1 / 24

ON THE ROMANIAN YIELD CURVE: THE EXPECTATIONS HYPOTHESIS AND CONNECTIONS TO THE REAL ECONOMY

ACADEMY OF ECONOMIC STUDIES DOCTORAL SCHOOL OF FINANCE AND BANKING – DOFIN DISSERTATION PAPER. ON THE ROMANIAN YIELD CURVE: THE EXPECTATIONS HYPOTHESIS AND CONNECTIONS TO THE REAL ECONOMY. M.Sc. Student: Alina ŞTEFAN Advisor : Prof. Mois ă ALTĂR Bucharest 2008. Motivation - questions.

salena
Télécharger la présentation

ON THE ROMANIAN YIELD CURVE: THE EXPECTATIONS HYPOTHESIS AND CONNECTIONS TO THE REAL ECONOMY

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ACADEMY OF ECONOMIC STUDIES DOCTORAL SCHOOL OF FINANCE AND BANKING – DOFIN DISSERTATION PAPER ON THE ROMANIAN YIELD CURVE: THE EXPECTATIONS HYPOTHESIS AND CONNECTIONS TO THE REAL ECONOMY M.Sc. Student: Alina ŞTEFAN Advisor: Prof. Moisă ALTĂR Bucharest 2008

  2. Motivation - questions Romanian Yield Curve • Shape and movements • How does one analyze the yield curve • Predictive power • What can we learn from the yield curve? • Connections with the real economy • How is the yield curve influenced by inflation and real activity? • Caveat: data are scarce and volatile • Methodology: • All the tests are done in STATA • August 1999 – February 2008, monthly data

  3. Motivation – questions (2)

  4. Results • In the short run BUBOR is a good approximation for the Romanian T-bills yields • In the medium and long run the yield curve is flat or downward sloping • The expectation hypothesis does not hold, yet the market correctly anticipates the direction of yields • Parallel shifts in the yield curve represent the largest part of the movements in the yield curve • Yields on the primary market are higher than on the secondary market (related to the winner’s curse) • A backwards-looking Taylor rule performs well • Yields respond to shocks to inflation and real activity

  5. Short term • UK: Panel regression with Fixed Effects for GBP LIBOR on the T-bills yields •  = -0.01,  = 1.087, R2 = 0.99 • Cointegrated (using 3-Month data) • T-bills yields Granger cause LIBOR • The credit spread improves the model • Romania: Panel regression with Random Effects for 3M, 6M, 12M BUBOR on T-bills yields •  = 0.02,  = 1.035, R2 = 0.99 • The variables Granger cause each other • Romanian yields follow BUBOR closely

  6. Medium & long term • Construction of yield curve using cubic spline interpolation  Yi(t) = ai + bit + cit2 + dit3 • March 2007: • The shape of the yield curve reveals market expectations about future interest rates • Theory: term premium (liquidity premium) hypothesis / expectations hypothesis

  7. Expectation hypothesis • Explains the shape of the yield curve fj = E(YTMj)  YTMj= fj +  (1+YTMj)j = (1+YTMi)I (1+fi:j)j-i • Regress realized yields on forward rates (e.g. f2:5 compares with YTM3, 2 years from now) • Expectation hypothesis says  = 0,  = 1 • Alternative theory: term premium says  < 0,  = 1 • Fama & Bliss (1987) find that forward rates do not have predictive power at a short horizon

  8. Expectation hypothesis (2) • Realized yields on forward rates with Fixed Effects • No evidence for a term premium • The expectations hypothesis does not hold • Still, the market correctly anticipates the direction, but not the degree, of interest rate changes

  9. Movements of the yield curve • How to describe movements of the yield curve? • Group the yields into short term, medium term and long term and run a principal component analysis • Risk factors: slope, level, curvature • Scheinkman&Litterman (1991), Dai&Singleton (2000) • 68.22% of the movements of the yield curve are parallel shifts • For comparison, more than 99% of the movements in BUBOR are explained by parallel shifts (because of short maturities)

  10. Movements of the yield curve (2) • Principal component analysis • Alternative model: Evans & Marshall (1998)

  11. Primary vs. secondary markets • Two opposing theories: • Avoid winner’s curse yields on the primary market > yields on the secondary market – Neyt (1995) for Belgium • Liquidity hypothesis  yields on the primary market < yields on the secondary market – Krishnamurthy (2002) for the US • In Romania there is evidence of the former, although the data are scarce and volatile • Volatility on the primary market = 0.29, on the secondary = 0.58

  12. Taylor rules • Taylor rule (1993): rt = a0 + a'1ft0+ vt • Clarida et al (2000)  backwards-looking • rt = b0 + b'1Xt0+ vt, where Xt0= (ft0' ft0'-1, ..., ft0'-p-1 )' • I use 3-Month yields – logs, first difference; CPI and IP – deseasonalized, logs, first difference • For Romania: • In the original Taylor rule, R2 is very small (0.04) • In backwards-looking form, R2 is 0.67

  13. Taylor rules (2) • Taylor rule – backwards-looking

  14. Taylor rules (3) • Autocorrelations:

  15. Taylor rules (4) • Residuals from Taylor rules and the short rate:

  16. Taylor rules (5) • Also take into account: • Larger set of macroeconomic data • The Taylor rule is sensitive to the measures of inflation and real activity • The Taylor rule has a forward-looking component • Interest rate smoothing

  17. Vector autoregression • Analyze the interactions between yields and real economy • 2 models: • Short term yields, medium term yields, principal component for inflation (consumer price index, Brent price, production price index), industrial production • The commodity price also accounts for unexpected inflation • The inflation factor is closely correlated to the CPI (79.92%) and the PPI (82.62%) and less correlated with Brent (59.65%). • Short term yields, medium term yields, consumer price index, industrial production • The yields are in logs and first difference • The inflation and industrial production is seasonally adjusted, in logs and first difference

