scholarly journals Time-Varying Conditional Co-movement between Inter-Sector Stock Returns: Evidence from Ghana Stock Market

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Thomas Appiah ◽  
Abednego Forson
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Time Varying ◽  
Conditional Correlation ◽  
Domestic Markets ◽  
Dynamic Conditional Correlation ◽  
Fund Managers ◽  
Diversification Strategies ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Sector Returns

Investors generally exhibit home bias with regards to their investment destinations. To diversify their portfolio, such investors invest in different sectors within the domestic economy. However, such behaviour could be counter-productive in periods of increased co-movement of assets returns.  In this paper, we examine the inter-sector stock return co-movement among the major sectors of the Ghanaian economy with the view to shedding some light on the nature of assets return correlations and its implications for portfolio diversification.  A sample of 332 weekly observations of stock returns of five major sectors within the Ghanaian economy is used to undertake the analysis. Dynamic Conditional Correlation - Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) techniques are applied to the weekly stock return series from January 2010 to June 2017. The DCC-GARCH model was estimated with correlation targeting and asymmetric DCC. We find dynamic conditional correlation among stock returns of all the sectors, implying that the correlation between the sector returns is time-varying. This result challenges the assumption of constant correlation among stock returns of different sectors in the domestic markets. We also find that the conditional correlation between returns of the various sectors ranges from 0.234 to 0.998, which indicates medium to very high interdependence among the stock returns. Based on the result of this study, we propose that fund managers and investors should not limit their diversification strategies to inter-sector investments since in periods of uncertainty, the ability of the investor to enjoy diversification benefits is seriously undermined.

scholarly journals Monetary Stability and Stock Returns: A Bivariate Generalized Autoregressive Conditional Heteroscedasticity Modelling Study

2015 ◽  
Vol 5 (2) ◽  
pp. 1 ◽  
Author(s):  
Ning Zeng
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Inflation Rate ◽  
Common Stock ◽  
Conditional Correlation ◽  
Monetary Stability ◽  
The Core ◽  
The Us ◽  
Autoregressive Conditional Heteroscedasticity

<p class="ber"><span lang="EN-GB">This paper employs a constant conditional correlation bivariate EGARCH-in-mean model to investigate interactions among the rate of inflation, stock returns and their respective volatilities. This approach is capable of accommodating all the possible causalities among the four variables simultaneously, and therefore could deliver contemporary evidence of the nexus between monetary stability and stock market. The postwar dataset of the US inflation and stock returns is divided into pre- and post- Volcker period and the estimation results show some significant changes of inflation-stock return relation, as well as indirect links between two volatilities. The core findings in this study suggest that promoting monetary stability contributes to more mutual interactions among the four variables, in particular, common stock is a more effective hedge against inflation, and the level of inflation rate is central to explaining the relation between the two volatilities.</span></p>

scholarly journals Value-at-Risk Analysis for Measuring Stochastic Volatility of Stock Returns: Using GARCH-Based Dynamic Conditional Correlation Model

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402110057
Author(s):  
Fahim Afzal ◽  
Pan Haiying ◽  
Farman Afzal ◽  
Asif Mahmood ◽  
Amir Ikram
Keyword(s):  
At Risk ◽  
Stock Returns ◽  
Stock Markets ◽  
Value At Risk ◽  
Stock Exchange ◽  
Integrated Approach ◽  
Actual Behavior ◽  
Time Varying ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation

To assess the time-varying dynamics in value-at-risk (VaR) estimation, this study has employed an integrated approach of dynamic conditional correlation (DCC) and generalized autoregressive conditional heteroscedasticity (GARCH) models on daily stock return of the emerging markets. A daily log-returns of three leading indices such as KSE100, KSE30, and KSE-ALL from Pakistan Stock Exchange and SSE180, SSE50 and SSE-Composite from Shanghai Stock Exchange during the period of 2009–2019 are used in DCC-GARCH modeling. Joint DCC parametric results of stock indices show that even in the highly volatile stock markets, the bivariate time-varying DCC model provides better performance than traditional VaR models. Thus, the parametric results in the DCC-GRACH model indicate the effectiveness of the model in the dynamic stock markets. This study is helpful to the stockbrokers and investors to understand the actual behavior of stocks in dynamic markets. Subsequently, the results can also provide better insights into forecasting VaR while considering the combined correlational effect of all stocks.

scholarly journals The relationship between Google search interest for pulmonary symptoms and COVID-19 cases using dynamic conditional correlation analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Halit Cinarka ◽  
Mehmet Atilla Uysal ◽  
Atilla Cifter ◽  
Elif Yelda Niksarlioglu ◽  
Aslı Çarkoğlu
Keyword(s):  
Case Reports ◽  
Time Varying ◽  
Conditional Correlation ◽  
Web Based ◽  
Specific Symptom ◽  
Sliding Windows ◽  
Dynamic Conditional Correlation ◽  
The United Kingdom ◽  
Correlation Models ◽  
Google Search

AbstractThis study aims to evaluate the monitoring and predictive value of web-based symptoms (fever, cough, dyspnea) searches for COVID-19 spread. Daily search interests from Turkey, Italy, Spain, France, and the United Kingdom were obtained from Google Trends (GT) between January 1, 2020, and August 31, 2020. In addition to conventional correlational models, we studied the time-varying correlation between GT search and new case reports; we used dynamic conditional correlation (DCC) and sliding windows correlation models. We found time-varying correlations between pulmonary symptoms on GT and new cases to be significant. The DCC model proved more powerful than the sliding windows correlation model. This model also provided better at time-varying correlations (r ≥ 0.90) during the first wave of the pandemic. We used a root means square error (RMSE) approach to attain symptom-specific shift days and showed that pulmonary symptom searches on GT should be shifted separately. Web-based search interest for pulmonary symptoms of COVID-19 is a reliable predictor of later reported cases for the first wave of the COVID-19 pandemic. Illness-specific symptom search interest on GT can be used to alert the healthcare system to prepare and allocate resources needed ahead of time.

