Training Risk Measure Models to Ascertain Which Continent’ Equity Has the Highest Risk ForInvestment Based On Randomly Selected Individual Continents’ Equities Listed On The New YorkStock Exchange

Detta är en Master-uppsats från Mälardalens högskola/Akademin för utbildning, kultur och kommunikation

Sammanfattning: Western countries, institutions, and people from all walks of land, including Africans, have carried the notion that it is riskier to invest in African countries compared to countries in other continents. This study verified if that notion is empirically established or it is just a mere notion born out of people's imagination and unfounded belief. The study did select one special metal mining company listed on the New York stock exchange from every continent using a systematic random sampling of period five. All these stocks' data were daily data spanning the period 2003-06 - 2020:06 obtained from Yahoo Finance. The said duration was used for the analysis because one of the companies selected for the study only had stock data starting from 2003-06-25. Because of Generalized Autoregressive Conditionally Heteroscedastic (GARCH) ability to model the conditional randomly varying volatility, the study trained several of them for a different order of the GARCH terms σ2, and the order of the ARCH terms ε2 and for different distributions. Based on the AIC and BIC, the GARCH model that best fitted the data was GARCH (1,1), thus order one of the GARCH terms σ2 and order one of the ARCH terms ε2 based on student-t innovation. The study proceeded to estimate the risk measure using three of the approaches (risk metrics, Block Maxima Method under extreme value situation, and Generalized Pareto Distribution (GPD) for the tail ends of the distribution). None of the approaches or methods used in calculating VaR or conditional VaR (ES) of the stocks supported the conventional beliefs and age long-held purported gospel that African counties are the riskiest to invest on earth. In the risk metrics approach, the African stock was second riskiest to European stock. At the same time, in extreme value situations, it was third to European and South American; with GPD, it was third once again to South American and European stock. The study proceeded to verify if this founding were statistically significant. Applying analysis of variance (ANOVA), found that none of the differences established above is statistically significant. Meaning, statistically, the value and conditional value of one's investment that will be at risk is not different based on the investment's continental location. Thus, it is not statistically riskier to invest in one continent than the other.  

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