Search results
1 – 10 of over 3000The purpose of this paper is to determine and contrast the risk mitigating effectiveness from optimal multiproduct time-varying hedge ratios, applied to the margin of a cattle…
Abstract
Purpose
The purpose of this paper is to determine and contrast the risk mitigating effectiveness from optimal multiproduct time-varying hedge ratios, applied to the margin of a cattle feedlot operation, over single commodity time-varying and naive hedge ratios.
Design/methodology/approach
A parsimonious regime-switching dynamic correlations (RSDC) model is estimated in two-stages, where the dynamic correlations among prices of numerous commodities vary proportionally between two different regimes/levels. This property simplifies estimation methods for a large number of parameters involved.
Findings
There is significant evidence that resulting simultaneous correlations among the prices (spot and futures) for each commodity attain different levels along the time-series. Second, for in and out-of-sample data there is a substantial reduction in the operation's margin variance provided from both multiproduct and single time-varying optimal hedge ratios over naive hedge ratios. Lastly, risk mitigation is attained at a lower cost given that average optimal multiproduct and single time-varying hedge ratios obtained for corn, feeder cattle and live cattle are significantly below the naive full hedge ratio.
Research limitations/implications
The application studied is limited in that once a hedge position has been set at a particular period, it is not possible to modify or update at a subsequent period.
Practical implications
Agricultural producers, specifically cattle feeders, may profit from a tool using improved techniques to determine hedge ratios by considering a larger amount of up-to-date information. Moreover, these agents may apply hedge ratios significantly lower than one and thus mitigate risk at lower costs.
Originality/value
Feedlot operators will benefit from the potential implementation of this parsimonious RSDC model for their hedging operations, as it provides average optimal hedge ratios significantly lower than one and sizeable advantages in margin risk mitigation.
Details
Keywords
Tien Foo Sing and Zhuang Yao Tan
Understanding correlations between stock and direct real estate returns, which is the key factor that determines diversification benefits in a portfolio, helps formulate and…
Abstract
Purpose
Understanding correlations between stock and direct real estate returns, which is the key factor that determines diversification benefits in a portfolio, helps formulate and implement better investors' asset allocation and risk management strategies. The past studies find that direct real estate returns have a low unconditionally (long‐run) correlation with the returns of equities. However, assuming that such correlation is constant throughout all periods is implausible. The purpose of this study is to test the time‐varying correlations of returns between general stocks and direct real estate.
Design/methodology/approach
This study uses the dynamic conditional correlation (DCC) model, which is a simplified version of the multivariate generalised autoregressive conditional heteroskedasticity (GARCH) model, proposed by Engle to test the time‐varying correlations between stock and direct real estate returns in six markets, which include the USA, the UK, Ireland, Australia, Hong Kong and Singapore.
Findings
The empirical results show significant time‐varying effects in the conditional covariance between stock returns and direct real estate returns. The results vary across different real estate sub‐sectors, and across different countries. It is observed that the conditional covariance increases in the boom markets, but becomes weaker in the post‐crisis periods. The authors observed significant jumps in the conditional covariance between the two asset markets in Singapore and Hong Kong in the post‐1977 Asian Financial crisis periods and in the post‐2007 US Sub‐prime crisis periods.
Originality/value
The past studies find that direct real estate returns have a low unconditionally (long‐run) correlation with the returns of equities. However, assuming that such correlation is constant throughout all periods is implausible. This study fills in the gap by using the dynamic conditional correlation models to allow for time‐varying effects in the correlations between stock and real estate returns.
Details
Keywords
The purpose of this paper is to investigate the time series behavior of co‐movements among 11 European real estate securities markets, with each other as well as between…
Abstract
Purpose
The purpose of this paper is to investigate the time series behavior of co‐movements among 11 European real estate securities markets, with each other as well as between country‐averages, over the sample period from January 1999 to January 2010 by utilizing the asymmetric dynamic conditional correlation (ADCC) technique, long‐memory tests and multiple structural break methodology.
Design/methodology/approach
First the ADCC from the multivariate GJR‐GARCH model is used to estimate the pair‐wise conditional correlations between the 11 securitized real estate markets. Then, the 11 country‐average conditional correlation series is subject to a battery of four long‐memory tests to form an “on the balance of evidence” picture; the semi‐parametric Geweke and Porter‐Hudak procedure and Robinson test, as well as the non‐parametric Hurst‐Mandelbrot R/S and Lo's modified R/S tests. Finally, the Bai and Perron's multiple structural break methodology seeks to test whether the average conditional correlations are subject to regime switching via the detection of breaks in the co‐movements of real estate securities returns.
