Information on economic policy uncertainty does matter in predicting the change in oil prices. We compare the forecastability of standard, Bayesian and time-varying VAR against univariate models. The time-varying VAR model outranks all alternative models over the period 2007:1–2014:2.
{"title":"Oil Price Forecastability and Economic Uncertainty","authors":"S. Bekiros, Rangan Gupta, Alessia Paccagnini","doi":"10.2139/ssrn.2589853","DOIUrl":"https://doi.org/10.2139/ssrn.2589853","url":null,"abstract":"Information on economic policy uncertainty does matter in predicting the change in oil prices. We compare the forecastability of standard, Bayesian and time-varying VAR against univariate models. The time-varying VAR model outranks all alternative models over the period 2007:1–2014:2.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131853973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We identify a U.S.-driven factor using a monthly panel of fifteen bilateral exchange rates against the U.S. dollar since 1999. We find this factor is closely related to nominal and real macroeconomic variables, as well as financial market variables from the U.S. Using this factor alone, we show that the out-of-sample one-month-ahead forecasts outperform random walk forecasts for all currencies but the yen.
{"title":"The U.S. Factor in Explaining and Forecasting Bilateral U.S. Exchange Rates","authors":"N. Ponomareva, Jeffrey Sheen, B. Wang","doi":"10.2139/ssrn.2584734","DOIUrl":"https://doi.org/10.2139/ssrn.2584734","url":null,"abstract":"We identify a U.S.-driven factor using a monthly panel of fifteen bilateral exchange rates against the U.S. dollar since 1999. We find this factor is closely related to nominal and real macroeconomic variables, as well as financial market variables from the U.S. Using this factor alone, we show that the out-of-sample one-month-ahead forecasts outperform random walk forecasts for all currencies but the yen.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"53 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131746221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We reassess the predictability of U.S. recessions at horizons from three months to two years ahead for a large number of previously proposed leading-indicator variables. We employ an efficient probit estimator for partially missing data and assess relative model performance based on the receiver operating characteristic (ROC) curve. While the Treasury term spread has the highest predictive power at horizons four to six quarters ahead, adding lagged observations of the term spread significantly improves the predictability of recessions at shorter horizons. Moreover, balances in broker-dealer margin accounts significantly improve the precision of recession predictions, especially at horizons further out than one year.
{"title":"What Predicts U.S. Recessions?","authors":"Weiling Liu, E. Moench","doi":"10.2139/ssrn.2495083","DOIUrl":"https://doi.org/10.2139/ssrn.2495083","url":null,"abstract":"We reassess the predictability of U.S. recessions at horizons from three months to two years ahead for a large number of previously proposed leading-indicator variables. We employ an efficient probit estimator for partially missing data and assess relative model performance based on the receiver operating characteristic (ROC) curve. While the Treasury term spread has the highest predictive power at horizons four to six quarters ahead, adding lagged observations of the term spread significantly improves the predictability of recessions at shorter horizons. Moreover, balances in broker-dealer margin accounts significantly improve the precision of recession predictions, especially at horizons further out than one year.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125375834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many empirical studies have shown that factor models produce relatively accurate forecasts compared to alternative short-term forecasting models. These empirical findings have been established for different macroeconomic data sets and different forecast horizons. However, various specifications of the factor model exist and it is a topic of debate which specification is most effective in its forecasting performance. Furthermore, the forecast performances of the different specifications during the recent financial crisis are also not well documented. In this study we investigate these two issues in depth. We empirically verify the forecast performance of three factor model approaches and report our findings in an extended empirical out-of-sample forecasting competition for quarterly growth of gross domestic product in the euro area and its five largest countries over the period 1992-2012. We also introduce two extensions of existing factor models to make them more suitable for real-time forecasting. We show that the factor models have been able to systematically beat the benchmark autoregressive model, both before as well as during the financial crisis. The recently proposed collapsed dynamic factor model shows the highest forecast accuracy for the euro area and the majority of countries that we have analyzed. The forecast precision improvements against the benchmark model can range up to 77% in mean square error reduction, depending on the country and forecast horizon.
