Skip to main content
SpringerLink
Log in

Monetary Policy and Risk-Based Asset Allocation

  • Research Article
  • Published:
Open Economies Review Aims and scope Submit manuscript

Abstract

This paper focuses on the effects of the Fed’s monetary policy on stock and bond returns co-movement and their implications to risk-based asset allocation. Using a regime-switching model that controls for the economic effects of monetary policy we identify three co-movement regimes. We document that risk-based portfolio strategies poorly perform in the low correlation regime which features inflation shocks. We find outperformance evidence under the negative correlation regime with a high stock market risk and a very accommodating Fed policy. Less effectiveness is demonstrated under the positive correlation regime where bonds are regarded as risky assets and interest rate volatility is fueled by monetary policy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. Indeed, the implications of monetary policies for the aggregate financial market are not new issues to the literature. The effect of monetary policies disclosures has been discussed by several authors. Bernanke and Kuttner (2005) and Flemming and Piazzesi (2005) show for instance that the Fed monetary policy decisions have been well anticipated in general among market participants. This also holds true for the ECB monetary policy according to Wilhelmsen and Zaghini (2005). Consistently, Ehrmann and Fratzscher (2005a, 2005b, 2005c) provide evidence on monetary policy communication playing a key role in enhancing short-term predictability of asset returns. Gürkaynak et al. (2005) and Wongswan (2009) find that the US stock and bond markets react significantly to news about the near-term level of monetary policy and to changes in the related expectations. Similarly, for the euro area, Brand et al. (2006) suggest that revised ECB monetary policy expectations have a significant and sizeable impact on the level of medium to long-term interest rates. Jawadi et al. (2015) find that the unconventional monetary policy run by the Fed after the 2008 financial crisis gave a strong boost to asset prices, which is larger for stock prices than for housing prices.

  2. It is well documented that financial and economic time series dynamics occasionally exhibit noticeable breaks associated with specific events such as financial crises or abrupt changes in central banks policies. Since Hamilton’s (1989) seminal work, regime-switching econometric models have proven successful in identifying those breaks and capturing the effects of discrete changes in the related economic mechanisms. The success of a regime-switching modelling framework largely depends, however, on the nature of the data set to which it applies. For instance, the Markov-switching framework has been a very popular methodological choice in modelling stock returns volatility in the dynamic asset pricing field (Ang and Timmermann, 2012). A recent literature has established the relevance of this framework for asset allocation decisions (Ang and Bekaert, 2002; Tu, 2010). Moreover, in the Markov-switching framework the variable driving the switch across regimes is endogenous, which means that it allows for changes at random time points. Therefore, by contrast to the smooth/abrupt transition regression models, it presents the advantage of not requiring a specification of an exogenous transition variable. The Markov-switching models are, therefore, suitable for describing correlated time series that exhibit distinct dynamic patterns during different time periods.

  3. For robustness check purpose, we estimate 3 alternative specifications based on different macroeconomic variables. These specifications lead to comparable characterizations of the co-movement regimes. The related results can be provided by the authors upon request.

  4. Campbell et al. (2009) find that the permanent component of expected inflation reached it highest level in the early 1980’s and stagnated in the early 1990’s at a comparable level to that in the late 1970’s.

  5. We believe this assumption is reasonable given the standard level of brokerage fees practiced on bond and stock indices ETFs markets.

  6. Given the heterogeneity of portfolios returns skewness, we use the Adjusted for Skewness Sharpe Ratio measure (ASSR) introduced by Zakamouline and Koekebakker (2009) to account for the agent preference for skewness.

  7. We use two degrees of relative risk aversion (γ) which are consistent with the empirical estimates from the literature. For instance, Bliss and Panigirtzoglou (2004) estimated γ values between 3.4 and 9.5 from S&P 500 option data. Earlier studies, including Friend and Blume (1975); Kydland and Prescott (1982) and Constantinides (1990), estimated CRRA parameter values between 1 and 2.

  8. For a more detailed comparison of the properties of the MV and the ERC strategies see Maillard et al. (2010).

References

  • Äijö JJ, Vähämaa S (2011) The Fed’s policy decisions and implied volatility. J Futur Mark 31:995–1010

    Article  Google Scholar 

  • Andersen TG, Bollerslev T, Diebold FX, Vega C (2007) Real-time price discovery in stock, bond and foreign exchange markets. J Int Econ 73:251–277

    Article  Google Scholar 

  • Andersson M, Krylova E, Vähämaa S (2008) Why does the correlation between stock and bond returns vary over time? Appl Financ Econ 18:139–151

    Article  Google Scholar 

  • Ang A, Bekaert G (2002) International asset allocation with regime shifts. Rev Financ Stud 15:1137–1187

    Article  Google Scholar 

  • Ang A, Timmermann A (2012) Regime changes and financial markets. Annual Rev Financial Econ 4:313–333

    Article  Google Scholar 

  • Ang A, Boivin J, Dong S (2011) Monetary policy shifts and the term structure. Rev Econ Stud 78:429–457

    Article  Google Scholar 

  • Aruoba SB, Diebold FX (2010) Real-time macroeconomic monitoring: real activity, inflation, and interactions. Am Econ Rev 100:20–24

    Article  Google Scholar 

  • Barsky RB (1989) Why Don’t the prices of stocks and bonds move together? Am Econ Rev 79:1132–1145

    Google Scholar 

  • Bernanke B, Kuttner K (2005) What explains the stock market’s reaction to Federal Reserve policy? J Financ 60:1221–1257

    Article  Google Scholar 

  • Bikbov R, Chernov M (2013) Monetary policy regimes and the term structure of interest rates. J Econ 174:27–43

    Article  Google Scholar 

  • Bliss RR, Panigirtzoglou N (2004) Option-implied risk aversion estimates. J Financ 59:407–446

    Article  Google Scholar 

  • Brand, C., D. Buncic, and J. Turunen (2006) Using money markets to construct an indicator of ECB monetary policy. ECB Working Paper No 657.