Findings
Low to moderate conditional correlations are found for these European real estate securities market and a higher level of correlation in the aftermath of the global financial crisis. The long‐memory correlation effect is present for nine European real estate securities markets. In addition, the conditional correlations are subject to regime switching with two structural breaks in four country‐average correlation series. Across the regimes, a higher level of correlation is linked to a higher level of volatility and a lower level of return, and this happened around the global financial crisis period.
Research limitations/implications
The findings that national real estate securities correlations exhibit time‐varying and asymmetric behavior can help investors understand how real estate securities will co‐move in different market scenarios (e.g. “crisis” and “non‐crisis” times). Moreover, the process of dynamic covariance analysis and forecasting (the ultimate objective in portfolio management) should not rely too much on short‐term autoregressive moving average models. Instead, a combination of some appropriate long‐range dependence models and regime‐switching specifications is needed.
Originality/value
This paper offers useful insights into the time series behavior of average dynamic conditional correlations in European public property markets.
Details
Keywords
Existing multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models either impose strong restrictions on the parameters or do not guarantee a…
Abstract
Existing multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models either impose strong restrictions on the parameters or do not guarantee a well-defined (positive-definite) covariance matrix. I discuss the main multivariate GARCH models and focus on the BEKK model for which it is shown that the covariance and correlation is not adequately specified under certain conditions. This implies that any analysis of the persistence and the asymmetry of the correlation is potentially inaccurate. I therefore propose a new Flexible Dynamic Correlation (FDC) model that parameterizes the conditional correlation directly and eliminates various shortcomings. Most importantly, the number of exogenous variables in the correlation equation can be flexibly augmented without risking an indefinite covariance matrix. Empirical results of daily and monthly returns of four international stock market indices reveal that correlations exhibit different degrees of persistence and different asymmetric reactions to shocks than variances. In addition, I find that correlations do not always increase with jointly negative shocks implying a justification for international portfolio diversification.
Joseph H. Haslag and Yu-Chin Hsu
In this chapter, we examine the relationship between the cyclical components of output, the price level and the inflation rate. During the post-war period, there is a negative…
Abstract
In this chapter, we examine the relationship between the cyclical components of output, the price level and the inflation rate. During the post-war period, there is a negative correlation between output and the price level and a positive correlation between output and the inflation rate. A phase shift in the cyclical component between output and the price level can account for these two facts. The phase shift is consistent with movements in the price level Granger causes movements in output. In addition, we consider time-varying correlations between the two pairs of series. Spectral analysis suggest the price and output have different wavelengths, but the difference is not statistically significant.
Details
Keywords
Antonios Antoniou, Gioia M. Pescetto and Ibrahim Stevens
The paper seeks to investigate conditional correlations and conditional volatility spillovers across international stock markets and industrial sectors from the perspective of the…
Abstract
Purpose
The paper seeks to investigate conditional correlations and conditional volatility spillovers across international stock markets and industrial sectors from the perspective of the UK investor.
Design/methodology/approach
Utilizing the DCC model, the paper extracts the time‐varying conditional correlations between the UK, US and European stock markets and industrial sectors. It also uses the multivariate generalized autoregressive conditional heteroscedasticity (MVGARCH) to assess the transmission of volatility from the US and European stock markets to the UK.
Findings
The findings suggest that the UK equity market is more integrated with Europe, in terms of both aggregate stock markets and sectors. Correlations are higher during bear markets and tend to fall during periods of recovery. The sectoral analysis also provides interesting insights into the dynamics of volatility transmission across sectors.
Research limitations/implications
The results suggest that the search for a better understanding of the dynamics of correlations between markets and sectors must continue.
Practical implications
The investigation raises interesting questions for investors and regulators, as well as theoretical finance. For example, the finding that correlations increase in bear markets suggests that hedging strategies need to be revisited. The existence of sectoral idiosyncratic volatility offers further evidence that arbitrage may at times become more risky and thus limited.
Originality/value
The findings from analysing both market‐wide and sectoral integration raises the overarching question of whether studies of market integration and portfolio diversification, as well as the authorities overseeing financial stability, should be focusing on sectoral rather than market‐wide analysis.
Details
Keywords
This paper investigates the impact of a change in economic policy uncertainty
Abstract
Purpose
This paper investigates the impact of a change in economic policy uncertainty
Design/methodology/approach
The paper uses Engle's (2009) dynamic conditional correlation (DCC) model and Chiang's (1988) rolling correlation model to generate correlations of asset returns over time and analyzes their responses to
Findings
Evidence shows that stock-bond return correlations are negatively correlated to
Research limitations/implications
The findings are based entirely on the data for China's asset markets; further research may expand this analysis to other emerging markets, depending on the availability of GPR indices.
