Journal of Risk and Financial Management

Research

Jump to: Review

18 pages, 2256 KiB

Open AccessArticle

Dependencies and Volatility Spillovers among Chinese Stock and Crude Oil Future Markets: Evidence from Time-Varying Copula and BEKK-GARCH Models

by Xiaoling Yu and Kaitian Xiao

J. Risk Financial Manag. 2022, 15(11), 491; https://doi.org/10.3390/jrfm15110491 - 24 Oct 2022

Cited by 5 | Viewed by 1976

Abstract

This paper investigates co-movements among the Chinese stock market, Shanghai International Energy Exchange (INE) crude oil futures and West Texas Intermediate (WTI) crude oil futures. We use Copula models to capture tail dependencies and employ the VAR-BEKK-GARCH model to examine the direction of [...] Read more.

This paper investigates co-movements among the Chinese stock market, Shanghai International Energy Exchange (INE) crude oil futures and West Texas Intermediate (WTI) crude oil futures. We use Copula models to capture tail dependencies and employ the VAR-BEKK-GARCH model to examine the direction of volatility spillovers. We find that there are positively time-varying dependency relationships among the three markets. Compared with the corresponding upper-tail dependencies, the lower-tail dependencies were larger before the COVID-19 pandemic while relatively weaker after the breakout of the pandemic. Before the COVID-19 pandemic, there was only a statistically significant volatility spillover from WTI crude oil future market to the INE crude oil future market. After the breakout of the COVID-19 pandemic, there were statistically significant volatility spillovers in the two pairs of markets, namely, the WTI–INE and Chinese stock–WTI. However, we only find statistically significant evidence of unidirectional volatility spillover from the Chinese crude oil future market to the Chinese stock market during the pandemic. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

18 pages, 965 KiB

Open AccessArticle

International Information Spillovers and Asymmetric Volatility in South Asian Stock Markets

by Dinesh Gajurel and Akhila Chawla

J. Risk Financial Manag. 2022, 15(10), 471; https://doi.org/10.3390/jrfm15100471 - 18 Oct 2022

Cited by 2 | Viewed by 2382

Abstract

This is the first comprehensive study to investigate the dynamics of international information spillovers, regional linkages and fundamental forces driving return volatility in the SAARC (South Asian Association for Regional Cooperation) member nation equity markets. We propose a multi-factor model nested within the [...] Read more.

This is the first comprehensive study to investigate the dynamics of international information spillovers, regional linkages and fundamental forces driving return volatility in the SAARC (South Asian Association for Regional Cooperation) member nation equity markets. We propose a multi-factor model nested within the generalized autoregressive conditional heteroskedasticity framework and enlist comprehensive equity market data. While modeling, we consider global, regional (Asia), and largest neighboring (India) equity markets as sources of information spillover. Our results show that equity returns in all these South Asian markets have positive autocorrelation. The equity markets of India, Pakistan, and Sri Lanka have some degree of global integration; however, their degree of regional integration is comparatively higher. The stock markets of Bangladesh and Nepal, in contrast, lack both global and regional integration. We find limited evidence of neighborhood (India) spillover effect on other markets in the sample. The stock markets of Bangladesh, India and Pakistan stock markets exhibit asymmetric volatility responses, while Nepal exhibits an inverted asymmetric volatility response, and in contrast Sri Lanka exhibits a symmetric volatility response to return shocks. Finally, most of these markets experience volatility spillover effects from the US, Asia, and India stock markets. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

21 pages, 469 KiB

Open AccessArticle

Information Spillovers Prior to M&A Announcements

by Danjue Clancey-Shang

J. Risk Financial Manag. 2022, 15(10), 455; https://doi.org/10.3390/jrfm15100455 - 11 Oct 2022

Viewed by 1830

Abstract

In this paper, I study trading activities prior to M&A announcements pertaining to the rivals of the merging firms. I find that not only acquirers and targets experience increases in abnormal trading activities in stock and option markets, but also their rivals. The [...] Read more.

