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Article
Publication date: 6 February 2017

Kim Hiang Liow and Felix Schindler

Using a data set comprising 16 European office markets provided by the DTZ Research Institute from Q1 2003 to Q4 2013, the purpose of this paper is to measure the strength of the…

Abstract

Purpose

Using a data set comprising 16 European office markets provided by the DTZ Research Institute from Q1 2003 to Q4 2013, the purpose of this paper is to measure the strength of the unconditional transmission of volatility in the returns to direct property between 16 European office markets with the objective of determining the degree of unconditional spillover between markets.

Design/methodology/approach

To examine volatility spillovers across the 16 office markets, the authors adopted the generalized VAR methodology, variance decomposition and the generalized spillover index of Diebold and Yilmaz (2012) by measuring cross-office market volatility transmission in asset pricing through estimates of several “volatility spillover indices.”

Findings

Volatility spillovers are important and time-varying across the leading office markets, with cross-market volatility interaction being bi-directional and of relative endogenous nature for many markets. The London office market is the “volatility leader” and has exerted significant net volatility influence on the other markets. Additionally, the volatility spillovers between business cycle fluctuations and asset market cycle volatilities are linked across some European economies.

Research limitations/implications

Evidence of co-integration among the domestic volatility spillover cycles implies the presence of unobserved common shocks and might not be good news for international investors who pursue diversification strategies in European office real estate markets.

Originality/value

No previous study has addressed formally the measurement and assessment of the nature and intensity of volatility spillovers across direct office markets on such a broad range of European office markets. The relevance of the topic has been even increasing over the previous years as more and more investors seek for flexibility and participation in the investment process and asset management.

Details

Journal of Property Investment & Finance, vol. 35 no. 1
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 26 August 2014

Kim Hiang Liow

The purpose of this paper is to examine weekly dynamic conditional correlations (DCC) and vector autoregressive (VAR)-based volatility spillover effects within the three Greater…

Abstract

Purpose

The purpose of this paper is to examine weekly dynamic conditional correlations (DCC) and vector autoregressive (VAR)-based volatility spillover effects within the three Greater China (GC) public property markets, as well as across the GC property markets, three Asian emerging markets and two developed markets of the USA and Japan over the period from January 1999 through December 2013.

Design/methodology/approach

First, the author employ the DCC methodology proposed by Engle (2002) to examine the time-varying nature in return co-movements among the public property markets. Second, the author appeal to the generalized VAR methodology, variance decomposition and the generalized spillover index of Diebold and Yilmaz (2012) to investigate the volatility spillover effects across the real estate markets. Finally, the spillover framework is able to combine with recent developments in time series econometrics to provide a comprehensive analysis of the dynamic volatility co-movements regionally and globally. The author also examine whether there are volatility spillover regimes, as well as explore the relationship between the volatility spillover cycles and the correlation spillover cycles.

Findings

Results indicate moderate return co-movements and volatility spillover effects within and across the GC region. Cross-market volatility spillovers are bidirectional with the highest spillovers occur during the global financial crisis (GFC) period. Comparatively, the Chinese public property market's volatility is more exogenous and less influenced by other markets. The volatility spillover effects are subject to regime switching with two structural breaks detected for the five sub-groups of markets examined. There is evidence of significant dependence between the volatility spillover cycles across stock and public real estate, due to the presence of unobserved common shocks.

Research limitations/implications

Because international investors incorporate into their portfolio allocation not only the long-term price relationship but also the short-term market volatility interaction and return correlation structure, the results of this study can shed more light on the extent to which investors can benefit from regional and international diversification in the long run and short-term within and across the GC securitized property sector, with Asian emerging market and global developed markets of Japan and USA. Although it is beyond the scope of this paper, it would be interesting to examine how the two co-movement measures (volatility spillovers and correlation spillovers) can be combined in optimal covariance forecasting in global investing that includes stock and public real estate markets.

