日收益率波动率年化
文章 Quant Q&A · 作者: Orvar Korvar
总结
本文说明如何将滚动窗口内估算的股票日收益率波动率年化。在假设收益率独立同分布且方差与经过时间成正比的前提下,日收益率的标准差可估算日波动率。每年有 252 个交易日时,将日波动率估计值乘以 252 的平方根,即可换算成年化波动率。估算窗口中的观测数量影响用于估算的数据量,而不影响年化因子。
看似可行的另一种做法,是将六日波动率乘以 252 除以六的平方根;这适用于输入值是六日累计收益率的波动率。关键在于缩放前先确定所测收益率代表的时间单位。此解释依赖上述收益分布和独立性假设;若收益率存在依赖性、波动率变化或观测频率不同,简单的时间平方根缩放可能不准确。本文讨论的是日收益率,并未详述样本标准差与总体标准差等估算选择。
核心观点
- 年化取决于每个收益率代表的时间间隔,而非滚动估算窗口的长度。
- 对于日收益率波动率,应乘以一年交易日数量的平方根。
- 若输入是累计收益率的波动率,应按其时间间隔进行时间平方根调整。
- 这种缩放方法假设收益率相互独立,且方差与经过时间成正比。
- 年化前,请确认输入衡量的是日收益率还是多日收益率。
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# Annualized rolling volatility?
# Annualized rolling volatility?
I have 600 days of closing prices of a stock. I want to calculate the annualized volatility for 6 day window. How do i do that?
If I calculate the std dev of the first 6 days, i get, say 1%. This is the daily volatility of the first 6 days. To annualize it, should i just multiply 1% with sqrt(252)? Or, is this 1% the daily volatility of 6 days? In that case i should multiply with sqrt(252/6)? Is this number 1% the daily volatility for 1 day, or is it the dayily volatility for 6 days?
I dont get it, I am missing a parameter. The period should also be involved in the calculation, right?
So to annualize 6 day volatility, i multiply with sqrt(252/6)? And when do i multiply with sqrt(252)?
UPDATE1: Ami44 writes that the correct procedure to annualize a 6 day window, is to multiply with sqrt (252/6). See Converting 30day annualized vol to 2day annualized vol
UPDATE2: in the answer below, ForeignVolatility says that I should multiply with sqrt (252). This is contradictory to "UPDATE1" above. So I am confused. Should I multiply with sqrt (252) or sqrt(252/6)? And, if I have a 30 day window, should I still multiply with sqrt (252), or should I use sqrt(252/30)? Great confusion. Some say Ba, and other say Bu.
## Answer by foreignvol (score 4, accepted)
https://quant.stackexchange.com/a/70867
We work in annual units because $T=1$ means one year. This means that the time units must be converted to portions of a year. For example, in the case of daily observations, $\Delta t = 1 / 252$. Hence, in your example, we multiply by $\sqrt{252}$ because it's assumed that the variance is measured daily.
More generally, say you have $n$ returns observed with frequency $\Delta t$ arbitrary. Assume they are i.i.d. and follow a distribution $N(0,\sigma^2\Delta t)$. You then have $$ \mathbb E\left[\frac 1n \sum_{t=1}^n r_t^2\right] = \frac 1n \sum_{t=1}^n\mathbb E\left[r_t^2\right] = \frac 1n \sum_{t=1}^n\sigma^2\Delta t = \sigma^2\Delta t. $$ What you described, the sdt dev of the first 6 days, corresponds to the square-root to an estimation of the LHS with $n=6$. The value you're looking for is $\sigma^2$. Hence, you need to multiply by $1/\sqrt{\Delta t} = 1/(1/\sqrt{252}) = \sqrt{252}$.在遵守原作品许可的前提下,附作者信息全文展示。 许可协议: CC BY-SA 4.0 (Stack Exchange)
此摘要由 Stratmill 研究智能体根据原文撰写,并非原文副本。