The Assessment Of Risk Based On The Stock Market And Agribusiness: The Extreme Value Theory And Risk Metrics

Ghana is a nation that has a relevant history of adapting to extremes including flood,windstorm,rainstorm,drought and tidal waves(Hydro-Meteorological Disasters)and also Bush/Wildfires.These processes are,in many cases,adequate for emergency response but not for decreasing the vulnerability to rises in their incidence.Further,the cognizance of the increasing occurrence of extremes,or even the feeling that this is true and linked with climate variation,has the prospect to impact on Ghana's economy,mainly through altered consumption patterns and influence on the insurance regime.Given this,risk assessment have become a central concern for scholars,governments,financial institutions,organizations,market regulators,individuals and the investor community in general.Generally,extreme events that occur anywhere can lead to a structural adjustment of the world's economy as a whole,which can equally have effects in Ghana on agricultural productivity,trade and capital flows.To help gain a comprehensive insight of the study,six(6)specific objectives were developed to aid realized the general objective.To achieve the stated objectives,the study obtained data from Ghana Meteorological Agency(climate data),Ghana Food and Agriculture Organization(Agricultural Production Indexes)and from Annual Report Ghana(Ghana Stock exchange CI).Rainfall and temperature are considered the main determinants of the weather in the study that also constituted the independent variables as well.Similarly,the study was composed of two main dependent variables such as Agriculture Production: Food,Livestock,crop,cereal and cocoa production indexes and Stock Exchange Index constituting the Financial Sector.The production indexes in agriculture ranges from 1961-2016,whiles the indicators for weather ranges from January 1960 until July 2018 and the stock exchange index ranges from 1990-2016.The first task was to verify the stationary of the weather variables using the enhanced Dickey-Fuller(ADF)test and then the MannKendall test of the seasonality,which identified significant trends.Further Mann-Kendall test was employed to calculate the annual monthly precipitation anomalies to eliminate seasonal effects as opposed to wavelet analysis.The study also employed Structural Equation Modeling to study the relationship between extreme weather events and agricultural production.Again,the study employed current financial risk approaches: Back Testing Value-atRisk and Expected shortfall in view to estimating the volatility of the stock index.The predictive analysis saw the application of artificial neural network architect,which explored two models that estimated the tails behavior and the time the stock will gain,or fall within five months trading period.These estimates provided diagnostic test and model test as robust and stable for the conceptualization of the study.The resulting objectives provided an integrated framework that permits harmonising the results of a variety of climate-related effects on agriculture and finance,which is significant for multi-risk analyses.The significant climate extreme impacts affect all sectors and their objectives,places and people differentially subject to the levels of risk.The main conclusion from climate trends stems from the mean rainfall variability over Ghana and their periodicities analysed.It was observed that,high cumulative rainfall amounts ranging from 900 to 1900 mm are recorded over the entire nation per year with very high rainfall amounts between 1500 to 1900 mm recorded at the south-western part of the country and low rainfall amounts(900–1200 mm)recorded in the Savannah Zone and east coast of the country.In general,a decreasing trend was observed for the annual rainfall over all the agro-ecological zones except for the Coastal Zone where a slight increasing trend of 0.1600 mm per year was seen.The results from Extreme Value Theory(EVT)gave the levels of risk associate with climate extreme,which is a reliable tool for climate extreme scenarios construction,where maximum likelihood method supported the evaluation of distribution parameters for weather extreme.Generalised extreme value model is found to be the most suitable model with fulfilling all statistical selection criteria for Value-at-Risk and Return level.The return level for the model is constructed to predict the risk in weather extremes for a medium to long run-in future.There is generally an increase in climate risk as it consistently increasing from 5,10,25,for the next 100 years.The outcome from structural equation modelling aims at exploring the impact of climate on agriculture showed evidence that extreme maximum rainfall adversely affects cereal and cocoa production.Cereals and cocoa thrive well when the rainfall is well distributed and not concentrated in some months and leaving other months virtually without rains.Maximum extreme temperatures contribute positively to all the indicators under consideration.Minimum extreme temperatures also except cocoa production have a positive impact on the remaining agriculture indexes.The empirical results,which seeks to explore the impact of climate extremes on stock exchange market,showed that there were 42 days with extreme rainfall,with 23 occurrences resulting to 54.76% of impact on the Ghana Stock Exchange.As a result,there is a significant effect on the return on shares.On the other hand,there were 34 days extreme temperature and was established with 18 occurrences leading to 52.94% of impact on the Ghana Stock Exchange.Taken into consideration the methodology utilized in this study,the goal of the study is to identify the impact of extreme rainfall and its magnitude using Va Rs calculated(with confidence intervals of 90%,95% and 99%)for which the extreme event occurred.Both rainfall and temperature influenced significantly the Ghana stock exchange.The results indicate that the Ghana stock exchange analyzed with more than 50% of the extreme rainfall and temperature had a significant impact on the return on the stocks market.There are satisfactory results for the Ghana Stock Exchange explaining the behaviour of the data.Low and high volatility periods occur quite regularly for the Ghana Stock Exchange index.Based on past data,the model can capture other extremes satisfactorily.The study reveals that once every five months,at a 5% confidence level,the market is expected to gain and fall 2.12% and 2.23% respectively.The Ghana Stock Exchange Market showed a maximum monthly stock gaining above or below 2.12% in the fourth and fifth months,whiles maximum monthly stock fallen above or below 2.23% in the third and fourth months.The study reveals that once in every five months trading period,the stock market will gain and fall by almost an equal percentage,with a significant increase in value-at-risk and expected shortfall at the left tail as the quantiles increases compared to the right tail.To enhance Ghana‘s current and future development to the impacts of climate extremes,the study envisages that a policy direction of strengthen the adaptive capacity and building resilience of the society and ecosystems could be pursued by government.Unlike other simple observational research,this dissertation starts from trend analysis of Ghana climatic conditions with the application of Extreme Value Theory on a temporal and spatial distribution of climate extremes and uses the extreme value model to estimate the future risk of Ghana's climate on Agriculture,hence a new inroad in methodological approach.