Term structure surprises: the predictive content of curvature,level, and slope

This paper analyzes the predictive content of the term structure components level, slope, and curvature within a dynamic factor model of macroeconomic and interest rate data. Surprise changes of the three components are identified using sign restrictions, and their macroeconomic underpinnings are studied via impulse response analysis. The curvature factor is found to carry predictive information both about the future evolution of the yield curve and the macroeconomy. In particular, unexpected increases of the curvature factor precede a flattening of the yield curve and announce a significant decline of output more than 1 year ahead. Copyright © 2010 John Wiley & Sons, Ltd.     

Consumption asset pricing and the term structure

We investigate the relationship between consumption and the term structure using U.K. interest rate data. We demonstrate that the term structure contains information about future economic activity as implied by the benchmark time separable power utility consumption based capital asset pricing model (C-CAPM) since the yield spread has forecasting power for future consumption growth. Further, we analyze the ability of this benchmark and two alternative models which adopt utility functions characterized by non-separability, namely, the extension to the habit formation model of Campbell and Cochrane (1999) proposed by Wachter (2006) and the housing C-CAPM proposed by Piazzesi, Schneider and Tuzel (2007). Our findings are supportive of the habit formation specification of Wachter (2006), other models fail to yield economically plausible parameter values.     

What does money and credit tell us about real activity in the United States?

We analyse the forecasting power of different monetary aggregates and credit variables for US GDP. Special attention is paid to the influence of the recent financial market crisis. For that purpose, in the first step we use a three-variable single-equation framework with real GDP, an interest rate spread and a monetary or credit variable, in forecasting horizons of one to eight quarters. This first stage thus serves to pre-select the variables with the highest forecasting content. In a second step, we use the selected monetary and credit variables within different VAR models, and compare their forecasting properties against a benchmark VAR model with GDP and the term spread (and univariate AR models). Our findings suggest that narrow monetary aggregates, as well as different credit variables, comprise useful predictive information for economic dynamics beyond that contained in the term spread. However, this finding only holds true in a sample that includes the most recent financial crisis. Looking forward, an open question is whether this change in the relationship between money, credit, the term spread and economic activity has been the result of a permanent structural break or whether we might return to the previous relationships.     

The Fama-French’s five-factor model relation with interest rates and macro variables

Innovations in variables describing future investment opportunities command a risk premium and are correlated with Fama-French factors. As showed in literature, shocks to the aggregate dividend yield and term spread, default spread, and one-month T-bill rate are proxies for HML and SMB factors. However, in the context of five-factor model, they cannot explain RMW. As CPI is related to operational profitability, and so does RMW, we include its unanticipated shocks in the set of macro variables and factors to help explaining the cross section of returns. In the presence of CPI, RMW loses its explanatory power, and, combined with term structure’s slope innovations, all Fama-French factors lose their explanatory ability and the pricing errors become statistically close to zero. We show that for US data, inflation’s innovations not only proxy for RMW, but a model including only excess market returns, shocks to CPI and term structure’s slope explain the cross section of average returns better than innovations to the previous literature’s four-variable set and Fama-French five-factor model.     

Implied volatility term structure and exchange rate predictability

This paper provides empirical evidence of the predictive power of the currency implied volatility term structure (IVTS) for the behavior of the exchange rate from both cross-sectional and time series perspectives. Intriguingly, the direction of the prediction is not the same for developed and emerging markets. For developed markets, a high slope means low future returns, while for emerging markets it means high future returns. We analyze predictability from a cross-sectional perspective by building portfolios based on the slope of the term structure, and thus present a new currency trading strategy. For developed (emerging) currencies, we buy (sell) the two currencies with the lowest slopes and sell (buy) the two with the highest slopes. The proposed strategy performs better than common currency strategies – carry trade, risk reversal, and volatility risk premium (VRP) – based on the Sharpe ratio, considering only currency returns, which supports the exchange rate predictability of the IVTS from a cross-sectional perspective.     

