Nonlinear exchange rate predictability

We study whether the nonlinear behavior of the real exchange rate can help us account for the lack of predictability of the nominal exchange rate. We construct a smooth nonlinear error-correction model that allows us to test the hypotheses of nonlinear predictability of the nominal exchange rate and nonlinear behavior on the real exchange rate in the context of a fully specified cointegrated system. Using a panel of 19 countries and three numeraires, we find evidence of nonlinear predictability of the nominal exchange rate and of nonlinear mean reversion of the real exchange rate. Out-of-sample Theil’s U -statistics show a higher forecast precision of the nonlinear model than the one obtained with a random walk specification. Although the robustness of the out-of-sample results over different forecast windows is somewhat limited, we are able to obtain significant predictability gains—from a parsimonious structural model with PPP fundamentals—even at short-run horizons.     

An International Analysis of Historical and Forecast Earnings in Accounting-Based Valuation Models

Abstract:  In this paper we examine whether the valuation properties of historical accounting amounts, namely earnings and equity book value, differ from those of forecasted earnings for firms in 17 developed countries classified into six accounting regimes. We compare the performance of a historical model and a residual-income forecast model for explaining security prices. The historical model uses the book value of equities and actual historical earnings and the forecast model uses the book value of equities and analysts' forecasts of earnings in the residual income for estimating the intrinsic value of the firm. The results suggest that book values, historical earnings or forecasted earnings are value relevant in most regimes and countries examined. The forecast model offers significantly greater explanatory power for security prices than the historical model in the Anglo-Saxon and North American countries, Japan, Germany, and three Nordic countries. The explanatory power of the historical model is similar to that of the forecast model in the Latin countries, two Nordic countries, and Switzerland. We find that the forecast model performs similarly to the historical model where financial analysts' forecasts are noisy and analysts are less active. Further results indicate that the forecasted earnings are more value-relevant than the historical earnings in countries with stronger investor protection laws, less conservative GAAP, greater income conservatism, and more transparent accounting systems.     

Pricing currency risk in the stock market: Evidence from Finland and Sweden 1970-2009

We investigate the role of currency risk on stock markets in two interlinked Nordic countries exhibiting a gradual move from fixed to floating exchange rates. We apply the Ding and Engle (2001) covariance stationary specification in a multivariate GARCH-M setup to test a conditional international asset pricing model. Using a sample period from 1970 to 2009, we find that the currency risk is priced in both stock markets, and that the price and the risk premium are lower after the floatation of the currencies, especially for Finland. We also find the cross-country exchange rate shock from Finland to affect the price of currency risk in Sweden, but not vice versa. Finally, we discuss some of the potential issues in applying multivariate GARCH-M specifications in tests of asset pricing models.     

Comparative Value Relevance Studies: Country Differences Versus Specification Effects

This paper sheds light on the sensitivity of findings in comparative international value relevance studies regarding two fundamental methodological choices. We hypothesize and find that, first, using the regression vs. the portfolio returns specification and, second, the choice of the return window, is not arbitrary. Both choices will have an impact on country rankings and the significance of cross-country differences in comparative designs. This makes us conclude that findings in previous comparative international value relevance studies are partly driven by differences in market characteristics across countries. Extending the findings of Francis and Schipper (1999) and Collins and Kothari (1989), our results suggest that previous comparative studies might thus have overstated value relevance differences and institutional variables' power to explain these differences across countries. Findings are based on a treatment sample of 56,000 firm-year observations from 12 countries and from 12 matched U.S. control samples, with observations from 1988 to 2007.     

