Knowledge that Transforms

In dealership markets disclosure of size and price of details of public trades is typically incomplete. We examine whether full and prompt disclosure of public-trade details improves the welfare of a risk-averse investor. We analyze a model of dealership market where a market maker first executes a public trade and then offsets her position by trading with other market makers. We distinguish between quantity risk and price revision risk. We show that if the market maker learns some information about the motive behind public trade, neither regime is unambiguously welfare superior. This is because greater transparency improves quantity risk sharing but worsens price revision risk sharing.

This article shows that introducing derivative assets increases incentives to collect information about asset payoffs. The increase in information collection makes the price of the underlying asset more informative and causes the expected price to increase. Extending the model to a dynamic setting with multiple risky assets, we find the introducing derivative assets for one asset increases the expected prices of positively correlated assets and reduces price reaction to future earnings announcements. These findings are consistent with the bulk of the empirical evidence on the relationship between the introduction of derivative assets and the behavior of asset prices.

For a sample of 1163 mutual funds started over the period 1979–1992, we find that fund initiations are positively related to the level of assets invested in and the capital gains embedded in other funds with the same objective, the fund family's prior performance, the fraction of funds in the family in the low range of fees, and the decision by large families to open similar funds in the prior year. In addition, consistent with the presence of scale and scope economies in fund openings, we find that large families and families that have more experience in opening funds in the past are more likely to open new funds.

We examine the effects of price disclosure on market performance in a continuous experimental multiple-dealer market in which seven professional market makers trade a single security. The dealers trade with one another and with computerized informed and liquidity traders. Our key comparison is between fully public price queues (pretrade transparent market) and bilateral quoting (pretrade opaque). We find that opening spreads are wider and trading volume is lower in the opaque markets due to higher search costs there. More importantly, however, higher search costs also induce more aggressive pricing strategies, so that price discovery is much faster in the opaque markets.

Journal Article Filter Rules Based on Price and Volume in Individual Security Overreaction Get access Michael Cooper Michael Cooper Krannert School of Management Address correspondence to Michael Cooper, Krannert School of Management, 1310 Krannert Building, West Lafayette, IN 47907, or email: [email protected]. Search for other works by this author on: Oxford Academic Google Scholar The Review of Financial Studies, Volume 12, Issue 4, 2 July 1999, Pages 901–935, https://doi.org/10.1093/rfs/12.4.901 Published: 01 June 2015

Recent nonparametric estimation studies pioneered by Aït-Sahalia document that the diffusion of the short rate is similar to the parametric function, r^1.5, estimated by Chan et al., whereas the drift is substantially nonlinear in the short rate. These empirical properties call into question the efficacy of the existing affine term structure models and beg for alternative models which admit the observed behavior. This article presents such a model. Our model delivers closed-form solutions for bond prices and a concave relationship between the interest rate and the yields. We show that in empirical analyses, our model outperforms the one-factor affine models in both time-series as well as cross-sectional tests.

This study uses laboratory experiments to determine the effects of trade and quote disclosure on market efficiency, bid-ask spreads, and trader welfare. We show that trade disclosure increases the informational efficiency of transaction prices, but also increases opening bid-ask spreads, apparently by reducing market-makers' incentives to compete for order flow. As a result, trade disclosure benefits market makers at the expense of liquidity traders and informed traders. We find that quote disclosure has no discernible effects on market performance. Overall our results demonstrate that the degree of market transparency has important effects of market equilibria and on trader and market-maker welfare. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

I use daily mutual fund returns to shed new light on the question of whether or not mutual fund managers are successful market timers. Previous studies find that funds are unable to time the market return. I study the funds' ability to time market volatility. I show that volatility timing is an important factor in the returns of mutual funds and has led to higher risk-adjusted returns. The returns of surviving funds are especially sensitive to market volatility; those of nonsurvivors are not.

We empirically examine whether access to deposits with inelastic rates (core deposits) permits a bank to make contractual agreements with borrowers that are infeasible if the bank must pay market rates for funds. Such access insulates a bank's costs of funds from exogenous shocks, allowing it to insulate its borrowers against exogenous credit shocks. We find that, controlling for loan market competition, banks funded more heavily with core deposits provide more loan rate smoothing in response to exogenous changes in aggregate credit risk. Thus we provide evidence for a novel channel linking bank liabilities to relationship lending.

Statistical model selection criteria provide an informed choice of the model with best external (i.e., out-of-sample) validity. Therefore they guard against overfitting (“data snooping”). We implement several model selection criteria in order to verify recent evidence of predictability in excess stock returns and to determine which variables are valuable predictors. We confirm the presence of in-sample predictability in an international stock market dataset, but discover that even the best prediction models have no out-of-sample forecasting power. The failure to detect out-of-sample predictability is not due to lack of power.