Originality/value

This is one of very few papers that comprehensively analyze the dynamic return correlations and conditional volatility spillover effects among the three GC public property markets, as well as with their selected emerging and developed partners over the last decade and during the GFC period, which is the main contribution of the study. The specific contribution is to characterize and measure cross-public real estate market volatility transmission in asset pricing through estimates of several conditional “volatility spillover” indices. In this case, a volatility spillover index is defined as share of total return variability in one public real estate market attributable to volatility surprises in another public real estate market.

Article
Publication date: 1 August 2016

Kim Hiang Liow

This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate…

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Abstract

Purpose

This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles are linked across G7 from February 1990 to June 2014.

Design/methodology/approach

The empirical approaches include correlation analysis on Hodrick–Prescott (HP) cycles, HP cycle return spillovers effects using Diebold and Yilmaz’s (2012) spillover index methodology, as well as Croux et al.’s (2001) dynamic correlation and cohesion methodology.

Findings

There are fairly strong cycle-return spillover effects between the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles. The interactions among the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles in G7 are less positively pronounced or exhibit counter-cyclical behavior at the traditional business cycle (medium-term) frequency band when “pure” stock market cycles are considered.

Research limitations/implications

The research is subject to the usual limitations concerning empirical research.

Practical implications

This study finds that real estate is an important factor in influencing the degree and behavior of the relationship between cross-country business cycles and cross-country stock market cycles in G7. It provides important empirical insights for portfolio investors to understand and forecast the differential benefits and pitfalls of portfolio diversification in the long-, medium- and short-cycle horizons, as well as for research studying the linkages between the real economy and financial sectors.

Originality/value

In adding to the existing body of knowledge concerning economic globalization and financial market interdependence, this study evaluates the linkages between business cycles, stock market cycles and public real estate market cycles cross G7 and adds to the academic real estate literature. Because public real estate market is a subset of stock market, our approach is to use an original stock market index, as well as a “pure” stock market index (with the influence of real estate market removed) to offer additional empirical insights from two key complementary perspectives.

Details

Journal of European Real Estate Research, vol. 9 no. 2
Type: Research Article
ISSN: 1753-9269

Keywords

Article
Publication date: 6 January 2023

Biplab Kumar Guru and Inder Sekhar Yadav

This work investigates the volatility spillovers across stock markets and the nature of such spillovers through different periods of crises and tranquility.

405

Abstract

Purpose

This work investigates the volatility spillovers across stock markets and the nature of such spillovers through different periods of crises and tranquility.

Design/methodology/approach

Using daily stock return volatility data from June 2003 to June 2021, the generalized forecast error variance decomposition method (based on Diebold and Yilmaz, 2012 approach) is employed to measure the degree of volatility spillovers/connectedness among stock markets of 24 Asia–Pacific and 12 European Union (EU) economies.

Findings

The empirical results from static analysis suggested that about 28.1% (63.7%) of forecast error variance in return volatility for Asia–Pacific (EU) markets is due to spillovers. The evidence from dynamic analysis suggested that during mid of the global financial crisis, European debt crisis (EDC) and Covid-19, the gross volatility spillovers for Asia–Pacific (EU) was around 67% (80%), 65% (80%) and 73% (67%), respectively. The degree of net volatility transmission from Singapore (Denmark) to other Asia–Pacific (EU) markets was found to be highest.

Practical implications

The findings have crucial implications for the investors and portfolio managers in assessment of risk and optimum allocation of assets and investment decisions.

Originality/value

This study adds to the literature on risk management by systematically examining the impact of global financial crises, EDC and Covid-19 on the market interactions by capturing the magnitude, duration and pattern of the shock-specific market volatilities for a large sample of Asian and European markets using recent and large data set.

Article
Publication date: 29 April 2020

Hardik Marfatia

The objective of the paper is to explore the out-of-sample forecasting connections in income growth across the globe.