Practical implications
Evidence suggests that the performance of the Chinese market differs from advanced markets. This study shows that gold is a safe haven and can be viewed as an asset to hedge against policy uncertainty and geopolitical risk in Chinese financial markets.
Social implications
This study identify the special role for the gold prices in response to the economic policy uncertainty and the geopolitical risk. Evidence shows that stock and bond return correlation is negatively related to the ΔEPU and support the flight-to-quality hypothesis. However, the stock-gold return correlation is positively related to |ΔGPR|, resulting from the income or wealth effect.
Originality/value
The presence of a dynamic correlations between stock-bond and stock-gold relations in response to
Details
Keywords
The purpose of this paper is to quantify beta for an online gambling portfolio in the UK and investigates whether it is time-varying. It also examines the dynamic correlations of…
Abstract
Purpose
The purpose of this paper is to quantify beta for an online gambling portfolio in the UK and investigates whether it is time-varying. It also examines the dynamic correlations of the online gambling portfolio with both the market and socially responsible portfolios. In addition, this paper documents the effect of important UK gambling legislation on the betas and correlations of the online gambling portfolio.
Design/methodology/approach
This study uses static and time-varying models (e.g. rolling regressions, multivariate GARCH models) to estimate betas and correlations for a portfolio of UK online gambling stocks.
Findings
This study finds that beta for the online gambling portfolio is less than 1, indicative of defensiveness toward the market, a result that is consistent with prior literature for sin stocks. In addition, the conditional correlation between the market and online gambling portfolio is small when compared to the correlation of the market and socially responsible portfolios. Findings suggest that the adoption of the Gambling Act 2005 increases the conditional correlation between the market and online gambling portfolio and it also increases the conditional betas for the online gambling portfolio.
Research limitations/implications
This paper serves as a starting point for future research on online gambling stocks. Going forward, studies can focus on the financial performance or accounting performance of online gambling stocks.
Originality/value
This empirical investigation provides insight into the risk characteristics of publicly listed online gambling companies in the UK.
Weiou Wu and David G. McMillan
The purpose of this paper is to examine the dynamic dependence structure in credit risk between the money market and the derivatives market during 2004-2009. The authors use the…
Abstract
Purpose
The purpose of this paper is to examine the dynamic dependence structure in credit risk between the money market and the derivatives market during 2004-2009. The authors use the TED spread to measure credit risk in the money market and CDS index spread for the derivatives market.
Design/methodology/approach
The dependence structure is measured by a time-varying Gaussian copula. A copula is a function that joins one-dimensional distribution functions together to form multivariate distribution functions. The copula contains all the information on the dependence structure of the random variables while also removing the linear correlation restriction. Therefore, provides a straightforward way of modelling non-linear and non-normal joint distributions.
Findings
The results show that the correlation between these two markets while fluctuating with a general upward trend prior to 2007 exhibited a noticeably higher correlation after 2007. This points to the evidence of credit contagion during the crisis. Three different phases are identified for the crisis period which sheds light on the nature of contagion mechanisms in financial markets. The correlation of the two spreads fell in early 2009, although remained higher than the pre-crisis level. This is partly due to policy intervention that lowered the TED spread while the CDS spread remained higher due to the Eurozone sovereign debt crisis.
Originality/value
The paper examines the relationship between the TED and CDS spreads which measure credit risk in an economy. This paper contributes to the literature on dynamic co-movement, contagion effects and risk linkages.
This paper investigates the influence of three different sentiment indicators on the time-varying stock–bond correlation of 15 countries during the global crisis period of the…
Abstract
Purpose
This paper investigates the influence of three different sentiment indicators on the time-varying stock–bond correlation of 15 countries during the global crisis period of the coronavirus disease 2019 (COVID-19) pandemic.
Design/methodology/approach
The author uses the time-varying correlation estimated using the autoregressive moving average -dynamic conditional correlation - generalised autoregressive conditional heteroskedasticity (ARMA-DCC-GARCH) model to achieve this aim. The impact of investor sentiment on the stock–bond correlation was analysed using the Markov regime-switching regression.
Findings
The study results show that the sentiment indicators of fear, uncertainty and distress have a pronounced negative impact on the stock–bond correlation. They further provide evidence of a strong regime effect on the stock–bond correlation with sentiment indicators.
Practical implications
The paper has a relevant impact on policymakers and fund managers. First, the policymakers now have more insightful evidence of how the stock and bond markets react during crises. Second, the fund managers need to focus on behavioural variables as they may be driving factors in crisis periods that may impair portfolio management.
Originality/value
To the best of my knowledge, the paper is the first to throw light on the behaviour of the stock–bond correlation for 15 countries during the COVID-19 period.
Details