This paper shows that Edgeworth expansions for option valuation are equivalent to approximating option payoffs using Hermite polynomials. Consequently, the value of an option is the value of an infinite series of replicating polynomials. The resultant formulas express option values in terms of skewness, kurtosis, and higher moments. Unfortunately, the Hermite series diverges for fat-tailed models, so we provide alternative moment-based formulas. These formulas are a computationally efficient alternative to Fourier transform valuation and can value options even when the characteristic function is unknown. Applications include the first convergent solution for Hull and White’s stochastic volatility model.

We employ a novel brokerage account data set to investigate which individual investors are the most attentive, how investors allocate their attention, and the relation between investor attention and performance. Attention is positively related to investment performance, at both the portfolio return level and the individual trades level. We provide evidence that the superior performance of high-attention investors arises because they purchase attentiongrabbing stocks whose positive performance persists for up to six months. Finally, we show that paying attention is particularly profitable when trading stocks with high uncertainty, but for which a lot of public information is available. (

We study the nature and effects of cultural biases in choice under risk and uncertainty by comparing peer-to-peer loans the same individuals ( lenders ) make alone and after observing robo-advised suggestions. When unassisted, lenders are more likely to choose co-ethnic borrowers, facing 8% higher defaults and 7.3pp lower returns. Robo-advising does not affect diversification but reduces lending to high-risk co-ethnic borrowers. Lenders in locations with high inter-ethnic animus drive the results, even when borrowers reside elsewhere. Biased beliefs explain these results better than a conscious taste for discrimination: lenders rarely override robo-advised matches to ethnicities they discriminated against when unassisted.

We show a positive relation between network centrality and risk-adjusted performance in a delegated investment management setting. More connected managers take more portfolio risk and receive higher investor flows, consistent with these managers improving their ability to exploit investment opportunities through their network connections. Greater network connections are shown to be particularly important in reducing the diseconomies of scale for large managers who are well connected. We also use the exogenous merger of two investment consultants, which creates a sudden change in the network connections of the managers they oversee, to provide evidence that a greater number of connections translates into better portfolio performance.

Using a unique data set, we document two secular trends in the shift from centralized to decentralized pension fund management over the past few decades. First, across asset classes, sponsors replace generalist balanced managers with better‐performing specialists. Second, within asset classes, funds replace single managers with multiple competing managers following diverse strategies to reduce scale diseconomies as funds grow larger relative to capital markets. Consistent with a model of decentralized management, sponsors implement risk controls that trade off higher anticipated alphas of multiple specialists against the increased difficulty in coordinating their risk‐taking and the greater uncertainty concerning their true skills.