For a fixed large donation a matching scheme that simply uses a one-for-one match ratio can actually raise less money than a seed money scheme. But when the match ratio is chosen to reflect the characteristics of the small donor base so as to exhaust the large donor's willingness to give,...

This paper examines general properties of prices of contingent claims. When the underlying follows a one- dimensional diffusion and interest rates are deterministic, a claim's delta is bounded by the infimum and the supremum of its delta at maturity. Similar bounds hold for the bond position in...

This paper investigates the relation between investor sentiment, executive compensation and corporate investment. We derive a model that shows the share price will be jointly affected by investor sentiment and the corporate investment decision. The model predicts that, if a compensation contract...

We examine the optimal saving decision of individuals who face a multiplicative risk. An individual is defined to be multiplicative risk prudent if multiplying a pure risk to her future wealth raises her optimal savings. We show that convex marginal utility is not sufficient to induce...

AbstractFama and French (2006) use the dividend discount model to develop the joint role of three variables – expected profitability, expected investment and current BM – in predicting future stock returns. One reported empirical result is anomalous. The valuation model establishes that the...

We use machine-learning to determine the information content of the Item 1A Risk Factors section of S&P 1500 10-Ks. We identify and quantify 30 risk-factors and show a strong positive relation between levels of and contemporaneous changes in risk-factors and proxies for the associated risks....

Stock and options markets can disagree about a stock's value because of informed trading in options and/or price pressure in the stock. The predictability of stock returns based on this cross- market discrepancy in values is especially strong when accompanied by stock price pressure, and it does...

Machine-learning is used to investigate the information content of 10-K Item 1A Risk Factors disclosures by identifying and quantifying 30 risk-factors. Sentence-counts of salient risk-factors are strongly positively related to 14 familiar proxies for firm risk. The time-series average of the...