Equilibrium Asset Pricing With Heterogeneous Agents And Interdependent Habit Formation
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Habit Formation Heterogeneity
Author | : Eduard Dubin |
Publisher | : |
Total Pages | : 38 |
Release | : 2017 |
Genre | : |
ISBN | : |
We explicitly solve for the aggregate asset prices in a discrete-time general-equilibrium endowment economy with two agents who differ with respect to their preferences for risk aversion and sensitivity to habit, either internal or external. We compute equilibrium quantities -- equity premium, equity return volatility, Sharpe ratio, interest rate, interest rate volatility, and asset holdings -- via a generalized algorithm of Dumas and Lyasoff (2012, JF). Generalization addresses time-nonseparability of utility function induced by habit. We find that internal habits produce equilibrium asset prices that are more consistent with historically observed aggregate prices relative to external-habit preferences.
Essays on Equilibrium Asset Pricing with Heterogeneous Agents
Author | : Qi Zeng |
Publisher | : |
Total Pages | : 117 |
Release | : 2003 |
Genre | : |
ISBN | : |
My dissertation concerns the equilibrium asset pricing and its implications when agents are heterogenous. There are three chapters in the dissertation.
Equilibrium Asset Prices and Savings of Heterogeneous Agents in the Presence of Incomplete Markets and Portfolio Constraints
Author | : Albert Marcet |
Publisher | : |
Total Pages | : 30 |
Release | : 1998 |
Genre | : Consumption (Economics) |
ISBN | : |
A time homogeneous stationary equilibrium model of asset pricing with heterogeneous agents
Author | : George Vachadze |
Publisher | : |
Total Pages | : 19 |
Release | : 1999 |
Genre | : |
ISBN | : 9788086288192 |
Asset Pricing with Heterogeneous Agents
Author | : Gregory William Huffman |
Publisher | : London : Department of Economics, University of Western Ontario |
Total Pages | : 25 |
Release | : 1985 |
Genre | : |
ISBN | : 9780771406645 |
Asset Pricing with Heterogeneous Agents and Non-Tradeable Assets
Author | : Miguel Cantillo |
Publisher | : |
Total Pages | : 30 |
Release | : 2019 |
Genre | : |
ISBN | : |
This paper develops a tractable asset pricing framework based on an Arrow Debreu economy with heterogeneous agents. The assumption of heterogeneity recasts the market rather than aggregate consumption as the key element for pricing securities. The model expresses some asset pricing relationships in terms of four underlying variables. It develops a new formulation for the market risk premium and the earnings price ratio.The theoretical results are used to estimate preference parameters, which yield a value of relative risk aversion between 1.3 and 1.9, and a time preference discount rate between 2.8% and 4.6% per year.
A Unified Theory of Asset Pricing
Author | : Qing Yang |
Publisher | : |
Total Pages | : 75 |
Release | : 2019 |
Genre | : |
ISBN | : |
In this paper, we propose a general methodology to characterize (i.e. develop the recursive equation systems for) the dynamic stochastic general equilibrium asset pricing problems (DSGE) with arbitrary numbers of agents and financial assets in a Lucas economy and propose a convergent numerical method to solve the equation systems. Potentially, we can introduce arbitrary market structures, frictions or other exotic settings in agents' optimization problems, such as incomplete market, portfolio constraint, transaction cost, price impact, heterogeneous beliefs, habit formation, generalized recursive preferences, long run risks, idiosyncratic risk, rare disasters, ambiguity aversion, Knightian uncertainty, information asymmetry or some behavioral finance features, such as non-concave utility functions or probability distortions. In particular, we apply our method to three related theoretical asset pricing problems in the DSGE framework: asset pricing with complete market, or incomplete market, heterogeneous beliefs and external habits or generalized recursive preferences and portfolio constraints. A novel convergent numerical technique is proposed, which is based on convergent function approximation (e.g., machine learning function approximation via artificial neural networks). The numerical method introduced is powerful and can be applied to problems of high dimensions and extended to all types of the backward stochastic differential equations or partial differential equations in the literature. With the help of machine learning function approximation, we are able to accurately find the numerical solution of a DSGE or a partial equilibrium asset pricing problem in a future time-space grid. Machine learning technique is also combined with traditional stochastic differential equations with jumps to model the underlying asset prices, which opens the door to a completely new modeling field and therefore gives classical stochastic finance theory a new life. In the end, some forward-looking thoughts in financial modeling are provided. Numerical experiments are carried out and the solutions are analyzed.