|dc.description.abstract||In the ﬁrst essay, I decompose inﬂation risk into (i) a part that is correlated with real returns on the market portfolio and factors that determine investor’s preferences and investment opportunities and (ii) a residual part. I show that only the ﬁrst part earns a risk premium. All nominal Treasury bonds, including the nominal money-market account, are equally exposed to the residual part except inﬂation-protected Treasury bonds, which provide a means to hedge it. Every investor should put 100% of his wealth in the market portfolio and inﬂation-protected Treasury bonds and hold a zero-investment portfolio of nominal Treasury bonds and the nominal money market account.
In the second essay, I solve the dynamic asset allocation problem of ﬁnite lived, constant relative risk averse investors who face inﬂation risk and can invest in cash, nominal bonds, equity, and inﬂation-protected bonds when the investment opportunityset is determined by the expected inﬂation rate. I estimate the model with nominal bond, inﬂation, and stock market data and show that if expected inﬂation increases, then investors should substitute inﬂation-protected bonds for stocks and they should borrow cash to buy long-term nominal bonds.
In the lastessay, I discuss how heterogeneity in preferences among investors withexternal non-addictive habit forming preferences aﬀects the equilibrium nominal term structure of interest rates in a pure continuous time exchange economy and complete securities markets. Aggregate real consumption growth and inﬂation are exogenously speciﬁed and contain stochastic components thataﬀect their means andvolatilities. There are two classes of investors who have external habit forming preferences and diﬀerent localcurvatures oftheir utility functions. The eﬀects of time varying risk aversion and diﬀerent inﬂation regimes on the nominal short rate and the nominal market price of risk are explored, and simple formulas for nominal bonds, real bonds, and inﬂation risk premia that can be numerically evaluated using Monte Carlo simulation techniques are provided.||en