The Master Thesis build from the current literature on cryptocurrency and Portfolio Diversification aiming at creating a welldiversified portfolio which contain Bitcoin and trying to understand if it’s optimal for an investor to allocate a meaningful amount of his portfolio in Bitcoin. To understand that, a DCCGARCH model was exploited to analyze the Dynamic Conditional Correlation of Bitcoin with respect to the equity market of the most important Developed and Developing countries in the world. The result was that, correlation trend, become more relevant in Developed Countries, while for Developing Countries, correlation with Bitcoin remains low, thus there are room for inclusion in an investment portfolio in such countries. Because of market proximity and strength of the results of the DCCGARCH model, China and Hong Kong, were chosen as reference countries for equity investments of a potential investor. To do so, indices form the S&P500 database were exploited for the equity market in such countries, as well as indices from the commodities market as well as the energy, agriculture and bond ones. In order to perform a portfolio diversification technique, the two most important framework were exploited, the Modern Portfolio Theory and the PostModern Portfolio Theory, were in botch cases expected return, which were preferred to historical returns, were computed accordingly to CAPM. The results of this portfolio diversification approach show that such investor is better off with positive, in the single digit, portfolio allocation to Bitcoin, which increases if downside variance is preferred accordingly to PostModern Portfolio Theory. To conclude, some of the most important risk metrics, such as Value at Risk and Expected Shortfall, were used to investigate on the potential losses of the portfolio obtained in the diversification exercise. Such portfolios, because of the nature of Bitcoin and the countries analyzed, might lead to big losses in extreme market conditions, for this reason, even if the allocation is deemed optimal, an actual investor might decide to stay away as the fear of losses exceeds the potential gains, which is in line with the results of Behavioral Finance. To investigate what would be the result if this scenario is taken into account, a Modified formulation of Value at Risk is computed for the investment portfolio and used to compute a modified version of the Sharpe and Sortino Ratios, used to maximize the portfolio allocation. The result is that, such an investor is still better off with positive portfolio allocation in Bitcoin even if with a lower percentage. This result is informative as a very risk adverse scenario was exploited in the final computation, thus showing the strength of the results obtained with the DCCGARCH model for developing countries and especially for the China and Hong Kong markets.
The Master Thesis build from the current literature on cryptocurrency and Portfolio Diversification aiming at creating a welldiversified portfolio which contain Bitcoin and trying to understand if it’s optimal for an investor to allocate a meaningful amount of his portfolio in Bitcoin. To understand that, a DCCGARCH model was exploited to analyze the Dynamic Conditional Correlation of Bitcoin with respect to the equity market of the most important Developed and Developing countries in the world. The result was that, correlation trend, become more relevant in Developed Countries, while for Developing Countries, correlation with Bitcoin remains low, thus there are room for inclusion in an investment portfolio in such countries. Because of market proximity and strength of the results of the DCCGARCH model, China and Hong Kong, were chosen as reference countries for equity investments of a potential investor. To do so, indices form the S&P500 database were exploited for the equity market in such countries, as well as indices from the commodities market as well as the energy, agriculture and bond ones. In order to perform a portfolio diversification technique, the two most important framework were exploited, the Modern Portfolio Theory and the PostModern Portfolio Theory, were in botch cases expected return, which were preferred to historical returns, were computed accordingly to CAPM. The results of this portfolio diversification approach show that such investor is better off with positive, in the single digit, portfolio allocation to Bitcoin, which increases if downside variance is preferred accordingly to PostModern Portfolio Theory. To conclude, some of the most important risk metrics, such as Value at Risk and Expected Shortfall, were used to investigate on the potential losses of the portfolio obtained in the diversification exercise. Such portfolios, because of the nature of Bitcoin and the countries analyzed, might lead to big losses in extreme market conditions, for this reason, even if the allocation is deemed optimal, an actual investor might decide to stay away as the fear of losses exceeds the potential gains, which is in line with the results of Behavioral Finance. To investigate what would be the result if this scenario is taken into account, a Modified formulation of Value at Risk is computed for the investment portfolio and used to compute a modified version of the Sharpe and Sortino Ratios, used to maximize the portfolio allocation. The result is that, such an investor is still better off with positive portfolio allocation in Bitcoin even if with a lower percentage. This result is informative as a very risk adverse scenario was exploited in the final computation, thus showing the strength of the results obtained with the DCCGARCH model for developing countries and especially for the China and Hong Kong markets.
Bitcoin: Portfolio Diversification Analysis for Developing Countries
VENTURELLI, RICCARDO
2022/2023
Abstract
The Master Thesis build from the current literature on cryptocurrency and Portfolio Diversification aiming at creating a welldiversified portfolio which contain Bitcoin and trying to understand if it’s optimal for an investor to allocate a meaningful amount of his portfolio in Bitcoin. To understand that, a DCCGARCH model was exploited to analyze the Dynamic Conditional Correlation of Bitcoin with respect to the equity market of the most important Developed and Developing countries in the world. The result was that, correlation trend, become more relevant in Developed Countries, while for Developing Countries, correlation with Bitcoin remains low, thus there are room for inclusion in an investment portfolio in such countries. Because of market proximity and strength of the results of the DCCGARCH model, China and Hong Kong, were chosen as reference countries for equity investments of a potential investor. To do so, indices form the S&P500 database were exploited for the equity market in such countries, as well as indices from the commodities market as well as the energy, agriculture and bond ones. In order to perform a portfolio diversification technique, the two most important framework were exploited, the Modern Portfolio Theory and the PostModern Portfolio Theory, were in botch cases expected return, which were preferred to historical returns, were computed accordingly to CAPM. The results of this portfolio diversification approach show that such investor is better off with positive, in the single digit, portfolio allocation to Bitcoin, which increases if downside variance is preferred accordingly to PostModern Portfolio Theory. To conclude, some of the most important risk metrics, such as Value at Risk and Expected Shortfall, were used to investigate on the potential losses of the portfolio obtained in the diversification exercise. Such portfolios, because of the nature of Bitcoin and the countries analyzed, might lead to big losses in extreme market conditions, for this reason, even if the allocation is deemed optimal, an actual investor might decide to stay away as the fear of losses exceeds the potential gains, which is in line with the results of Behavioral Finance. To investigate what would be the result if this scenario is taken into account, a Modified formulation of Value at Risk is computed for the investment portfolio and used to compute a modified version of the Sharpe and Sortino Ratios, used to maximize the portfolio allocation. The result is that, such an investor is still better off with positive portfolio allocation in Bitcoin even if with a lower percentage. This result is informative as a very risk adverse scenario was exploited in the final computation, thus showing the strength of the results obtained with the DCCGARCH model for developing countries and especially for the China and Hong Kong markets.File  Dimensione  Formato  

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https://hdl.handle.net/20.500.12608/48244