This article analyzes optimal, dynamic portfolio and wealth/consumption policies of utility maximizing investors who must also manage market-risk exposure using Value-at-Risk (VaR). We find that VaR risk managers often optimally choose a larger exposure to risky assets than non-risk managers and consequently incur larger losses when losses occur. We suggest an alternative risk-management model, based on the expectation of a loss, to remedy the shortcomings of VaR. A general-equilibrium analysis reveals that the presence of VaR risk managers amplifies the stock-market volatility at times of down markets and attenuates the volatility at times of up markets.

We consider an economy populated by institutional investors alongside standard retail investors. Institutions care about their performance relative to a certain index. Our framework is tractable, admitting exact closed-form expressions, and produces the following analytical results. We find that institutions tilt their portfolios towards stocks that compose their benchmark index. The resulting price pressure boosts index stocks. By demanding more risky stocks than retail investors, institutions amplify the index stock volatilities and aggregate stock market volatility and give rise to countercyclical Sharpe ratios. Trades by institutions induce excess correlations among stocks that belong to their benchmark, generating an asset-class effect.

This article investigates a fund manager's risk-taking incentives induced by an increasing and convex relationship of fund flows to relative performance. In a dynamic portfolio choice framework, we show that the ensuing convexities in the manager's objective give rise to a finite risk-shifting range over which she gambles to finish ahead of her benchmark. Such gambling entails either an increase or a decrease in the volatility of the manager's portfolio, depending on her risk tolerance. In the latter case, the manager reduces her holdings of the risky asset despite its positive risk premium. Our empirical analysis lends support to the novel predictions of the model.

We develop a dynamic model of belief dispersion with a continuum of investors differing in beliefs. The model is tractable and qualitatively matches many of the empirical regularities in a stock price and its mean return, volatility, and trading volume. We find that the stock price is convex in cash‐flow news and increases in belief dispersion, while its mean return decreases when the view on the stock is optimistic, and vice versa when pessimistic. Moreover, belief dispersion leads to higher stock volatility and trading volume. We demonstrate that otherwise identical two‐investor heterogeneous‐beliefs economies do not necessarily generate our main results.

This paper analyzes the dynamic portfolio choice implications of strategic interaction among money managers who compete for fund flows. We study such interaction between two risk‐averse managers in continuous time, characterizing analytically their unique equilibrium investments. Driven by chasing and contrarian mechanisms when one is well ahead, they gamble in the opposite direction when their performance is close. We also examine multiple and mixed‐strategy equilibria. Equilibrium policy of each manager crucially depends on the opponent's risk attitude. Hence, client investors concerned about how a strategic manager may trade on their behalf should also learn competitors' characteristics.

Money managers are rewarded for increasing the value of assets under management. This gives a manager an implicit incentive to exploit the well-documented positive fund-flows to relative-performance relationship by manipulating her risk exposure. The misaligned incentives create potentially significant deviations of the manager’s policy from that desired by fund investors. In the context of a familiar continuous-time portfolio choice model, we demonstrate how a simple risk management practice that accounts for benchmarking can ameliorate the adverse effects of managerial incentives. Our results contrast with the conventional view that benchmarking a fund manager is not in the best interest of investors.