An empirical analysis of the use of the can–do futures in agricultural commodity silo auction market : the case of the South African hedge funds
- Authors: Mataboge, Mpho
- Date: 2017
- Subjects: Hedge funds - South Africa , Johannesburg Stock Exchange , Basel III (2010)
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/271980 , uj:28938
- Description: M.Com. (Financial Economics) , Abstract: Since the 2008/09 financial crisis, hedge funds have been criticised for their excessive risk taking and lack of transparency involved in their trading strategies, facilitated by OTC derivatives. Basel III guidelines saw countries adopting stricter regulations to control for these risks, which led to increased costs of leverage – or initial margin – associated with the use of OTC derivatives. In addition, these regulations prohibit the ownership of physical commodities for South African hedge funds in particular. These regulations make it difficult for a South African hedge fund to participate in the JSE’s silo auction market for profit making opportunities. This study demonstrates a practical application of how a product offering from the JSE, called the ‘can-do’ future, allows hedge funds to participate in this market, thereby allowing them to trade basis. The study finds that initial margin is a key feature in profit making. Comparing the initial margin set by the JSE, and calculating using Basel guidelines, it appears cheaper to obtain leverage using an exchange cleared future such as the can-do, compared to a similar type of OTC derivative. As banks are not bound to follow Basel guidelines, the study goes further, to explore how initial margin calculated using 1-day VaR estimated by Historical simulation, Parametric and Monte-Carlo simulation methods compare. It is revealed that, should a bank opt to use these alternate methods of quantifying initial margin, the Historical method produces the cheapest and most accurate initial margin.
- Full Text:
- Authors: Mataboge, Mpho
- Date: 2017
- Subjects: Hedge funds - South Africa , Johannesburg Stock Exchange , Basel III (2010)
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/271980 , uj:28938
- Description: M.Com. (Financial Economics) , Abstract: Since the 2008/09 financial crisis, hedge funds have been criticised for their excessive risk taking and lack of transparency involved in their trading strategies, facilitated by OTC derivatives. Basel III guidelines saw countries adopting stricter regulations to control for these risks, which led to increased costs of leverage – or initial margin – associated with the use of OTC derivatives. In addition, these regulations prohibit the ownership of physical commodities for South African hedge funds in particular. These regulations make it difficult for a South African hedge fund to participate in the JSE’s silo auction market for profit making opportunities. This study demonstrates a practical application of how a product offering from the JSE, called the ‘can-do’ future, allows hedge funds to participate in this market, thereby allowing them to trade basis. The study finds that initial margin is a key feature in profit making. Comparing the initial margin set by the JSE, and calculating using Basel guidelines, it appears cheaper to obtain leverage using an exchange cleared future such as the can-do, compared to a similar type of OTC derivative. As banks are not bound to follow Basel guidelines, the study goes further, to explore how initial margin calculated using 1-day VaR estimated by Historical simulation, Parametric and Monte-Carlo simulation methods compare. It is revealed that, should a bank opt to use these alternate methods of quantifying initial margin, the Historical method produces the cheapest and most accurate initial margin.
- Full Text:
Dependence structure and insurance credit default swaps
- Mudiangombe Mudiangombe, Benjamin
- Authors: Mudiangombe Mudiangombe, Benjamin
- Date: 2017
- Subjects: Credit , Financial risk management. , Derivative securities
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/271650 , uj:28896
- Description: Abstract: We examine the dependence structure of credit default swap (CDS) indices in the pairs of different markets of the United Kingdom (UK), Eurozone (EU) and United States (US) insurance industries during the period of August 2004 to February 2015. We applied the Archimedean Clayton copula to model the lower tail and the Gumbel copula to model the upper tail of the empirical distributions. The empirical results show a significant dependence structure for both constant and time-varying copulas, implying the co-movement in the pairs of markets during the study period, influencing the contagion risk. The highest tail dependence and positive adjustment parameters seen in crisis and debt-crisis in the lower regime explains the link between these markets. The crucial findings show confirmation of asymmetric tail dependence proposing the propagation of risks of default among UK, EU and US markets. The conditional tail of the time-varying dependence structure explains the behaviour of dependence better than the constant level. This finding is robust when measuring the evolution of the dependence structure over time. The results are consistent for risk managers and investors to select the portfolio investment in different markets during stress period. , M.Com. (Financial Economics)
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- Authors: Mudiangombe Mudiangombe, Benjamin
- Date: 2017
- Subjects: Credit , Financial risk management. , Derivative securities
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/271650 , uj:28896