中国利率期限结构对经济周期波动的预测能力检验——基于动态Probit模型的研究途径

本文对我国利率期限结构对经济周期波动的预测能力进行实证研究.首先,利用时差相关分析方法选择我国经济周期波动的利差先行指标.然后,利用基于利差先行指标的动态Probit模型检验我国利率期限结构对经济周期波动状态的预测能力,并且对静态Probit模型和动态Probit模型、各种动态Probit模型之间的预测效果也进行了比较.研究结果表明,我国利率期限结构变动对未来3个月的经济周期波动状态具有比较稳定的指示作用,利用经济状态先验信息的动态Probit模型的预测效果优于静态Probit模型.     

Yield curve responses to market sentiments and monetary policy

Central banks recently started to target longer term interest rates. The empirical failure of the rational expectations theory of the yield curve, however, limits its applicability to monetary policy analysis. The success of agent-based behavioral asset pricing models and behavioral macroeconomic models in replicating statistical regularities of empirical data series motivates to apply them to yield curve modeling. This paper analyses how the interaction of monetary policy and market sentiments shape the yield curve in a behavioral model with heterogeneous and bounded-rational agents. One result is that the behavioral model replicates empirical facts of term structure data. Moreover, it overcomes one major deficiency of rational expectations models of the yield curve in explaining the empirically observed uncertain responses of longer term yields to changes in the central bank rate. These are explained by the behavioral model’s ability to generate different responses of market sentiments to shocks at different times which lead to a variety of interest rate responses. Further results of this paper can be used as policy advice on how central banks can target the level, slope and curvature of the yield curve by targeting market sentiments about inflation and the business cycle.     

Evaluating factor forecasts for the UK: The role of asset prices

This paper applies a large data set, consisting of 167 monthly time series for the UK, both economic and financial, to simulate out-of-sample predictions of industrial production, inflation, 3-month Treasury Bills, and other variables. Fifteen dynamic factor models that allow forecasting based on large panels of time series are considered. The performances of these factor models are then compared to the following competing models: a simple univariate autoregressive, a vector autoregressive, a leading indicator, and a Phillips curve models. The results show that the best dynamic factor models outperform the competing models in forecasting at 6-, 12-, and 24-month horizons. Thus, the financial markets may have predictive power for the economic activity. This can be a useful tool for central banks and financial institutions, which may use the factor models to construct leading indicators of the economic conditions. In addition, researchers can see a strategic application of factor models.     

The expected real yield and inflation components of the nominal yield curve

The term structure of real yields and expected inflation are two unobserved components of the nominal yield curve. The primary objectives of this study are to decompose nominal yields into their expected real yield and inflation components and to examine their behaviour using state-space and regime-switching frameworks. The dynamic yield-curve models capture three well-known latent factors – level, slope, and curvature – that accurately aggregate the information for the nominal yields and the expected real and inflation components for all maturities. The nominal yield curve is found to increase slightly with a slope of about 120 basis points, while the real yield curve slopes upward by about 20 basis points, and the expected inflation curve is virtually flat at slightly above 2 per cent. The regime-switching estimations reveal that the nominal yield, real yield and expected inflation curves have shifted down significantly since 1999.     

Belgian economic policy uncertainty index: Improvement through text mining

Recently, the literature has measured economic policy uncertainty using news references, resulting in the frequently-mentioned ‘Economic Policy Uncertainty index’ (EPU). In the original setup, a news article is assumed to address policy uncertainty if it contains certain predefined keywords. We argue that the original setup is prone to measurement error, and propose an alternative methodology using text mining techniques. We compare the original method to modality annotation and support vector machines (SVM) classification in order to create an EPU index for Belgium. Validation on an out-of-sample test set speaks in favour of using an SVM classification model for constructing a news-based policy uncertainty indicator. The indicators are then used to forecast 10 macroeconomic and financial variables. The original method of measuring EPU does not have predictive power for any of these 10 variables. The SVM indicator has a higher predictive power and, notably, changes in the level of policy uncertainty during tumultuous periods of high uncertainty and risk can predict changes in the sovereign bond yield and spread, the credit default swap spread, and consumer confidence.     

