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VAR Models (var + models)
Selected AbstractsThe empirics of monetary policy rules in open economiesINTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, Issue 4 2001Richard H. Clarida This paper uses the empirical framework for formulating and estimating forward looking monetary policy rules developed in Clarida, Gali and Gertler (1998, 1999, 2000, 2001) and Clarida (2000) to assess what we know, don't know, and can't tell about monetary policy making in an open economy with an (implicit) inflation target. Among the issues discussed are: the relationship between structural VAR models of monetary policy and exchange rates and estimates of forward-looking Taylor rules; the relationship between inflation targeting and leaning against the (exchange rate) wind; why central bankers are averse to even wide-band target zones; quantifying stresses and costs of a one-size-fits-all monetary policy for the members of a monetary union or currency bloc. Copyright © 2001 John Wiley & Sons, Ltd. [source] Forecasting interest rate swap spreads using domestic and international risk factors: evidence from linear and non-linear modelsJOURNAL OF FORECASTING, Issue 8 2007Ilias Lekkos Abstract This paper explores the ability of factor models to predict the dynamics of US and UK interest rate swap spreads within a linear and a non-linear framework. We reject linearity for the US and UK swap spreads in favour of a regime-switching smooth transition vector autoregressive (STVAR) model, where the switching between regimes is controlled by the slope of the US term structure of interest rates. We compare the ability of the STVAR model to predict swap spreads with that of a non-linear nearest-neighbours model as well as that of linear AR and VAR models. We find some evidence that the non-linear models predict better than the linear ones. At short horizons, the nearest-neighbours (NN) model predicts better than the STVAR model US swap spreads in periods of increasing risk conditions and UK swap spreads in periods of decreasing risk conditions. At long horizons, the STVAR model increases its forecasting ability over the linear models, whereas the NN model does not outperform the rest of the models.,,Copyright © 2007 John Wiley & Sons, Ltd. [source] Permanent-transitory Decomposition in Var Models With Cointegration and Common CyclesOXFORD BULLETIN OF ECONOMICS & STATISTICS, Issue 4 2000Alain Hecq In this paper we derive permanent-transitory decompositions of non-stationary multiple times series generated by (r)nite order Gaussian VAR(p) models with both cointegration and serial correlation common features. We extend existing analyses to the two classes of reduced rank structures discussed in Hecq, Palm and Urbain (1998). Using the corresponding state space representation of cointegrated VAR models in vector error correction form we show how decomposition can be obtained even in the case where the number of common feature and cointegration vectors are not equal to the number of variables. As empirical analysis of US business fluctuations shows the practical relevance of the approach we propose. [source] The Impact of Day-Trading on Volatility and Liquidity,ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 2 2009Jay M. Chung Abstract We examine day-trading activities for 540 stocks traded on the Korea Stock Exchange using transactions data for the period from 1999 to 2000. Our cross-sectional analysis reveals that day-traders prefer lower-priced, more liquid, and more volatile stocks. By estimating various bivariate VAR models using minute-by-minute data, we find that greater day-trading activity leads to greater return volatility and that the impact of a day-trading shock dissipates gradually within an hour. Past return volatility also positively affects future day-trading activity. We also find that past day-trading activity negatively affects bid-ask spreads, and past bid-ask spreads negatively affect future day-trading activity. Finally, we find that day-traders use short-term contrarian strategies and their order imbalance affects future returns positively. This result is consistent with a cyclical behavior of day-traders who concentrate their buy or sell trades at the bottom or peak of the short-term price cycles, respectively. [source] LABOUR MOBILITY AND TRANS-TASMAN CURRENCY UNION,AUSTRALIAN ECONOMIC PAPERS, Issue 1 2006ADAM CREIGHTONArticle first published online: 7 MAR 200 The prospect of a common currency for Australia and New Zealand has been canvassed by senior poli-ticians and bureaucrats, and has been the subject of academic debate. According to Mundell (1961), a high degree of internal labour mobility is a desirable feature of currency unions. This study looks at the extent to which long-term migration between Australia and New Zealand responds to output shocks. Estimated VAR models and panel Granger-causality tests demonstrate that shocks to relative per capita output have a significant and symmetrical impact on migration flows between Australia and New Zealand, and most of the impact is felt after about one year. Separating the shocks to Australia and New Zealand shows that ,pull' effects are more important than ,push' effects. Additionally, the trajectory of the Australian economy proves particularly influential for the choice of New Zealand emigrants. Although permanent migration responds intuitively to the state of the economy in Australia and New Zealand, the level of these migration flows is low in comparison to Australian inter-state migration; yet it is high in relation to any third country. [source] Evaluating predictive performance of value-at-risk models in emerging markets: a reality checkJOURNAL OF FORECASTING, Issue 2 2006Yong Bao Abstract We investigate the predictive performance of various classes of value-at-risk (VaR) models in several dimensions,unfiltered versus filtered VaR models, parametric versus nonparametric distributions, conventional versus extreme value distributions, and quantile regression versus inverting the conditional distribution function. By using the reality check test of White (2000), we compare the predictive power of alternative VaR models in terms of the empirical coverage probability and the predictive quantile loss for the stock markets of five Asian economies that suffered from the 1997,1998 financial crisis. The results based on these two criteria are largely compatible and indicate some empirical regularities of risk forecasts. The Riskmetrics model behaves reasonably well in tranquil periods, while some extreme value theory (EVT)-based models do better in the crisis period. Filtering often appears to be useful for some models, particularly for the EVT models, though it could be harmful for some other models. The CaViaR quantile regression models of Engle and Manganelli (2004) have shown some success in predicting the VaR risk measure for various periods, generally more stable than those that invert a distribution function. Overall, the forecasting performance of the VaR models considered varies over the three periods before, during and after the crisis. Copyright © 2006 John Wiley & Sons, Ltd. [source] Permanent-transitory Decomposition in Var Models With Cointegration and Common CyclesOXFORD BULLETIN OF ECONOMICS & STATISTICS, Issue 4 2000Alain Hecq In this paper we derive permanent-transitory decompositions of non-stationary multiple times series generated by (r)nite order Gaussian VAR(p) models with both cointegration and serial correlation common features. We extend existing analyses to the two classes of reduced rank structures discussed in Hecq, Palm and Urbain (1998). Using the corresponding state space representation of cointegrated VAR models in vector error correction form we show how decomposition can be obtained even in the case where the number of common feature and cointegration vectors are not equal to the number of variables. As empirical analysis of US business fluctuations shows the practical relevance of the approach we propose. [source] | ||||||||||||||||||||||