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
What does it mean when the U.S. dollar weakens in the foreign exchange market? While the U.S. dollar weakens in the foreign exchange market one U.S. dollar buys smaller amount un

Let us look into few floaters that have constant quoted margin. 1. De-leveraged Floaters 2.  Inverse Floaters 3.  Dual-Indexed Flo

Explain and critically evaluate : a)  The relevance of committed fixed costs in deciding the optimal mix of products to maximum a company's profit and the importance of relevant

Q. Show Function of the Financial decision? Financial decision: the second major decision is involved in financial management is the financial decision the investment decision

What is the primary advantage to a corporation of investing some of its funds in working capital?  By investing in working capital a firm acquires the liquidity it needs helpin

Citilink will start a new business line on 1st July, 2011 to make and sell bus souvenirs. The target sales and production volume are 525,000 in next year. The following projected

Capital structure theory: Use the following information to answer the questions: Case I: Capital structure theory ( no tax ) Case II: Capital struct

Define Sources of risk with types???? how can we analysis the risk in bussiness?? plese help!!!!!

Question 1: (a) Explain fully the following financial accounting techniques: i. Cash accounting ii. Accrual accounting iii. Fund accounting iv. B

ARR AND PAYBACK (a) Accounting rate of return (ARR) is a computation of the return on an investment where the annual profit prior to interest and tax is expressed as a percen