This companion file describes the programs used in Charles Bos, Ronald Mahieu and Herman van Dijk, "Daily Exchange Rate Behaviour and Hedging of Currency Risk", Journal of Applied Econometrics, Vol. 15, No. 6, 2000, pp. Declaration files ----------------- In the course of the paper, a range of programs have been used. Some programs are specifically targetted at computations concerning a specific model. If so, the programs loads the settings from a set of declaration files. These files are simox.dec - Model settings, including indication of name, dataset, routines with posterior density function etc. prior.dec - Settings on the prior density of the parameters mhsamp.dec - Settings controlling the length of the Metropolis-Hastings chain gibsamp.dec - Settings controlling the length of the Gibbs chain A range of declaration files can be found in the directory bmvd_jae/decl/. They contain settings for madu.dec - The white noise (WN) model mbdu.dec - The local level (LL) model mcdu.dec - The generalized local level (GLL) model mddu.dec - The generalized local level-GARCH (GLL-GARCH) model medu.dec - The generalized local level-Stochastic Volatility (GLL-SV) model mfdu.dec - The generalized local level-Student t (GLL-St) model mgdu.dec - The generalized local level-GARCH-Student t (GLL-GARCH-St) model Copy one of these files over bmvd_jae/simox.dec to change the model. The length of the sample can be controlled changing parameters in mhsamp.dec or gibsamp.dec. It is also possible to copy bmvd_jae/decl/sample/XXshort.dec or bmvd_jae/decl/sample/XXlong.dec over bmvd_jae/XXsamp.dec, to change to a `short' or `long' sample. The long sample is the one used in the article, but a Gibbs sampler may well take a day to calculate on a 400 Mhz Sun Sparc system. Also the computation of the marginal likelihood using output from the Gibbs sampler is very time consuming: For the models containing GARCH components, timing may reach 27 hours. The priors are fixed to the priors used in the article. Program files ------------- The programs are all written in Ox, and make use of a dynamic link library which is available for the Linux, Sun Solaris and Windows operating systems. On other systems, the C code is replaced by (slower) Ox code. Apart from Ox, the graphing package GnuDraw (see http://www2.tinbergen.nl/~cbos/gnudraw.html) has to be installed, together with GnuPlot (http://www.gnuplot.org). The following programs are available in the bmvd_jae-directory: plotdaty.ox - Plot graphs concerning the dataset, as in figures 2 and 3 in the paper. mhflex6.ox - Sample from a posterior density, using a Metropolis- Hastings algorithm. Valid for the WN, LL, GLL and GLL-GARCH models gibgas20.ox - Sample from a posterior density, using Gibbs sampling, and calculate the one-step ahead predictive density. Valid for the LL, GLL, GLL-GARCH, GLL-Student t and GLL- GARCH-Student t models. A picture similar to figure 6 is drawn. gibsv20.ox - Sample from the posterior density of the GLL-SV model, and calculate the one-step ahead predictive density. This program creates figure 6 of the paper. calcdre4.ox - Calculate the one-step ahead predictive density. Valid (and needed) only for the models on which the MH sampler was run. A picture similar to figure 6 is drawn. mixpltub.ox - Plot the posterior density for one model (as indicated by simox.dec). postana6.ox - Analyze and plot the posterior density, together with the priors and the 95% HPD region, for all models. Results in output from which tables 2 and 3 and figures 4 and 5 of the paper were constructed. mlwn.ox - Calculate the marginal likelihood using output from the Gibbs sampler, for the WN model. mlgas6.ox - Calculate the marginal likelihood using output from the Gibbs sampler, for the LL, GLL, GLL-GARCH, GLL-Student t and GLL-GARCH-Student t models. mlgsv3.ox - Calculate the marginal likelihood using output from the Gibbs sampler, for the GLL-SV model. Output of mlwn, mlgas6 and mlgs3 is combined into table 4. mlkern.ox - Calculate the marginal likelihood using a LaPlace, harmonic mean or kernel approximation. Only valid for models on which the MH sampler could be used. hedrat7.ox - Use the predictive densities of all models to calculate the hedge ratios. Outputs loads of tables for values of gamma between -20 and 0.5. Among these, the information of tables 5, 6 and 7 can be found. It also plots the relation between gamma and the final return, utility, maximum 3-month loss and 3-month gain. Figures similar to figures 7 and 8 also are created using this program. foreris2.ox - Evaluate the forecasting capabilities of the models, resulting in table 8, in the output under the heading `Single sided coverage test'. numacc3.ox - Check the relative numerical efficiency, by comparing the usual covariance matrix to a correlation consistent estimate of the covariance matrix. Output from the programs ------------------------ Model-specific output from the programs is written to a file in the directory bmvd_jae/excl/mXdu/, with X a letter (a-g) indicating the model. Not model-specific output can be found in bmvd_jae/excl/, or, concerning the program hedrat7.ox, in excl/hedret. Output may come in a file with the extension .out (indicating a pure text file), or in a file .plb. This latter extension indicates a graphic file, to be shown on the screen using the (GnuDraw) command plb2scr or translated to eps using plb2eps This only works if both GnuPlot (http://www.gnuplot.org) and GnuDraw (http://www2.tinbergen.nl/~cbos/gnudraw.html) are installed correctly. Furthermore, intermediate results are saved in matrix files with the extension .fmt or .mat. Order of execution ------------------ Most programs depend on output from other programs; e.g. the sampling has of course to be done before the predictive density can be calculated. In the script-file compall, or batch file compall.bat, the commands are given to run all calculations consecutively. Note that a complete run may take quite some time, e.g. around 7 hours on a Sun Sparc 400Mhz machine, for the `short' sample. Charles Bos, 16/11/2000 cbos@few.eur.nl http://www2.tinbergen.nl/~cbos/