Abstract

Purpose

The objective of the paper is to explore the out-of-sample forecasting connections in income growth across the globe.

Design/methodology/approach

An autoregressive distributed lag (ARDL) framework is employed and the forecasting performance is analyzed across several horizons using different forecast combination techniques.

Findings

Results show that the foreign country's income provides superior forecasts beyond what is provided by the country's own past income movements. Superior forecasting power is particularly held by Belgium, Korea, New Zealand, the UK and the US, while these countries' income is rather difficult to predict by global counterparts. Contrary to conventional wisdom, improved forecasts of income can be obtained even for longer horizons using our approach. Results also show that the forecast combination techniques yield higher forecasting gains relative to individual model forecasts, both in magnitude and the number of countries.

Research limitations/implications

The forecasting paths of income movement across the globe reveal that predictive power greatly differs across countries, regions and forecast horizons. The countries that are difficult to predict in the short run are often seen to be predictable by global income movements in the long run.

Practical implications

Even while it is difficult to predict the income movements at an individual country level, combining information from the income growth of several countries is likely to provide superior forecasting gains. And these gains are higher for long-horizon forecasts as compared to the short-horizon forecast.

Social implications

In evaluating the forward-looking social implications of economic policy changes, the policymakers should also consider the possible global forecasting connections revealed in the study.

Originality/value

Employing an ARDL model to explore global income forecasting connections across several forecast horizons using different forecast combination techniques.

Details

Journal of Economic Studies, vol. 47 no. 5
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 26 November 2019

Tihana Škrinjarić and Boško Šego

The purpose of this paper is to empirically evaluate risk spillovers between selected CESEE (Central, Eastern and South-Eastern Europe) stock markets in order to evaluate the…

Abstract

Purpose

The purpose of this paper is to empirically evaluate risk spillovers between selected CESEE (Central, Eastern and South-Eastern Europe) stock markets in order to evaluate the possibilities of an international diversification of a portfolio.

Design/methodology/approach

The VAR model and the Diebold and Yilmaz (2009, 2012) spillover index are used, with rolling indices estimation over time in order to observe dynamics, which is important for investment strategies. Data are monthly and include selected CESEE stock market indices which were available to the researcher.

Findings

The empirical analysis for the period of January 2012–June 2019 indicates that some country risks were the net emitter of shocks in the system (Slovenia and Czech Republic), whereas some were net receivers (Croatia and Ukraine). The results are robust with respect to changing the length of the rolling window analysis, which means that investors could utilize such an approach in a dynamic portfolio selection.

Research limitations/implications

Observing only selected markets due to data (un)availability.

Practical implications

The paper shows how international investors can utilize the aforementioned methodology in order to make a more detailed analysis of the dynamics of stock markets connectedness so that international portfolios can be rebalanced according to the results and investors’ preferences.

Originality/value

This is the first such research which focuses on CESEE countries, since existing research is focused on more developed stock markets. Moreover, the empirical analysis extends to commenting the pairwise net indices over time, which is important for the dynamic portfolio rebalancing over time.

Details

China Finance Review International, vol. 10 no. 4
Type: Research Article
ISSN: 2044-1398

Keywords

Article
Publication date: 27 May 2021

Onur Polat and Eylül Kabakçı Günay

The purpose of this study is to investigate volatility connectedness between major cryptocurrencies by the virtue of market capitalization. In this context, this paper implements…

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Abstract

Purpose

The purpose of this study is to investigate volatility connectedness between major cryptocurrencies by the virtue of market capitalization. In this context, this paper implements the frequency connectedness approach of Barunik and Krehlik (2018) and to measure short-, medium- and long-term connectedness between realized volatilities of cryptocurrencies. Additionally, this paper analyzes network graphs of directional TO/FROM spillovers before and after the announcement of the COVID-19 pandemic by the World Health Organization.

