Risk Management and Probability distribution By Dr. Bobby Srinivasan and Dr. Sudhakar Balachandran

June 25, 2015 | Posted by bobbysrinivasan << back to blog

This blog is to create awareness among students as to how they can use probability distribution to predict future interest rates.

The US economy is currently enjoying a partial revival after a prolonged slowdown. This is happening with an increase in the inflation rate. The latest data indicates that the core inflation (other than food and energy) has recorded 2.7% much higher than the targeted inflation of 2%. Janet Yellen the US Federal Chairwoman had indicated earlier that as long as the non-farm payroll figures continue to stay above 2,00,000 for a prolonged period of time with a moderately high inflation rate exceeding 2% the open market committee will consider nudging up the discount rate from the current frozen level of 0%. This is a conversation between a student and his professor.

Student: Professor, I had my education in engineering. I had no exposure to management subjects. Currently, I am taking a course in statistics. Our professor is talking about various probability distributions, particularly with reference to risk measurement. Please help me understand this concept better.

Professor: It is important that you learn to measure risk, since all your assessment about the future outcome can only be done only through probabilities. Let me illustrate this, as I had indicated earlier that there is a possibility of the US interest rate going up. Let us look at the alternatives the US Federal Reserve may face.

Alternative 1: The future inflation rate will stay above 2% and the future monthly job creation will (A1) continue to be above 2,00,000.

Alternative 2: The future inflation rate will be less than 2% and the future monthly job creation will (A2) continue to be above 2,00,000.

Alternative 3: The future inflation rate will be more than 2% and the future monthly job creation (A3) will be less than 2,00,000.

Then they assess the probabilities of these alternatives happening in the future which, for example could be P(A₁) = 0.6 P(A₂) = 0.2 P(A₃) = 0.2

So now you have the probability distribution.

Event Probability of possible outcome

A₁ 0.6

A₂ 0.2

A₃ 0.2

———–

1.0

———–

Student: This is simple. Thank you, Professor. But what happens that future data changes these probabilities.

Professor: Of course, these probabilities can be revised. These are called a priori probabilities. With additional information, these probabilities could be changed. They will then be called a posteriori probabilities. The probability concepts are extremely powerful. Bankers use them to calculate risks of exposure. Traders use them to design their hedging strategies. When you go deeper in the subject you will learn how different types of probability distribution can be constructed and put to use in real life.

Student: Thanks Professor.

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