In this paper, I study trading activities prior to M&A announcements pertaining to the rivals of the merging firms. I find that not only acquirers and targets experience increases in abnormal trading activities in stock and option markets, but also their rivals. The rise in option trading is especially strong for options that informed traders are most likely to trade. I find that the implied volatility spread (IV spread) constructed from a rival’s option prices the day before the announcement can predict this rival’s cumulative abnormal return (CAR) over the M&A announcement window. As the IV spread is widely adopted as a proxy for informed trading activities in the option market, my findings provide evidence for information spillovers from merging firms to their rivals prior to the announcements of the M&A deals. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

20 pages, 4387 KiB

Open AccessArticle

Testing of a Volatility-Based Trading Strategy Using Behavioral Modified Asset Allocation

by Jonas Freibauer and Silja Grawert

J. Risk Financial Manag. 2022, 15(10), 435; https://doi.org/10.3390/jrfm15100435 - 27 Sep 2022

Viewed by 2902

Abstract

The performance of volatility-based trading strategies depends, among other factors, on the asset selection and the associated risk preference. For this study, we conducted a representative survey for Germany to determine the asset preferences of individuals with lower-risk and higher-risk preference. These two [...] Read more.

The performance of volatility-based trading strategies depends, among other factors, on the asset selection and the associated risk preference. For this study, we conducted a representative survey for Germany to determine the asset preferences of individuals with lower-risk and higher-risk preference. These two types of behavioral modified asset allocations (lower-risk and higher-risk) form the basis for testing our volatility-based trading strategy with different risk and loss levels. The tests are based on historical asset price data over a period of nearly the last eleven years. The goal was to historically outperform the broad market by changing various factors, such as the initial asset allocation, the asset reallocation, and the risk and loss level underlying the trading strategy. We achieve this by using the riskier initial asset allocation and applying our trading strategy with a risk and loss level of 10% each. In this case, a historical return of 326% could have been achieved with our trading strategy over the period under review. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

11 pages, 324 KiB

Open AccessArticle

Carbon Futures and Clean Energy Stocks: Do They Hedge or Safe Haven against the Climate Policy Uncertainty?

by Mohammad Enamul Hoque and Sourav Batabyal

J. Risk Financial Manag. 2022, 15(9), 397; https://doi.org/10.3390/jrfm15090397 - 6 Sep 2022

Cited by 14 | Viewed by 2297

Abstract

Using the GARCH model and quantile regression with dummy variables, we investigate the hedging and safe haven properties of carbon futures and clean energy stocks against the U.S. climate policy uncertainty (CPU). We discover that carbon futures and clean energy stocks [...] Read more.

Using the GARCH model and quantile regression with dummy variables, we investigate the hedging and safe haven properties of carbon futures and clean energy stocks against the U.S. climate policy uncertainty (CPU). We discover that carbon futures and clean energy stocks have a weak hedge and a semi-strong safe haven in different market conditions. Carbon futures exhibit a strong safe haven in both bull and bear markets, depending on the degree of uncertainty. Clean energy stocks, on the other hand, possess a weak hedge across market conditions and a strong safe haven in bull markets. Sub-sample analyses of prior- and post-Paris Agreement of 2016 also exhibit consistent results for safe haven properties of carbon futures and clean energy stocks. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

15 pages, 3735 KiB

Open AccessArticle

Co-Movement, Portfolio Diversification, Investors’ Behavior and Psychology: Evidence from Developed and Emerging Countries’ Stock Markets

by Mohammad Sahabuddin, Md. Aminul Islam, Mosab I. Tabash, Suhaib Anagreh, Rozina Akter and Md. Mizanur Rahman

J. Risk Financial Manag. 2022, 15(8), 319; https://doi.org/10.3390/jrfm15080319 - 22 Jul 2022

Cited by 10 | Viewed by 4292

Abstract

The issue of co-movements is still crucial and arguable in international finance. An optimum and significant level of co-movement is highly desirable to investors, and it mostly depends on investors’ decisions (behavior and psychology). We use frequency–time bands and multi-scale-based wavelet analysis to [...] Read more.

