Week07 - Ch10 - Market risk

Week07 Ch10- - Market Risk Market Overview This chapter discusses how market risk arises and how it can threaten the solvency of FIs We learn how

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Market Risk Market Risk
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12-2 Overview This chapter discusses how market risk arises and how it can threaten the solvency of FIs. We learn how to measure market risk. We learn about the concepts of the RiskMetrics model and the back simulation approach. We discuss how regulators measure market risk exposures for capital adequacy purposes.
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12-3 Introduction Market risk is the uncertainty resulting from changes in market prices. It can be measured over periods as short as one day. Usually measured in terms of dollar exposure amount or as a relative amount against some benchmark.
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12-4 Market Risk Measurement Why is Market Risk Measurement (MRM) Important? Management information, Setting risk limits, Resource allocation, Performance evaluation, Regulation. Calculating Market Risk Exposure RiskMetrics, Historic or back simulation, Monte Carlo simulation.
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Normal distribution and confidence intervals The normal distribution or Gaussian distribution is a continuous probability distribution that often gives a good description of data that cluster around the mean. The graph of the associated probability density function is bell-shaped, with a peak at the mean, and is known as the Gaussian function or bell curve. Confidence intervals: A range around some specific value which has a certain probability to occur. Assuming normality, 90% of the time the disturbance will be within 1.65 standard deviations (σ) from the mean (μ). Probability ( μ - 1.65σ < x < μ + 1.65σ) = 90% Probability (x <= μ - 1.65σ) = 5% Probability (x >= μ + 1.65σ) = 5%
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12-6 The RiskMetrics Model Developed by JP Morgan. The idea is to estimate the potential loss under adverse market circumstances and use the estimated loss to gauge the market risk exposure. Daily earnings at risk (DEAR) = Potential daily loss under adverse circumstances = Dollar market value of the position × daily return under adverse circumstances (normally set as 5% worst case, but you can make it 1% worst case if you are more risk averse) If daily return follows a normal distribution, Ret ~ N(μ, σ), then from the previous slide we know that daily return under 5% worst case = μ - 1.65σ (in most cases, we assume μ = 0, then it is - 1.65σ ). It is referred as price volatility in the textbook. But this term is really confusing. Implication of DEAR: the potential loss under adverse market scenario, and the actual loss could go beyond this number, which will occur with only a 5% chance. (so why set to 1% if you are more risk averse?)
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12-7 Applying RiskMetrics to Foreign Exchange Position Daily earnings at risk (DEAR) = Potential daily loss under adverse circumstances = Dollar market value of the position × daily return under adverse circumstances
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This note was uploaded on 05/26/2011 for the course FIN 5530 taught by Professor Lee during the Three '11 term at University of New South Wales.

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Week07 Ch10- - Market Risk Market Overview This chapter discusses how market risk arises and how it can threaten the solvency of FIs We learn how

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