Forecasting the New York State economy: The coincident and leading indicators approach

Currently there are no reliable summary indicators of the economic and fiscal condition of states and localities. This deficiency has hampered the efforts of policy makers at the sub-national level to monitor changes in the economic environment and predict how those changes will impact the fiscal health of governments. This paper attempts to fill this analytical vacuum by providing summary indicators of economic and fiscal health for New York State. The models developed are based on the single-index methodology developed by Stock and Watson [(1991). A probability model of the coincident economic indicators. In K. Lahiri and G. H. Moore (eds.), Leading economic indicators: new approaches and forecasting records (pp. 63–85). New York: Cambridge University Press]. This approach allows us to date New York business cycles and compare local cyclical behavior with the nation as a whole. We develop a leading index of economic indicators which predicts future movements in the coincident indicator. The Stock and Watson approach is used to create a fiscal indicator which acts as a summary indicator of revenue performance for New York. In addition, we explore the ability of our economic indicator series to predict future changes in state revenues. We find that changes in the leading indicator series have significant predictive power in forecasting changes in our revenue index.     

High-frequency credit spread information and macroeconomic forecast revision

We examine whether professional forecasters incorporate high-frequency information about credit conditions when revising their economic forecasts. Using a mixed data sampling regression approach, we find that daily credit spreads have significant predictive ability for monthly forecast revisions of output growth, at both the aggregate and individual forecast levels. The relationships are shown to be notably strong during ‘bad’ economic conditions, which suggests that forecasters anticipate more pronounced effects of credit tightening during economic downturns, indicating an amplification effect of financial developments on macroeconomic aggregates. The forecasts do not incorporate all financial information received in equal measures, implying the presence of information rigidities in the incorporation of credit spread information.     

Further evidence on financial information and economic activity forecasts in the United States

Our study provides substantially robust evidence for the predictive power of financial variables in forecasting the business cycle at a further step. We select several interesting and representative financial variables and reveal that they can predict significant information regarding future equity premiums as well as future macroeconomic activity, which are proxied by comprehensive fresh macroeconomic variables. The predictive power remains stable in out-of-sample estimations and can generate profits in an active market-timing trading strategy in excess of the historical mean forecast strategy. Cochrane provides one of the core interpretations for such forecasts in the theoretical asset pricing framework.     

GDP trend deviations and the yield spread: the case of eight E.U. countries

Several studies have established the predictive power of the yield curve in terms of real economic activity. In this paper we use data for a variety of E.U. countries: both EMU (Germany, France, Italy, Portugal and Spain) and non-EMU members (Norway, Sweden and the U.K.). The data used range from 1991:Q1 to 2009:Q3. For each country, we extract the long run trend and the cyclical component of real economic activity, while the corresponding ECB euro area government benchmark bond interest rates of long and short term maturities are used for the calculation of the yield spreads. We also augment the models tested with non monetary policy variables: the respective unemployment rates and stock indices. The methodology employed in the effort to forecast real output, is a probit model of the inverse cumulative distribution function of the standard distribution, using several formal forecasting and goodness of fit evaluation criteria. The results show that the yield curve augmented with the non-monetary variables has significant forecasting power in terms of real economic activity but the results differ qualitatively between the individual economies examined raising non-trivial policy implications.     

Credit in the euro area: An empirical investigation using aggregate data

This paper uses multivariate cointegration techniques to estimate a model of aggregate bank lending in the euro area. The model provides a quantitative benchmark for assessing conjunctural developments in loans to the area-wide private sector. Large and protracted deviations of realised loans from the paths implied by the model may reveal information about the emergence of financial imbalances as well as about the state of the economy, particularly about the strength of inflationary pressures. A specific application of the model shows that its error-correction term contains information on future changes in inflation over forecast horizons of relevance for monetary policy.     

