Sharpe Ratio Portfolio Optimization Model
Trial 1 - 9/1/2022
The following trial was conducted on 10 random stocks from NSE Website. Stocks ranged from finance to machinery, covering a vast range of sectors helping to understand the model better. This was my first trial so there can be a lot of flaws in the assumptions and data I have derived, so am open to all the changes.
To give a basic understanding, in this model we expect the solver to give the maximum Sharpe ratio for the given constraints of minimum and maximum weightage of the stocks. Now Sharpe ratio is derived from the expected value from the return on asset subtracted with a risk-free rate upon the standard deviation or the volatility of the net portfolio. Here one assumption I followed was, for the expected value I used the beta for the stock which was calculated from the given historic return of the NIFTY50 Index for the past year. The overall time frame for the current model is 1 year from Jan2021-Jan2022. With the help of all the given data, we can see the solution with the Sharpe ratio coming to be 1.82.
Observations - Every time I heard a lot of people say smaller timeframes generate vague results which cannot be reliable. But I was never convinced with this argument. But as I solved this model, I understood the value of the statement. Now we all agree that 2020 and 2021 were quite unique with the Nifty50 index giving around 25% returns. This is not usual and hence if you are able to see, the solver is giving an expected return of 32.1209%, which is not that feasible I think for 2022.
Conclusion - For the next trial, will use a larger timeframe of 3 years followed by 5 years to see how the model is performing, and how close is it to the median returns of an average portfolio. Till then have a good day. See you soon.