- Description: Abstract: We examine the dependence structure of credit default swap (CDS) indices in the pairs of different markets of the United Kingdom (UK), Eurozone (EU) and United States (US) insurance industries during the period of August 2004 to February 2015. We applied the Archimedean Clayton copula to model the lower tail and the Gumbel copula to model the upper tail of the empirical distributions. The empirical results show a significant dependence structure for both constant and time-varying copulas, implying the co-movement in the pairs of markets during the study period, influencing the contagion risk. The highest tail dependence and positive adjustment parameters seen in crisis and debt-crisis in the lower regime explains the link between these markets. The crucial findings show confirmation of asymmetric tail dependence proposing the propagation of risks of default among UK, EU and US markets. The conditional tail of the time-varying dependence structure explains the behaviour of dependence better than the constant level. This finding is robust when measuring the evolution of the dependence structure over time. The results are consistent for risk managers and investors to select the portfolio investment in different markets during stress period. , M.Com. (Financial Economics)
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Dynamic portfolio insurance and tactical asset allocation on the JSE
- Authors: Mngomezulu, Zwelakhe Sizwe
- Date: 2016
- Subjects: Portfolio management , Asset allocation , Financial risk management , Options (Finance) - Prices - Mathematical models
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/245956 , uj:25487
- Description: M.Com. (Financial Economics) , Abstract: The pressing question on the minds of academics and investment professionals is whether portfolio managers can evidently protect investors’ capital during a period of economic downturn and provide superior returns with a minimum level of risk. This study attempts to answer this question by evaluating the performance of portfolio insurance methods using different asset classes traded on the local Johannesburg Stock Exchange and other global markets. The chosen data period for evaluation starts from 02 June 2004 to 31 December 2013. The study compares insured portfolios (made up of two methods: the Option-Based Portfolio Insurance and the Constant Proportion Portfolio Insurance) with uninsured portfolios made of these asset classes in order to demonstrate the benefit of portfolio insurance in protecting investors’ capital during both bull and bear markets. The study makes use of different asset allocation approaches including buy and hold, risk parity, minimum variance, and momentum in order to build an optimal uninsured portfolio. The results of the study show that the minimum variance approach of the Constant Proportion Portfolio Insurance strategy with a static multiplier of m=2 consistently outperforms uninsured and the Option-Based Portfolio Insurance portfolios. It is argued that this outperformance might be due to holding risky assets with lower volatility. Furthermore, when a dynamic multiplier is used, it was found that the risk parity approach for the Constant Proportion Portfolio Insurance results in the best-performing asset allocation method due to its lower downside deviation, higher Calmar ratio and fewer months to recover from a maximum drawdown. Both the static and dynamic Constant Proportion Portfolio Insurance strategy methods provided 100% protection of investors’ capital even during the 2008-2009 Global Financial Crisis. In contrast with the Constant Proportion Portfolio Insurance strategy, it was found that an Option-Based Portfolio Insurance strategy with the buy and hold asset allocation approach fails to provide maximum protection for investors’ capital during periods of financial crises, since it lost 9, 45% in 2008. Hence, the Option-Based Portfolio Insurance portfolios (insured) with a buy and hold approach underperform uninsured portfolios.
- Full Text:
- Authors: Mngomezulu, Zwelakhe Sizwe
- Date: 2016
- Subjects: Portfolio management , Asset allocation , Financial risk management , Options (Finance) - Prices - Mathematical models
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/245956 , uj:25487
- Description: M.Com. (Financial Economics) , Abstract: The pressing question on the minds of academics and investment professionals is whether portfolio managers can evidently protect investors’ capital during a period of economic downturn and provide superior returns with a minimum level of risk. This study attempts to answer this question by evaluating the performance of portfolio insurance methods using different asset classes traded on the local Johannesburg Stock Exchange and other global markets. The chosen data period for evaluation starts from 02 June 2004 to 31 December 2013. The study compares insured portfolios (made up of two methods: the Option-Based Portfolio Insurance and the Constant Proportion Portfolio Insurance) with uninsured portfolios made of these asset classes in order to demonstrate the benefit of portfolio insurance in protecting investors’ capital during both bull and bear markets. The study makes use of different asset allocation approaches including buy and hold, risk parity, minimum variance, and momentum in order to build an optimal uninsured portfolio. The results of the study show that the minimum variance approach of the Constant Proportion Portfolio Insurance strategy with a static multiplier of m=2 consistently outperforms uninsured and the Option-Based Portfolio Insurance portfolios. It is argued that this outperformance might be due to holding risky assets with lower volatility. Furthermore, when a dynamic multiplier is used, it was found that the risk parity approach for the Constant Proportion Portfolio Insurance results in the best-performing asset allocation method due to its lower downside deviation, higher Calmar ratio and fewer months to recover from a maximum drawdown. Both the static and dynamic Constant Proportion Portfolio Insurance strategy methods provided 100% protection of investors’ capital even during the 2008-2009 Global Financial Crisis. In contrast with the Constant Proportion Portfolio Insurance strategy, it was found that an Option-Based Portfolio Insurance strategy with the buy and hold asset allocation approach fails to provide maximum protection for investors’ capital during periods of financial crises, since it lost 9, 45% in 2008. Hence, the Option-Based Portfolio Insurance portfolios (insured) with a buy and hold approach underperform uninsured portfolios.
