Skewness aur Kurtosis: portfolio risk ke liye practical guide
Skewness aur kurtosis kya batate hain, return distribution ka shape kaise padhen, aur VaR/CVaR/drawdown ke saath kaise use karein.
शनिवार, 28 फ़रवरी 2026
Skewness aur kurtosis kyun important hain
Sirf average return aur volatility se pura risk picture nahi milta. Skewness aur kurtosis distribution shape aur tail-risk ko samjhate hain.
Skewness: return asymmetry
- Positive skewness: right tail heavy, kabhi-kabhi bade gains.
- Negative skewness: left tail heavy, kabhi-kabhi bade losses.
Negative skewness wali strategies me abrupt downside risk zyada hota hai.
Kurtosis: tail thickness
Kurtosis batata hai ki tails normal distribution ke mukable kitni heavy hain.
- High kurtosis: extreme events ka chance zyada.
- Low kurtosis: extremes kam.
High kurtosis ka matlab tail-risk controls aur bhi important ho jate hain.
Practical reading
- Same volatility, different skewness: real downside risk alag ho sakta hai.
- Similar VaR, different kurtosis: extreme-loss severity alag ho sakti hai.
Isliye inhe VaR, CVaR aur drawdown ke saath padho.
Next step
- Risk profile Wallible app me dekho
- Portfolio backtesting me scenarios compare karo
- Related guides: VaR 95%/99% , CVaR 95%/99% , Maximum Drawdown
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