Estimating portfolio value at risk by a conditional copula approach in BRICS countries

Abstract : This thesis used daily log returns of indices of BRICS countries from the period of March 11th 2013 to May 16th 2017. Its main focus was to estimate the value at risk (VaR) of a portfolio of the BRICS financial markets using a conditional copula approach. A useful starting point was to apply the model of AR (1)-GARCH (1,1) with t-distribution and AR (1)-GARCH (1,1), using returns of the normal errors for the marginal distribution models in the copula framework. Two copulas, the normal and the symmetric Joe Clayton (SJC) copulas, were estimated as both constant and time-varying. The log likelihood of the time-varying copula was significantly more suitable than the constant copula. The comparison of the performance of the copula models to the benchmark AR (1)-GARCH (1,1) was done using the Christoffersen test. The 99% VaR appeared fairly accurate, suggesting that the VaR models were dependable. The standard level of comparison AR (1)-GARCH (1,1) did not perform well compared to the SJC copula; i.e. the time-varying SJC copula performed better than the benchmark model. The time-varying SJC copula model used to estimate the portfolio VaR also showed a minimum number of exceptions in the back-test. This copula thus meets regulatory capital requirement for investors as stipulated in Basel II.M.Com. (Financial Economics

An Assessment of Contagion Risks in the Banking System Using Non- Parametric and Copula Approaches

This study endeavours to shed some light on the Contagion risk in the Vietnamese banking system. In so doing, we analyse the contagion risk through stock returns on listed commercial banks by employing non-parametric and Copula approaches. A rich set of empirical approaches are employed, including non-parametric (Chi-plots, Kendall-plots) and parametric Copula estimations to define the dependence structure of pairs of daily returns, balanced by a total of 36 copulas with 17,456 observations over the period from July 2006 to September 2017. Our results show that the risk of each individual bank may transmit to other banks through stock returns, which are reflected in their price information. The results also suggest existence of contagion risk and strong dependency in the structure of stock returns of banks under analysis. As a consequence, to avoid negative returns for the portfolio, careful diversification is required while investing in the Vietnamese banking sector, when showing a Clayton relationship (left-tail dependency). Our findings have profound implications for investors, policymakers and authorities responsible for financial stability

Did COVID-19 challenge the volatility of the sustainable stock market? An examination of Asian market

The coronavirus outbreak at the end of 2019 hit many aspects of the financial sector, especially the stock market. This research examines the impacts of the COVID-19 pandemic, exchange rates, gold price, and the Brent oil price on the volatility of the Sustainable Stock Market in Asia. A quantitative research method is applied using average monthly panel data from March 2020 to April 2022, covering the COVID-19 pandemic period. We employed panel regressions and applied Feasible Generalized Least Square (FGLS) in the analysis, which also serves as a robustness check. This study contributes to the literature by examining the variables significantly impacting sustainable investing, particularly in the sustainable stock market. Empirical results find that COVID-19, gold price and the exchange rate have negatively affected sustainable stock market volatility, while the Brent oil price has a positive impact on the volatility of the sustainable stock market. This study's recommendations infer that both investors and managers should consider the increase of COVID-19 cases and frequency-varying exchange rates to the USD on the Asian sustainable stock market volatility

The role of institutions in mitigating the risk of push and pull factors on economic growth

It is widely acknowledge that both push (global) and pull (domestic) factors can be important in driving foreign capital flows. While both the risk from push and pull factors are able to direct or indirectly cripple economic growth, it is essential for the countries to deal and adequately manage both the push and pull factors. The main objective in this study is to analyze the role of institutional quality both political and social institutions in mitigating the potential adverse effects of push and pull factors on growth. We provide new evidence the relationship between political and social institutions, push or pull factors, and economic growth. Generally, our finding indicate that institutions quality play an important role in mitigating several components of both push and pull push factors. Good political institutional, high democracy and stable political institutions positively and significantly offsetting the negative effect of push factors global uncertainty shocks and changes of global growth rate on growth, while weak social problems assist country in alleviating potential severe of destructive global interest rate on country. The results robust using several proxies of political institutions. For pull factor, political stability assist country in reducing negative effect of inflation uncertainty, while social cohesion reduce the detriment of high debt. We confirm that improvement institutional quality both political and social institutions especially political institutions be an imperative strategy in ensuring the effectiveness of policies on mitigating the changes of changes of global factors risk shocks. The policymakers should take advantages from the findings of this research in search for strategy stability on financial and macroeconomic to boost economic growth

The impact of oil and gold price fluctuations on the South African equity market: volatility spillovers and implications for portfolio management

This paper aims to study the impact of gold and oil price fluctuations on the volatility of the South African stock market and its component indices or sectors – namely, the financial, industrial and resource sectors – making use of the asymmetric dynamic conditional correlation (ADCC) generalised autoregressive conditional heteroskedasticity (GARCH) model. Moreover, the study assesses the magnitude of the optimal portfolio weight, hedge ratio and hedge effectiveness for portfolios that are constituted of a pair of assets, namely oil-stock and gold-stock pairs. The findings of the study show that there is significant volatility spillover between the gold and the stock markets, and the oil and stock markets. This finding suggests the importance of the link between futures commodity markets and the stock markets, which is essential for portfolio management. With reference to portfolio optimisation and the possibility of hedging when using the pairs of assets under study, the findings suggest the importance of combining oil and stocks as well as gold and stocks for effective hedging against any risk

The impact of oil and gold price fluctuations on the South African equity market: volatility spillovers and implications for portfolio management

