The lecture Quantifying Volatility in VaR Model by Edu Pristine is from the course Archiv - Valuation and Risk Models. It contains the following chapters:
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... period of time. Market conditions may cause the mean and variances to change over the period of time, which leads to fat-tailed distributions. The fat-tailed unconditional distribution ...
... accurate measure of risk would be to measure the risk or volatility in these high and low risk areas separately, and then base our ...
... is informative. More information in recent past than ...
... day n as estimated at the end of day n-1. Variance estimate for next day is usually calculated as: Variance = average squared deviation from average return over last ‘n’ days ...
... of time. Market conditions may cause the mean and variances to change over the period of time, which leads to fat-tailed distributions. ...
... accurate measure of risk would be to measure the risk or volatility in these high and low risk areas separately, and then base our forecast ...
... changes is informative. More information in recent past than ...
... day n as estimated at the end of day n-1 variance estimate for next day is usually calculated as: • Variance = average squared deviation from average return ov er last ‘n’ days ...