## Correlation and Regression Analysis

Finance Junkie
Posts: 99
Joined: Sat Apr 07, 2012 10:24 am

### Correlation and Regression Analysis

pls explain below 2 qns:

Q1:
Illiquid positions will create
a. Zero autocorrelation in returns
b. An overstatement of the systematic risk measure
c. Positive autocorrelation in returns
d. Negative autocorrelation in returns

Q2:
Assume an asset price variance increases linearly with time. Suppose the expected asset price volatility for the next two months is 15%(annualized), and for the one month that follows, the expected volatility is 35% (annualized).What is the average expected volatility over the next three months?
(i) 24%
(ii) 22%
(iii) 25%
(iv) 35%

content.pristine
Finance Junkie
Posts: 356
Joined: Wed Apr 11, 2012 11:26 am

### Re: Correlation and Regression Analysis

Hi Suresh,

A1) An asset is called illiquid when it is not traded often. When an asset is illiquid, its price becomes "sticky". That means even if the entire market moves up by 5%, the illiquid asset's price doesn't change, just because it wasn't traded since the move(the price remains at the last traded price). Now, while we perform a regression of this asset price with the index, we see that due to the sticky nature of prices, we find positive auto-correlation.

A2) Volatility over the period = [(0.15)^2 + (0.15)^2+ (0.35)^2]^(1/2) = 40.92%
This is for 3 months
The average for one month = 40.92%/sqrt(n) = 40.92%/((3)^(1/2))= 23.62%

Hope this helps