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Lesson 8 of 8

Probability of Attaining a Return Goal

Earlier we looked at calculating the probability of beating a fixed target. Now we will look at calculating the probability of beating a benchmark which is itself stochastic.

Let us consider two assets A and B with the following details:

MeanStandard DeviationCorrelation
AμA=10%\mu_{A}=10\%μA​=10%σA=20%\sigma_{A}=20\%σA​=20%ρAB=30%\rho_{AB}=30\%ρAB​=30%
BμB=12%\mu_{B}=12\%μB​=12%σB=26%\sigma_{B}=26\%σB​=26%

We have a total of $10 million to invest. Our objective is to beat a benchmark.

Let us take the 50-50 portfolio, which has the following returns:

r1=0.5A+0.5Br_{1} = 0.5A + 0.5Br1​=0.5A+0.5B

Suppose the benchmark has the following returns:

r2=0.4A+0.6Br_{2} = 0.4A + 0.6Br2​=0.4A+0.6B

We need to find that probability that our portfolio will beat the benchmark index, i.e., P(r1>r2)P(r_{1} > r_{2})P(r1​>r2​)

This can be expressed as:

P(r1−r2>0)P(r_{1} - r_{2} > 0)P(r1​−r2​>0)

We can write this as:

P(0.5A+0.5B−0.4A−0.6B>0)P(0.5A + 0.5B - 0.4A - 0.6B > 0)P(0.5A+0.5B−0.4A−0.6B>0)

or

P(0.1A−0.1B)>0P(0.1A - 0.1B) > 0P(0.1A−0.1B)>0

0.1A - 0.1B is normally distributed.

Therefore, it's mean and standard deviation will be given as follows:

Mean, E(0.1A−0.1B)=0.1μA−0.1μB=0.1(10%)−0.1(12%)=−0.2%E(0.1A-0.1B) = 0.1\mu_{A} - 0.1\mu_{B} = 0.1(10\%)-0.1(12\%) = -0.2\%E(0.1A−0.1B)=0.1μA​−0.1μB​=0.1(10%)−0.1(12%)=−0.2%

Standard Deviation, σ(0.1A−0.1B)=0.12σA2+0.12σB2−2(0.1)(0.1)σAσBρ\sigma(0.1A-0.1B) = \sqrt{0.1^{2}\sigma_{A}^{2}+0.1^{2}\sigma_{B}^{2}-2(0.1)(0.1)\sigma_{A}\sigma_{B}\rho}σ(0.1A−0.1B)=0.12σA2​+0.12σB2​−2(0.1)(0.1)σA​σB​ρ​

=2.76%= 2.76\%=2.76%

We can write our probability as follows:

P(0.1A−0.1B>0)=P(0.1A−0.1B+0.0020.0276>0+0.0020.0276)P(0.1A-0.1B>0) = P\left ( \frac{0.1A-0.1B+0.002}{0.0276} > \frac{0 + 0.002}{0.0276} \right )P(0.1A−0.1B>0)=P(0.02760.1A−0.1B+0.002​>0.02760+0.002​)

=P(Z>0.0725)= P(Z>0.0725)=P(Z>0.0725)

where Z is the standard normal variable.

P(Z>0.0725)=47.1%P(Z>0.0725) = 47.1\%P(Z>0.0725)=47.1%, using 1-NORMSDIST(0.0725) in excel.

Therefore, the 50-50 portfolio has a 47.1% chance of beating the benchmark portfolio of 40-60.

This probability of beating the benchmar depends on the correlation between the assets. With high correlation, the probability will decrease and vice verse.

Previous Lesson

Probability of One Portfolio Outperforming Another Portfolio

Back to ebook

Understanding Portfolio Math

8 lessons

Lessons

1
Mean, Variance, Standard Deviation and Correlation
2
Constructing an Efficient Frontier
3
Minimum Variance Hedge Ratio
4
What is Serial Correlation (Autocorrelation)?
5
Diversification and Portfolio Risk
6
Value at Risk (VaR) of a Portfolio
7
Probability of One Portfolio Outperforming Another Portfolio
8
Probability of Attaining a Return Goal
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