Monetary policy on twitter and asset prices: Evidence from computational text analysis

In this paper, we dissect the Twitter debate about the future course of monetary policy and trace the effects of selected topics of this discourse on U.S. asset prices. We focus on the “taper tantrum” episode in 2013, a period with large revisions in expectations about future Fed policy. Based on a novel data set of 90,000 Twitter messages (“tweets”) covering the debate of Fed tapering on Twitter, we use Latent Dirichlet Allocation, a computational text analysis tool, to quantify the content of the discussion. Several estimated topic frequencies are then included in a VAR model to estimate the effects of topic shocks on asset prices. We find that the discussion about Fed policy on social media contains price-relevant information. Shocks to the discussion about the timing of the tapering, about the broader economic policy context and worrying investors are shown to lead to significant asset price changes. We also show that the effects are mostly due to changes in the term premium of yields consistent with the portfolio balance channel of unconventional monetary policy.     

The small open macroeconomy and the yield curve: A state-space representation

This study extends a state-space representation of the yield curve and the macroeconomy to a small open economy in order to study the dynamic interaction between the yield curves in Canada and the U.S. The framework treats the U.S. term structure of interest rates as being exogenous to both the Canadian yield curve and macroeconomy. The empirical results support very strong links between the yield curves in the two countries, with the U.S. yield curve accounting for as much as 45 per cent of the variation of the movement in the level and about 30 per cent of the movements in the slope and the curvature of the Canadian yield curve. Canadian yield-curve factors are found to account for about 50 per cent of the variation in output and the monetary policy rate, and about 25 per cent of the variation in inflation, much larger than the yield curve effects found for future developments of the macroeconomies of other countries. A relatively strong bilateral relationship is found to exist between the yield curve and the instrument of monetary policy, supporting recent studies that find the dynamic relationship between the yield curve and the macroeconomy is due to the pivotal role that monetary policy plays in the macroeconomy.     

The VIX,the variance premium and stock market volatility

We decompose the squared VIX index, derived from US S&P500 options prices, into the conditional variance of stock returns and the equity variance premium. We evaluate a plethora of state-of-the-art volatility forecasting models to produce an accurate measure of the conditional variance. We then examine the predictive power of the VIX and its two components for stock market returns, economic activity and financial instability. The variance premium predicts stock returns while the conditional stock market variance predicts economic activity and has a relatively higher predictive power for financial instability than does the variance premium.     

Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach

This paper suggests a term structure model which parsimoniously exploits a broad macroeconomic information set. The model uses the short rate and the common components of a large number of macroeconomic variables as factors. Precisely, the dynamics of the short rate are modeled with a Factor-Augmented Vector Autoregression and the term structure is derived using parameter restrictions implied by no-arbitrage. The model has economic appeal and provides better out-of-sample yield forecasts at intermediate and long horizons than a number of previously suggested approaches. The forecast improvement is highly significant and particularly pronounced for short and medium-term maturities.     

The effects of external and internal shocks on total factor productivity

This paper examines structural changes that occur in the total factor productivity (TFP) within countries. It is possible that some episodes of high economic growth or economic decline are associated with permanent productivity shocks; therefore, this research has two objectives. The first one is to estimate the structural changes present in TFP for a sample of 77 countries between 1950 (1960) and 2000. The second one is to identify possible explanations for breaks. Two sources were analyzed: (i) episodes in political and economic history; (ii) changes in international trade – a measure of absorption of technology. The results suggest that about one-third of the TFP time-series present at least one structural break. Downwards breaks are more common, indicating that after a break the TFP has much difficulty to recover. When we investigated factors related with structural change, developed countries presented a break near the first oil shock while the developing countries’ breaks are more spread along the decades. Thus, external strikes seem to be more relevant for developed countries. However, for each country and break date, it was possible to find an event close to the break date endogenously detected. Last, the relevance of international trade, measured by trade share percentage of GDP, seems to be limited to explain abrupt changes in TFP.