  18. Vector autoregression (2) • The first model: • VAR with 3 lags – economically significant • R2 is 80.11% for the short-term yields equation and 52.03% for the medium-term yields • Ang & Piazzesi(2003) find that 85% of the US short-term rate is explained by macroeconomic factors(they also identify latent factors)

  19. Vector autoregression (3) • The VAR is stable, the residuals are correlated at lag 2, errors are not normally distributed • Yields are Granger caused by inflation and real activity

  20. Vector autoregression (4) • Impulse response functions:

  21. Conclusions • In the short run BUBOR is a good approximation for the Romanian T-bills yields • In the medium and long run the yield curve is flat or downward sloping • The expectation hypothesis does not hold, yet the market correctly anticipates the direction of yields • Parallel shifts in the yield curve represent the largest part of the movements in the yield curve • Yields on the primary market are higher than on the secondary market (related to the winner’s curse) • A backwards-looking Taylor rule performs well • Yields respond to shocks to inflation and real activity

  22. References • "Stata: Time Series", Stata Press, 2007 • Acock, Alan C., 2006,"A Gentle Introduction to Stata",Stata Press • Ang A., Piazzesi M., 2003,"A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables", Journal of Monetary Economics 50, 745-787 • Ang, Andrew, Dong, Sen, Piazzesi, Monika, 2007,"No-Arbitrage Taylor Rules", NBER Working Papers 13448 • Baum, Christopher F., 2006, "An Introduction to Modern Econometrics Using Stata", Stata Press • Bodie, Zvi, Kane, Alex, Marcus, Alan J., 2008, "Investments, Eigth Edition", McGraw-Hill • Boţel, Cezar, 2002,"Cauzeleinflaţiei în România, iunie 1997-august 2001. Analiză bazată pe vectorul autoregresiv structural", BNR, Caiete de studii 11 • Chen, R. R., Scott, L., 1993, "Maximum likelihood estimation for a multi-factor equilibrium model of the term structure of interest rates", Journal of Fixed Income 3, 1993, 14-31 • Christiano, Lawrence J., Eichenbaum, Martin, Evans, Charles L., 1998,"Monetary Policy Shocks: What Have We Learned and to What End?", NBER Working Paper, 6400 • Christiano, Lawrence J., Eichenbaum, Martin, Evans, Charles L., 2001,"Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy", NBER Working Papers, 8403 • Clarida, R., Gali, J., Gertler, M., 2000,"Monetary policy rules and macroeconomic stability: evidence and some theory", Quarterly Journal of Economics 41, 277-300 • Clinebell, John M., Kahl, Douglas R., Stevens, Jerry L., 2000, "Integration of LIBOR and Treasury bill yields over different monetary regimes", Global Finance Journal, 17-30 • Dai, Q., Singleton, K., 2000, "Specification Analysis of affine term structure models", Journal of Finance 55, 1943-1978 • Duffie, D., Kan, R., 1996,"A yield-factor model of interest rates", Mathematical Finance 6, 379-406 • European Central Bank, 2003, "Bond Markets and Long-Term Interest Rates in European Union Accesion Countries" • Evans C.L., Marshall D., 1998,"Monetary policy and the term structure of nominal interest rates evidence and theory", Carnegie-Rochester Conference Series on Public Policy 49

  23. References (2) • Fama, Eugene F., Bliss, Robert R., 1987, "The information in Long-Maturity Forward Rates", The American Economic Review, 680-692 • Greene, William H., 2003,"Econometric Analysis, Fifth Edition", Prentice Hall • Hamilton, James D., 1994, "Time Series Analysis", Princeton University Press • Krishnamurthy, Arvind, 2002, "The Bond/Old Bond Spread", Forthcoming Journal of Financial Economics • Kuttner, Kenneth, N., Mosser, Patricia, P., 2002, "The Monetary Transmission Mechanism: Some Answers and Further Questions ", FRBNY Economic Policy Review/ May 2002 • Litterman, R., Scheinkman, J., 1991,"Common factors affecting bond returns", Journal of Fixed Income 1, 51-61 • Longstaff, F.A., Schwartz, E.S., 1992,"Interest rate volatility and the term structure: a two factor general equilibrium model", Journal of Finance 47, 1252-1282 • McCulloh, J. Huston, 1975,"An Estimate of the Liquidity Premium", The Journal of Political Economy, 95-120 • Mönch, Emanuel, 2005, "Forecasting the Yield Curve in a Data Rich Environment: A No-Arbitrage Factor Augmented VAR Approach", ECB Working Papers, 544 • Neyt, R., 1995, "Evidence on the Yield Differentials between the Primary and Secondary Market for Belgian Treasury Bills", Tijdschrift voor Economie en Management, Vol. XLI. I, 1996 • Rotemberg, Julio, Woodford, Michael, 1998, "Interest Rate Rules in an Estimated Sticky Price Model ", NBER Working Papers, 6618

  24. References (3) • Taylor, J.B., 1993,"Discretion versus policy rules in practice ", Carnegie-Rochester Conference Series on Public Policy 39, 195-214 • Varian, Hal R,., 2005"Intermediate Microeconomics: A Modern Approach, Seventh Edition", W. W. Norton • Veronesi, Pietro, 2007, "Recent Advances in Fixed Income Securities Modeling Techniques", presentation made at the Bank of Italy, July 2007 • Wooldridge, Jeffrey M., 2002,"Econometric Analysis of Cross Section and Panel Data", The MIT Press • Wu, T., 2003,"What makes the yield curve move?", FRBSF Economic Letter

More Related