Exchange rate volatility and the returns on diversified South African investment portfolios
- Authors: Mulamu, Murendeni
- Date: 2022-04-06
- Subjects: Foreign exchange rates South Africa , Rate of return , Investments , GARCH model , Regression analysis , Autoregressive distributed lag (ARDL) model
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/284581 , vital:56076
- Description: Globalisation has made it much easier to invest in foreign countries. This creates endless options accessible to investors, including exploiting opportunities for investment in international economies. Although foreign investment portfolio diversification provides significant opportunities for financial returns, exchange rate volatility may play a prominent role when investing in foreign markets. Since the introduction of a floating exchange rate system, together with the inflation-targeting monetary policy framework in South Africa, there has been significant volatility in the exchange rate, far more than during the previous dispensations. This, however, creates a strong need to consider how the unpredictable nature of the exchange rate affects these investments. The purpose of this study is to analyse the effect of exchange rate volatility on the returns on diversified South African investment portfolios. This research examined whether there is a homogenous relationship between South African (domestic) portfolios and the internationally diversified portfolios. In addition, the study investigated the long-run relationship between the exchange rate volatility and both domestic portfolios and the internationally diversified portfolios for the period 2007-2019. To achieve these goals, a panel ARDL model was employed. This study found that exchange rate volatility does not account for a significant portion of returns on investment portfolios fluctuations. Moreover, the relationship is not homogenous because returns on domestic investment portfolios react positively to the exchange rate volatility, whereas returns international investment portfolios respond negatively/positively to the exchange rate volatility depending on whether the relationship is short or long run. This study will contribute to the existing literature, and it is important for investors intending to diversify their investment portfolios both domestically and internationally using different mutual funds in South Africa. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2022
- Full Text:
- Date Issued: 2022-04-06
- Authors: Mulamu, Murendeni
- Date: 2022-04-06
- Subjects: Foreign exchange rates South Africa , Rate of return , Investments , GARCH model , Regression analysis , Autoregressive distributed lag (ARDL) model
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/284581 , vital:56076
- Description: Globalisation has made it much easier to invest in foreign countries. This creates endless options accessible to investors, including exploiting opportunities for investment in international economies. Although foreign investment portfolio diversification provides significant opportunities for financial returns, exchange rate volatility may play a prominent role when investing in foreign markets. Since the introduction of a floating exchange rate system, together with the inflation-targeting monetary policy framework in South Africa, there has been significant volatility in the exchange rate, far more than during the previous dispensations. This, however, creates a strong need to consider how the unpredictable nature of the exchange rate affects these investments. The purpose of this study is to analyse the effect of exchange rate volatility on the returns on diversified South African investment portfolios. This research examined whether there is a homogenous relationship between South African (domestic) portfolios and the internationally diversified portfolios. In addition, the study investigated the long-run relationship between the exchange rate volatility and both domestic portfolios and the internationally diversified portfolios for the period 2007-2019. To achieve these goals, a panel ARDL model was employed. This study found that exchange rate volatility does not account for a significant portion of returns on investment portfolios fluctuations. Moreover, the relationship is not homogenous because returns on domestic investment portfolios react positively to the exchange rate volatility, whereas returns international investment portfolios respond negatively/positively to the exchange rate volatility depending on whether the relationship is short or long run. This study will contribute to the existing literature, and it is important for investors intending to diversify their investment portfolios both domestically and internationally using different mutual funds in South Africa. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2022
- Full Text:
- Date Issued: 2022-04-06
Stock market volatility during times of crisis: a comparative analysis of the conditional volatilities of JSE stock indices during the 2007/08 global financial crisis and COVID-19
- Authors: Wang, Zixiao
- Date: 2022-04-06
- Subjects: Stock exchanges , Johannesburg Stock Exchange , Global Financial Crisis, 2008-2009 , COVID-19 (Disease) Economic aspects , Economic forecasting , Stock exchanges and current events , GARCH model
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/284603 , vital:56078
