«John Y. Campbell, Carolin Pﬂueger, and Luis M. Viceira1 First draft: March 2012 This draft: June 2014 1 Campbell: Department of Economics, Littauer ...»
Monetary Policy Drivers of Bond and Equity Risks
John Y. Campbell, Carolin Pﬂueger, and Luis M. Viceira1
First draft: March 2012
This draft: June 2014
Campbell: Department of Economics, Littauer Center, Harvard University, Cambridge MA 02138, USA,
and NBER. Email john email@example.com. Pﬂueger: University of British Columbia, Vancouver BC
V6T 1Z2, Canada. Email carolin.pﬂueger@sauder.ubc.ca. Viceira: Harvard Business School, Boston MA
02163 and NBER. Email firstname.lastname@example.org. We are grateful to Alberto Alesina, Yakov Amihud, Robert Barro, Philip Bond, Mikhail Chernov, Paul Beaudry, Ian Dew-Becker, Alexander David, Adlai Fisher, Ben Friedman, Lorenzo Garlappi, Joao Gomes, Gita Gopinath, Robin Greenwood, Joshua Gottlieb, Howard Kung, Leonid Kogan, Deborah Lucas, Greg Mankiw, Harald Uhlig, Michael Woodford, conference and seminar participants at the University of British Columbia, the Harvard Monetary Economics Seminar, the 2013 HBS Finance Research Retreat, the University of Calgary, the University of Miami, the Vienna Graduate School of Finance, ECWFC 2013, PNWCF 2014, the Jackson Hole Finance Conference 2014, the ASU Sonoran Winter Finance Conference 2014, the Duke/UNC Asset Pricing Workshop, the Monetary Policy and Financial Markets Conference at the Federal Reserve Bank of San Francisco, the Adam Smith Asset Pricing Workshop, NYU Stern School, the Federal Reserve Bank of New York, the Bank of Canada, and especially our discussants Gregory Duﬀee, Martin Lettau, Rossen Valkanov, Jules van Binsbergen, and Stanley Zin for helpful comments and suggestions. This material is based upon work supported by Harvard Business School Research Funding and the PH&N Centre for Financial Research at UBC.
Abstract The exposure of US Treasury bonds to the stock market has moved considerably over time.
While it was slightly positive on average in the period 1960-2011, it was unusually high in the 1980s and negative in the 2000s, a period during which Treasury bonds enabled investors to hedge macroeconomic risks. This paper explores the eﬀects of monetary policy parameters and macroeconomic shocks on nominal bond risks, using a New Keynesian model with habit formation and discrete regime shifts in 1979 and 1997. The increase in bond risks after 1979 is attributed primarily to a shift in monetary policy towards a more anti-inﬂationary stance, while the more recent decrease in bond risks after 1997 is attributed primarily to an increase in the persistence of monetary policy interacting with continued shocks to the central bank’s inﬂation target. Endogenous responses of bond risk premia amplify these eﬀects of monetary policy on bond risks.
1 Introduction In diﬀerent periods of history, long-term US Treasury bonds have played very diﬀerent roles in investors’ portfolios. During the Great Depression of the 1930s, and once again in the ﬁrst decade of the 21st Century, Treasury bonds served to hedge other risks that investors were exposed to: the risk of a stock market decline, and more generally the risk of a weak macroeconomy, with low output and high unemployment. Treasuries performed well both in the Great Depression and in the two recessions of the early and late 2000s. During the 1970s and particularly the 1980s, however, Treasury bonds added to investors’ macroeconomic risk exposure by moving in the same direction as the stock market and the macroeconomy.
A number of recent papers including Baele, Bekaert, and Inghelbrecht (2010), Campbell, Sunderam, and Viceira (2013), Christiansen and Ranaldo (2007), David and Veronesi (2013), Guidolin and Timmermann (2006), and Viceira (2012) have documented these developments.
In this paper we ask what macroeconomic forces determine the risk properties of US Treasury bonds, and particularly their changes over time. One common approach to this question uses identities that link bond returns to movements in bond yields, and that link nominal bond yields to expectations of future short-term real interest rates, expectations of future inﬂation rates, and time-varying risk premia on longer-term bonds over short-term bonds. Barsky (1989), Shiller and Beltratti (1992), and Campbell and Ammer (1993) were early examples of this approach. A more recent literature has proceeded in a similar spirit, building on the no-arbitrage restrictions of aﬃne term structure models (Duﬃe and Kan 1996, Dai and Singleton 2000, 2002, Duﬀee 2002) to estimate multifactor term structure models with both macroeconomic and latent factors (Ang and Piazzesi 2003, Ang, Dong, and Piazzesi 2007, Rudebusch and Wu 2007). Although these exercises can be informative, they 1 are based on a reduced-form econometric representation of the stochastic discount factor and the process driving inﬂation. This limits the insights they can deliver about the economic determinants of bond risks.
