This paper investigates the efficiency of household investment decisions in a unique dataset containing the disaggregated wealth and income of the entire population of Sweden. The analysis focuses on two main sources of inefficiency in the financial portfolio: underdiversification of risky assets (“down”) and nonparticipation in risky asset markets (“out”). We find that while a few households are very poorly diversified, the cost of diversification mistakes is quite modest for most of the population. For instance, a majority of participating Swedish households are sufficiently diversified internationally to outperform the Sharpe ratio of their domestic stock market. We document that households with greater financial sophistication tend to invest more efficiently but also more aggressively, so the welfare cost of portfolio inefficiency tends to be greater for these households. The welfare cost of nonparticipation is smaller by almost one half when we take account of the fact that nonparticipants would be unlikely to invest efficientlyiftheyparticipatedinrisky asset markets.

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.

under a Research Grant to Sodini, the HEC Foundation, the National Science Foundation under Grant This paper investigates the dynamics of individual portfolios in a unique dataset containing the disaggregated wealth and income of all households in Sweden. Between 1999 and 2002, the average share of risky assets in the financial portfolio of participants fell moderately, implying little aggregate rebalancing in response to the decline in risky asset prices during this period. We show that these aggregate patterns conceal strong household-level evidence of active rebalancing, which on average offsets about one half of idiosyncratic passive variations in the risky asset share. Sophisticated households with greater education, wealth, and income, and with better diversified portfolios, tend to rebalance more actively. We find some evidence that households rebalance towards a higher risky share as they become richer. We also study the decisions to enter and exit risky financial markets, and patterns of rebalancing for individual assets. We find that households are more likely to fully sell directly held stocks if those stocks have performed well, and more

Motivated by psychological evidence that attention is a scarce cognitive resource, we model investors ’ attention allocation in learning and study the effects of this on asset-price dynamics. We show that limited investor attention leads to category-learning behavior, i.e., investors tend to process more market and sector-wide information than firm-specific information. This endogenous structure of information, when combined with investor overconfidence, generates important features observed in return comovement that are otherwise difficult to explain with standard rational expectations models. Our model also demonstrates new cross-sectional implications for return predictability.

We model the relationship between asset float (tradeable shares) and speculative bubbles. Investors trade a stock with limited float because of insider lock-ups. They have heterogeneous beliefs due to overconfidence and face short-sales constraints. A bubble arises as price overweighs optimists’ beliefs and investors anticipate the option to resell to those with even higher valuations. The bubble’s size depends on float as investors anticipate an increase in float with lock-up expirations and speculate over the degree of insider selling. Consistent with the internet experience, the bubble, turnover and volatility decrease with float and prices drop on the lock-up expiration date.

, respectively. Over the last twenty years, the field of behavioral finance has grown from a startup operation into a mature enterprise, with well-developed bodies of both theory and empirical evidence. On the empirical side, the benchmark null hypothesis is that one should not be able to forecast a stock’s return with anything other than measures of its riskiness, such as its beta; this hypothesis embodies the familiar idea that any other form of predictability would represent a profitable trading rule and hence a free lunch to investors. Yet in a striking rejection of this null, a large catalog of variables with no apparent connection to risk have been shown to forecast stock returns, both in the time series and the cross-section. Many of these results have been replicated in a variety of samples and have stood up sufficiently well that they are generally considered to be established facts. One prominent set of patterns from the cross-section has to do with medium-term momentum and post-earnings drift in returns. These describe the tendency for stocks that have had unusually high past returns or good earnings news to continue to deliver relatively strong returns over the subsequent six to twelve months (and vice-versa for

Yes! We study the time-varying risk patterns of value and growth stocks across business cycles. We find that the conditional market betas of value stocks covary positively with the expected market risk premium, and that value stocks are riskier than growth stocks in bad times when the expected market risk premium is high. The opposite is true for growth stocks. Methodologically, we measure time-varying risk by sorting conditional betas on the theoretically justified expected market risk premium, instead of the ex post realized market excess return. Our findings lend support to the predictions of recent rational asset pricing theory.

This paper proposes a functional approach to designing and managing the financial systems of countries, regions, firms, households, and other entities. It is a synthesis of the neoclassical, neo-institutional, and behavioral perspectives. Neoclassical theory is an ideal driver to link science and global practice in finance because its prescriptions are robust across time and geopolitical borders. By itself, however, neoclassical theory provides little prescription or prediction of the institutional structure of financial systems — that is, the specific kinds of financial intermediaries, markets, and regulatory bodies that will or should evolve in response to underlying changes in technology, politics, demographics, and cultural norms. The neoclassical model therefore offers important, but incomplete, guidance to decision makers seeking to understand and manage the process of institutional change. In accomplishing this task, the neo-institutional and behavioral perspectives can be very useful. In this proposed synthesis of the three approaches, functional and structural finance (FSF), institutional structure is endogenous. When particular transaction costs or behavioral patterns produce large departures from the predictions of the ideal frictionless neoclassical equilibrium for a given institutional structure, new institutions tend to develop that partially

We estimate a dynamic asset pricing model characterized by heterogeneous boundedly rational agents. The fundamental value of the risky asset is publicly available to all agents, but they have different beliefs about the persistence of deviations of stock prices from the fundamental benchmark. An evolutionary selection mechanism based on relative past profits governs the dynamics of the fractions and switching of agents between different beliefs or forecasting strategies. A strategy attracts more agents if it performed relatively well in the recent past compared to other strategies. We estimate the model to annual US stock price data from 1871 until 2003. The estimation results support the existence of two expectation regimes, and a bootstrap F-test rejects linearity in favor of our nonlinear two-type heterogeneous agent model. One regime can be characterized as a fundamentalists regime, because agents believe in mean reversion of stock prices toward the benchmark fundamental value. The second regime can be characterized as a chartist, trend following regime because agents expect the deviations from the fundamental to trend. The fractions of agents using the fundamentalists and trend following forecasting rules show substantial time variation and switching between predictors. The model offers an explanation for the recent stock prices run-up. Before the 90s the trend following regime was active only occasionally. However, in the late 90s the trend following regime persisted and created an extraordinary deviation of stock prices from the fundamentals. Recently, the activation of the mean reversion regime has contributed to drive stock prices back closer to their fundamental valuation.

a r t i c l e i n f o a b s t r a c t The recent financial crisis has led to a vigorous debate about the pros and cons of fair-value accounting (FVA). This debate presents a major challenge for FVA going forward and standard setters' push to extend FVA into other areas. In this article, we highlight four important issues as an attempt to make sense of the debate. First, much of the controversy results from confusion about what is new and different about FVA. Second, while there are legitimate concerns about marking to market (or pure FVA) in times of financial crisis, it is less clear that these problems apply to FVA as stipulated by the accounting standards, be it IFRS or US GAAP. Third, historical cost accounting (HCA) is unlikely to be the remedy. There are a number of concerns about HCA as well and these problems could be larger than those with FVA. Fourth, although it is difficult to fault the FVA standards per se, implementation issues are a potential concern, especially with respect to litigation. Finally, we identify several avenues for future research.