Minimum distance estimation of the errors-in-variables model using linear cumulant equations

We consider a multiple mismeasured regressor errors-in-variables model. We develop closed-form minimum distance estimators from any number of estimating equations, which are linear in the third and higher cumulants of the observable variables. Using the cumulant estimators alters qualitative inference relative to ordinary least squares in two applications related to investment and leverage regressions. The estimators perform well in Monte Carlos calibrated to resemble the data from our applications. Although the cumulant estimators are asymptotically equivalent to the moment estimators from Erickson and Whited (2002), the finite-sample performance of the cumulant estimators exceeds that of the moment estimators.     

Examining bias in estimators of linear rational expectations models under misspecification

Most rational expectations models involve equations in which the dependent variable is a function of its lags and its expected future value. We investigate the asymptotic bias of generalized method of moment (GMM) and maximum likelihood (ML) estimators in such models under misspecification. We consider several misspecifications, and focus more specifically on the case of omitted dynamics in the dependent variable. In a stylized DGP, we derive analytically the asymptotic biases of these estimators. We establish that in many cases of interest the two estimators of the degree of forward-lookingness are asymptotically biased in opposite direction with respect to the true value of the parameter. We also propose a quasi-Hausman test of misspecification based on the difference between the GMM and ML estimators. Using Monte-Carlo simulations, we show that the ordering and direction of the estimators still hold in a more realistic New Keynesian macroeconomic model. In this set-up, misspecification is in general found to be more harmful to GMM than to ML estimators.     

The dynamic relationship between stock,bond and foreign exchange markets

This paper investigates whether the deviation of a currency from its fundamentally determined rate of return affects the relationship between interest rates and stock market yields. A time-varying transition probability, the Markov-switching vector autoregressive (MS-VAR) model, is utilized for this purpose. Wald and likelihood ratio tests are computed and used as model adequacy measures. In order to analyze the link between the variables, impulse–response functions are employed. A sticky price exchange rate model is used to show the fundamentally determined rate of return of currencies. States are defined as either overvalued or undervalued, depending on the position of the observed exchange rate compared to its fundamentally determined rate. The model is applied to four major currencies: the Australian Dollar, the Canadian Dollar, the Japanese Yen, and the British Pound. Transition between the states is linked to the risk-adjusted excess return (the Sharpe ratio) of the debt and equity markets of the respective currencies in order to understand whether over- and undervaluation is connected to the returns in these markets. The results provide evidence that the relationship between economic fundamentals and nominal exchange rates are subject to change depending on the over- or undervaluation of the currencies relative to their fundamentally determined rate of return. An extension of this result shows that the Sharpe ratios of debt and equity investments in the currencies influence the evolution of the transitional dynamics of the exchange rates’ deviation from their fundamental values.     

Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan

This paper provides closed-form likelihood approximations for multivariate jump-diffusion processes widely used in finance. For a fixed order of approximation, the maximum-likelihood estimator (MLE) computed from this approximate likelihood achieves the asymptotic efficiency of the true yet uncomputable MLE as the sampling interval shrinks. This method is used to uncover the realignment probability of the Chinese Yuan. Since February 2002, the market-implied realignment intensity has increased fivefold. The term structure of the forward realignment rate, which completely characterizes future realignment probabilities, is hump-shaped and peaks at mid-2004. The realignment probability responds quickly to economic news releases and government interventions.     

Time series properties of ARCH processes with persistent covariates

We investigate the time series properties of a volatility model, whose conditional variance is specified as in ARCH with an additional persistent covariate. The included covariate is assumed to be an integrated or nearly integrated process, with its effect on volatility given by a wide class of nonlinear volatility functions. In the paper, such a model is shown to generate many important characteristics that are commonly observed in financial time series. In particular, the model yields persistence in volatility, and also well predicts leptokurtosis. This is true for any type of volatility functions considered in the paper, as long as the covariate is integrated or nearly integrated. Stationary covariates cannot produce important characteristics observed in many financial time series. We present two empirical applications of the model, which show that the default premium (the yield spread between Baa and Aaa corporate bonds) affects stock return volatility and the interest rate differential between two countries accounts for exchange rate return volatility. The forecast evaluation shows that the model generally outperforms GARCH and FIGARCH at relatively lower frequencies.     

Good timing: The economics of optimal stopping

This paper presents an economic interpretation of the optimal “stopping” of perpetual project opportunities under both certainty and uncertainty. Prior to stopping, the expected rate of return from delay exceeds the rate of interest. The expected rate of return from delay is the sum of the expected rate of change in project value and the expected rate of change in the option premium associated with waiting. At stopping the expected rate of return from delay has fallen to the rate of interest. Viewing stopping in this way unifies the theoretical and practical insights of the theory of stopping under certainty and uncertainty.     

