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on Forecasting |
| By: | Kazuhiko NISHINA (Graduate School of Economics, Osaka University); Tatsuro Nabil MAGHREBI (Faculty of Economics, Wakayama University); Moo-Sung KIM (College of Business Administration, Pusan National University) |
| Abstract: | This study develops a new model-free benchmark of implied volatility for the Japanese stock market similar in construction to the new VIX based on the S&P 500 index. It also examines the stochastic dynamics of the implied volatility index and its relationship with realized volatility in both markets. There is evidence that implied volatility is governed by a long-memory process. Despite its upward bias, implied volatility is more reflective of changes in realized volatility than alternative GARCH models, which account for volatility persistence and the asymmetric impact of news. The implied volatility index is also found to be inclusive of some but not all information on future volatility contained in historical returns. However, its higher out-of sample performance provides further support to the rationale behind drawing inference about future stock market volatility based on the incremental information contained in options prices. |
| Keywords: | Licensing; Implied volatility index, Out-of-sample forecasting, GARCH modelling |
| JEL: | C52 C53 G14 |
| Date: | 2006–03 |
| URL: | http://d.repec.org/n?u=RePEc:osk:wpaper:0609&r=for |
| By: | Duo Qin (Queen Mary, University of London); Marie Anne Cagas (Asian Development Bank (ADB), and University of the Philippines); Geoffrey Ducanes (Asian Development Bank (ADB), and University of the Philippines); Nedelyn Magtibay-Ramos (Asian Development Bank (ADB)); Pilipinas Quising (Asian Development Bank (ADB)) |
| Abstract: | This paper compares forecast performance of the ALI method and the MESMs and seeks ways of improving the ALI method. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and the Philippines. The ALI method is found to produce better forecasts than those by MESMs in general, but the method is found to involve greater uncertainty in choosing indicators, mixing data frequencies and utilizing unrestricted VARs. Two possible improvements are found helpful to reduce the uncertainty: (i) give theory priority in choosing indicators and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the VARs by means of the general→specific model reduction procedure. |
| Keywords: | Dynamic factor models, Model reduction, VAR |
| JEL: | E31 C53 |
| Date: | 2006–03 |
| URL: | http://d.repec.org/n?u=RePEc:qmw:qmwecw:wp554&r=for |
| By: | Christophe Van Nieuwenhuyze (National Bank of Belgium, Research Department) |
| Abstract: | This paper aims to extract the common variation in a data set of 509 conjunctural series as an indication of the Belgian business cycle. The data set contains information on business and consumer surveys of Belgium and its neighbouring countries, macroeconomic variables and some worldwide watched indicators such as the ISM and the OECD confidence indicators. The statistical framework used is the One-sided Generalised Dynamic Factor Model developed by Forni, Hallin, Lippi and Reichlin (2005). The model splits the series in a common component, driven by the business cycle, and an idiosyncratic component. Well-known indicators such as the EC economic sentiment indicator for Belgium and the NBB overall synthetic curve contain a high amount of business cycle information. Furthermore, the richness of the model allows to determine the cyclical properties of the series and to forecast GDP growth all within the same unified setting. We classify the common component of the variables into leading, lagging and coincident with respect to the common component of quarter-on-quarter GDP growth. 22% of the variables are found to be leading. Amongst the most leading variables we find asset prices and international confidence indicators such as the ISM and some OECD indicators. In general, national business confidence surveys are found to coincide with Belgian GDP, while they lead euro area GDP and its confidence indicators. Consumer confidence seems to lag. Although the model captures the dynamic common variation contained in the data set, forecasts based on that information are insufficient to deliver a good proxy for GDP growth as a result of a nonnegligible idiosyncratic part in GDP's variance. Lastly, we explore the dependence of the model's results on the data set and show through a data reduction process that the idiosyncratic part of GDP's quarter-on-quarter growth can be dramatically reduced. However, this does not improve the forecasts. |
| Keywords: | Dynamic factor model, business cycle, leading indicators, forecasting, data reduction. |
| JEL: | C33 C43 E32 E37 |
| Date: | 2006–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbb:reswpp:200603-2&r=for |
| By: | Guillaume Chevillon |
| Abstract: | To forecast at several, say h, periods into the future, a modeller faces two techniques: iterating one-step ahead forecasts (the IMS technique) or directly modelling the relation between observations separated by an h-period interval and using it for forecasting (DMS forecasting). It is known that unit-root non-stationarity and residual autocorrelation benefit DMS accuracy in finite samples. We analyze here the effect of structural breaks as observed in unstable economies, and show that the benefits of DMS stem from its better appraisal of the dynamic relationships of interest for forecasting. It thus acts in between congruent modelling and intercept correction. We apply our results to forecasting the South African GDP over the last thirty years as this economy exhibits significant unstability. We analyze the forecasting properties of 31 competing models. We find that the GDP of South Africa is best forecast, 4 quarters ahead, using direct multi-step techniques, as with our theoretical results. |
| Keywords: | Multi-step Forecasting, Structural Breaks, South Africa |
| JEL: | C32 C53 E3 |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:oxf:wpaper:257&r=for |
| By: | Duo Qin (Queen Mary, University of London); Marie Anne Cagas (Asian Development Bank (ADB)); Geoffrey Ducanes (Asian Development Bank (ADB)); Xinhua He (Institute of World Economics & Politics (IWEP), Chinese Academy of Social Sciences (CASS)); Rui Liu (Institute of World Economics & Politics (IWEP), Chinese Academy of Social Sciences (CASS)); Shiguo Liu (Institute of World Economics & Politics (IWEP), Chinese Academy of Social Sciences (CASS)); Nedelyn Magtibay-Ramos (Asian Development Bank (ADB)); Pilipinas Quising (Asian Development Bank (ADB)) |
| Abstract: | This paper describes a quarterly macroeconometric model of the Chinese economy. The model comprises household consumption, investment, government, trade, production, prices, money, and employment blocks. The equilibrium-correction form is used for all the behavioral equations and the general→simple dynamic specification approach is adopted. Great efforts have been made to achieve the best possible blend of standard long-run theories, country-specific institutional features and short-run dynamics in data. The tracking performance of the model is evaluated. Forecasting and empirical investigation of a number of topical macroeconomic issues utilizing model simulations have shown the model to be immensely useful. |
| Keywords: | Macroeconometric model, Chinese economy, Forecasts, Simulations |
| JEL: | C51 E17 |
| Date: | 2006–03 |
| URL: | http://d.repec.org/n?u=RePEc:qmw:qmwecw:wp553&r=for |
| By: | Refet S. Gürkaynak; Brian Sack; Eric Swanson |
| Abstract: | A number of recent papers have used different financial market instruments to measure near-term expectations of the federal funds rate and the high-frequency changes in these instruments around FOMC announcements to measure monetary policy shocks. This paper evaluates the empirical success of a variety of financial market instruments in predicting the future path of monetary policy. All of the instruments we consider provide forecasts that are clearly superior to those of standard time series models at all of the horizons considered. Among financial market instruments, we find that federal funds futures dominate all the other securities in forecasting monetary policy at horizons out to six months. For longer horizons, the predictive power of many of the instruments we consider is very similar. In addition, we present evidence that monetary policy shocks computed using the current-month federal funds futures contract are influenced by changes in the timing of policy actions that do not influence the expected course of policy beyond a horizon of about six weeks. We propose an alternative shock measure that captures changes in market expectations of policy over slightly longer horizons. |
| Keywords: | Monetary policy ; Federal funds rate ; Financial markets |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedfwp:2006-04&r=for |