An extended macro-finance model with financial factors

This paper extends the benchmark Macro-Finance model by introducing, next to the standard macroeconomic factors, additional liquidity-related and return forecasting factors. Liquidity factors are obtained from a decomposition of the TED spread while the return-forecasting (risk premium) factor is extracted by imposing a single factor structure on the one-period expected excess holding returns. The model is estimated on US data using MCMC techniques. Two findings stand out. First, the model outperforms significantly most structural and non-structural Macro-Finance yield curve models in terms of cross-sectional fit of the yield curve. Second, we find that financial shocks, either in the form of liquidity or risk premium shocks have a statistically and economically significant impact on the yield curve. The impact of financial shocks extends throughout the yield curve but is most pronounced at the high and intermediate frequencies.

An Extended Macro-Finance Model with Financial Factors

This paper extends the benchmark Macro-Finance model by introducing, next to the standard macroeconomic factors, additional liquidity-related and return forecasting factors. Liquidity factors are obtained from a decomposition of the TED spread while the return-forecasting (risk premium) factor is extracted by imposing a single factor structure on the one-period expected excess holding returns. The model is estimated on US data using MCMC techniques. Two findings stand out. First, the model outperforms significantly most structural and non-structural Macro-Finance yield curve models in terms of cross-sectional fit of the yield curve. Second, we find that financial shocks, either in the form of liquidity or risk premium shocks, have a statistically and economically significant impact on the yield curve. The impact of financial shocks extends throughout the yield curve but is most pronounced at the high and intermediate frequencies.yield curve, affine models, macroeconomics and financial factors, Bayesian estimation

An extended macro-finance model with financial factors.

This paper extends the benchmark Macro-Finance model by introducing, next to the standard macroeconomic factors, additional liquidity-related and return forecasting factors. Liquidity factors are obtained from a decomposition of the TED spread while the return-forecasting (risk premium)factor is extracted by imposing a single factor structure on the one-period expected excess holding returns. The model is estimated on US data using MCMC techniques. Two findings stand out. First, the model outperforms significantly most structural and non-structural Macro-Finance yield curve models in terms of cross-sectional .t of the yield curve. Second, we find that financial shocks, either in the form of liquidity or risk premium shocks have a statistically and conomically significant impact on the yield curve. The impact of financial shocks extends throughout the yield curve but is most pronounced at the high and intermediate frequencies.

A New-Keynesian model of the yield curve with learning dynamics: A Bayesian evaluation

We estimate a New-Keynesian macro-finance model of the yield curve incorporating learning by private agents with respect to the long-run expectation of inflation and the equilibrium real interest rate. A preliminary analysis shows that some liquidity premia, expressed as some degree of mispricing relative to no-arbitrage restrictions, and time variation in the prices of risk are important features of the data. These features are, therefore, included in our learning model. The model is estimated on U.S. data using Bayesian techniques. The learning model succeeds in explaining the yield curve movements in terms of macroeconomic shocks. The results also show that the introduction of a learning dynamics is not sufficient to explain the rejection of the extended expectations hypothesis. The learning mechanism, however, reveals some interesting points. We observe an important difference between the estimated inflation target of the central bank and the perceived long-run inflation expectation of private agents, implying the latter were weakly anchored. This is especially the case for the period from mid-1970s to mid-1990s. The learning model also allows a new interpretation of the standard level, slope, and curvature factors based on macroeconomic variables. In line with standard macro-finance models, the slope and curvature factors are mainly driven by exogenous monetary policy shocks. Most of the variation in the level factor, however, is due to shocks to the output-neutral real rate, in contrast to the mentioned literature which attributes most of its variation to long-run inflation expectations.New-Keynesian model; Affine yield curve model; Learning; Bayesian estimation

A New-Keynesian model of the yield curve with learning dynamics: A Bayesian evaluation

We estimate a New-Keynesian macro-finance model of the yield curve incorporating learning by private agents with respect to the long-run expectation of inflation and the equilibrium real interest rate. A preliminary analysis shows that some liquidity premia, expressed as some degree of mispricing relative to no-arbitrage restrictions, and time variation in the prices of risk are important features of the data. These features are, therefore, included in our learning model. The model is estimated on U.S. data using Bayesian techniques. The learning model succeeds in explaining the yield curve movements in terms of macroeconomic shocks. The results also show that the introduction of a learning dynamics is not sufficient to explain the rejection of the extended expectations hypothesis. The learning mechanism, however, reveals some interesting points. We observe an important difference between the estimated inflation target of the central bank and the perceived long-run inflation expectation of private agents, implying the latter were weakly anchored. This is especially the case for the period from mid-1970s to mid-1990s. The learning model also allows a new interpretation of the standard level, slope, and curvature factors based on macroeconomic variables. In line with standard macro-finance models, the slope and curvature factors are mainly driven by exogenous monetary policy shocks. Most of the variation in the level factor, however, is due to shocks to the output-neutral real rate, in contrast to the mentioned literature which attributes most of its variation to long-run inflation expectations

The response of euro area sovereign spreads to the ECB unconventional monetary policies. National Bank of Belgium Working Paper No. 309

We analyse variations in sovereign bond yields and spreads following unconventional monetary policy announcements by the European Central Bank. Using a two-country, arbitrage-free, shadow-rate dynamic term structure model (SR-DTSM), we decompose countries' yields into expectation and risk premium components. By means of an event study analysis, we show that the ECB's announcements reduced both the average expected instantaneous spread and risk repricing components of Italian and Spanish spreads. For countries such as Belgium and France, the ECB announcements impacted primarily the risk repricing component of the spread

Stock-bond return correlations:Moving away from “one-frequency-fits-all” by extending the DCC-MIDAS approach

This paper explores the determinants of U.S. stock-bond correlations estimated at various frequencies. For this purpose, the two-component DCC-MIDAS model of correlation (Colacito et al. 2011) is used and extended to incorporate a third correlation frequency component. Subsequently, macroeconomic and financial variables are studied as determinants of each component. We show that the daily correlation component is driven by financial market factors, while the monthly component is more influenced by macroeconomic factors. Finally, the yearly component is determinedbyfundingopportunitiesintheeconomy. Theseresultsareimportantasthey show that different correlation components and determinants should be considered for different investment horizons

A macro-financial analysis of the corporate bond market. National Bank of Belgium, Working Paper No. 360

We assess the contribution of economic and financial factors in the determination of euro area corporate bond spreads over the period 2001-2015. The proposed multi-market, no-arbitrage affine term structure model is based on the methodology proposed by Dewachter, Iania, Lyrio, and Perea (2015). We model jointly the ‘risk-free curve’, measured by overnight index swap (OIS) rates, and the corporate yield curves for two rating classes (A and BBB). The model includes four spanned and six unspanned factors. We find that, in general, both economic (real activity and inflation) and financial factors (proxying risk aversion, flight to liquidity and general financial market stress) play a significant role in the determination of the spanned factors and hence in the dynamics of the risk-free yield curve and corporate bond spreads. Across the risk-free OIS curve, macroeconomic and financial factors are each responsible on average for explaining 30 and 65 percent of yield variation, respectively. For A-and BBB-rated corporate debt, the selected financial variables explain on average 50 percent of the variation in corporate spreads during the last decade