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Non-parametric approach to VaR for portfolios in the South African equity market
- Authors: Saffy, Kyle
- Date: 2017
- Subjects: Stock exchanges - South Africa , Risk management - South Africa , GARCH model
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/271875 , uj:28924
- Description: M.Com. (Economics) , Abstract: The best measure for market risk is still a question that has remained largely unanswered. There are a variety of different methodologies that attempt to answer this question. The goal of this study is to assess how combining different elements of different Value at Risk (VaR) models contributes to better estimations of the risk inherent within a portfolio, thereby resulting is a sufficient risk capital allocation without over providing for risk that does not exist within the system. This study makes use of three VaR models, namely Constant Volatility Portfolio VaR approach, Conditional Volatility Single Asset VaR approach, and Conditional Volatility Portfolio VaR approach. The Constant Volatility Portfolio VaR approach consists of using Standard Deviation in order to estimate the volatility and the Pearson Correlation Coefficient in order to estimate how the constituents of the portfolio interact with one another; this is constructed using a standard Variance Covariance approach. The Conditional Volatility Single Asset VaR approach is constructed using a Historical Simulation VaR approach, where the historical returns dataset is scaled using the most recent volatility within the portfolio in order to give the estimation some symmetry based on what has occurred during stressed periods. No decomposition of the portfolio is used and therefore the end of day price of the portfolio is used to generate the returns dataset, thereby giving the portfolio a single asset appearance. The Conditional Volatility Portfolio VaR approach uses a GARCH(1,1) process in order to estimate volatility on a constituent based approach and then uses the Variance Covariance approach to combine the constituent’s volatility and the correlation, which is calculated using Kendall’s Tau. In order to evaluate the performance of each VaR model, back-testing is used. The techniques used are the Traffic Light Test, Probability of Failure and a measure of the amount of capital that is used. The use of capital test is designed to assess how much capital is utilised as a proportion of the underlying volatility. This test is only useful if the calculation passes the two aforementioned tests. Using daily financial time series of the JSE TOP40 index and the JSE DTOP index from 02 June 2008 to 14 April 2016, the VaR calculations are generated and the back-testing is appropriately conducted. Based on the back-testing results, it is found that the best approach was Conditional Volatility Portfolio VaR approach because it passed both of the back-tests, as well as having the lowest capital usage figure if only a portion of the back-testing passes are considered. It is found that the capital requirement obtained with this methodology find that the capital number should be bound between 3.77% and 6.70% on the TOP40 and 3.82% and 6.78% on the DTOP.
- Full Text:
- Authors: Saffy, Kyle
- Date: 2017
- Subjects: Stock exchanges - South Africa , Risk management - South Africa , GARCH model
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/271875 , uj:28924
- Description: M.Com. (Economics) , Abstract: The best measure for market risk is still a question that has remained largely unanswered. There are a variety of different methodologies that attempt to answer this question. The goal of this study is to assess how combining different elements of different Value at Risk (VaR) models contributes to better estimations of the risk inherent within a portfolio, thereby resulting is a sufficient risk capital allocation without over providing for risk that does not exist within the system. This study makes use of three VaR models, namely Constant Volatility Portfolio VaR approach, Conditional Volatility Single Asset VaR approach, and Conditional Volatility Portfolio VaR approach. The Constant Volatility Portfolio VaR approach consists of using Standard Deviation in order to estimate the volatility and the Pearson Correlation Coefficient in order to estimate how the constituents of the portfolio interact with one another; this is constructed using a standard Variance Covariance approach. The Conditional Volatility Single Asset VaR approach is constructed using a Historical Simulation VaR approach, where the historical returns dataset is scaled using the most recent volatility within the portfolio in order to give the estimation some symmetry based on what has occurred during stressed periods. No decomposition of the portfolio is used and therefore the end of day price of the portfolio is used to generate the returns dataset, thereby giving the portfolio a single asset appearance. The Conditional Volatility Portfolio VaR approach uses a GARCH(1,1) process in order to estimate volatility on a constituent based approach and then uses the Variance Covariance approach to combine the constituent’s volatility and the correlation, which is calculated using Kendall’s Tau. In order to evaluate the performance of each VaR model, back-testing is used. The techniques used are the Traffic Light Test, Probability of Failure and a measure of the amount of capital that is used. The use of capital test is designed to assess how much capital is utilised as a proportion of the underlying volatility. This test is only useful if the calculation passes the two aforementioned tests. Using daily financial time series of the JSE TOP40 index and the JSE DTOP index from 02 June 2008 to 14 April 2016, the VaR calculations are generated and the back-testing is appropriately conducted. Based on the back-testing results, it is found that the best approach was Conditional Volatility Portfolio VaR approach because it passed both of the back-tests, as well as having the lowest capital usage figure if only a portion of the back-testing passes are considered. It is found that the capital requirement obtained with this methodology find that the capital number should be bound between 3.77% and 6.70% on the TOP40 and 3.82% and 6.78% on the DTOP.
- Full Text:
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