Browsing School of Pure and Applied Sciences by Author "Mwita, Peter N."
Now showing items 1-20 of 39
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Application of Conditional Autoregressive Value at Risk Model to Kenyan Stocks: A Comparative Study
(Science Publishing Group, 2017-05-22)Value at Risk (VaR) became the industry accepted measure for risk by financial institutions and their regulators after the Basel I Accords agreement of 1996. As a result, many methodologies of estimating VaR models used ... -
Application of Conditional Autoregressive Value at Risk Model to Kenyan Stocks: A Comparative Study
(Science Publishing Group, 2017-05-22)Value at Risk (VaR) became the industry accepted measure for risk by financial institutions and their regulators after the Basel I Accords agreement of 1996. As a result, many methodologies of estimating VaR models used ... -
An Application Of Extreme Value Theory In Modelling Electricity Production In Kenya
(IISTE, 2014)Extreme Value Theory provides a well-established statistical model for the computation of extreme risk measure which includes, Value at Risk and Expected Shortfall. In this paper we apply Univariate Extreme Value Theory ... -
Application of extreme value theory in the estimation of value at risk in Kenyan stock market
(Int. J. Cur. Tr. Res, 2013)Most financial institutions have faced a lot of losses due to the fluctuations of commodities prices. Traditionally normal distribution was applied and could not capture rare events which caused enormous losses. The ... -
Application of Nonparametric Methods in Studying Energy Consumption
(University of Rwanda, 2011)Consumer behaviour towards different forms of energy varies over time. The variance can be so large that the quality of the estimation functional relationship between the response variable and its associated explanatory ... -
Bootstrap of Kernel Smoothing in Quantile Autoregression Process
(Journal of Statistical and Econometric Methods, 2013)The paper considers the problem of bootstrapping kernel estimator of conditional quantiles for time series, under independent and identically distributed errors, by mimicking the kernel smoothing in nonparametric autoregressive ... -
Bootstrap Uniform Confidence Bands for A Local Linear Nonparametric Estimator and Applications to Financial Risk Management
(2012)This paper considers the problem of bootstrapping a local linear estimator in conditional quantile estimation of a financial time series assuming independent and identically distributed errors. A nonparametric ... -
Conditional scale function estimate in the presence of unknown conditional quantile function
(African Network of Scientific and Technical Institutions (ANSTI), 2005)Standard approach for modeling and understanding the variability of statistical data or, generally, dependant data, is often based on the mean variance regression models. However, the assumptions employed on standardized ... -
Conditional Volatility Estimation by Conditional Quantile Autoregression
(HIKARI Ltd, 2014)This paper considers the problem of estimating conditional volatility function using conditional quantile autoregression function. We estimate the interquantile autoregression range and the conditional volatility function ... -
Conflict resolution using statistical approach
(Academic Journals, 2010)Conflict can be described as a condition in which actions of one person prevent or compel some outcome at the resistance of the other. Quite often this can be seen as “two or more competing, often incompatible, responses ... -
Consistency of the Model Order Change-Point Estimator for GARCH Models
(Scientific Research Publishing Inc., 2018)GARCH models have been commonly used to capture volatility dynamics in financial time series. A key assumption utilized is that the series is stationary as this allows for model identifiability. This however violates the ... -
Discussion on Generalized Modified Inverse Rayleigh
(2018-01-01)In this paper, a generalization of the modified inverse Rayleigh distribution called the new exponentiated generalized modified inverse Rayleigh distribution is proposed and studied. Various sub-models of the new distribution ... -
Estimating Dependence Structure and Risk of Financial Market Crash
(Canadian Center of Science and Education, 2016-10)In this paper, we estimate the dependence structure between international stock markets using copulas. Different relationships that exist in normal and extreme periods were estimated using Clayton copula. The Inference ... -
Estimation of Conditional Weighted Expected Shortfall under Adjusted Extreme Quantile Autoregression
(Scientific Research Publishing Inc., 2021-07-14)In this paper, we present an estimator that improves the well-calibrated coherent risk measure: expected shortfall by restructuring its functional form to incorporate dynamic weights on extreme conditional quantiles used ... -
Estimation of Critical Streamflow Discharge Level Using Nonparametric Quantile Regression Model
(2016)Various parametric models have been designed to analyze volatility in river flow time series data. For maximum likelihood estimation these parametric methods assumes a known conditional distribution. This paper considers ... -
ESTIMATION OF EXTREME VALUE AT RISK IN RWANDA EXCHANGE RATE
(European Centre for Research Training and Development UK, 2014-12)Estimating the probability of rare and extreme events is a crucial issue in the risk estimation of exchange rate returns. Extreme Value Theory (EVT) is a well-developed theory in the field of probability that studies the ... -
Estimation of Risk in Rwanda Exchange Rate
(2014)Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approach was applied to Rwanda Exchange rate returns to estimating current volatility. We fitted autoregressive (AR) model with GARCH errors to the daily ... -
Exponentiated generalized exponential Dagum distribution
(Elsevier, 2017)In this study, the exponentiated generalized exponential Dagum distribution has been proposed and studied. This family of distribution consists of a number of sub-models such as the exponentiated generalized Dagum ... -
Exponentiated Generalized Power Series Family of Distributions
(2018)In this paper, a new family of distributions called the exponentiated generalized power series family is proposed and studied. Statistical properties such as stochastic order, quantile function, entropy, mean residual ... -
Exponentiated Generalized Transformed-Transformer Family of Distributions
(Scienpress Ltd, 2017)Recently, the development of generalized class of distributions has become an issue of interest, to both applied and theoretical statisticians, due to their wider application in different fields of studies. Thus, ...
