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on Forecasting |
| By: | Afees A. Salisu (Centre for Econometric and Allied Research, University of Ibadan); Umar N. Ndako (Monetary Policy Department, Central Bank of Nigeria, Nigeria.) |
| Abstract: | The extant literature on exchange rate forecasting on the basis of the Dornbusch- Frankel, Frenkel-Bilson and Hooper-Morton models prominently reveals the dominance of the autoregressive models over the theory-based models. Some studies have however attempted to upturn the results by including the lagged dependent variable in the theory-based models which somewhat implies comparing a modified random walk with a traditional random walk. We follow a different approach both in terms of theory and methodology. We offer an innovative exposition of the Portfolio Balance theory to stock price – exchange rate nexus. Consequently, a predictive model for exchange rate where stock price is a predictor is formulated. The formulated model is expressed in both linear and nonlinear form in order to account for the role of asymmetric changes in stock prices in exchange rate forecasting. Thereafter, we employ the Lewellen (2004) and Westerlund and Narayan (2014) methods which account for any inherent statistical properties of the predictors. Our results validate the Portfolio Balance theory where we show that the sector-level stock prices consistently turn up as good predictors of the exchange rates. The predictive model proposed in this work does not require the inclusion of a lagged dependent variable to beat the autoregressive models which is the practice in the existing literature. We further demonstrate that asymmetry matters to a large extent in the nexus both for the in-sample and out-of-sample predictability. |
| Keywords: | portfolio balance theory; US sectoral stock prices; exchange rates; asymmetry |
| JEL: | C53 F31 G11 |
| Date: | 2017–10 |
| URL: | http://d.repec.org/n?u=RePEc:cui:wpaper:0031&r=for |
| By: | Obermüller, Frank (Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI)) |
| Abstract: | With the increasing share of volatile renewable energies, weather prediction becomes more important to electricity markets. The weather-driven uncertainty of renewable forecast errors could have price increasing impacts. This research sets up an analytic model to show that the day-ahead optimal bidding under uncertain renewable production is below the expected production and thus price increasing. In a second step, the price increasing effect on forward premiums by specific weather types and their renewable production uncertainty is proved via empirical methods. Weather types are identified in which renewable production is harder to predict. The findings connect weather dependent renewable forecast uncertainty to forward premiums and support the consideration of weather types in price forecasting models. |
| Keywords: | Forward Premium; Weather Type; Uncertainty; Volatile Renewable Production |
| JEL: | D21 D22 D41 D81 Q41 Q42 Q47 |
| Date: | 2017–09–28 |
| URL: | http://d.repec.org/n?u=RePEc:ris:ewikln:2017_010&r=for |
| By: | Christian Menden; Christian R. Proaño |
| Abstract: | The analysis of the financial cycle and its interaction with the macroeconomy has become a central issue for the design of macroprudential policy since the 2007-08 financial crisis. This paper proposes the construction of financial cycle measures for the US based on a large data set of macroeconomic and financial variables. More specifically, we estimate three synthetic financial cycle components that account for the majority of the variation in the data set using a dynamic factor model. We investigate whether these financial cycle components have significant predictive power for economic activity, inflation and short-term interest rates by means of Granger causality tests in a factor-augmented VAR set-up. Further, we analyze if the synthetic financial cycle components have significant forecasting power for the prediction of economic recessions using dynamic probit models. Our main findings indicate that all financial cycle measures improve the quality of recession forecasts significantly. In particular, the factor related to financial market participants' uncertainty and risk aversion - related to Rey's (2013) global financial cycle - seems to serve as an appropriate early warning indicator for policymakers. |
| Keywords: | Financial cycle, dynamic factor model, Granger causality, recession forecasting, dynamic probit models, early warning systems |
| JEL: | C35 C38 C52 C53 E32 E47 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:imk:wpaper:183-2017&r=for |
| By: | Pönkä, Harri |
| Abstract: | We explore the relationship between investor, consumer, and business sentiment and the direction of excess stock market returns in the US. Our findings indicate that measures of investor sentiment are useful predictors, even after controlling for the predictive ability of commonly used predictors of stock returns and for the effects of recession. Measures of consumer and business sentiment do not hold similar predictive ability. The findings hold both in- and out-of-sample. |
| Keywords: | Equity return, Probit model, Sentiment variable, Sign predictability |
| JEL: | C22 C58 G12 G17 |
| Date: | 2017–10–09 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:81861&r=for |
| By: | Thomas Lustenberger; Enzo Rossi |
| Abstract: | In a large sample of countries across different geographic regions and over a long period of time, we find limited country- and variable-specific effects of central bank transparency on forecast accuracy and their dispersion among a large set of professional forecasts of financial and macroeconomic variables. More communication even increases forecast errors and Dispersion. |
| Keywords: | Central bank transparency, central bank communication,central bank independence, inflation targeting, forward guidance, macroeconomic forecasts, financial forecasts, panel data models with truncated data |
| JEL: | C23 C53 E37 E58 D8 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:snb:snbwpa:2017-12&r=for |