connectedness between key uncertainty measures and precious metals in their returns and volatility forms using the TVP-VAR frequency-based connectedness approach.
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