In the recent years several commentators hinted at an increase of the correlation between equity and commodity prices, and blamed investment in commodity-related products for this. First, this paper investigates such claims by looking at various measures of correlation. Next, we assess to what extent correlations between oil and equity prices can be exploited for asset allocation. We develop a time-varying Bayesian Dynamic Conditional Correlation model for volatilities and correlations and find that joint modelling of oil and equity prices produces more accurate point and density forecasts for oil which lead to substantial benefits in portfolio wealth.
{"title":"Oil Price Density Forecasts: Exploring the Linkages with Stock Markets","authors":"Marco J. Lombardi, F. Ravazzolo","doi":"10.2139/ssrn.2269233","DOIUrl":"https://doi.org/10.2139/ssrn.2269233","url":null,"abstract":"In the recent years several commentators hinted at an increase of the correlation between equity and commodity prices, and blamed investment in commodity-related products for this. First, this paper investigates such claims by looking at various measures of correlation. Next, we assess to what extent correlations between oil and equity prices can be exploited for asset allocation. We develop a time-varying Bayesian Dynamic Conditional Correlation model for volatilities and correlations and find that joint modelling of oil and equity prices produces more accurate point and density forecasts for oil which lead to substantial benefits in portfolio wealth.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131806970","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}
What is the probability of high inflation; how high, when? These questions are important to all investors since even the 2% level to which we are accustomed will cut an investor’s portfolio by over 17% during a decade. This 2% level is the target of the Federal Reserve, along with near 0% interest rates, for a risk free rate of -2%. This guarantees portfolio erosion absent risk-taking, which could result in even lower returns if the risks of loss are realized. An AARP article characterizes this as The War On Savers. Higher inflation is possible, at 4% or more, with even worse effects. There are heated debates about the probability and timing of high inflation, but our review of the extensive literature reveals no reliable way to predict its onset or extent. Expert opinion predicts inflation best, but it has failed to predict the onset or extent of inflation, and past inflation predicts the experts’ estimates as well as the experts predict future inflation. Debt levels are very high, and inflation is one of the possibilities for deleveraging. The Japanese have proved that high debt can exist without inflation for at least a decade or two, at least in their particular circumstances. Our high debt levels are partly due to the housing collapse. We propose months of unsold housing inventory as an indicator likely to decline before a sustained housing rally, and shelter is both the largest single component of inflation and affects consumer wealth and psychology. We also propose that portfolio erosion through 2% inflation is likely to continue for the present, and that much higher inflation is unlikely until the economy strengthens, but that it remains a risk until deleveraging has occurred by some other means. We suggest monitoring banks’ Federal Reserve deposit levels, which are reported weekly, as another barometer of inflation risk. A portfolio invested in traditional liquid assets – stocks, bonds, and cash – is unlikely to weather high inflation intact; the extent of the damage to each of these asset categories varies widely among inflationary periods and is volatile within these periods.
{"title":"Predicting Inflation: Portfolio Erosion or Collapse?","authors":"George Crawford, J. Liew, A. Marks","doi":"10.2139/ssrn.2156966","DOIUrl":"https://doi.org/10.2139/ssrn.2156966","url":null,"abstract":"What is the probability of high inflation; how high, when? These questions are important to all investors since even the 2% level to which we are accustomed will cut an investor’s portfolio by over 17% during a decade. This 2% level is the target of the Federal Reserve, along with near 0% interest rates, for a risk free rate of -2%. This guarantees portfolio erosion absent risk-taking, which could result in even lower returns if the risks of loss are realized. An AARP article characterizes this as The War On Savers. Higher inflation is possible, at 4% or more, with even worse effects. There are heated debates about the probability and timing of high inflation, but our review of the extensive literature reveals no reliable way to predict its onset or extent. Expert opinion predicts inflation best, but it has failed to predict the onset or extent of inflation, and past inflation predicts the experts’ estimates as well as the experts predict future inflation. Debt levels are very high, and inflation is one of the possibilities for deleveraging. The Japanese have proved that high debt can exist without inflation for at least a decade or two, at least in their particular circumstances. Our high debt levels are partly due to the housing