Design/methodology/approach

In this study, we examine the volatility connectedness among eight major cryptocurrencies by the virtue of market capitalization by using the frequency connectedness approach over the period July 26, 2017 and October 28, 2020. To this end, this paper computes short-, medium- and long-cycle overall spillover indexes on different frequency bands. All indexes properly capture well-known events such as the 2018 cryptocurrency market crash and COVID-19 pandemic and markedly surge around these incidents. Furthermore, owing to notably increased volatilities after the official announcement of the COVID-19 pandemic, this paper concentrates on network connectedness of volatility spillovers for two distinct periods, July 26, 2017–March 10, 2020 and March 11, 2020–October 28, 2020, respectively. In line with the related studies, major cryptocurrencies stand at the epicenter of the connectedness network and directional volatility spillovers dramatically intensify based on the network analysis.

Findings

Overall spillover indexes have fluctuated between 54% and 92% in May 2018 and April 2020. The indexes gradually escalated till November 9, 2018 and surpassed their average values (71.92%, 73.66% and 74.23%, respectively). Overall spillover indexes dramatically plummeted till January 2019 and reached their troughs (54.04%, 57.81% and 57.81%, respectively). Etherium catalyst the highest sum of volatility spillovers to other cryptocurrencies (94.2%) and is followed by Litecoin (79.8%) and Bitcoin (76.4%) before the COVID-19 announcement, whereas Litecoin becomes the largest transmitter of total volatility (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%). Except for Etherium, the magnitudes of total volatility spillovers from each cryptocurrency notably increase after – COVID-19 announcement period. The medium-cycle network topology of pairwise spillovers indicates that the largest transmitter of total volatility spillover is Litecoin (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%) before the COVID-19 announcement. Etherium keeps its leading role of transmitting the highest sum of volatility spillovers (89.4%), followed by Bitcoin (88.9%) and Litecoin (88.2%) after the COVID-19 announcement. The largest transmitter of total volatility spillovers is Etherium (95.7%), followed by Litecoin (81.2%) and Binance Coin (75.5%) for the long-cycle connectedness network in the before-COVID-19 announcement period. These nodes keep their leading roles in propagating volatility spillover in the latter period with the following sum of spillovers (Etherium-89.5%, Bitcoin-88.9% and Litecoin-88.1%, respectively).

Research limitations/implications

The study can be extended by including more cryptocurrencies and high-frequency data.

Originality/value

The study is original and contributes to the extant literature threefold. First, this paper identifies connectedness between major cryptocurrencies on different frequency bands by using a novel methodology. Second, this paper estimates volatility connectedness between major cryptocurrencies before and after the announcement of the COVID-19 pandemic and thereby to concentrate on its impact on the cryptocurrency market. Third, this paper plots network graphs of volatility connectedness and herewith picture the intensification of cryptocurrencies due to a major financial distress event.

Details

Studies in Economics and Finance, vol. 38 no. 5
Type: Research Article
ISSN: 1086-7376

Keywords

Article
Publication date: 26 June 2023

Athanasios Tsagkanos, Dimitrios Koumanakos and Michalis Pavlakis

The purpose of this study is to examine the transmission of volatility between business confidence index and stock market indices in Greece. The country remains the riskiest…

Abstract

Purpose

The purpose of this study is to examine the transmission of volatility between business confidence index and stock market indices in Greece. The country remains the riskiest project in European Union (EU) and previous studies fail to reach an accurate conclusion regarding the direction of this transmission.

Design/methodology/approach

The study covers the period from January 2013 to August 2022 in monthly basis where important economic events occur. Considering that these economic events derive strong volatility moments, the authors adopt a new methodology that measures the transmission of volatility with higher precision. This is the generalized spillover analysis by Diebold and Yilmaz (2009, 2012).

Findings

The results indicate that Business Confidence Index (BCI) is the main receiver of volatility spillovers in Greece under all aspects of the used methodology. The specificity of the results shows that business activity through a green growth model is what drives investor confidence and then their activities.