Internet gambling stock returns: empirical evidence from the UK

2017 ◽  
Vol 13 (1) ◽  
pp. 36-49
Author(s):  
Daniel Perez Liston
Keyword(s):  
Stock Returns ◽  
Multivariate Garch ◽  
Online Gambling ◽  
Future Research ◽  
Time Varying ◽  
Conditional Correlation ◽  
Socially Responsible ◽  
Content Type ◽  
Starting Point ◽  
The Uk

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.

scholarly journals Time-Varying Risk and the Relation between Idiosyncratic Risk and Stock Return

2021 ◽  
Vol 14 (9) ◽  
pp. 432
Author(s):  
Chengbo Fu
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Idiosyncratic Risk ◽  
Point Of View ◽  
Time Varying ◽  
Total Risk ◽  
Risk Return ◽  
Long Run ◽  
Book To Market Ratio ◽  
The 1960S

This paper studies the historical time-varying dynamics of risk for individual stocks in the U.S. market. Total risk of an individual stock is decomposed into two components, systematic risk and idiosyncratic risk, and both components are studied separately. We start from the historical trend in the magnitude of risk and then turn to the relation between idiosyncratic risk and stock returns. The result shows that both components of risk for individual stocks are changing over time. They increased from the 1960s to the 1990s/2000s and then declined until today. This paper also studies the risk-return tradeoff by investigating the relation between idiosyncratic risk and stock return in the long run. Stocks are sorted into portfolios for analysis and the whole sample period is further decomposed into decades for subgroup analysis. Multivariable regressions are used to study this relation as we control for beta, size, book-to-market ratio, momentum and liquidity. From a historical point of view, we show that the relation between idiosyncratic risk and stock return is time-varying, and it did not exist in certain decades. The results indicate that the risk-return tradeoff also varied in history.

scholarly journals A Multivariate Analysis of the Effects of Structural Breaks on Stock Return Volatility Persistence: The Case of the US and Japan

2019 ◽  
Vol 10 (3) ◽  
pp. 39
Author(s):  
Chikashi Tsuji
Keyword(s):  
Multivariate Analysis ◽  
Stock Returns ◽  
Stock Return ◽  
Structural Breaks ◽  
Structural Break ◽  
Return Volatility ◽  
Time Varying ◽  
Stock Return Volatility ◽  
Volatility Persistence ◽  
The Us

This paper quantitatively inspects the effects of structural breaks in stock returns on their volatility persistence by using the stock return data of the US and Japan. More concretely, applying the diagonal BEKK-MGARCH model with and without structural break dummies to the returns of S&P 500 and TOPIX, we reveal the following interesting findings. (1) First, we clarify that for both the US and Japanese stock returns, the values of the GARCH parameters, namely, the values of the volatility persistence parameters in the diagonal BEKK-MGARCH models decrease when we include the structural break dummies in the models. (2) Second, we further find that interestingly, during the Lehman crisis in 2008, the estimated time-varying volatilities from the diagonal BEKK-MGARCH model with structural break dummies are slightly higher than those from the no structural break dummy model. (3) Third, we furthermore reveal that also very interestingly, the estimated time-varying correlations from the diagonal BEKK-MGARCH model with no structural break dummy are slightly higher than those from the structural break dummy model.

scholarly journals Does Gold Act as a Hedge or a Safe Haven against Equity and Currency in Asia?

2018 ◽  
Vol 20 (1) ◽  
pp. 105-118 ◽  
Author(s):  
Muhammad Aftab ◽  
Syed Zulfiqar Ali Shah ◽  
Izlin Ismail
Keyword(s):  
Financial Markets ◽  
National Currency ◽  
Currency Markets ◽  
Safe Haven ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
The Us ◽  
Us Dollar ◽  
Managing Risk ◽  
Autoregressive Conditional Heteroscedasticity

In recent years, uncertainty in financial markets has stimulated the need to explore alternative avenues for safeguarding wealth and managing risk. In this strand of research, gold has been particularly important due to its potential to mitigate risk and preserve wealth. This study investigates gold behaviour against equities and currencies in three regions across Asia. We follow Engle’s (2002) dynamic conditional correlation-multivariate generalized autoregressive conditional heteroscedasticity (DCC-MGARCH) model to test the gold link with equity and currency markets. We use a weekly series of exchange rate (national currency/the US dollar), equity and gold prices in national currency over the weekly period, 1995–2013. The sample consists of 12 countries covering East Asia, South Asia and Southeast Asia. Findings suggest that gold is just a diversifier against stocks in the Asian economies except in Korea, Singapore and Thailand. However, gold acts as a hedge and safe haven against Asian currencies—except China and Hong Kong—thus still preserving its monetary role.

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