The issue of co-movements is still crucial and arguable in international finance. An optimum and significant level of co-movement is highly desirable to investors, and it mostly depends on investors’ decisions (behavior and psychology). We use frequency–time bands and multi-scale-based wavelet analysis to investigate the co-movement between developed and emerging countries’ stock markets for better asset allocation and portfolio diversification strategies. The results show that a significant level of co-movement is observed between conventional and Islamic stock markets in developed and emerging countries, and it varies in terms of its time–frequency domain properties. Particularly, the dependency among conventional and Islamic stock markets is strong at 4–512-band scales. However, the USA Islamic stock market illustrates a higher level of coherency with the UK, Japan and China’s Islamic stock markets, while a relatively lower level of co-movement is detected with the Chinese composite, Malaysian and Indonesian Islamic stock markets. The findings further confirm that the developed countries’ stock markets are substantially influenced by the GFC in 2007–2008 and the European debt crisis in 2012, while this trend is surprisingly not observed in the emerging markets on a similar scale. Therefore, these crises have opened the door for the grabbing of portfolio diversification benefits from the emerging countries’ stock markets. These findings give some interesting insights to policymakers, investors and fund managers for portfolio diversification and risk management strategies. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

25 pages, 2438 KiB

Open AccessArticle

Surviving Black Swans: The Challenge of Market Timing Systems

by Pankaj Topiwala and Wei Dai

J. Risk Financial Manag. 2022, 15(7), 280; https://doi.org/10.3390/jrfm15070280 - 24 Jun 2022

Cited by 5 | Viewed by 3886

Abstract

It is an open secret that most investment funds actually underperform the market. Yet, millions of individual investors fare even worse, barely treading water. Algorithmic trading is now so common, it accounts for over 80% of all trades and is the domain of [...] Read more.

It is an open secret that most investment funds actually underperform the market. Yet, millions of individual investors fare even worse, barely treading water. Algorithmic trading is now so common, it accounts for over 80% of all trades and is the domain of professionals. Can it also help the small investor? Individual investors are advised to buy-and-hold an index fund or a balanced portfolio including stocks, bonds, and cash equivalents. That would ensure market performance. However, market indices also occasionally have deep drawdowns (such as the devastating market crash of 1929 and other so-called Black Swan events). In contrast to received wisdom, we argue with evidence from backtesting on major U.S. market indices, as well as some select stocks that simple ideas in rule-based market timing can in fact be useful. One can not only obtain good results, but outperform market indices, while, at the same time, reducing deep drawdowns, surviving Black Swan events. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

19 pages, 2478 KiB

Open AccessArticle

The Effect of Index Option Trading on Stock Market Volatility in China: An Empirical Investigation

by Kai Wu, Yi Liu and Weiyang Feng

J. Risk Financial Manag. 2022, 15(4), 150; https://doi.org/10.3390/jrfm15040150 - 24 Mar 2022

Cited by 3 | Viewed by 3427

Abstract

In this study, we examine the effect of introducing SSE 50ETF index options trading on stock market volatility using a panel data evaluation approach. Based on the cross-sectional dependence among international stock indices and macroeconomic indicators, we estimate the counterfactual volatility of the [...] Read more.

In this study, we examine the effect of introducing SSE 50ETF index options trading on stock market volatility using a panel data evaluation approach. Based on the cross-sectional dependence among international stock indices and macroeconomic indicators, we estimate the counterfactual volatility of the SSE 50 index and find that the introduction of index options reduces stock market volatility significantly in the long term. The primary findings are robust to alternative econometric models, including principal component analysis, GARCH-family model, and LASSO regression. The results of this paper suggest that the introduction of SSE index options provides investors with risk management tools and improves price discovery in the stock market. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

11 pages, 301 KiB

Open AccessArticle

Responses of the International Bond Markets to COVID-19 Containment Measures

by Bao Cong Nguyen To, Tam Van Thien Nguyen, Nham Thi Hong Nguyen and Hoai Thu Ho

J. Risk Financial Manag. 2022, 15(3), 127; https://doi.org/10.3390/jrfm15030127 - 8 Mar 2022

Cited by 4 | Viewed by 3319

Abstract

Using an international sample during the COVID-19 outbreak, our study gives evidence that COVID-19 containment measures impact volatility in the international bond markets in different ways. We found that the positive effect of increasing new COVID-19 vaccinations markedly mitigates bond market volatility, while [...] Read more.

