Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 52 for “"Value-at-Risk (VaR)"”.
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Is Value-at-Risk (VaR) a Fair Proxy for Market Risk Under Conditions of Market Leverage?
Ex-post intraday market-risk extrema are compared with ex-ante standard RiskMetrics parametric Value-at-Risk (VaR) limits for three foreign currency futures markets (British Pound, Japanese Yen, Swiss Frank) to determine whether forecasted volatility of market returns based on settlement price data …
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The impact of estimation frequency on Value at Risk (VaR) and Expected Shortfall (ES) forecasts: an empirical study on conditional extreme value models
This study investigates extreme market events which occur in the tails of a distribution. The extreme events occur with a very low probability, but with significant consequences, which is what makes them of interest. In this study 20 years of data from both the S&P 500 and the JSE All Share index …
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Application of GARCH Type Models in Forecasting Value at Risk
Dynamic risk management requires the risk measures to adapt to information at different times, such that this dynamic framework takes into account the time consistency of risk measures interrelated at different times. The value-at-risk (VaR) is one of the most well-known downside risk measures due …
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Kockázati mértékek és kapcsolódó kockázatkezelési kérdések
Az operációs kockázat egyik a három fő kockázati típus közül, mely fenyegetheti a pénzügyi intézeteket. Az operációs kockázat mellett bemutatásra kerülnek a működési kockázatot szabályozó intézkedések is. Különböző kockázati mértékek alakultak ki az évek folyamán, melyek a tőkeképzés alapjait …
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Quantifying Model Risk in Option Pricing and Value-at-Risk Models
… use models in order to price, hedge and measure risk. These models are reliant on assumptions and are prone to ”model risk”. Increased innovation in complex financial products has lead to increased risk exposure and has spurred research into understanding model risk and its underlying factors. …
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Industry value at risk in Australia
Value at Risk (VaR) models have gained increasing momentum in recent years. Market VaR is an important issue for banks since its adoption as a primary risk metric in the Basel Accords and the requirement that it is calculated on a daily basis. Credit risk modelling has become increasingly important …
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Investigation on the efficient frontier based on CVaR under copula dependence structure with applications to South African JSE stocks
… the feasihility of using a coherent monetary risk measure, Conditional Value at Risk (CVaR) also known as Expected Shortfall (ES), to optimise a portfolio of South African stocks. Value at Risk (VaR) is not a sub-additive risk measure and therefore does not possess one of the four properties …
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Daily and intradaily stochastic covariance : value at risk estimates for the foreign exchange market
The importance of time varying volatility in securities prices (e.g. GARCH) has by now been amply established in the literature, both in terms of the magnitude and pervasiveness of the phenomenon, and in terms of its significance for risk management in institutional portfolios. Less attention has …
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Distintas ópticas de riesgo financiero: aplicación para el mercado bursátil argentino
… se definió como principal medida de riesgo su varianza de rendimientos. Con el correr del tiempo, se formularon nuevas métricas que dieron más información, fundamentalmente comparando el rendimiento de una cartera con su riesgo a través de las llamadas “unidades de riesgo”. Se pueden nombrar …
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Risco de Crédito: uma aplicação no mercado de capitais para debêntures
… O presente trabalho apresenta o modelo CreditRisk+ e o método de Simulação de Monte Carlo ajustados a uma carteira teórica de debêntures. O objetivo do estudo é mensurar o risco de crédito do portfólio em cenários com e sem stress, e variando o nível de confiança. Através da aplicação dos …
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Aukšto dažnio duomenų agregavimas ir vertės pokyčio rizika /
Value-at-risk (VaR) model as a tool to estimate market risk is considered in the thesis. It is a statistical model defined as the maximum future loss due to likely changes in the value of financial assets portfolio during a certain period with a certain probability. A new definition of the …
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Acceleration of Monte Carlo Value at Risk Estimation Using Graphics Processing Unit (GPU)
"Value at Risk (VaR) is one of the most popular tools used to estimate the exposure to market risks, and it measures the worst expected loss at a given confidence level. Monte Carlo simulation is one of the best methods to calculate VaR and it is widely used in financial industry. Unfortunately, it …
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RESEARCH ON THE MEASUREMENT AND INFLUENCING FACTORS OF SYSTEMIC RISKS IN CHINESE FINANCIAL INSTITUTIONS IN CASE OF MAJOR PUBLIC EMERGENCIES
… measurement and influencing factors of systemic risks in Chinese financial institutions based on three dimensions: overall situation, industries, and institutions. First, it uses the DTW-MST network model to describe the dependence structure between financial institutions and between industries. …
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The impact of the FRTB on Market Risk Capital for the South African InterBank Interest Rate Market
Regulations require banks to hold a minimum amount of capital for market risk resulting from their trading operations and prescribe two approaches to calculating this minimum capital requirement: (i) a Standardised Approach (SA); and (ii) an Internal Models Approach (IMA). The global financial …
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Estimating value at risk and expected shortfall: a kalman filter approach
Calculating Value-at-Risk (VaR) to estimate the maximum loss a portfolio may incur at a given confidence level and over a specified time has undergone several adaptations, iterations, and additions since its inception in 1994. In 2013, the Basel Committee on Banking Supervision (BCBS) replaced VaR …
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An Application of Generative Adversarial Networks to One-Dimensional Value-at-Risk
A generative adversarial network (GAN) is an implicit generative model made up of two neural networks. This minor dissertation applies GANs to recover target statistical distributions. GANs have a distinctive training architecture designed to create examples that reproduce target data samples. …
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A model for cash management : an aquaculture case study
… earned on cash surplus gained from a firm's operation can involve considerable complexity, especially when there are seasonal and uncertainty factors involved. The network flow model with gains and losses for use in cash management was first presented in 1979 by Golden and Libertore. Their model …
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Parallel computing with improved techniques for Monte Carlo simulation in VaR
"Value at Risk ( VaR ) is a widely used tool for the assessment of one’s investments. VaR is used to evaluate the risk of loss on a financial portfolio. This metric can be computed in several ways. In the historical approach, past trends of the appropriate combination of stocks is used to estimate …
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Risk Management in South Africa Before, During, and After the 2008 Global Financial Crisis: An Application to Different Sectors
The risk management functions of most financial institutions occupy themselves with the estimation of the value at risk (VaR) of their portfolios as a measure of market risk. Various methods are available to calculate the VaR measure, and this can be done at various degrees of confidence. This …
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Essays in asset pricing and market imperfections
… a dynamic model where investors face the risk of potential liquidity crises. We find that investors choose optimal portfolios not only to hedge the risk of asset fundamentals, but also to hedge the risk of potential liquidity crashes. The potentially illiquid assets tend to have a lower …
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