리스크 & 수익 통계

확률적 시나리오 또는 과거 수익률 데이터에서 E(r), σ², σ, 샤프, 왜도, 첨도를 계산합니다. 설정 없이 빠른 문제 해결을 위해 설계되었습니다.

Statistics Lab

Probabilistic scenarios + historical return series — every step shown

Enter scenarios with probabilities (must sum to 1.00) and returns. The Lab computes E(r), σ², and σ in real time, with every step shown.

Scenario	Probability (p)	p × r	(r − E(r))²	p × (r − E(r))²
		0.0900	0.03610	0.01083
		0.0500	0.00010	0.00005
		-0.0300	0.06760	0.01352
Total	1.00	E(r) = 0.1100		σ² = 0.02440

E(r)

11.00%

σ²

0.02440

15.62%

Sharpe

0.448

r_f = 4.0%

Step 1: E(r) = Σ p × r

Step 2: σ² = Σ p × (r − E(r))²

Step 3: σ = √σ²

Step 4: Sharpe = (E(r) − r_f) / σ

Want the full lesson? Visit Week 4 of the Investment Management course for the formulas, derivations, and a 5-question quiz with worked solutions.

Every investment can be summarized by two headline numbers: how much it returns on average and how much it bounces around. The first is expected return, the second is volatility. From those two, plus higher moments like skew and kurtosis, you can compute Sharpe and decide whether the bet is worth it.

모든 랩은 표준 교과서 수학에 근거합니다 (Bodie / Kane / Marcus, Fabozzi, Tandelilin). Read the full methodology in the How It Works panel above.

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Scenario

Probability (p)

Return (r)

p × r

(r − E(r))²

p × (r − E(r))²

0.0900

0.03610

0.01083

0.0500

0.00010

0.00005

-0.0300

0.06760

0.01352

Total

1.00

E(r) = 0.1100

σ² = 0.02440