  • Campbell JY, Ammer J (1993) What moves the stock and bond markets? A variance decomposition for long term asset returns. J Financ 48:3–37

    Article  Google Scholar 

  • Campbell JY, Sunderam A, Viceira LM (2009) Inflation bets or deflation hedges? The changing risks of nominal bonds. Working paper, Harvard Business School

    Book  Google Scholar 

  • Connolly, R., C. Stivers, and L. Sun (2005) Stock market uncertainty and the stock-bond return relation. J Financ Quant Anal 40, 161—194.

  • Constantinides G (1990) Habit formation: a resolution of the equity premium puzzle. J Polit Econ 98:519–543

    Article  Google Scholar 

  • David A, Veronesi P (2001) Inflation and earnings uncertainty and the volatility of asset prices: an empirical investigation. University of Chicago, Working Paper

    Google Scholar 

  • Ehrmann M, Fratzscher M (2003) Interdependence between the euro area and the US: what role for the EMU? Intern Financ 6:309–328

    Article  Google Scholar 

  • Ehrmann M, Fratzscher M (2005a) Communication and decision-making by central bank committees: different strategies, same effectiveness? J Money, Credit, Bank 39:509–541

    Article  Google Scholar 

  • Ehrmann, M. and M. Fratzscher (2005b) How should central banks communicate? ECB Working Paper No 557.

  • Ehrmann, M. and M. Fratzscher (2005c) The timing of central bank communication. ECB Working Paper No 565.

  • Flemming M, Piazzesi M (2005) Monetary policy tick-by-tick. University of Chicago, Working Paper

    Google Scholar 

  • Friend I, Blume ME (1975) The demand for risky assets. Am Econ Rev 65:900–922

    Google Scholar 

  • Gulko L (2002) Decoupling. J Portf Manag 28:59–66

    Article  Google Scholar 

  • Gürkaynak RS, Sack B, Swanson E (2005) Do actions speak louder than words? The response of asset prices to monetary policy actions and statements. Intern J Central Banking 1:55–93

    Google Scholar 

  • Hamilton JD (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57:357–384

    Article  Google Scholar 

  • Jawadi F, Sousa R, Traverso R (2015) On the macroeconomic and wealth effects of unconventional monetary policy. Working paper, University of Évry-Val-d'Essonne, France

  • Kydland FE, Prescott EC (1982) Time to build and aggregate fluctuations. Econometrica 50:1345–1370

    Article  Google Scholar 

  • Levin A, Taylor BT (2010) Falling behind the curve: a positive analysis of stop-start monetary policies and the great inflation. Stanford University, Working paper

    Book  Google Scholar 

  • Li L (2002) Macroeconomic factors and the correlation of stock and bond returns. In: Working paper. Center for Finance, Yale International

    Google Scholar 

  • Maillard S, Roncalli T, Teïletche J (2010) The properties of equally weighted risk contribution portfolios. J Portf Manag 36:60–70

    Article  Google Scholar 

  • Newey WK, West KD (1987) A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55:703–708

    Article  Google Scholar 

  • Palomino F (2012) Bond risk premiums and optimal monetary policy. Rev Econ Dyn 15:19–40

    Article  Google Scholar 

  • Scruggs JT, Glabadanidis P (2001) Risk premia and the dynamic covariance between stock and bond returns. J Financ Quant Anal 38:295–316

    Article  Google Scholar 

  • Shiller RJ, Beltratti AE (1992) Stock prices and bond yields. J Monet Econ 30:25–46

    Article  Google Scholar 

  • Stivers C, Sun L (2002) Stock market uncertainty and the relation between stock and bond returns. University of Georgia, Working Paper

    Google Scholar 

  • Tu J (2010) Is regime switching in stock returns important in portfolio decisions? Manag Sci 56:1198–1215

    Article  Google Scholar 

  • Wilhelmsen, B. R. and A. Zaghini (2005) Monetary policy predictability in the euro area: An international comparison. ECB Working Paper No 504.

  • Wongswan J (2009) The response of global stock indexes to US monetary policy announcements. J Int Money Financ 28:344–365

    Article  Google Scholar 

  • Zakamouline V, Koekebakker S (2009) Portfolio performance evaluation with generalized Sharpe ratios: beyond the mean and variance. J Bank Financ 33:1242–1254

    Article  Google Scholar 

  • Zhuanxin, D. (2012) An implementation of Markov regime switching model with time varying transition probabilities in Matlab. Memo.

Download references

Author information

Authors and Affiliations

  1. NATIXIS Asset Management, 21 Quai d’Austerlitz, 75013, Paris, France

    Alexis Flageollet & Hamza Bahaji

  2. University of Paris Dauphine, Paris, France

    Hamza Bahaji

Authors
  1. Alexis Flageollet
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hamza Bahaji
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hamza Bahaji.

Additional information

The authors are mostly grateful to the FMND workshop organizers and to the referees for the insightful comments which allowed them to improve the quality of the paper in a substantial way.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Flageollet, A., Bahaji, H. Monetary Policy and Risk-Based Asset Allocation. Open Econ Rev 27, 851–870 (2016). https://doi.org/10.1007/s11079-016-9404-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11079-016-9404-1

Keywords

JEL Classification

Search

Navigation