{"title":"Nowcasting and Forecasting Economic Growth in the Euro Area Using Principal Components","authors":"Irma Hindrayanto, S. J. Koopman, Jasper de Winter","doi":"10.2139/ssrn.2485279","DOIUrl":"https://doi.org/10.2139/ssrn.2485279","url":null,"abstract":"Many empirical studies have shown that factor models produce relatively accurate forecasts compared to alternative short-term forecasting models. These empirical findings have been established for different macroeconomic data sets and different forecast horizons. However, various specifications of the factor model exist and it is a topic of debate which specification is most effective in its forecasting performance. Furthermore, the forecast performances of the different specifications during the recent financial crisis are also not well documented. In this study we investigate these two issues in depth. We empirically verify the forecast performance of three factor model approaches and report our findings in an extended empirical out-of-sample forecasting competition for quarterly growth of gross domestic product in the euro area and its five largest countries over the period 1992-2012. We also introduce two extensions of existing factor models to make them more suitable for real-time forecasting. We show that the factor models have been able to systematically beat the benchmark autoregressive model, both before as well as during the financial crisis. The recently proposed collapsed dynamic factor model shows the highest forecast accuracy for the euro area and the majority of countries that we have analyzed. The forecast precision improvements against the benchmark model can range up to 77% in mean square error reduction, depending on the country and forecast horizon.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131872062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we replicate the main results of Rudebusch and Williams (2009), who show that the use of the yield spread in a probit model can predict recessions better than the Survey of Professional Forecasters. We investigate the robustness of their results in several ways: extending the sample to include the 2007-09 recession, changing the starting date of the sample, changing the ending date of the sample, using rolling windows of data instead of just an expanding sample, and using alternative measures of the actual" value of real output. Our results show that the Rudebusch-Williams findings are robust in all dimensions.
{"title":"The Continuing Power of the Yield Spread in Forecasting Recessions","authors":"Dean Croushore, Katherine Marsten","doi":"10.2139/ssrn.2401017","DOIUrl":"https://doi.org/10.2139/ssrn.2401017","url":null,"abstract":"In this paper, we replicate the main results of Rudebusch and Williams (2009), who show that the use of the yield spread in a probit model can predict recessions better than the Survey of Professional Forecasters. We investigate the robustness of their results in several ways: extending the sample to include the 2007-09 recession, changing the starting date of the sample, changing the ending date of the sample, using rolling windows of data instead of just an expanding sample, and using alternative measures of the actual\" value of real output. Our results show that the Rudebusch-Williams findings are robust in all dimensions.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126323085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Much research studies US inflation history with a trend-cycle model with unobserved components. A key feature of this model is that the trend may be viewed as the Fed’s evolving inflation target or long-horizon expected inflation. We provide a new way to measure the slowly evolving trend and the cycle (or inflation gap), based on forecasts from the Survey of Professional Forecasters. These forecasts may be treated either as rational expectations or as adjusting to those with sticky information. We find considerable evidence of inflation-gap persistence and some evidence of implicit sticky information. But statistical tests show we cannot reconcile these two widely used perspectives on US inflation and professional forecasts, the unobserved-components model and the sticky-information model.
{"title":"Measuring the Slowly Evolving Trend in US Inflation with Professional Forecasts","authors":"James M. Nason, Gregor W. Smith","doi":"10.2139/ssrn.2382326","DOIUrl":"https://doi.org/10.2139/ssrn.2382326","url":null,"abstract":"Much research studies US inflation history with a trend-cycle model with unobserved components. A key feature of this model is that the trend may be viewed as the Fed’s evolving inflation target or long-horizon expected inflation. We provide a new way to measure the slowly evolving trend and the cycle (or inflation gap), based on forecasts from the Survey of Professional Forecasters. These forecasts may be treated either as rational expectations or as adjusting to those with sticky information. We find considerable evidence of inflation-gap persistence and some evidence of implicit sticky information. But statistical tests show we cannot reconcile these two widely used perspectives on US inflation and professional forecasts, the unobserved-components model and the sticky-information model.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126287997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we build forecasts for Chilean year-on-year inflation using simple time-series models augmented with different measures of international inflation. Broadly speaking, we construct two families of international inflation factors. The first family is built using year-on-year inflation of 18 Latin American (LA) countries (excluding Chile). The second family is built using year-on-year inflation of 30 OECD countries (excluding Chile). We show sound in-sample and pseudo out-of-sample evidence indicating that these international factors do help forecast Chilean inflation at several horizons. Incorporating the international factors reduce the Root Mean Squared Prediction Error of pure univariate SARIMA models statistically speaking. We also show that the predictive pass-through from international to local inflation has increased in the recent years. As a robustness check we construct another international inflation factor as an average of the inflation of fifteen countries from which Chile gets a high percentage of its imports. With the aid of this factor the models outperform our univariate benchmarks but also underperform the results obtained with the broader factors built with LA or OECD countries, suggesting that imported inflation is not the only channel explaining our findings.