Varying risk premia in international bond markets

Cochrane and Piazzesi [Cochrane, J.H., Piazzesi, M., 2005. Bond risk premia. American Economic Review 95, 138–160] use forward rates to forecast future bond returns. We extend their approach by applying their model to international bond markets. Our results indicate that the unrestricted Cochrane and Piazzesi (2005) model has a reasonable forecasting power for future bond returns. The restricted model, however, does not perform as well on an international level. Furthermore, we cannot confirm the systematic tent shape of the estimated parameters found by Cochrane and Piazzesi (2005). The forecasting models are used to implement various trading strategies. These strategies exhibit high information ratios when implemented in individual countries or on an international level and outperform alternative approaches. We introduce an alternative specification to forecast future bond returns and achieve superior risk-adjusted returns in our trading strategy. Bayesian model averaging is used to enhance the performance of the proposed trading strategy.     

A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns

This study uses economic policy uncertainty (EPU) indices for ten developed countries, three diffusion models, and five combination methods to forecast excess returns in the U.S. stock market. It shows empirically that, over the period January 1997 to January 2022, non-U.S. EPU indices have better predictive power for U.S. equity market excess returns than the U.S. EPU index itself. This illustrates how economic information from international markets can affect the U.S. stock market. This finding challenges the extensively recognized view that the U.S. is where important market signals are initially transmitted to other markets, suggesting that this belief is incomplete. Our outcomes are robust to a battery of tests covering model selection, model specification, forecast horizons, and the pandemic period, and their economic values are assessed. The findings are essential for the financial field to confront future fierce situations and crises.     

A New Model of Inflation,Trend Inflation,and Long‐Run Inflation Expectations

This paper develops a bivariate model of inflation and a survey‐based long‐run forecast of inflation that allows for the estimation of the link between trend inflation and the long‐run forecast. Thus, our model allows for the possibilities that long‐run forecasts taken from surveys can be equated with trend inflation, that the two are completely unrelated, or anything in between. Using a variety of inflation measures and survey‐based forecasts for several countries, we find that long‐run forecasts can provide substantial help in refining estimates and fitting and forecasting inflation. It is less helpful to simply equate trend inflation with the long‐run forecasts.     

Do measures of systemic risk predict U.S. corporate bond default rates?

Using univariate and multivariate Mixed Data Sampling (MIDAS) and LASSO estimation methodologies, we explore whether the U.S. annual average corporate bond default rate can be predicted by 12 monthly systemic risk measures proposed in the literature. We find that nearly all of the systemic risk indicators have predictive power for the default rate. Granger causality tests based on multivariate mixed frequency VAR models further support this conclusion. On the basis of MIDAS models, we illustrate that five of these indicators are able to forecast out-of-sample the 2009 corporate default crisis. Using a LASSO multivariate model, it is further shown that the systemic risk indicators can forecast out-of-sample both the 2009 default rate and the default rates during the buildup before the crisis and in the aftermath of the crisis. Institution-specific and volatility systemic risk measures are the most relevant for modeling U.S. corporate bond default rates, with the Conditional VaR measure of Adrian and Brunnermeier (2016) exhibiting the best performance.     

Forecasting the return distribution using high-frequency volatility measures

The aim of this paper is to forecast (out-of-sample) the distribution of financial returns based on realized volatility measures constructed from high-frequency returns. We adopt a semi-parametric model for the distribution by assuming that the return quantiles depend on the realized measures and evaluate the distribution, quantile and interval forecasts of the quantile model in comparison to a benchmark GARCH model. The results suggest that the model outperforms an asymmetric GARCH specification when applied to the S&P 500 futures returns, in particular on the right tail of the distribution. However, the model provides similar accuracy to a GARCH (1, 1) model when the 30-year Treasury bond futures return is considered.     

Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models

We compare forecasts of the realized volatility of the pound, mark and yen exchange rates against the dollar, calculated from intraday rates, over horizons ranging from one day to three months. Our forecasts are obtained from a short memory ARMA model, a long memory ARFIMA model, a GARCH model and option implied volatilities. We find intraday rates provide the most accurate forecasts for the one-day and one-week forecast horizons while implied volatilities are at least as accurate as the historical forecasts for the one-month and three-month horizons. The superior accuracy of the historical forecasts, relative to implied volatilities, comes from the use of high frequency returns, and not from a long memory specification. We find significant incremental information in historical forecasts, beyond the implied volatility information, for forecast horizons up to one week.     