collapse. We propose months of unsold housing inventory as an indicator likely to decline before a sustained housing rally, and shelter is both the largest single component of inflation and affects consumer wealth and psychology. We also propose that portfolio erosion through 2% inflation is likely to continue for the present, and that much higher inflation is unlikely until the economy strengthens, but that it remains a risk until deleveraging has occurred by some other means. We suggest monitoring banks’ Federal Reserve deposit levels, which are reported weekly, as another barometer of inflation risk. A portfolio invested in traditional liquid assets – stocks, bonds, and cash – is unlikely to weather high inflation intact; the extent of the damage to each of these asset categories varies widely among inflationary periods and is volatile within these periods.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130750281","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 aim of this paper is to investigate the evidence and implications of time-variation and asymmetry in the persistence of U.S. inflation. We evaluate these features by comparing the out-of-sample forecast performance of two specifications, a Quantile Auto-Regressive (QAR) model and a parametric Auto-Regressive (AR) model in which the volatility of the errors depends on the level of inflation. The results of the comparison show that the parametric quantile forecasts are at least as accurate as the semi-parametric QAR model, in particular for the core inflation measures. This leads us to conclude that the persistence of core inflation can be considered constant and high, but declined for the headline inflation measures. In addition, we find that the recent findings of asymmetric persistence of inflation shocks can be mostly attributed to the positive relation between inflation level and its volatility.
{"title":"Asymmetric Quantile Persistence and Predictability: The Case of U.S. Inflation","authors":"S. Manzan, D. Zerom","doi":"10.2139/ssrn.2160422","DOIUrl":"https://doi.org/10.2139/ssrn.2160422","url":null,"abstract":"The aim of this paper is to investigate the evidence and implications of time-variation and asymmetry in the persistence of U.S. inflation. We evaluate these features by comparing the out-of-sample forecast performance of two specifications, a Quantile Auto-Regressive (QAR) model and a parametric Auto-Regressive (AR) model in which the volatility of the errors depends on the level of inflation. The results of the comparison show that the parametric quantile forecasts are at least as accurate as the semi-parametric QAR model, in particular for the core inflation measures. This leads us to conclude that the persistence of core inflation can be considered constant and high, but declined for the headline inflation measures. In addition, we find that the recent findings of asymmetric persistence of inflation shocks can be mostly attributed to the positive relation between inflation level and its volatility.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123748695","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 compares the behavior of subject' uncertainty in different monetary policy environments when forecasting inflation in the laboratory. We find that inflation targeting produces lower uncertainty and higher accuracy of interval forecasts than inflation forecast targeting. We also establish several stylized facts about the behavior of individual uncertainty, aggregate distribution of forecasts,and disagreement between individuals. We find that the average confidence interval is the measure that performs best in forecasting inflation uncertainty. Subjects correctly perceive the underlying inflation uncertainty in only 60% of cases and tend to report asymmetric confidence intervals, perceiving higher uncertainty with respect to inflation increases.
{"title":"Uncertainty and Disagreement in Forecasting Inflation: Evidence from the Laboratory","authors":"D. Pfajfar, Blaž Žakelj","doi":"10.2139/ssrn.1836455","DOIUrl":"https://doi.org/10.2139/ssrn.1836455","url":null,"abstract":"This paper compares the behavior of subject' uncertainty in different monetary policy environments when forecasting inflation in the laboratory. We find that inflation targeting produces lower uncertainty and higher accuracy of interval forecasts than inflation forecast targeting. We also establish several stylized facts about the behavior of individual uncertainty, aggregate distribution of forecasts,and disagreement between individuals. We find that the average confidence interval is the measure that performs best in forecasting inflation uncertainty. Subjects correctly perceive the underlying inflation uncertainty in only 60% of cases and tend to report asymmetric confidence intervals, perceiving higher uncertainty with respect to inflation increases.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127897012","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 examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out-of-sample predictive power over and above the predictive power contained by the price-rent ratio, autoregressive benchmarks, and regression models based on small datasets.
