This paper solves a realistically calibrated life-cycle model of consumption and portfolio choice with uninsurable labor income risk and borrowing constraints. Since labor income substitutes for riskless asset holdings the optimal share invested in equities is roughly decreasing over life. We compute a measure of the importance of non-tradable human capital for investment behavior to find that ignoring labor income generates large utility costs, while the cost of ignoring only its risk is an order of magnitude smaller. We also quantify the utility cost associated with typical heuristics advocated by financial advisors. The issue of portfolio choice over the life-cycle is encountered by every investor. Popular finance books (e.g. Malkiel, 1996) and financial counselors generally give the advice to shift the portfolio composition towards relatively safe assets, such as T-bills, and away from risky stocks as the investor grows older and reaches retirement. But what could be the economic

In a model with housing collateral, the ratio of housing wealth to human wealth shifts the conditional distribution of asset prices and consumption growth. A decrease in house prices reduces the collateral value of housing, increases household exposure to idiosyncratic risk, and increases the conditional market price of risk. Using aggregate data for the US, we find that a decrease in the ratio of housing wealth to human wealth predicts higher returns on stocks. Conditional on this ratio, the covariance of returns with aggregate risk factors explains eighty percent of the cross-sectional variation in annual size and book-to-market portfolio returns. 1

The paper discusses the current state of the behavioral finance literature. I argue that more direct evidence on investors ’ actions and expectations would make existing theories more convincing to outsiders and would help sort among behavioral theories for a given asset pricing phenomenon. Furthermore, evidence on the dependence of a given bias on investor wealth/sophistication would be useful for determining if the bias could be due to (fixed) information or transactions costs or is likely to require a behavioral explanation, and for determining which biases are likely to be most important for asset prices. I analyze a novel data set on investor expectations and actions obtained from UBS PaineWebber/Gallup. The data suggest that, even for high wealth investors, expected returns were high at the peak of the market, many investors thought the market was overvalued but would not correct quickly, and investors ’ beliefs depend strongly on their own investment experience. I then review evidence on the dependence of a series of “irrational ” investor behaviors on investor wealth and conclude that many such behaviors diminish substantially with wealth. As an example of the cost needed to explain a particular type of “irrational”

In textbook theory, demand curves for stocks are kept flat by arbitrage between perfect substitutes. Myron Scholes argues in his study of large-block sales that “the market will price assets such that the expected

This paper surveys research on computational agent-based models used in finance. It will concentrate on models where the use of computational tools is critical in the process of crafting models which give insights into the importance and dynamics of investor heterogeneity in many financial settings.

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In this paper, we analyze the economic value of predicting index returns as well as volatility. On the basis of fairly simple linear models, estimated recursively, we produce genuine out-of-sample forecasts for the return on the S&P 500 index and its volatility. Using monthly data from 1954 to 1998, we test the statistical significance of return and volatility predictability and examine the economic value of a number of alternative trading strategies.

I survey work on the intersection between macroeconomics and finance. The challenge is to find the right measure of “bad times,” rises in the marginal value of wealth, so that we can understand high average returns or low prices as compensation for assets’ tendency to pay off poorly in “bad times.” I survey the literature, covering the time-series and cross-sectional facts, the equity premium, consumption-based models, general equilibrium models, and labor income/idiosyncratic risk approaches.

We construct a dynamic general equilibrium production economy to explicitly link expected stock returns to firm characteristics such as firm size and the book-to-market ratio. Stock returns in the model are completely characterized by a conditional capital asset pricing model (CAPM). Size and book-to-market are correlated with the true conditional market beta and therefore appear to predict stock returns. The cross-sectional relations between firm characteristics and returns can subsist even after one controls for typical empirical estimates of beta. These findings suggest that the empirical success of size and book-to-market can be consistent with a single-factor conditional CAPM model. We gratefully acknowledge the helpful comments of Andy Abel, Jonathan Berk, Michael

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