Equity, MF, FD

This post is the first of the many post I plan to write about OR(Operational Research). 

OR caught my attention in one of the webinars where the presenter alluded to the possibilities of OR and ML in solving some tough business problems. 

Many organizations use excel based linear models or extrapolation techniques to build project plans. Project constraints like availability of people, skill set and equipment are handled or adjusted manually in the plans. 

Manual approach while on one side provide confidence to the manager/program team on how to control and execute the program however this technique:

• Does not provide the true potential of available resources(except for very simple scenarios).
• Manual planning limits the number of constraints considered.
• Manual planning discourages continuous planning. 

Today I will not discuss how OR can help with project planning but another use case with respect to personal financial planning specifically distribution of your investment in equity, debt and bank FDs. 

OR(Operational Research) techniques are an excellent application to make investment decisions in financial markets. With the improvements in near real time availability of data, transparency of data and power of computers the OR techniques can provide a quantitative technique to make a descision instead of gut or hearsay. 

Consider you have Rs.100 to invest and you want to ascertain the most optimal allocation(max profit or min loss) of your funds across Equity, Debt and Bank FDs with following assumptions. 

With the given data(above) and using OR Linear programming technique the most optimal allocation will be 60% Equity, 20% Debt and 20% FDs minimizing the potential loss to ~ Rs (12).  

The reason for negative return is the high risk probability on Equity investment & when changed to 10% results in overall positive return of ~2%. 

For me I never imagined I can use this technique for my own investment descision, it helped meals understand the possible downside. 

You can find an excel model in the GitHub link available in the reference section below(and try couple of iterations yourself).

Now we can take this on notch higher, by introducing iterative/continuous optimization based on the risk perception, change in rate of return and availability of new sources of investment. 

My plan for this post was to introduce OR and share with you the possibilities of OR application and building a real time use on Software Engineering. 

Happy reading, will be back soon with my next post!

References:

Link to Model( GitHub )