Is the relationship between prices and exchange rates homogeneous?

Empirical tests of purchasing power parity (PPP) are implicitly based on the conditions of symmetry and proportionality of the price coefficients. We investigate a separate condition, which we term homogeneity. Specifically, while there may be factors that drive a wedge between prices and exchange rates, when these factors are held constant we would expect a change in exchange rates to be associated with a proportional, or homogeneous, change in prices. To test for the existence of homogeneity in prices, we conduct two experiments. First, we apply a time-varying-coefficient procedure to nine euro-area countries as well as the euro area as a whole during the (monthly) sample period, 1999:M1 to 2011:M3. Second we apply the same procedure to the same group of countries, plus Canada, Japan and Mexico, over the longer period, 1957:M4 to 2011:M3. We find that averages of the price coefficients, corrected for specification biases, are uniformly homogeneous in the long run, providing strong support for PPP.     

Product market competition and analyst forecasting activity: International evidence

In this study, we investigate how product market competition affects the extent of analyst following and the properties of analyst forecasts. Using a broad sample of firms from 37 countries over the 1990–2008 period, we find that firms that operate in more concentrated industries and with stronger pricing power are associated with greater analyst following, higher forecast accuracy, and lower forecast dispersion. Moreover, the effect of product market power on analyst following and forecast properties is more pronounced in countries with less effective competition laws and higher entry costs. These findings suggest that high industry concentration and a dominant market position enhance the earnings predictability of firms and lower their information uncertainty, and that country-level institutions that promote competition effectively constrain the power in product markets.     

Modeling Mortality With Jumps: Applications to Mortality Securitization

In this article, we incorporate a jump process into the original Lee–Carter model, and use it to forecast mortality rates and analyze mortality securitization. We explore alternative models with transitory versus permanent jump effects and find that modeling mortality via transitory jump effects may be more appropriate in mortality securitization. We use the Swiss Re mortality bond in 2003 as an example to show how to apply our model together with the distortion measure approach to value mortality-linked securities. Pricing the Swiss Re mortality bond is challenging because the mortality index is correlated across countries and over time. Cox, Lin, and Wang (2006) employ the normalized multivariate exponential tilting to take into account correlations across countries, but the problem of correlation over time remains unsolved. We show in this article how to account for the correlations of the mortality index over time by simulating the mortality index and changing the measure on paths.     

Time-varying integration,interdependence and contagion

Bekaert et al. (2005) define contagion as “correlation over and above what one would expect from economic fundamentals”. Based on a two-factor asset pricing specification to model fundamentally-driven linkages between markets, they define contagion as correlation among the model residuals, and develop a corresponding test procedure. In this paper, we investigate to what extent conclusions from this contagion test depend upon the specification of the time-varying factor exposures. We develop a two-factor model with global and regional market shocks as factors. We make the global and regional market exposures conditional upon both a latent regime variable and three structural instruments, and find that, for a set of 14 European countries, this model outperforms more restricted versions. The structurally-driven increase in global (regional) market exposures and correlations suggest that market integration has increased substantially over the last three decades. Using our optimal model, we do not find evidence that further integration has come at the cost of contagion. We do find evidence for contagion, however, when more restricted versions of the factor specifications are used. We conclude that the specification of the global and regional market exposures is an important issue in any test for contagion.     