Using an international sample during the COVID-19 outbreak, our study gives evidence that COVID-19 containment measures impact volatility in the international bond markets in different ways. We found that the positive effect of increasing new COVID-19 vaccinations markedly mitigates bond market volatility, while non-pharmaceutical government interventions resembling bad news increase volatility in bond markets. Besides this, changes in total COVID-19 cases and total deaths have co-movement and a significant relationship with this volatility. Our results imply that the investors’ responses to the trigger of increased uncertainty seem to differ in a way that depends on bad or good news as a reflection of the possibility of pandemic control and the health of the economy. The mass vaccinations not only signal a lower probability of stringent government responses to the pandemic but also stabilize investors’ behavior and mitigate compliance fears to open a period of safe living with coronavirus. Our findings are still robust when using alternative measures of independent variables and different forecasting models of conditional volatility. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

18 pages, 3022 KiB

Open AccessArticle

Predictability of the Realised Volatility of International Stock Markets Amid Uncertainty Related to Infectious Diseases

by Sisa Shiba, Juncal Cunado and Rangan Gupta

J. Risk Financial Manag. 2022, 15(1), 18; https://doi.org/10.3390/jrfm15010018 - 5 Jan 2022

Cited by 2 | Viewed by 1589

Abstract

In the context of the great turmoil in the financial markets caused by the COVID-19 pandemic, the predictability of daily infectious diseases-related uncertainty (EMVID) for international stock markets volatilities is examined using heterogeneous autoregressive realised variance (HAR-RV) models. A recursive estimation approach in [...] Read more.

In the context of the great turmoil in the financial markets caused by the COVID-19 pandemic, the predictability of daily infectious diseases-related uncertainty (EMVID) for international stock markets volatilities is examined using heterogeneous autoregressive realised variance (HAR-RV) models. A recursive estimation approach in the short-, medium- and long-run out-of-sample predictability is considered and the main findings show that the EMVID index plays a significant role in forecasting the volatility of international stock markets. Furthermore, the results suggest that the most vulnerable stock markets to EMVID are those in Singapore, Portugal and The Netherlands. The implications of these results for investors and portfolio managers amid high levels of uncertainty resulting from infectious diseases are discussed. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure A1

22 pages, 1316 KiB

Open AccessArticle

A Bayesian Semiparametric Realized Stochastic Volatility Model

by Jia Liu

J. Risk Financial Manag. 2021, 14(12), 617; https://doi.org/10.3390/jrfm14120617 - 19 Dec 2021

Cited by 3 | Viewed by 2611

Abstract

This paper proposes a semiparametric realized stochastic volatility model by integrating the parametric stochastic volatility model utilizing realized volatility information and the Bayesian nonparametric framework. The flexible framework offered by Bayesian nonparametric mixtures not only improves the fitting of asymmetric and leptokurtic densities [...] Read more.

This paper proposes a semiparametric realized stochastic volatility model by integrating the parametric stochastic volatility model utilizing realized volatility information and the Bayesian nonparametric framework. The flexible framework offered by Bayesian nonparametric mixtures not only improves the fitting of asymmetric and leptokurtic densities of asset returns and logarithmic realized volatility but also enables flexible adjustments for estimation bias in realized volatility. Applications to equity data show that the proposed model offers superior density forecasts for returns and improved estimates of parameters and latent volatility compared with existing alternatives. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

22 pages, 4444 KiB

Open AccessArticle

Multiscale Decomposition and Spectral Analysis of Sector ETF Price Dynamics

by Tim Leung and Theodore Zhao

J. Risk Financial Manag. 2021, 14(10), 464; https://doi.org/10.3390/jrfm14100464 - 2 Oct 2021

Cited by 2 | Viewed by 2289

Abstract

We present a multiscale analysis of the price dynamics of U.S. sector exchange-traded funds (ETFs). Our methodology features a multiscale noise-assisted approach, called the complementary ensemble empirical mode decomposition (CEEMD), that decomposes any financial time series into a number of intrinsic mode functions [...] Read more.