{"title":"Housing Price Forecastability: A Factor Analysis","authors":"Lasse Bork, S. Møller","doi":"10.1111/1540-6229.12185","DOIUrl":"https://doi.org/10.1111/1540-6229.12185","url":null,"abstract":"We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out-of-sample predictive power over and above the predictive power contained by the price-rent ratio, autoregressive benchmarks, and regression models based on small datasets.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132300602","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}
Economists have long investigated the cyclical behavior of real wages in order to draw inferences regarding the relative stickiness of prices and wages. Recent studies have adopted techniques intended to identify monetary shocks and examined the response of real wages and output or employment to such shocks. A finding that real wages are procyclical in response to a positive monetary policy shock, for example, is taken as evidence that prices are stickier than wages. In this paper, we show that factors other than wage and price stickiness affect the response of real wages to a monetary policy shock. Accordingly, examining the response of real wages is not enough to sort out the relative stickiness of prices and wages. We use two prominent DSGE models to help us address this issue. These models incorporate both sticky wages and prices but in different ways. The first model (Huang, Liu, and Phaneuf, American Economic Review, 2004) is relatively simple and is not intended for policy analysis. Its relative simplicity allows us to approach the issues both analytically and through simulations. The second model (Smets and Wouters, American Economic Review, 2007) is a relatively complex model of the U.S. economy with many frictions and intended to be useful for policy analysis. Because of its complexity, we must rely principally on simulation exercises. Using these models we offer robust evidence that the real wage response to monetary policy is affected in important ways by properties of the economy other than stickiness of wages and prices, such as the importance of intermediate goods in the production process and the size of key elasticities. Consequently, we cannot appropriately infer the relative stickiness of wages and prices from examining only the response of real wages to a monetary policy shock.
长期以来，经济学家一直在研究实际工资的周期性行为，以得出有关价格和工资相对粘性的推论。最近的研究采用了旨在确定货币冲击的技术，并检查了实际工资和产出或就业对这种冲击的反应。例如，在积极的货币政策冲击下，实际工资是顺周期的，这一发现被认为是价格比工资更具粘性的证据。在本文中，我们证明了工资和价格粘性以外的因素会影响实际工资对货币政策冲击的反应。因此，考察实际工资的反应不足以理清价格和工资的相对粘性。我们使用两个突出的DSGE模型来帮助我们解决这个问题。这些模型结合了粘性工资和价格，但方式不同。第一个模型(Huang, Liu, and Phaneuf, American Economic Review, 2004)相对简单，不用于政策分析。它的相对简单性使我们能够通过分析和模拟来处理问题。第二个模型(Smets and Wouters, American Economic Review, 2007)是一个相对复杂的美国经济模型，有许多摩擦，旨在对政策分析有用。由于其复杂性，我们必须主要依靠模拟练习。使用这些模型，我们提供了强有力的证据，证明实际工资对货币政策的反应在重要方面受到经济属性的影响，而不是工资和价格的粘性，例如中间产品在生产过程中的重要性和关键弹性的大小。因此，我们不能仅仅通过考察实际工资对货币政策冲击的反应来适当地推断工资和价格的相对粘性。
{"title":"Real Wages and Monetary Policy: A DSGE Approach","authors":"B. Perry, Kerk L. Phillips, David E. Spencer","doi":"10.2139/ssrn.2012630","DOIUrl":"https://doi.org/10.2139/ssrn.2012630","url":null,"abstract":"Economists have long investigated the cyclical behavior of real wages in order to draw inferences regarding the relative stickiness of prices and wages. Recent studies have adopted techniques intended to identify monetary shocks and examined the response of real wages and output or employment to such shocks. A finding that real wages are procyclical in response to a positive monetary policy shock, for example, is taken as evidence that prices are stickier than wages. In this paper, we show that factors other than wage and price stickiness affect the response of real wages to a monetary policy shock. Accordingly, examining the response of real wages is not enough to sort out the relative stickiness of prices and wages. We use two prominent DSGE models to help us address this issue. These models incorporate both sticky wages and prices but in different ways. The first model (Huang, Liu, and Phaneuf, American Economic Review, 2004) is relatively simple and is not intended for policy analysis. Its relative simplicity allows us to approach the issues both analytically and through simulations. The second model (Smets and Wouters, American Economic Review, 2007) is a relatively complex model of the U.S. economy with many frictions and intended to be useful for policy analysis. Because of its complexity, we must rely principally on simulation exercises. Using these models we offer robust evidence that the real wage response to monetary policy is affected in important ways by properties of the economy other than stickiness of wages and prices, such as the importance of intermediate goods in the production process and the size of key elasticities. Consequently, we cannot appropriately infer the relative stickiness of wages and prices from examining only the response of real wages to a monetary policy shock.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131157826","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 uses artificial intelligence text analysis methods to construct indices of economic sentiment from a database of 47,000 articles from the Financial Times. The indices have high explanatory power for predicting Federal Open Market Committee interest rate decisions; the effect is both statistically and economically significant. This is partially explained by the incremental predictive power for economic growth the measures exhibit even when accounting for FOMC Greenbook forecasts. However, the FOMC is found to respond strongly even to uninformative components of newspaper sentiment. The result is therefore similar to Romer and Romer (2008), who find that the FOMC reacts to uninformative private forecasts.