{"title":"International Inflation's Predictive Ability","authors":"Pablo M. Pincheira, Andrés Gatty","doi":"10.2139/ssrn.2371727","DOIUrl":"https://doi.org/10.2139/ssrn.2371727","url":null,"abstract":"In this paper we build forecasts for Chilean year-on-year inflation using simple time-series models augmented with different measures of international inflation. Broadly speaking, we construct two families of international inflation factors. The first family is built using year-on-year inflation of 18 Latin American (LA) countries (excluding Chile). The second family is built using year-on-year inflation of 30 OECD countries (excluding Chile). We show sound in-sample and pseudo out-of-sample evidence indicating that these international factors do help forecast Chilean inflation at several horizons. Incorporating the international factors reduce the Root Mean Squared Prediction Error of pure univariate SARIMA models statistically speaking. We also show that the predictive pass-through from international to local inflation has increased in the recent years. As a robustness check we construct another international inflation factor as an average of the inflation of fifteen countries from which Chile gets a high percentage of its imports. With the aid of this factor the models outperform our univariate benchmarks but also underperform the results obtained with the broader factors built with LA or OECD countries, suggesting that imported inflation is not the only channel explaining our findings.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123716335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a global solution method to DSGE models, which does not depend on a grid and hence does not suffer from the curse of dimensionality. The method enables to approximate the Taylor series of the policy function at any arbitrary point of the state space. Once the Taylor series is approximated at a given point, the constant term of the series provides the model solution at that point. Since the solution is not based on a grid, the computational costs are significantly lower compared to grid-based methods, because the model is solved only at points of interests (e.g. along a simulation path). Accuracy is high, compared to other methods, and it improves significantly by discretizing time into short periods.
{"title":"Solving DSGE Models Without a Grid","authors":"Oren Levintal","doi":"10.2139/ssrn.2344258","DOIUrl":"https://doi.org/10.2139/ssrn.2344258","url":null,"abstract":"This paper presents a global solution method to DSGE models, which does not depend on a grid and hence does not suffer from the curse of dimensionality. The method enables to approximate the Taylor series of the policy function at any arbitrary point of the state space. Once the Taylor series is approximated at a given point, the constant term of the series provides the model solution at that point. Since the solution is not based on a grid, the computational costs are significantly lower compared to grid-based methods, because the model is solved only at points of interests (e.g. along a simulation path). Accuracy is high, compared to other methods, and it improves significantly by discretizing time into short periods.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117005793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, we test a set of country macro sentiment indexes that measure the trailing sentiment on both scheduled and unscheduled economic and geopolitical news events. We develop a cross-over strategy in the FX market based on short to long-term news sentiment inflection points covering the seven major currency pairs. The sentiment indexes are proven to predict short-term price movements in the major currency pairs for up to several hours after an inflection point.
{"title":"Country News Sentiment Factors Predict Forex Prices","authors":"Peter Hafez, Junqiang Xie","doi":"10.2139/ssrn.2269716","DOIUrl":"https://doi.org/10.2139/ssrn.2269716","url":null,"abstract":"In this study, we test a set of country macro sentiment indexes that measure the trailing sentiment on both scheduled and unscheduled economic and geopolitical news events. We develop a cross-over strategy in the FX market based on short to long-term news sentiment inflection points covering the seven major currency pairs. The sentiment indexes are proven to predict short-term price movements in the major currency pairs for up to several hours after an inflection point.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123704568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The ongoing threat of the U.S. public sector sliding over the 'fiscal cliff' urges financial economists to better understand the foundations for how government spending affects the real economy and financial markets. This paper is the first study to document that uncertainty about future government spending is a first-order risk factor in the bond market, leading to rising real and nominal interest rates, a steeper term spread, an increase in bond market volatility and bond premia. We study an equilibrium asset pricing model with a forward-looking representative agent and a forward-looking government to shed light on these empirical facts.
{"title":"How does the Bond Market Perceive Government Interventions?","authors":"Maxim Ulrich","doi":"10.2139/ssrn.1566932","DOIUrl":"https://doi.org/10.2139/ssrn.1566932","url":null,"abstract":"The ongoing threat of the U.S. public sector sliding over the 'fiscal cliff' urges financial economists to better understand the foundations for how government spending affects the real economy and financial markets. This paper is the first study to document that uncertainty about future government spending is a first-order risk factor in the bond market, leading to rising real and nominal interest rates, a steeper term spread, an increase in bond market volatility and bond premia. We study an equilibrium asset pricing model with a forward-looking representative agent and a forward-looking government to shed light on these empirical facts.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133416119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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