Originality/value

Although a handful of studies have considered the transmission of volatility between BCI and stock market indices, this study contributes in several ways. This study focuses on one country (Greece), avoiding the dispersion of the results from the examination of the relationship in several countries. The used country remains the riskiest project in EU even nowadays, while other studies fail to confirm the main direction of volatility spillovers from business confidence to stock returns. This study covers a period that is ignored by previous studies and includes important economic events. In addition, considering that these economic events derive strong volatility moments, a new methodology is adopted in this field of research that measures the transmission of volatility with higher accuracy.

Details

Journal of Economic Studies, vol. 51 no. 2
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 26 June 2020

Sercan Demiralay, Nikolaos Hourvouliades and Athanasios Fassas

This paper aims to examine dynamic equicorrelations (DECO) and directional volatility spillover effects among four energy futures markets, namely, West Texas Intermediate crude…

Abstract

Purpose

This paper aims to examine dynamic equicorrelations (DECO) and directional volatility spillover effects among four energy futures markets, namely, West Texas Intermediate crude oil, heating oil, natural gas and reformulated blendstock for oxygenate blending gasoline, by using a multivariate fractionally integrated asymmetric power ARCH–DECO–generalized autoregressive conditional heteroskedasticity (GARCH) model and the spillover index technique.

Design/methodology/approach

The empirical analysis uses the dynamic equicorrelation model of Engle and Kelly (2012) to examine time-varying correlations at equilibrium. The authors further analyze dynamic volatility transmission among energy futures by using Diebold and Yilmaz (2012) dynamic spillover index based on generalized value-at-risk framework.

Findings

The empirical results provide evidence of heightened equicorrelations at times of financial turmoil. More specifically, the dynamic spillover analysis shows that volatility is transmitted predominantly from crude oil to the other markets and risk transfer among four markets exhibits asymmetries. Spillovers are found to be highly responsive to dramatic events such as the 9/11 terror attack, 2008–2009 global financial crisis and 2014–2016 oil glut.

Practical implications

The results of this study have important practical implications for investors, portfolio managers and energy policymakers as the presence of time-varying co-movements and spillovers suggests the need for dynamic trading strategies. There are also implications regarding risk management practices, as there is evidence of increased volatility transmission at times of financial turmoil and uncertainty. Finally, the results provide insights to policymakers in a better understanding of the spillover dynamics.

Originality/value

This paper investigates the DECOs and spillover effects among crude oil, natural gas, heating oil and gasoline futures markets. To the best of the knowledge, this is one of a few studies that examine co-movements and risk transfer in energy futures in a comprehensive framework.

Details

Studies in Economics and Finance, vol. 37 no. 4
Type: Research Article
ISSN: 1086-7376

Keywords

Book part
Publication date: 24 October 2013

Suk-Joong Kim, Linda Lee and Eliza Wu

This chapter investigates the impact of policy interest rate news from the U.S. Federal Reserve (Fed) and the European Central Bank (ECB) on stock returns and volatilities of U.S…

Abstract

This chapter investigates the impact of policy interest rate news from the U.S. Federal Reserve (Fed) and the European Central Bank (ECB) on stock returns and volatilities of U.S. NYSE and German DAX listed commercial banks. We find that Fed news has the most influence on both U.S. and German listed bank stocks and an unexpected policy rate increase (decrease) lowers (raises) returns and raises volatility in the majority of cases. On the other hand, ECB news generally increases bank stock volatility in the United States but has little impact within its own domestic banking industry. While our results for the U.S. listed banks confirm that their stock prices are more responsive in bad economic times and also during periods of monetary tightening, we find disparities for German banks suggesting that U.S. and European banking industries respond heterogeneously to monetary policy news but the Global Financial Crisis increased the sensitivity of all banks to monetary policy news.

Details

Global Banking, Financial Markets and Crises
Type: Book
ISBN: 978-1-78350-170-0

Keywords

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