Results 1  10
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285
Comparing Predictive Accuracy
 JOURNAL OF BUSINESS AND ECONOMIC STATISTICS, 13, 253265
, 1995
"... We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic, and need not even be symmetri ..."
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Cited by 901 (26 self)
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We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic, and need not even be symmetric), and forecast errors can be nonGaussian, nonzero mean, serially correlated, and contemporaneously correlated. Asymptotic and exact finite sample tests are proposed, evaluated, and illustrated.
Predictive regressions
 Journal of Financial Economics
, 1999
"... When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's "nitesample properties, derived here, can depart substantially from the standard regression set ..."
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Cited by 318 (13 self)
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When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's "nitesample properties, derived here, can depart substantially from the standard regression setting. Bayesian posterior distributions for the regression parameters are obtained under speci"cations that di!er with respect to (i) prior beliefs about the autocorrelation of the regressor and (ii) whether the initial observation of the regressor is speci"ed as "xed or stochastic. The posteriors di!er across such speci"cations, and asset allocations in the presence of estimation risk exhibit sensitivity to those
Order Flow and Exchange Rate Dynamics
 Journal of Political Economy
, 2002
"... This paper presents an exchange rate model of a new kind. Instead of relying exclusively on macroeconomic determinants, the model includes a determinant from the field of microstructure finance— order flow. Order flow is a determinant because it conveys information. This is a radically different app ..."
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Cited by 219 (20 self)
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This paper presents an exchange rate model of a new kind. Instead of relying exclusively on macroeconomic determinants, the model includes a determinant from the field of microstructure finance— order flow. Order flow is a determinant because it conveys information. This is a radically different approach to exchange rates. It is also strikingly successful. Our model of daily deutsche mark/dollar log changes produces an R 2 statistic above 60 percent. For the deutsche mark/dollar spot market as a whole, we find that $1 billion of net dollar purchases increases the deutsche mark price of a dollar by 0.5 percent. I.
Exchange Rates and Fundamentals
 Journal of Political Economy
, 2005
"... We show analytically that in a rational expectations presentvalue model, an asset price manifests near–random walk behavior if fundamentals are I(1) and the factor for discounting future fundamentals is near one. We argue that this result helps explain the wellknown puzzle that fundamental variabl ..."
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Cited by 187 (8 self)
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We show analytically that in a rational expectations presentvalue model, an asset price manifests near–random walk behavior if fundamentals are I(1) and the factor for discounting future fundamentals is near one. We argue that this result helps explain the wellknown puzzle that fundamental variables such as relative money supplies, outputs, inflation, and interest rates provide little help in predicting changes in floating exchange rates. As well, we show that the data do exhibit a related link suggested by standard models—that the exchange rate helps predict these fundamentals. The implication is that exchange rates and fundamentals are linked in a way that is broadly consistent with assetpricing models of the exchange rate. I.
Micro Effects of Macro Announcements: RealTime Price Discovery in Foreign Exchange
, 2002
"... Using a new dataset consisting of six years of realtime exchange rate quotations, macroeconomic expectations, and macroeconomic realizations (announcements), we characterize the conditional means of U.S. dollar spot exchange rates versus German Mark, British Pound, Japanese Yen, Swiss Franc, and th ..."
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Cited by 187 (20 self)
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Using a new dataset consisting of six years of realtime exchange rate quotations, macroeconomic expectations, and macroeconomic realizations (announcements), we characterize the conditional means of U.S. dollar spot exchange rates versus German Mark, British Pound, Japanese Yen, Swiss Franc, and the Euro. In particular, we find that announcement surprises (that is, divergences between expectations and realizations, or "news") produce conditional mean jumps; hence highfrequency exchange rate dynamics are linked to fundamentals. The details of the linkage are intriguing and include announcement timing and sign effects. The sign effect refers to the fact that the market reacts to news in an asymmetric fashion: bad news has greater impact than good news, which we relate to recent theoretical work on information processing and price discovery. Key Words: Exchange Rates; Macroeconomic News Announcements; Jumps; Market Microstructure; HighFrequency Data; Expectations Data; Anticipations Data; Order Flow; Asset Return Volatility; Forecasting.