Forecasting returns: New European evidence

This paper builds on the recent debate on the in-sample and out-of-sample predictability of US aggregate returns using a wide range of predictors by providing new evidence for smaller and less market-oriented European countries.We find evidence that macro and technical predictors can (statistically) improve forecast accuracy and (economically) generate gains to investors; in contrast to the US results, predictability in our sample of European countries exists in recent data. We also find that simple forecast combinations consistently yield substantial benefits both in forecast accuracy and economic gain. For example, the magnitude of the forecasting gains for our European countries is often larger than those found for the US and other G7 countries. We provide initial evidence on the link between country characteristics and out-of-sample forecast performance. Our empirical results indicate that market development is related to the forecast performance of macro variables. There is also some evidence that forecast performance is related to market size and liquidity.     

Testing for rational bubbles in the presence of structural breaks: Evidence from nonstationary panels

This paper presents new results on the rational bubbles hypothesis for a panel of 18 OECD countries using the model developed by Campbell (2000). We provide an analysis of international data that exploits increased power deriving from the panel unit root and cointegration methodology, together with the flexibility of allowing explicitly for multiple endogenous structural breaks in the individual series. Differently from the time series methodology, the panel data approach allows for a global analysis of the financial crashes that are related to rational bubbles. We find strong evidence in favor of bubbles phenomena.     

Disagreement and Biases in Inflation Expectations

Disagreement in inflation expectations observed from survey data varies systematically over time in a way that reflects the level and variance of current inflation. This paper offers a simple explanation for these facts based on asymmetries in the forecasters' costs of over- and underpredicting inflation. Our model implies (i) biased forecasts, (ii) positive serial correlation in forecast errors, (iii) a cross-sectional dispersion that rises with the level and the variance of the inflation rate, and (iv) predictability of forecast errors at different horizons by means of the spread between the short- and long-term variance of inflation. We find empirically that these patterns are present in inflation forecasts from the Survey of Professional Forecasters. A constant bias component, not explained by asymmetric loss and rational expectations, is required to explain the shift in the sign of the bias observed for a substantial portion of forecasters around 1982.     

我国广义货币供应量M2的回归模型与预测

货币供应量是货币政策工具重要的中介变量。该文通过分解我国货币供应量的诸多宏观影响因素,尝试建立一个较为完整的货币供应量多变量回归模型,揭示宏观经济变量对货币供应量的影响程度,并运用该模型对货币供应量的短期变化进行预测,以期为把握宏观经济形势、理解货币政策变化及预判金融市场走势提供参考依据。检验结果表明,该模型对货币供应量的预测比较符合实际情况。     

Forecasting the macroeconomy with contemporaneous financial market information: Europe and the United States

Using Economic Tracking Portfolios (ETP), I find that it is possible to forecast future values of inflation and changes in industrial production in the United States and three core euro countries - Italy, France and Germany - utilizing only current and past financial market information. The longer the forecasting horizon, the better the forecasts based solely on financial market information compared to results from other methods. Of the countries I analyze, the overall forecasting performance of the tracking portfolios is the best for the U.S., and my method outperforms the forecasting performance of a VAR approach.     

Exchange rate bubbles: Fundamental value estimation and rational expectations test

We propose a model of periodically collapsing bubbles which extends the Van Norden (1996) model, and nests it, by considering a non-linear specification for the bubble size in the survival regime, and the endogenous determination of the level of the fundamental value of the stochastic process. They allow us to test for rationality in the formation of expectations, and remove the arbitrariness of exogenously setting the level of the fundamental value. This general model is applied to the exchange rate of the Brazilian real to the US dollar from March 1999 to February 2011. The futures market exchange rate is used as a proxy of its expected future value, and three different structural models are considered for the determination of the fundamental value. The first two imply that the exchange rate satisfies either purchasing power parity (PPP), or a modified version of it. The third structural model is a version of the monetary model of exchange rate determination, fitted to the period under consideration. We obtain the maximum likelihood estimate of the parameters of the models, explore the properties of the errors, test its restricted versions, and compare the three specifications for the fundamental. We find that the models we propose fit well the data, and are useful in the heuristic interpretation of the exchange rate movements of the period. Finally we select the structural models that display the best performance, according to several criteria.