Global ETD Search
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Showing 1 to 15 of 15 for “"expected shortfall, ES"”.
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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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Investigation on the efficient frontier based on CVaR under copula dependence structure with applications to South African JSE stocks
… 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 that all coherent risk measures must satisfy. Using copula to …
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Risco de Crédito: uma aplicação no mercado de capitais para debêntures
Nos últimos anos as debêntures, título de renda fixa e com boa rentabilidade, tem apresentado uma grande participação no mercado de capitais, em média 45\% desde 2015. Por esse motivo a análise de risco para esse produto tem se tornado cada vez mais relevante. O presente trabalho apresenta o modelo …
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The impact of the FRTB on Market Risk Capital for the South African InterBank Interest Rate Market
… 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 crisis of 2008 highlighted flaws …
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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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Banking regulation: a Bayesian network approach to risk management
… conditions in employing machine learning techniques to estimate and forecast market risk metrics such as value at risk (VaR) and expected shortfall (ES). This study consists of three sections. First, this study comprehensively examines the performance of various market risk models when producing …
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Portfolio Liquidity Risk Management with Expected Shortfall Constraints
In this thesis we quantify the potential cost of liquidity constraints on a long equity portfolio using the liquidity risk framework of Acerbi and Scandolo (2008). The model modifies the classical mark-to-market valuation model, and incorporates the impact of liquidity policies of portfolios on the …
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Hawkes processes and some financial applications
The self-exciting point process, which is now more commonly known as the Hawkes process, is a model for a point process on the real line introduced by Hawkes (1971). The distinguishing feature of such processes is that they allow all past `events' to affect the intensity function at the current …
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Banking regulation: a bayesian network approach to risk management
… conditions in employing machine learning techniques to estimate and forecast market risk metrics such as value at risk (VaR) and expected shortfall (ES). This study consists of three sections. First, this study comprehensively examines the performance of various market risk models when producing …
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Volatility Modeling and Risk Measurement using Statistical Models based on the Multivariate Student's t Distribution
An effective risk management program requires reliable risk measurement. Failure to assess inherited risks in mortgage-backed securities in the U.S. market contributed to the financial crisis of 2007–2008, which has prompted government regulators to pay greater attention to controlling risk in …
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Applications of quantile regression to estimation and detection of some tail characteristics
… inference based on the ordinary least squares regression is sub-optimal when the distributions are skewed or when the quantity of interest is the upper or lower tail of the distributions. For example, the changes in Total Sharp Scores (TSS), the primary measurements of the treatment effects …
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Modelling spot prices, risk management, and investment strategies for the energy markets
This thesis addresses the topics of spot price modelling, risk management, and investment applications in the energy markets. Eight of the most important energy markets that trade futures contracts on NYMEX, and one Spot Energy Index (SEI) proposed for the first time in this thesis, are …
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Multi-period market risk estimation and performance evaluation : evidence from univariate, multi-variate and options data
There are different risk management approaches available, as different firms have different risk goals. Value at risk (VaR) is the most frequently used risk measure for asset or portfolio risk and certainly, per the Basel framework, is a preferred measure for market risk for banks and financial …
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Measurement of Operational Risks with Stochastic Models in Turkish Banking System
… and indirect impacts of operational risk, endorses the need for the measurement and management of this risk. In order to manage operational risk, it must be quantified and measured properly. Measurement of operational risk requires considerably different and more sophisticated quantitative …
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A rendszerszinten jelentős pénzügyi intézmények azonosítása és kockázatainak mérséklési lehetőségei az Európai Unióban
… szuboptimális döntéseket hozhatnak, mert nem veszik figyelembe a státuszukból fakadó, rendszerszinten jelentkező negatív externáliákat. Ezen intézmények kapcsán felmerülő kockázatok nem csak nemzetközi szinten, hanem az Európai Unióban és a közép-kelet európai régióban is relevánsak. …