Zeynep Senyuz

A Joint Dynamic Bi-Factor Model of the Yield Curve and the Economy as a Predictor of Business Cycles

This paper proposes an econometric model of the joint dynamic relationship between the yield curve and the economy to predict business cycles. We examine the predictive value of the yield curve to forecast both future economic growth as well as the beginning and end of economic recessions at the monthly frequency. The proposed multivariate dynamic factor model takes into account not only the popular term spread but also information extracted from the entire yield curve. The nonlinear model is used to investigate the interrelationship between the phases of the bond market and of the business cycle. The results indicate a strong interrelation between these two sectors. Although the popular term spread has a reasonable forecasting performance, the proposed factor model of the yield curve exhibits substantial incremental predictive value. This result holds in-sample and out-of-sample, using revised or real time unrevised data.

What does financial volatility tell us about macroeconomic fluctuations

This paper provides an extensive analysis of the predictive ability of financial volatility measures for economic activity. We construct monthly measures of aggregated and industry-level stock volatility, and bond market volatility from daily returns. We model log financial volatility as composed of a long-run component that is common across all series, and a short-run component. If volatility has components, volatility proxies are characterized by large measurement error, which veils analysis of their fundamental information and relationship with the economy. We find that there are substantial gains from using the long term component of the volatility measures for linearly projecting future economic activity, as well as for forecasting business cycle turning points. When we allow for asymmetry in the long-run volatility component, we find that it provides early signals of upcoming recessions. In a real-time out-of-sample analysis of the last recession, we find that these signals are concomitant with the first signs of distress in the financial markets due to problems in the housing sector around mid-2007 and the implied chronology is consistent with the crisis timeline.

A Dynamic Factor Model of the Yield Curve as a Predictor of the Economy

In this paper, we propose an econometric model of the joint dynamic relationship between the yield curve and the economy to predict business cycles. We examine the predictive value of the yield curve to forecast future economic growth as well as the beginning and end of economic recessions at the monthly frequency. The proposed nonlinear multivariate dynamic factor model takes into account not only the popular term spread but also information extracted from the level and curvature of the yield curve and from macroeconomic variables. The nonlinear model is used to investigate the interrelationship between the phases of the bond market and of the business cycle. The results indicate a strong interrelation between these two sectors. The proposed factor model of the yield curve exhibits substantial incremental predictive value compared to several alternative specifications. This result holds in-sample and out-of-sample, using revised or real time unrevised data.

Cyclical Dynamics of the Turkish Economy and the Stock Market

Abstract We analyze the cyclical dynamics of the Turkish economy and the stock market as well as their interactions. We use hidden Markov models that are robust to parameter instability arising from major shifts in economic policy, which have been typically observed in the Turkish economy. These models provide estimates of turning points for the growth, business, and stock market cycles. We identify three states of growth cycles and two states of business cycles in Turkey characterized by different mean estimates. We find that the economy went through five recessions since 1987. Crises are characterized by sharp drops in economic activity and are preceded by slowdowns. These crises are typically followed by strong recoveries during which the economy grows above its long-run average rate. We show that the Turkish stock market goes through three regimes having distinct risk-return dynamics. Bear markets associated with negative returns precede every recession with an average lead time of three quarters, suggesting that the stock market may be a useful forward-looking indicator of the Turkish economy.

Effects of Changing Monetary and Regulatory Policy on Overnight Money Markets

Money markets have been operating under a new monetary policy implementation framework since the Federal Reserve started paying interest on bank reserves in late 2008. The regulatory environment has also evolved substantially over this period. We develop and test hypotheses regarding the effects of changes in the monetary and regulatory policy on dynamics of key overnight funding markets. We find that the federal funds rate continued to provide an anchor, albeit weaker, for unsecured funding rates amid substantial decline in activity and changing composition of trades, while its transmission to the repo market had been hampered. The overnight reverse repurchase (ON RRP) operations that started in late 2013 contributed to stronger co-movement among overnight funding rates and markedly reduced their volatility. The change in the FDIC assessment fees and Basel III leverage ratio regulations have exacerbated financial-reporting-day effects in unsecured markets. In contrast, consistent with lower dealer leverage in the post-crisis period, such effects have weakened in the repo market, especially after the inception of the ON RRP facility. Finally, superabundant bank reserves appear to have significantly diminished the effects of reserve-maintenance on the money market rates.