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發(fā)布時間:2021-12-20 09:43編輯:融躍教育FRM
在FRM考試中,考生需要記憶的內(nèi)容有很多,比如Quantifying volatility in VaR models。下文是對Quantifying volatility in VaR models內(nèi)容的詳細介紹,一起了解一下!
Deviations from normality:
Normal returns;
Symmetrical distribution——“Normal” Tails——Stable distribution》2022年新版FRM一二級內(nèi)部資料免費領?。 揪A版】
Actual financial returns;
Skewed——Fat-tailed (leptokurtosis)——Time-varying parameters
Fat tails & Regime-switching volatility model:
Existence of fat tails;
A distribution is unconditional if tomorrow’s distribution is the same as today’s distribution.
But fat tails could be explained by a conditional distribution: a distribution that changes over time.
Regime-switching volatility model:
the regime (state) switches from low to high volatility, but is never in between.
a risk manager may assume (and measure) an unconditional volatility but the distribution is actually regime switching.
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