nep-for New Economics Papers
on Forecasting
Issue of 2017‒10‒29
four papers chosen by
Rob J Hyndman
Monash University

  1. The Role of Economic Uncertainty in Forecasting Exchange Rate Returns and Realized Volatility: Evidence from Quantile Predictive Regressions By Christina Christou; Rangan Gupta; Christis Hassapis; Tahir Suleman
  2. Friends Without Benefits? New EMU Members and the "Euro Effect" on Trade By Alina Mika; Robert Zymek
  3. Sparse Signals in the Cross-Section of Returns By Alexander M. Chinco; Adam D. Clark-Joseph; Mao Ye
  4. Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle By Kai Carstensen; Markus Heinrich; Magnus Reif; Maik H. Wolters

  1. By: Christina Christou (School of Economics and Management, Open University of Cyprus, Latsia, Cyprus); Rangan Gupta (University of Pretoria, Pretoria, South Africa); Christis Hassapis (School of Economics and Management, Department of Economics, University of Cyprus, Nicosia, Cyprus); Tahir Suleman (School of Economics and Finance, Victoria University of Wellington and School of Business, Wellington Institute of Technology)
    Abstract: In this paper, we investigate whether the news-based measure of economic policy uncertainty (EPU), can be used to forecast exchange rate returns and volatility using a quantile regression approach, which accounts for persistence and endogeneity, using data from thirteen different countries. Our main findings suggest that: (i) EPU is useful for forecasting exchange rate returns and volatility, (ii) forecasting ability-quantile order relationships exhibit U-shape, possibly asymmetric form around the median and (iii) asymmetries are more pronounced in the case of forecasting volatility.
    Keywords: Economic Policy Uncertainty, Exchange Rate Returns, Volatility, Quantile Predictive Regressions, Developed and Emerging Markets
    JEL: C32 C53 E60 F31
    Date: 2017–10
  2. By: Alina Mika; Robert Zymek
    Abstract: We re-visit the evidence about the trade benefits of European Monetary Union (EMU), focusing on the experience of countries which adopted the common currency since 2002. Based on “state of the art†gravity estimations for the period 1992-2013, we reach three main conclusions. First, estimates from an appropriately specified and estimated gravity equation provide no evidence of a euro effect on trade flows among early euro adopters up to the year 2002. Second, this finding is robust to extending the sample period to incorporate data up to 2013, covering five additional euro accessions. Third, while there is no robust evidence of a euro effect, there is evidence that intra-EU trade flows have expanded faster than the global average during the 2002-2013 period. Using the functional form of a theory-consistent gravity equation, we perform pseudo out-of-sample forecasts of trade flows for recent euro joiners. In line with our estimation results, we show that pseudo forecasts of the change in trade flows after euro accession, assuming no euro effect, outperform forecasts based on the expectation of a significantly positive effect. This suggests that euro accession countries should not expect a significant boost to their trade from joining EMU.
    Keywords: euro, trade, gravity, poisson
    JEL: F14 F15 F17 F33
    Date: 2017
  3. By: Alexander M. Chinco; Adam D. Clark-Joseph; Mao Ye
    Abstract: This paper applies the Least Absolute Shrinkage and Selection Operator (LASSO) to make rolling 1-minute-ahead return forecasts using the entire cross section of lagged returns as candidate predictors. The LASSO increases both out-of-sample fit and forecast-implied Sharpe ratios. And, this out-of-sample success comes from identifying predictors that are unexpected, short-lived, and sparse. Although the LASSO uses a statistical rule rather than economic intuition to identify predictors, the predictors it identifies are nevertheless associated with economically meaningful events: the LASSO tends to identify as predictors stocks with news about fundamentals.
    JEL: C58 G12 G14
    Date: 2017–10
  4. By: Kai Carstensen; Markus Heinrich; Magnus Reif; Maik H. Wolters
    Abstract: We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show that a two-state model is not sensitive enough to reliably detect relatively mild recessions when the Great Recession of 2008/2009 is included in the sample. Adding a third state helps to clearly distinguish normal and severe recessions, so that the model identifies reliably all business cycle turning points in our sample. In a real-time exercise the model detects recessions timely. Combining the estimated factor and the recession probabilities with a simple GDP forecasting model yields an accurate nowcast for the steepest decline in GDP in 2009Q1 and a correct prediction of the timing of the Great Recession and its recovery one quarter in advance.
    Keywords: Markov-Switching Dynamic Factor Model, business cycles, Great Recession, leading indicators, turning points, GDP-nowcasting, GDP-forecasting
    JEL: C53 E32 E37
    Date: 2017

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