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R-CMD-check Last-changedate packageversion CRAN_Status_Badge

tstests

The tstests package provides a number of tests for evaluating the goodness of fit of estimated time series models as well as forecast evaluation tests. In addition to a standard print method, each test has an as_flextable method for pretty printing to various document formats. The table below provides an overview of the implemented tests, some of which were ported over from rugarch, others re-written and some are new.

Test Function Reference
Berkowitz Forecast Density Test berkowitz_test Berkowitz (2001)
Non Parametric Density Test hongli_test Hong and Li (2005)
Directional Accuracy Tests dac_test Pesaran (1992), Anatolyev (2005)
GMM Orthogonality Test gmm_test Hansen (1982)
Mincer-Zarnowitz Test minzar_test Mincer (1969)
Sign Bias Test signbias_test Engle (1993)
Nyblom-Hansen Parameter Constancy Test nyblom_test Nyblom (1989)
Expected Shortfall Test shortfall_de_test Du (2017)
Value at Risk Test var_cp_test Christoffersen (1998,2004)

Installation

The package can be installed from CRAN or the tsmodels repo.

install.packages("tstests")
remotes::install_github("tsmodels/tstests", dependencies = TRUE)

Note, that in order to make use of symbolic output in some of the tests, flextable requires equatags to be installed which has a dependency on xlst which in turn has SystemRequirements libxslt. Therefore, if you are seeing NA printed in place of symbols, then it is likely that xlst is not installed.

References

Berkowitz,J. (2001). Testing density forecasts, with applications to risk management. Journal of Business & Economic Statistics, 19(4), 465–474.

Hong, Y., and Li, H. (2005), Nonparametric specification testing for continuous-time models with applications to term structure of interest rates, Review of Financial Studies, 18(1), 37–-84.

Pesaran,M.H., Timmermann,A. (1992). A simple nonparametric test of predictive performance. Journal of Business & Economic Statistics, 10(4), 461–465

Anatolyev,S., Gerko,A. (2005). A trading approach to testing for predictability. Journal of Business & Economic Statistics, 23(4), 455–461.

Hansen,L.P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50(4), 1029–1054.

Mincer JA, Zarnowitz V (1969). The evaluation of economic forecasts. In Economic forecasts and expectations: Analysis of forecasting behavior and performance, 3–46. NBER.

Nyblom,J. (1989). Testing for the constancy of parameters over time. Journal of the American Statistical Association, 84(405), 223–230.

Du Z, Escanciano JC (2017). Backtesting expected shortfall: accounting for tail risk. Management Science, 63(4), 940–958.

Christoffersen PF (1998). Evaluating interval forecasts. International Economic Review, 841–862.

Christoffersen,P., Pelletier,D. (2004). Backtesting value-at-risk: A duration-based approach. Journal of Financial Econometrics, 2(1), 84–108.

Engle RF, Ng VK (1993). Measuring and testing the impact of news on volatility. The Journal of Finance, 48(5), 1749–1778.