A more ambitious approach is to build a general equilibrium model of bond pricing.
Real business cycle models have an exogenous real economy, driven by shocks to either goods endowments or production, and an inﬂation process that is either exogenous or driven by monetary policy reactions to the real economy. Papers in the real business cycle tradition often assume a representative agent with Epstein-Zin preferences, and generate time-varying bond risk premia from stochastic volatility in the real economy and/or the inﬂation process (Bansal and Shaliastovich 2013, Buraschi and Jiltsov 2005, Burkhardt and Hasseltoft 2012, Gallmeyer et al 2007, Piazzesi and Schneider 2006). Some papers instead derive time-varying risk premia from habit formation in preferences (Bekaert, Engstrom, and Grenadier 2010, Bekaert, Engstrom, and Xing 2009, Buraschi and Jiltsov 2007, Dew-Becker 2013, Wachter 2006). Under either set of assumptions, this work allows only a limited role for monetary policy, which determines inﬂation (at least in the long run) but has no inﬂuence on the real economy.2 Accordingly a recent literature has explored the asset pricing implications of New Keynesian models, in which price stickiness allows monetary policy to have real eﬀects.
Recent papers in this literature include Andreasen (2012), Bekaert, Cho, and Moreno (2010), Van Binsbergen et al (2012), Dew-Becker (2014), Kung (2013), Li and Palomino (2013), Palomino (2012), Rudebusch and Wu (2008), and Rudebusch and Swanson (2012).
We follow this second approach and quantitatively investigate two candidate explanations for the empirical instability in bonds’ risk properties: changes in monetary policy or changes 2 A qualiﬁcation to this statement is that in some models, such as Buraschi and Jiltsov (2005), a nominal tax system allows monetary policy to aﬀect ﬁscal policy and, through this indirect channel, the real economy.
2 in macroeconomic shocks. US monetary policy has altered substantially between the period of rising inﬂation in the 1960s and 1970s, the inﬂation-ﬁghting period under Federal Reserve Board chairmen Paul Volcker and Alan Greenspan and, as we newly identify in our analysis, the most recent period of increased central bank transparency, gradualism, and renewed attention to output stabilization. If the central bank aﬀects the macroeconomy through nominal interest rates, it is natural to think that these changes should aﬀect the risks of bonds and stocks. The nature of economic shocks has also changed over time. While oil supply shocks were prominent during the 1970s and 1980s, more recent output ﬂuctuations have been associated with the information technology revolution and shocks to the ﬁnancial sector. It is intuitive that whenever supply shocks are dominant, bonds should be risky assets. Macroeconomic supply shocks, such as the oil supply shocks of the 1970s and 1980s, might generate high-inﬂation recessions and therefore lead bonds to perform poorly at the same time as stocks.
Figure 1 helps motivate our analysis, showing a timeline of changing US bond risks, monetary policy regimes, and oil price shocks from Hamilton (2009). Figure 1 measures bond risks with ﬁltered estimates of CAPM betas and return volatilities using daily returns on tenyear nominal bonds. Before 1979, the beta of bonds was close to zero but slightly positive.
The bond beta became strongly positive during the 1980s and 1990s, but it declined sharply and turned negative in the late 1990s. Figure 1 also shows two dates that correspond to shifts in monetary policy. The ﬁrst monetary policy break date corresponds to the appointment of Paul Volcker as chairman of the Federal Reserve Board, which arguably marked a signiﬁcant change from the previous more accommodative monetary policy regime (Clarida, Gali, and Gertler 1999). The second monetary policy break date marks the ﬁrst quarter of 1997, coinciding with Alan Greenspan’s well known “Central Banking in a Democratic Society” 3 speech (Greenspan 1996). At ﬁrst glance, monetary policy changes in the late 1990s might not be as salient as Paul Volcker’s appointment. However, we show that this was a period of signiﬁcant monetary policy shifts towards transparency and gradualism and a renewed emphasis on output stabilization, with the central bank being more aware of its inﬂuence of its inﬂuence on ﬁnancial markets, taking more cautious interest rate decisions, and implementing them over longer periods of time. A tangible manifestation of this cautious approach to monetary policy is that the number of dissenting votes at Federal Open Market Committee (FOMC) meetings started to fall in the mid-1990’s and has been very close to zero since 1997 (our regime shift date).3 The Federal Reserve also implemented a number of important changes in transparency starting in the mid-1990’s, such as the publication of more detailed minutes of the FOMC meetings, the explicit announcement of the numerical target for the Federal Funds rate immediately after the meetings, and the release of detailed transcripts of FOMC meetings, albeit with a ﬁve-year delay.