{"title":"Using Textual Information in Econometrics: Quantifying Newspaper Sentiment","authors":"Maciej Kula","doi":"10.2139/ssrn.1999800","DOIUrl":"https://doi.org/10.2139/ssrn.1999800","url":null,"abstract":"This paper uses artificial intelligence text analysis methods to construct indices of economic sentiment from a database of 47,000 articles from the Financial Times. The indices have high explanatory power for predicting Federal Open Market Committee interest rate decisions; the effect is both statistically and economically significant. This is partially explained by the incremental predictive power for economic growth the measures exhibit even when accounting for FOMC Greenbook forecasts. However, the FOMC is found to respond strongly even to uninformative components of newspaper sentiment. The result is therefore similar to Romer and Romer (2008), who find that the FOMC reacts to uninformative private forecasts.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130383780","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}
With the concept of trend inflation now widely understood as to be important as a measure of the public's perception of the inflation goal of the central bank and important to the accuracy of longer-term inflation forecasts, this paper uses Bayesian methods to assess alternative models of trend inflation. Reflecting models common in reduced-form inflation modeling and forecasting, we specify a range of models of inflation, including: AR with constant trend; AR with trend equal to last period's inflation rate; local level model; AR with random walk trend; AR with trend equal to the long-run expectation from the Survey of Professional Forecasters; and AR with time-varying parameters. We consider versions of the models with constant shock variances and with stochastic volatility. We first use Bayesian metrics to compare the fits of the alternative models. We then use Bayesian methods of model averaging to account for uncertainty surrounding the model of trend inflation, to obtain an alternative estimate of trend inflation in the U.S. and to generate medium-term, model-average forecasts of inflation. Our analysis yields two broad results. First, in model fit and density forecast accuracy, models with stochastic volatility consistently dominate those with constant volatility. Second, for the specification of trend inflation, it is difficult to say that one model of trend inflation is the best. Among alternative models of the trend in core PCE inflation, the local level specification of Stock and Watson (2007) and the survey-based trend specification are about equally good. Among competing models of trend GDP inflation, several trend specifications seem to be about equally good.
{"title":"A Bayesian Evaluation of Alternative Models of Trend Inflation","authors":"Todd E. Clark, Tae-Yong Doh","doi":"10.26509/WP-201134","DOIUrl":"https://doi.org/10.26509/WP-201134","url":null,"abstract":"With the concept of trend inflation now widely understood as to be important as a measure of the public's perception of the inflation goal of the central bank and important to the accuracy of longer-term inflation forecasts, this paper uses Bayesian methods to assess alternative models of trend inflation. Reflecting models common in reduced-form inflation modeling and forecasting, we specify a range of models of inflation, including: AR with constant trend; AR with trend equal to last period's inflation rate; local level model; AR with random walk trend; AR with trend equal to the long-run expectation from the Survey of Professional Forecasters; and AR with time-varying parameters. We consider versions of the models with constant shock variances and with stochastic volatility. We first use Bayesian metrics to compare the fits of the alternative models. We then use Bayesian methods of model averaging to account for uncertainty surrounding the model of trend inflation, to obtain an alternative estimate of trend inflation in the U.S. and to generate medium-term, model-average forecasts of inflation. Our analysis yields two broad results. First, in model fit and density forecast accuracy, models with stochastic volatility consistently dominate those with constant volatility. Second, for the specification of trend inflation, it is difficult to say that one model of trend inflation is the best. Among alternative models of the trend in core PCE inflation, the local level specification of Stock and Watson (2007) and the survey-based trend specification are about equally good. Among competing models of trend GDP inflation, several trend specifications seem to be about equally good.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126190114","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 tests the efficiency of macroeconomic forecasts, contributing to the existing literature using a rolling-event approach. We construct a monthly economic surprises index, aggregating several macroeconomic news surprises for the nine largest economic areas (G9), which we further analyze the impact on stock, bonds and foreign exchange markets using monthly data. Consequently we extend both research branches mostly focused on efficiency analysis and event studies in macroeconomic news impact. Consistently with the slow adjustment of analysts to news, our results suggest the existence of persistent unexpected economic surprises, presenting a strong autocorrelation for the aggregated G9 economic areas and, individually for USA, Eurozone and Japan. Business cycle decomposition shows that this is more intense in recession phases. Moreover, we provide evidence of a significant relation between economic news surprises and the returns of bond and stock markets. At last, a comparative study of investment decisions and asset allocation rules is also provided, concluding that past economic surprises can be used to predict future returns, providing stronger hit-ratios and higher returns than buy-and-hold and auto-regressive based strategies.