A Comprehensive Look at the Empirical Performance of Equity Premium Prediction,” working paper
, 2004
"... Given the historically high equity premium, is it now a good time to invest in the stock market? Economists have suggested a whole range of variables that investors could or should use to predict: dividend price ratios, dividend yields, earningsprice ratios, dividend payout ratios, net issuing rati ..."
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Cited by 160 (4 self)
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Given the historically high equity premium, is it now a good time to invest in the stock market? Economists have suggested a whole range of variables that investors could or should use to predict: dividend price ratios, dividend yields, earningsprice ratios, dividend payout ratios, net issuing ratios, bookmarket ratios, interest rates (in various guises), and consumptionbased macroeconomic ratios (cay). The typical paper reports that the variable predicted well in an insample regression, implying forecasting ability. Our paper explores the outofsample performance of these variables, and finds that not a single one would have helped a realworld investor outpredicting the thenprevailing historical equity premium mean. Most would have outright hurt. Therefore, we find that, for all practical purposes, the equity premium has not been predictable, and any belief about whether the stock market is now too high or too low has to be based on theoretical prior, not on the empirically variables we have explored.
Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach
 Journal of Financial and Quantitative Analysis
, 1997
"... The views expressed are those of the individual authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors. Federal Reserve Bank of St. Louis Working Papers are preliminary materials circulated to stimulat ..."
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Cited by 154 (16 self)
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The views expressed are those of the individual authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors. Federal Reserve Bank of St. Louis Working Papers are preliminary materials circulated to stimulate discussion and critical comment. References in publications to Federal Reserve Bank of St. Louis Working Papers (other than an acknowledgment that the writer has had access to unpublished material) should be cleared with the author or authors. Photo courtesy of The Gateway Arch, St. Louis, MO. www.gatewayarch.com
Why is it so Difficult to Beat the Random Walk Forecast of Exchange Rates
 Journal of International Economics
, 2003
"... Most TI discussion papers can be downloaded at ..."
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Forecast Evaluation and Combination
 IN G.S. MADDALA AND C.R. RAO (EDS.), HANDBOOK OF STATISTICS
, 1996
"... It is obvious that forecasts are of great importance and widely used in economics and finance. Quite simply, good forecasts lead to good decisions. The importance of forecast evaluation and combination techniques follows immediately forecast users naturally have a keen interest in monitoring and ..."
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Cited by 122 (29 self)
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It is obvious that forecasts are of great importance and widely used in economics and finance. Quite simply, good forecasts lead to good decisions. The importance of forecast evaluation and combination techniques follows immediately forecast users naturally have a keen interest in monitoring and improving forecast performance. More generally, forecast evaluation figures prominently in many questions in empirical economics and finance, such as: Are expectations rational? (e.g., Keane and Runkle, 1990; Bonham and Cohen, 1995) Are financial markets efficient? (e.g., Fama, 1970, 1991) Do macroeconomic shocks cause agents to revise their forecasts at all horizons, or just at short and mediumterm horizons? (e.g., Campbell and Mankiw, 1987; Cochrane, 1988) Are observed asset returns &quot;too volatile&quot;? (e.g., Shiller, 1979; LeRoy and Porter, 1981) Are asset returns forecastable over long horizons? (e.g., Fama and French, 1988; Mark, 1995)
Insample or outofsample tests of predictability: which one should we use
 CEPR Discussion Papers 3671, CEPR Discussion Papers
, 2002
"... It is widely known that signiÞcant insample evidence of predictability does not guarantee signiÞcant outofsample predictability. This is often interpreted as an indication that insample evidence is likely to be spurious and should be discounted. In this paper we question this conventional wisdom ..."
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Cited by 117 (11 self)
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It is widely known that signiÞcant insample evidence of predictability does not guarantee signiÞcant outofsample predictability. This is often interpreted as an indication that insample evidence is likely to be spurious and should be discounted. In this paper we question this conventional wisdom. Our analysis shows that neither data mining nor parameter instability is a plausible explanation of the observed tendency of insample tests to reject the no predictability null more often than outofsample tests. We provide an alternative explanation based on the higher power of insample tests of predictability. We conclude that results of insample tests of predictability will typically be more credible than results of outofsample tests.