Figure 1 suggests that changes in monetary policy are important for understanding changing bond risks. Changes in bond betas, shown in Panel A, line up closely with monetary policy breaks. Bond return volatility, shown in Panel B, also increases sharply at the ﬁrst monetary policy break date, although there is also variation at other times, most notably a short-lived spike at the beginning of the middle subperiod. In contrast, oil price shocks do not line up closely with nominal bond betas. This observation suggests that changes in the volatility of supply shocks are insuﬃcient to explain changes in bond risks. Oil price shocks represent only a subset of macroeconomic supply shocks and therefore the evidence in Figure 1 is merely suggestive. However, the main empirical analysis in this paper systematically examines the role of time-varying shock volatilities for nominal bond betas and corroborates 3 Joshua Zumbrun, 2013, “Greenspan’s Bequest to Yellen Is Board Harmony Shown in Records”, Bloomberg News, November 6.
This paper builds on the New Keynesian asset pricing literature and makes two contributions. First, we formulate a New Keynesian model in which bonds and stocks can both be priced from assumptions about their payoﬀs, and in which time-varying risk premia, driven by habit formation and stochastic volatility, generate realistic variances and covariances for these asset classes. Most previous New Keynesian asset pricing papers have concentrated on the term structure of interest rates, and have paid little attention to the implied pricing of equities. This contrasts with the integrated treatment of the bond and stock markets in several papers that use reduced-form aﬃne or real business cycle models (Ang and Ulrich, 2012, Bansal and Shaliastovich 2013, Bekaert, Engstrom, and Grenadier 2010, Koijen, Lustig, and Van Nieuwerburgh, 2010, Campbell 1986, Campbell, Sunderam, and Viceira 2013, d’Addona and Kind 2006, Dew-Becker 2013, Eraker 2008, Hasseltoft 2008, Lettau and Wachter 2011, Wachter 2006).
Second, we use our model to relate changes in bond risks to periodic regime changes in the parameters of the central bank’s monetary policy rule and the volatilities of macroeconomic shocks, including the regime shift that we newly identify in the late 1990s. In this way we contribute to the literature on monetary policy regime shifts (Andreasen 2012, Ang, Boivin, Dong, and Kung 2011, Bikbov and Chernov 2013, Boivin and Giannoni 2006, Chib, Kang, and Ramamurthy 2010, Clarida, Gali, and Gertler 1999, Palomino 2012, Rudebusch and Wu 2007, Smith and Taylor 2009). While this literature has begun to focus on the implications of monetary regime shifts for the term structure of interest rates, previous papers have not looked at the implications for the comovements of bonds and equities as we do here. Our structural analysis takes account of various channels by which the monetary 5 policy regime aﬀects the sensitivities of bond and stock returns to macroeconomic shocks, including endogenous responses of risk premia.
The organization of the paper is as follows. Section 2 lays out a basic New Keynesian model that explains interest rates, inﬂation, and medium-term deviations of output from trend (the “output gap”) using three structural equations: an investment-saving curve (IS) that describes real equilibrium in the goods market based on the Euler equation of a representative consumer, a Phillips curve (PC) that describes the eﬀects of nominal frictions on inﬂation, and a monetary policy reaction function (MP) embodying a Taylor rule as in Clarida, Gali, and Gertler (1999), Taylor (1993), and Woodford (2001). This section also solves for the stochastic discount factor (SDF) implied by the New Keynesian IS curve, and uses it to price bonds and stocks.
Section 3 describes our data sources and presents summary statistics for our full sample period, 1960Q1 through 2011Q4, and for three subperiods, 1960Q1–1979Q2, 1979Q3– 1996Q4, and 1997Q1–2011Q4. These subperiods are chosen to match both shifts in monetary policy and changes in measured bond risks. This section also estimates the parameters of the monetary policy reaction function, over the full sample and the three subperiods, using reduced-form regression methodology.