Using out-of-sample mean squared prediction errors to test the Martingale difference hypothesis

By Todd E. Clark, Ken West. 2006

473 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9f5404f89f341e8cb9ed2edee435b46a48539b81

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Citations in the corpus

Comparing forecast accuracy: A Monte Carlo investigation (2013, background): “ENC − F = Pf / σ̂(2) 2, (7) where σ̂(2) 2 is the mean squared forecast error of the nesting model as in (4).”
Some Theoretical Results on Forecast Combinations (2018, unknown): “This difference in MSFE is also defined as the MSFE “adjustment” in Clark and West (2006). The third observation from Corollary 2 is that the sum of each row in Ω must be the same for simple average to be the optimal weight.”
Predictive Regressions with Time-Varying Coefficients (2012, unknown): “Clark and West (2006), however, point out that, for the purpose of comparing the performance of two nested prediction models, the MSPEs have to be adjusted for different model specifications.7 Each model’s adjustment depends on the variation in the model’s prediction8 and is calculated as (for…”
Exchange Rate Predictability (2013, unknown): “The main exception is the work by Clark and West (2006) regarding the out-of-sample predictive ability of UIRP; the next sections will investigate the reasons why their …nding is di¤erent from the rest of the literature.”
Taylor Rules with Real-Time Data: A Tale of Two Countries and One Exchange Rate (2008, methodology): “ Clark and West (2006) propose a simple correction, which results in the following asymptotically normally”
Exchange rate predictability in a changing world (2014, unknown): “It turns out that the FE panel regression accumulates relatively many “Yes” answers in the first forecast sample; and mostly for h = 4,8,12 quarters.”
What Do We Learn from the Price of Crude Oil Futures (2010, unknown): “Nested model comparisons with estimated parameters are based on Clark and West (2006).”
Evaluating Direct Multistep Forecasts (2005, methodology): “Moreover, in applications in which the null forecasting model is a random walk, Clark and West ( 2004 ) find that using the HAC estimator of Hodrick ( 1992 ) rather than the common Newey and West ( 1987 ) estimator greatly improves the size of t -tests for equal MSE and forecast encompassing.”
Statistical tests for multiple forecast comparison (2012, background): “See, among others, Giacomini and White (2006), Clark and West (2006), Clark and West (2007) and McCracken (2007).”
The Continuing Puzzle of Short Horizon Exchange Rate Forecasting (2008, methodology): “…main component of the DMW test statistic) as: P 1 t=TX t=R+1 ê21;t+1 P 1 t=TX t=R+1 ê22;t+1 = 2P 1 t=TX t=R+1 (yt+1Xtb̂t) P 1 t=TX t=R+1 (Xtb̂t) 2: Clark and West (2006, 2007) argue that under the null hypothesis e1;t+1 = e2;t+1 = yt+1; and since Clark and West (2006, 2007) assume that the…”
Out-of-sample exchange rate predictability with Taylor rule fundamentals (2009, unknown): “…methods and estimate rolling rather than recursive regressions for comparison with the extensive literature following Meese and Rogoff (1983a), and choose a rolling window of 120 observations to estimate alternative forecast models following the empirical exercise in Clark and West (2006).”
On the sources of uncertainty in exchange rate predictability (2018, unknown): “To assess the statistical significance of the differences in the forecasts, many papers employ the Diebold and Mariano (1995) and West (1996) tests (hereafter DMW), and/or the Clark and West (2006, 2007) test (hereafter CW).”
On the Forecasting Accuracy of Multivariate GARCH Models (2010, background): “Important generalizations can be found West (1996), Clark and McCracken (2001), Clark and West (2006) and Clark and West (2007).”
A Comprehensive Look at Financial Volatility Prediction by Economic Variables (2011, unknown): “Since the benchmark model is nested by the model of interest, the asymptotic test put forth by Clark and West (2007) may be used.”
Approximately Normal Tests for Equal Predictive Accuracy in Nested Models (2007, background): “(2005) (recursive) and Cooper et al. (2005) and Ang et al.”
A Simple Explanation of the Forecast Combination Puzzle (2009, methodology): “This analysis is extended to the forecast evaluation of competing nested models by Clark and West (2006).”
Advances in Forecasting Under Instability (2012, unknown): “…between these approaches and Giacomini and White (2006) is that they test two di¤erent null hypotheses: the null hypothesis in West (1996) and Clark and West (2006, 2007) concerns forecast losses that are evaluated at the population parameters, whereas in Giacomini and White (2006) the…”