在FRM考试中，考生需要记忆的内容有很多，比如Quantifying volatility in VaR models。下文是对Quantifying volatility in VaR models内容的详细介绍，一起了解一下！
Deviations from normality：
Normal returns；
Symmetrical distribution——“Normal” Tails——Stable distribution》2022年新版FRM一二级内部资料免费领取！【精华版】
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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