Forecasting yield volatility, Financial Management

There are several methods available to forecast yield volatility. But before that, let us look into the calculation of forecasted standard deviation.

Assume that a trader wants to forecast volatility at the end of 07/08/2007, by using the 20 most recent days of trading and update the forecast at the end of each trading day. To calculate these, the trader can calculate a 20-day moving average of the daily percentage yield change.

Still now it has been assumed that the moving average is an appropriate value to use for the expected value of the change in yield. But, some experts view that it would be more appropriate to assume the expected value of the change in yield to be zero. In eq. (1) by substituting zeros in place of moving average X, we get

         Variance =  380_forecasting yield volatility.png                                                                                       ...Eq (2) 

An equal weightage is assigned to all observations by the daily standard deviation given by equation 2. Therefore, a weightage of 20% for each day is given if the trader is calculating volatility based on the most recent 20 days of trading.

Greater weightage is given to recent movements in the yield or price while determining volatility, and less weightage is given to the observations that are farther in the past. Revising equation 2 to include the weightages we get,

         Variance =  1498_forecasting yield volatility1.png                                                                                        ...Eq. (3)

Wt is the weight assigned to the observations t. The sum of all the weights assigned to the observation will be equal to 1.

A time series characteristic of financial assets suggests that a high volatility period is followed by a high volatility period and a low volatility period is followed by a low volatility period. From this observation, we can tell that the recent past volatility influences current volatility. This time series property of volatility can be estimated with the help of statistical models like autoregressive conditional heteroskedasticity.

Posted Date: 9/10/2012 3:46:53 AM | Location : United States







Related Discussions:- Forecasting yield volatility, Assignment Help, Ask Question on Forecasting yield volatility, Get Answer, Expert's Help, Forecasting yield volatility Discussions

Write discussion on Forecasting yield volatility
Your posts are moderated
Related Questions
Managing Risk and Contingency Plan: An essential component of any financial management framework is the validation and protection of the information contained in the system. In

Disclaimer of Opinion - Statement by an AUDITOR indicating inability to express an opinion on the fairness of FINANCIAL STATEMENTS provided and reason for the inability. The audito

Timing of Financial Reports: Just as the actual report requirements differ depending on the requirements of the stakeholder that will be using them, so too will the timing of t

What are the negative consequences of a company holding too much cash? A company holding so much cash would be giving up the opportunity to invest much more in income producing a

How can we calculate ration analysis in financial management?? Determine the ration analysis? Need assignemt help on this topic

Liquidity risk tends to change as and when there exists a change in the spread between the bid and the ask price. Market liquidity change is a matter of concern f

Q. What do you mean by Hedge Fund? In the easiest strategy a hedge fund borrows Hong Kong dollars (HKD) and then sells them in the market against USD that is they short the HKD

Should a company pursue price hike or focus on increasing sales volume

Compare and contrast mutual and stockholder-owned savings and loan associations. A few savings and loan associations are owned by stockholders, just like commercial banks and ot

Q. Define the Constructive Receipt? Constructive Receipt - A taxpayer is considered to have received income even though monies are not in hand, it may have been set aside or ot