{"title":"Inefficiency in Macroeconomic News Forecasts: Effects on Asset Prices and Asset Allocation Rules","authors":"João Vasco Tavares da Luz Soares, David Cardoso","doi":"10.2139/ssrn.2076074","DOIUrl":"https://doi.org/10.2139/ssrn.2076074","url":null,"abstract":"This paper tests the efficiency of macroeconomic forecasts, contributing to the existing literature using a rolling-event approach. We construct a monthly economic surprises index, aggregating several macroeconomic news surprises for the nine largest economic areas (G9), which we further analyze the impact on stock, bonds and foreign exchange markets using monthly data. Consequently we extend both research branches mostly focused on efficiency analysis and event studies in macroeconomic news impact. Consistently with the slow adjustment of analysts to news, our results suggest the existence of persistent unexpected economic surprises, presenting a strong autocorrelation for the aggregated G9 economic areas and, individually for USA, Eurozone and Japan. Business cycle decomposition shows that this is more intense in recession phases. Moreover, we provide evidence of a significant relation between economic news surprises and the returns of bond and stock markets. At last, a comparative study of investment decisions and asset allocation rules is also provided, concluding that past economic surprises can be used to predict future returns, providing stronger hit-ratios and higher returns than buy-and-hold and auto-regressive based strategies.","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133714468","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}
Contemporary global economic life is measured in days and hours, but most common economic indicators have inevitable lags of months and sometimes quarters (GDP). Moreover, the real-time picture of economic dynamics may differ in some sense from the same picture in its historical perspective, because all fluctuations receive their proper weights only in the context of the whole. Therefore, it’s important to understand whether the existing indicators are really capable of providing important information for decision-makers. In other words, could they be useful in real-time? Why then was it so difficult for the experts to recognize the turning points in real time? What hampers this ability to recognize? Can a turning points’ forecast be entirely objective? The paper answers these questions in terms of three cyclical indicators for the USA (LEI by the Conference Board, CLI by OECD and PMI by ISM) during the last 2008–2009 recession
{"title":"Those Unpredictable Recessions","authors":"S. Smirnov","doi":"10.2139/ssrn.1996991","DOIUrl":"https://doi.org/10.2139/ssrn.1996991","url":null,"abstract":"Contemporary global economic life is measured in days and hours, but most common economic indicators have inevitable lags of months and sometimes quarters (GDP). Moreover, the real-time picture of economic dynamics may differ in some sense from the same picture in its historical perspective, because all fluctuations receive their proper weights only in the context of the whole. Therefore, it’s important to understand whether the existing indicators are really capable of providing important information for decision-makers. In other words, could they be useful in real-time? Why then was it so difficult for the experts to recognize the turning points in real time? What hampers this ability to recognize? Can a turning points’ forecast be entirely objective? The paper answers these questions in terms of three cyclical indicators for the USA (LEI by the Conference Board, CLI by OECD and PMI by ISM) during the last 2008–2009 recession","PeriodicalId":445951,"journal":{"name":"ERN: Forecasting & Simulation (Prices) (Topic)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126086219","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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