- Description: This research analyses the comparative behaviour of stock market volatility during two crises. The goal of this research is to determine whether assumed cyclical and defensive sectors have either retained or revealed their expected properties during both the Global Financial Crisis (GFC) and COVID-19 by analysing sectoral volatility amid these two crises. Understanding how volatility changes amid crises helps to determine whether the volatility assumptions of diversified investment portfolios for both defensive and cyclical sectors still held given the different causes of each crisis. In turn, this knowledge can assist with risk management and portfolio allocation in stock market investments. The study can also contribute towards the enhancement of financial markets’ resistance against systemic risks through portfolio diversification, and aid government decision-making targeted at tackling the weaknesses of different economic sectors especially in times of overall economic weakness. This research makes use of the GARCH model to analyse a group of daily time series that consists of eleven sectoral indices and one benchmark index, all based on the South African stock markets. These observed series are categorised into two full sample periods, one designated to the Global Financial Crisis (January 2006 to May 2009) and the other for COVID-19 (January 2018 to May 2021). These are further divided into two sets of sub-sample periods, each made up of a pre-crisis and during-crisis. Furthermore, the dummy variables representing the occurrence of structural breaks are inserted into the full sample periods’ conditional variance equations. This is aimed at capturing the asymmetrical impact of the crises themselves on all observed series. Based on the movement of volatility persistency from pre-crisis to during-crisis for both crises, the results show that, firstly, Health Care and Consumer Goods are considered defensive Sectors. Secondly, Banks, Basic Materials, Chemicals, Telecommunications, and Financials are considered cyclical Sectors. Thirdly, Automobiles & Parts, Consumer Services, and Technology are considered indeterminable Sectors due to the inconsistent behaviour of these sectors’ volatility persistency throughout the sub-sample periods of both crises. Overall, according to the average volatility persistency, the observed series for COVID-19’s full sample period are generally less volatile than those of the GFC. However, the sub-sample periods suggest that the observed series for both pre-crisis and during-crisis periods of COVID-19 are more volatile than those same sub-samples of the Global Financial Crisis. Being able to analyse the characteristics of stock market sectors is crucial for risk management and optimal portfolio allocation of stock market investments. This can be achieved through portfolio diversification by investing in a variety of stocks, both cyclical and defensive, and adjusted over time based the needs of stock market investors. Diversified portfolios do not only serve the interests of individual investors, but can also enhance the financial markets’ overall resistance against systemic risks. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2022
- Full Text:
- Date Issued: 2022-04-06
- Authors: Wang, Zixiao
- Date: 2022-04-06
- Subjects: Stock exchanges , Johannesburg Stock Exchange , Global Financial Crisis, 2008-2009 , COVID-19 (Disease) Economic aspects , Economic forecasting , Stock exchanges and current events , GARCH model
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/284603 , vital:56078
- Description: This research analyses the comparative behaviour of stock market volatility during two crises. The goal of this research is to determine whether assumed cyclical and defensive sectors have either retained or revealed their expected properties during both the Global Financial Crisis (GFC) and COVID-19 by analysing sectoral volatility amid these two crises. Understanding how volatility changes amid crises helps to determine whether the volatility assumptions of diversified investment portfolios for both defensive and cyclical sectors still held given the different causes of each crisis. In turn, this knowledge can assist with risk management and portfolio allocation in stock market investments. The study can also contribute towards the enhancement of financial markets’ resistance against systemic risks through portfolio diversification, and aid government decision-making targeted at tackling the weaknesses of different economic sectors especially in times of overall economic weakness. This research makes use of the GARCH model to analyse a group of daily time series that consists of eleven sectoral indices and one benchmark index, all based on the South African stock markets. These observed series are categorised into two full sample periods, one designated to the Global Financial Crisis (January 2006 to May 2009) and the other for COVID-19 (January 2018 to May 2021). These are further divided into two sets of sub-sample periods, each made up of a pre-crisis and during-crisis. Furthermore, the dummy variables representing the occurrence of structural breaks are inserted into the full sample periods’ conditional variance equations. This is aimed at capturing the asymmetrical impact of the crises themselves on all observed series. Based on the movement of volatility persistency from pre-crisis to during-crisis for both crises, the results show that, firstly, Health Care and Consumer Goods are considered defensive Sectors. Secondly, Banks, Basic Materials, Chemicals, Telecommunications, and Financials are considered cyclical Sectors. Thirdly, Automobiles & Parts, Consumer Services, and Technology are considered indeterminable Sectors due to the inconsistent behaviour of these sectors’ volatility persistency throughout the sub-sample periods of both crises. Overall, according to the average volatility persistency, the observed series for COVID-19’s full sample period are generally less volatile than those of the GFC. However, the sub-sample periods suggest that the observed series for both pre-crisis and during-crisis periods of COVID-19 are more volatile than those same sub-samples of the Global Financial Crisis. Being able to analyse the characteristics of stock market sectors is crucial for risk management and optimal portfolio allocation of stock market investments. This can be achieved through portfolio diversification by investing in a variety of stocks, both cyclical and defensive, and adjusted over time based the needs of stock market investors. Diversified portfolios do not only serve the interests of individual investors, but can also enhance the financial markets’ overall resistance against systemic risks. , Thesis (MCom) -- Faculty of Commerce, Economics and Economic History, 2022
- Full Text:
- Date Issued: 2022-04-06
Stochastic models in finance
- Authors: Mazengera, Hassan
- Date: 2017
- Subjects: Finance -- Mathematical models , C++ (Computer program language) , GARCH model , Lebesgue-Radon-Nikodym theorems , Radon measures , Stochastic models , Stochastic processes , Stochastic processes -- Computer programs , Martingales (Mathematics) , Pricing -- Mathematical models
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/162724 , vital:40976
- Description: Stochastic models for pricing financial securities are developed. First, we consider the Black Scholes model, which is a classic example of a complete market model and finally focus on Lévy driven models. Jumps may render the market incomplete and are induced in a model by inclusion of a Poisson process. Lévy driven models are more realistic in modelling of asset price dynamics than the Black Scholes model. Martingales are central in pricing, especially of derivatives and we give them the desired attention in the context of pricing. There are an increasing number of important pricing models where analytical solutions are not available hence computational methods come in handy, see Broadie and Glasserman (1997). It is also important to note that computational methods are also applicable to models with analytical solutions. We computationally value selected stochastic financial models using C++. Computational methods are also used to value or price complex financial instruments such as path dependent derivatives. This pricing procedure is applied in the computational valuation of a stochastic (revenue based) loan contract. Derivatives with simple pay of functions and models with analytical solutions are considered for illustrative purposes. The Black-Scholes P.D.E is complex to solve analytically and finite difference methods are widely used. Explicit finite difference scheme is considered in this thesis for computational valuation of derivatives that are modelled by the Black-Scholes P.D.E. Stochastic modelling of asset prices is important for the valuation of derivatives: Gaussian, exponential and gamma variates are simulated for the valuation purposes.
- Full Text:
- Date Issued: 2017
- Authors: Mazengera, Hassan
- Date: 2017
- Subjects: Finance -- Mathematical models , C++ (Computer program language) , GARCH model , Lebesgue-Radon-Nikodym theorems , Radon measures , Stochastic models , Stochastic processes , Stochastic processes -- Computer programs , Martingales (Mathematics) , Pricing -- Mathematical models
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/162724 , vital:40976
- Description: Stochastic models for pricing financial securities are developed. First, we consider the Black Scholes model, which is a classic example of a complete market model and finally focus on Lévy driven models. Jumps may render the market incomplete and are induced in a model by inclusion of a Poisson process. Lévy driven models are more realistic in modelling of asset price dynamics than the Black Scholes model. Martingales are central in pricing, especially of derivatives and we give them the desired attention in the context of pricing. There are an increasing number of important pricing models where analytical solutions are not available hence computational methods come in handy, see Broadie and Glasserman (1997). It is also important to note that computational methods are also applicable to models with analytical solutions. We computationally value selected stochastic financial models using C++. Computational methods are also used to value or price complex financial instruments such as path dependent derivatives. This pricing procedure is applied in the computational valuation of a stochastic (revenue based) loan contract. Derivatives with simple pay of functions and models with analytical solutions are considered for illustrative purposes. The Black-Scholes P.D.E is complex to solve analytically and finite difference methods are widely used. Explicit finite difference scheme is considered in this thesis for computational valuation of derivatives that are modelled by the Black-Scholes P.D.E. Stochastic modelling of asset prices is important for the valuation of derivatives: Gaussian, exponential and gamma variates are simulated for the valuation purposes.
- Full Text:
- Date Issued: 2017
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