This paper aims to study the impact of gold and oil price fluctuations on the volatility of the South African stock market and its component indices or sectors – namely, the financial, industrial and resource sectors – making use of the asymmetric dynamic conditional correlation (ADCC) generalised autoregressive conditional heteroskedasticity (GARCH) model. Moreover, the study assesses the magnitude of the optimal portfolio weight, hedge ratio and hedge effectiveness for portfolios that are constituted of a pair of assets, namely oil-stock and gold-stock pairs. The findings of the study show that there is significant volatility spillover between the gold and the stock markets, and the oil and stock markets. This finding suggests the importance of the link between futures commodity markets and the stock markets, which is essential for portfolio management. With reference to portfolio optimisation and the possibility of hedging when using the pairs of assets under study, the findings suggest the importance of combining oil and stocks as well as gold and stocks for effective hedging against any risk

Impact of oil prices on stock market performance

The study investigates the impact of oil prices on stock market performance in ten countries, including Canada. The volatility in oil prices and the accompanying swings in stock market performance raised the question of what, if any, is the relationship between these variables. The research seeks to address six strands of the phenomenon. The study evaluates the impact of oil prices on stock performance at the stock market’s aggregate and sector market levels. It establishes the effects of macroeconomic variables on stock market performance. Furthermore, it evaluates the role of the business cycle in the oil price shocks and stock market interface. Lastly, it examines the influence of oil prices on stock market performance in net oil-importing and oil-exporting countries. The empirical investigation uses monthly data from January 2003 to December 2020 and quarterly data from 1990Q1 to 2020Q4. Primary and secondary data were analysed using statistical tools and econometric modelling. The investigation employs the impulse response function, EGARCH and Markov switching models. The thesis concludes that the relationship between oil prices and stock market performance is time-varying, asymmetrical, heterogeneous and complex as several sector or country-specific factors drive the relationship. Specifically, the findings suggest that the response of the stock market sectors to oil price shocks differs substantially, depending on their degree of oil dependence and multiple transmission mechanisms. The findings further indicate that stock returns-generating processes in a net oil-exporting country like Canada exhibited a high degree of persistence in conditional variance, and the modelling of asymmetry was positive. Positive shocks from macroeconomic variables impact the country’s stock market more than negative shocks of the same magnitude. Two structural breaks are identified in the Canadian economy between 1990 and 2020. The data was further divided into two subsamples to reflect the two possible states for an economy, the bear and bull periods. Empirical analysis revealed that GDP, exchange rate, inflation rate, interest rate, and oil prices are significant drivers of the country’s stock market performance in economic contraction. During the expansion era, all the variables considered in the study, excluding GDP, significantly drive stock market performance. Hence, oil prices and stock market relationships tend to improve more during the economic expansion period than during the contraction era. Further analysis affirmed that the impact of oil price shocks is only significant in the top two net oil-importing countries. These findings convey information that guides policymakers in formulating macroeconomic policies, investors and portfolio managers in risk diversification relating to decision-making and investment strategies. The study investigates the impact of oil prices on stock market performance in ten countries, including Canada. The volatility in oil prices and the accompanying swings in stock market performance raised the question of what, if any, is the relationship between these variables. The research seeks to address six strands of the phenomenon. The study evaluates the impact of oil prices on stock performance at the stock market’s aggregate and sector market levels. It establishes the effects of macroeconomic variables on stock market performance. Furthermore, it evaluates the role of the business cycle in the oil price shocks and stock market interface. Lastly, it examines the influence of oil prices on stock market performance in net oil-importing and oil-exporting countries. The empirical investigation uses monthly data from January 2003 to December 2020 and quarterly data from 1990Q1 to 2020Q4. Primary and secondary data were analysed using statistical tools and econometric modelling. The investigation employs the impulse response function, EGARCH and Markov switching models. The thesis concludes that the relationship between oil prices and stock market performance is time-varying, asymmetrical, heterogeneous and complex as several sector or country-specific factors drive the relationship. Specifically, the findings suggest that the response of the stock market sectors to oil price shocks differs substantially, depending on their degree of oil dependence and multiple transmission mechanisms. The findings further indicate that stock returns-generating processes in a net oil-exporting country like Canada exhibited a high degree of persistence in conditional variance, and the modelling of asymmetry was positive. Positive shocks from macroeconomic variables impact the country’s stock market more than negative shocks of the same magnitude. Two structural breaks are identified in the Canadian economy between 1990 and 2020. The data was further divided into two subsamples to reflect the two possible states for an economy, the bear and bull periods. Empirical analysis revealed that GDP, exchange rate, inflation rate, interest rate, and oil prices are significant drivers of the country’s stock market performance in economic contraction. During the expansion era, all the variables considered in the study, excluding GDP, significantly drive stock market performance. Hence, oil prices and stock market relationships tend to improve more during the economic expansion period than during the contraction era. Further analysis affirmed that the impact of oil price shocks is only significant in the top two net oil-importing countries. These findings convey information that guides policymakers in formulating macroeconomic policies, investors and portfolio managers in risk diversification relating to decision-making and investment strategies

Using Conditional Copula to Estimate Value-at-Risk in Vietnam's Foreign Exchange Market

In this paper, we briefly review the basics of copula theory and the problem of estimating Value-at-Risk (VaR) of portfolio composed by several assets. We present two VaR estimation models in which each return series is assumed to follow AR(1)-GARCH(1, 1) model and the innovations are simultaneously generated using Gaussian copula and Student t copula. The presented models are applied to estimate VaR of a portfolio consisting of 6 currencies to VND. The results are compared with results from two VaR estimation models using AR(1)-GARCH(1, 1) model and the innovations are separately generated using univariate standard normal and Student t distribution