We present a multiscale analysis of the price dynamics of U.S. sector exchange-traded funds (ETFs). Our methodology features a multiscale noise-assisted approach, called the complementary ensemble empirical mode decomposition (CEEMD), that decomposes any financial time series into a number of intrinsic mode functions from high to low frequencies. By combining high-frequency modes or low-frequency modes, we show how to filter the financial time series and estimate conditional volatilities. The results show the different dynamics of the sector ETFs on multiple timescales. We then apply Hilbert spectral analysis to derive the instantaneous energy-frequency spectrum of each sector ETF. Using historical ETF prices, we illustrate and compare the properties of various timescales embedded in the original time series. Through the new metrics of the Hilbert power spectrum and frequency deviation, we are able to identify differences among sector ETF and with respect to SPY that were not obvious before. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

11 pages, 287 KiB

Open AccessArticle

Gamesmanship and Seasonality in U.S. Stock Returns

by Lucy F. Ackert and George Athanassakos

J. Risk Financial Manag. 2021, 14(5), 206; https://doi.org/10.3390/jrfm14050206 - 3 May 2021

Viewed by 2869

Abstract

We re-examined the seasonal pattern in the excess returns of highly visible American firms. In contrast to the seasonality for risky, less visible firms, we found that highly visible stocks display return seasonality that shows the opposite trend. Fund managers are prone to [...] Read more.

We re-examined the seasonal pattern in the excess returns of highly visible American firms. In contrast to the seasonality for risky, less visible firms, we found that highly visible stocks display return seasonality that shows the opposite trend. Fund managers are prone to gamesmanship, putting downward pressure on prices for highly visible firms at the beginning of the year, which is reversed later with buying pressure. Due to the bonus culture, fund managers start the year by buying small, risky stocks in order to beat benchmarks. Once targets are met, they adjust toward visible, less risky stocks to lock in returns, providing them with a seasonal returns pattern opposite to that of small firms. A re-examination is warranted because the world has become increasingly globalized, and some argue that managers’ incentives are aligned with investors due to increased scrutiny. We used analyst following as a proxy for visibility and examined the seasonal pattern for 1997–2018. Though the anomaly was first reported twenty years ago, it persists in recent data. Rational investors may be limited in their ability to arbitrage mispricing because institutional investors who drive the market are self-interested. Future research may examine the seasonal pattern in countries with more stringent regulation of financial professionals or with high-frequency data. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

Review

Jump to: Research

23 pages, 2184 KiB

Open AccessReview

Mapping the Trend, Application and Forecasting Performance of Asymmetric GARCH Models: A Review Based on Bibliometric Analysis

by Neenu Chalissery, Suhaib Anagreh, Mohamed Nishad T. and Mosab I. Tabash

J. Risk Financial Manag. 2022, 15(9), 406; https://doi.org/10.3390/jrfm15090406 - 12 Sep 2022

Cited by 2 | Viewed by 2566

Abstract

The past few years have witnessed renewed interest in modelling and forecasting asymmetry in financial time series using a variety of approaches. The most intriguing of these strategies is the “asymmetric” or “leverage” volatility model. This study aims to conduct a review of [...] Read more.

The past few years have witnessed renewed interest in modelling and forecasting asymmetry in financial time series using a variety of approaches. The most intriguing of these strategies is the “asymmetric” or “leverage” volatility model. This study aims to conduct a review of asymmetric GARCH models using bibliometric analysis to identify their key intellectual foundations and evolution, and offers thematic and methodological recommendations for future research to advance the domain. Bibliometric analysis was used to identify patterns in and perform descriptive analysis of articles, including citation, co-authorship, bibliographic coupling, and co-occurrence analysis. The study located 856 research papers from the Scopus database between 1992 and 2021 using key phrase and reference search methods. Publication trends, most influential authors, leading countries, and top journals are described, along with a systematic review of highly cited articles. The study summarises the development, application, and performance evaluation of asymmetric GARCH models, which will help researchers and academicians significantly contribute to this literature by addressing gaps. Full article

(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Financial Markets, Financial Volatility and Beyond

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (14 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI