Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds

We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits variation in the cross‐section of returns. The nonlinearities are mirror images for stocks and bonds, revealing flight‐to‐safety: expected returns increase for stocks when volatility increases from moderate to high levels while they decline for Treasuries. These findings provide support for dynamic asset pricing theories in which the price of risk is a nonlinear function of market volatility.     

NUMERICAL SIMULATION OF NONOPTIMAL DYNAMIC EQUILIBRIUM MODELS

In this article, we propose a recursive equilibrium algorithm for the numerical simulation of nonoptimal dynamic economies. This algorithm builds upon a convergent operator over an expanded set of state variables. The fixed point of this operator defines the set of all Markovian equilibria. We study approximation properties of the operator. We also apply our recursive equilibrium algorithm to various models with heterogeneous agents, incomplete financial markets, endogenous and exogenous borrowing constraints, taxes, and money.     

The Dynamic Properties of Financial‐Market Equilibrium with Trading Fees

We incorporate trading fees into a dynamic, multiagent general‐equilibrium model in which traders optimally decide when to trade. For that purpose, we propose an innovative algorithm that synchronizes the traders. Securities prices are not so much affected by the payment of the fees itself, but rather by the trade‐off that the traders face between smoothing consumption and smoothing holdings. In calibrated examples, the interest rate and welfare decline with trading fees, while risk premia and volatilities increase. Liquidity risk and expected liquidity are priced, leading to deviations from the consumption‐CAPM. With trading fees, capital is slow‐moving, generating slow price reversal.     

A Structural VAR Model of the Australian Economy

We develop an 11-variable structural VAR for the Australian economy over the period 1980 to 1998. The VAR methodology has only relatively recently been applied in the Australian context, despite its popularity in quantitative macroeconomics internationally. Our model includes an overseas sector which distinguishes between goods and asset markets so as to disentangle the effects of shocks emanating from each source. We utilize our model to dissect the Australian growth cycle into its separate influences and to study the Asian crisis. Throughout there is a strong emphasis upon identifying the impact of monetary policy.