Transcript ON THE ROMANIAN YIELD CURVE: THE EXPECTATIONS HYPOTHESIS

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
MOTIVATION - QUESTIONS
Romanian Yield Curve
 Shape and movements


Predictive power



What can we learn from the yield curve?
Connections with the real economy


How does one analyze the yield curve
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

2
MOTIVATION – QUESTIONS (2)
3
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
4
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
5
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
6
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

7
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

8
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)

9
MOVEMENTS OF THE YIELD CURVE (2)

Principal component analysis

Alternative model: Evans & Marshall (1998)
10
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
11
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

12
TAYLOR RULES (2)

Taylor rule – backwards-looking
13
TAYLOR RULES (3)

Autocorrelations:
14
TAYLOR RULES (4)

Residuals from Taylor rules and the short rate:
15
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

16
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

17
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 shortterm rate is explained by macroeconomic factors
(they also identify latent factors)
18
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
19
VECTOR AUTOREGRESSION (4)

Impulse response functions:
20
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
21
REFERENCES
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"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, "Cauzele inflaţiei 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
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Dai, Q., Singleton, K., 2000, "Specification Analysis of affine term structure models", Journal of Finance 55, 19431978
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Duffie, D., Kan, R., 1996, "A yield-factor model of interest rates", Mathematical Finance 6, 379-406
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European Central Bank, 2003, "Bond Markets and Long-Term Interest Rates in European Union Accesion Countries"
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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
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REFERENCES (2)
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Fama, Eugene F., Bliss, Robert R., 1987, "The information in Long-Maturity Forward Rates", The
American Economic Review, 680-692
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Greene, William H., 2003, "Econometric Analysis, Fifth Edition", Prentice Hall
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Hamilton, James D., 1994, "Time Series Analysis", Princeton University Press
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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, 95120
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
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REFERENCES (3)
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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
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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
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