Econometric analysis of present value models when the discount factor is near one

This paper develops asymptotic econometric theory to help understand data generated by a present value model with a discount factor near one. A leading application is to exchange rate models. A key assumption of the asymptotic theory is that the discount factor approaches one as the sample size grows. The finite sample approximation implied by the asymptotic theory is quantitatively congruent with the modest departures from random walk behavior that are typically found and with imprecise estimation of a well-studied regression relating spot and forward exchange rates.     

The influence of international oil price fluctuation on the exchange rate of countries along the “Belt and Road”

In recent years, the international crude oil price has become increasingly volatile. It influences the exchange rate changes of relevant countries through economic growth, price level, international balance of payments, and other channels. Such exchange rate fluctuations have caused certain risks for the development of China’s “Belt and Road” Initiative. This article analyzes the impact of oil price changes on the exchange rates of countries. Because the fluctuation of oil prices and exchange rates has shown the characteristics of multiple time scales, this study used the empirical mode decomposition (EMD) method to obtain the long-cycle and short-cycle sequences of oil prices and the exchange rates of various countries, then analyzed the impact of oil price changes on exchange rates under different time scales. The results showed that oil price fluctuations have an impact on the exchange rate changes of countries along the “Belt and Road” under different time scales. However, this effect is asymmetric between oil-producing countries and non-oil-producing countries, and the transmission path of oil prices to exchange rates varies from cycle to cycle.     

The risk spillover between China’s economic policy uncertainty and commodity markets: Evidence from frequency spillover and quantile connectedness approaches

Based on the frequency spillover method extended by Baruník and Křehlík (2018), we explore the risk spillover relationship between China’s economic policy uncertainty (CNEPU) and commodity futures in different frequency domains with daily settlement price data of 14 commodity futures in China. The results show that the risk spillover relationship between CNEPU and the commodity market mainly occurs in the short term. Quantile connectedness results show that economic policy uncertainty, which mainly plays the role of risk transmitter, is more closely related to the commodity market during the market boom and recession. Soybeans, soybean meal, and corn have shown high investment value in the process of market recovery, which is exposed to less risk spillover from policy uncertainty. Finally, the economic crisis with different characteristics will have specific impacts on asymmetric risk spillovers based on certain impact mechanisms.     

Multi-scale tests for serial correlation

This paper introduces a new family of portmanteau tests for serial correlation. Using the wavelet transform, we decompose the variance of the underlying process into the variance of its low frequency and of its high frequency components and we design a variance ratio test of no serial correlation in the presence of dependence. Such decomposition can be carried out iteratively, each wavelet filter leading to a rich family of tests whose joint limiting null distribution is a multivariate normal. We illustrate the size and power properties of the proposed tests through Monte Carlo simulations.     

Impact of an unexplained component of real exchange rate volatility on FDI: Evidence from transition countries

The aim of this paper is to examine the impact of an unexplained component of real exchange rate volatility on FDI in transition economies. We make an attempt to overcome some problems associated with previous studies; the aggregation problem, inadequate measures of volatility, short-run focus and the endogeneity problem. Using a GARCH specification, we focus on long-run volatility, while we control for the endogeneity problem by applying SYS-GMM estimation. The obtained results show that the impact of the unexplained component of real exchange rate volatility on FDI differs among economic activities since 2000. As part of the re-estimation exercise, we use two alternative measures of volatility to avoid arbitrariness. The obtained results are to a large extent in accordance with the first one.     

What do movements in financial traders’ net long positions reveal about aggregate stock returns?

Previous financial economics studies have successfully identified the existence of informed trading in futures markets; however, there is no study on the specific type of strategy chosen by informed agents to maximize profits. To fill this gap in the literature, we investigate the importance of movements in futures traders’ net long positions in predicting aggregate equity market returns. This study finds that movements in the net long positions of bond, commodity, and stock futures traders are strong predictors of aggregate stock returns as they outperform a large number of popular return predictors both in and out of sample. In addition, a one-standard-deviation change in futures traders’ net long positions can lead to an increase (decrease) of up to 3.4% (4.12%) in annualized market excess equity returns. The study’s first-order autocorrelation results reveal an absence of persistence in the net long predictors. A vector autoregression decomposition shows that the economic source of financial traders’ net long position predictive power stems predominantly from the discount rate and cash flow channels. Overall, the study finds that financial traders are informed traders who are able to anticipate future aggregate cash flows and associated discount rate news.