Hi everyone I am trying to estimate the optimal hedge variance ratio for cross hedging two commodities. the price levels are used (compared to price change and % price change) and used the OLS with dummy variable for estimating the co-efficients. the equation looks like this Y = B + B1*D1 + B2*X + B3*(X*D1) Where Y = Daily Cash market price D1 = Dummy variable taking value 1 for period Oct-Mar and 0 for Apr-Sep X = Daily futures market price on which cross hedging is done. B,B1,B2,B3 are the slope co-efficients. The results look like this Regression Statistics Multiple R 0.948702709 R Square 0.900036831 Adjusted R Square 0.89981135 Standard Error 25.52050965 Observations 1334 Coefficients Standard Error t Stat P-value Intercept 53.817 4.375 12.300 0.000 X 0.986 0.012 80.283 0.000 D1 27.399 6.106 4.487 0.000 D1 * X -0.100 0.017 -5.820 0.000 It is understood the slope co-efficients for different periods are significant as indicated by t-table value. But I feel suspicious on the reliability of this values. I have used 5 years of daily price data for running the regression, and I feel suscpicious becasue, the monthly correlations (pearson correlation co-efficient) are highly varying between spot and futures and some times even negative. Can someone suggest me a) the tests to judge the reliability of hedge-variance values b) Is there any other better method than described here for estimating the hedge-variance values Thank you for the attention and look forward for an early reply rgds snvk

You have not told us what software you used to get the results you present. My first question is whether you are working with prices or log(prices)? If the former, I suggest you consider the latter; price changes tend to be much better behaved, more nearly normal, etc., on the log scale than in dollars, Euros, Rupias, or whatever. Secondly, have you made a normal probability plot of the residuals, preferably using "studres" in library(MASS)? (If you don't have Venables and Ripley 2002 Modern Applied Statistis with S, Springer, I recommend you get it and spend some time with it. In addition to "studres", it has an excellent chapter devoted to an introductory discussion of time series analysis.) Outliers suggest you may need to be working with some of the more sophisticated Rmetrics tools, but I'm not sufficiently familiar with those to say much more about that at the present time. If I had outliers, I might just delete them initially. However, I would definitely want to come back to them later, because the outliers could provide more information than other observations to predict, for example, a structural change in the market. Modeling and reacting properly to such signals could make the difference between stellar performance and disaster in managing a hedge fund. Thirdly, have you made acf and pacf of the residuals? Also, have you computed the Box-Ljung statistic (function Box.test)? If no, I suggest you do that as a next step. If they indicate some kind of autocorrelation structure, I might then try to model and estimate that along with your regression model using function "arima". If you still have questions (which I suspect), then feel free to ask another question. However, before you do that, PLEASE do read the posting guide prior! "http://www.R-project.org/posting-guide.html". Many people find answers to their own questions in the process of working through the posting guide. Questions posted following that process tend to be clearer, easier for others to understand and respond to. On average, this tends to increase the speed, volume and utility of replies. spencer graves Krishna wrote:> Hi everyone > > I am trying to estimate the optimal hedge variance ratio for cross > hedging two commodities. the price levels are used (compared to price > change and % price change) and used the OLS with dummy variable for > estimating the co-efficients. the equation looks like this > > Y = B + B1*D1 + B2*X + B3*(X*D1) > > Where Y = Daily Cash market price > D1 = Dummy variable taking value 1 for period Oct-Mar and 0 for Apr-Sep > X = Daily futures market price on which cross hedging is done. > B,B1,B2,B3 are the slope co-efficients. > > The results look like this > Regression Statistics > Multiple R 0.948702709 > R Square 0.900036831 > Adjusted R Square 0.89981135 > Standard Error 25.52050965 > Observations 1334 > > > Coefficients Standard Error t Stat P-value > Intercept 53.817 4.375 12.300 0.000 > X 0.986 0.012 80.283 0.000 > D1 27.399 6.106 4.487 0.000 > D1 * X -0.100 0.017 -5.820 0.000 > > It is understood the slope co-efficients for different periods are > significant as indicated by t-table value. But I feel suspicious on > the reliability of this values. > > I have used 5 years of daily price data for running the regression, > and I feel suscpicious becasue, the monthly correlations (pearson > correlation co-efficient) are highly varying between spot and futures > and some times even negative. > > Can someone suggest me > a) the tests to judge the reliability of hedge-variance values > b) Is there any other better method than described here for estimating > the hedge-variance values > > Thank you for the attention and look forward for an early reply > > rgds > > snvk > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html-- Spencer Graves, PhD Senior Development Engineer PDF Solutions, Inc. 333 West San Carlos Street Suite 700 San Jose, CA 95110, USA spencer.graves at pdf.com www.pdf.com <http://www.pdf.com> Tel: 408-938-4420 Fax: 408-280-7915