Economic theory suggests that a commitment by a firm to increased levels of disclosure should lower the information asymmetry component of the firm's cost of capital. But while the theory is compelling, so far empirical results relating increased levels of disclosure to measurable economic benefits have been mixed. One explanation for the mixed results among studies using data from firms publicly registered in the United States is that, under current U.S. reporting standards, the disclosure environment is already rich. In this paper, we study German firms that have switched from the German to an international reporting regime (1AS or U.S. GAAP), thereby committing themselves to increased levels of disclosure. We show that proxies for the information asymmetry component of the cost of capital for the switching firmsnamely, the bid-ask spread and trading volume-behave in the predicted direction compared to firms employing the German reporting regime.

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The Economic Consequences of Increased Disclosure

In this article we compare three models of the stochastic behavior of commodity prices that take into account mean reversion, in terms of their ability to price existing futures contracts, and their implication with respect to the valuation of other financial and real assets. The first model is a simple one-factor model 'in which the logarithm of the spot price of the commodity is assumed to follow a mean reverting process. The second model takes into account a second stochastic factor, the convenience yield of the commodity, which is assumed to follow a mean reverting process. Finally, the third model also includes stochastic interest rates. The Kalman filter methodology is used to estimate the parameters of the three models for two commercial commodities, copper and oil, and one precious metal, gold. The analysis reveals strong mean reversion in the commercial commodity prices. Using the estimated parameters, we analyze the implications of the models for the term structure of futures prices and volatilities beyond the observed contracts, and for hedging contracts for future delivery. Finally, we analyze the implications of the models for capital budgeting decisions. THE STOCHASTIC BEHAVIOR OF commodity prices plays a central role in the models for valuing financial contingent claims on the commodity, and in the procedures for evaluating investments to extract or produce the commodity. Earlier studies, by assuming that interest rates and convenience yields are constant allowed for a straight forward extension of the procedures developed for common stock option pricing to the valuation of financial and real commodity contingent claims. The assumption, however, is clearly not very satisfactory since it implies that the volatility of future prices is equal to the volatility of spot prices, and that the distribution of future spot prices under the equivalent martingale measure has a variance that increases without bound as the horizon increases. In an equilibrium setting we would expect that when prices are relatively high, supply will increase since higher cost producers of the commodity will enter the market putting a downward pressure on prices. Conversely, when prices are relatively low, supply will decrease since some of

The stochastic behavior of commodity prices: Implications for valuation and hedging

Size, Value, and Momentum in International Stock Returns §

We propose a new and direct measure of investor attention using search frequency in Google (Search Volume Index (SVI)). In a sample of Russell 3000 stocks from 2004 to 2008, we find that SVI (1) is correlated with but different from existing proxies of investor attention; (2) captures investor attention in a more timely fashion and (3) likely measures the attention of retail investors. An increase in SVI predicts higher stock prices in the next 2 weeks and an eventual price reversal within the year. It also contributes to the large first-day return and long-run underperformance of IPO stocks.

In Search of Attention

Financial press reports claim that Internet stock message boards can move markets We study the effect of more than 15 million messages posted on Yahoo! Finance and Raging Bull about the 45 companies in the Dow Jones Industrial Average and the Dow Jones Internet Index Bullishness is measured using computational linguistics methods Wall Street Journal news stories are used as controls We find that stock messages help predict market volatility Their effect on stock returns is statistically significant but economically small Consistent with Harris and Raviv (1993), disagreement among the posted messages is associated with increased trading volume MANY PEOPLE ARE DEVOTING a considerable amount of time and effort creating and reading the messages posted on Internet stock message boards News stories report that the message boards are having a significant impact on financial markets The Securities and Exchange Commission has prosecuted people for Internet messages All this attention to Internet stock messages caused us to wonder whether these messages actually contain financially relevant information 1 We consider three specific issues Does the number of messages posted or the bullishness of these messages help to predict returns? Is disagreement among the messages associated with more trades? Does the level of message posting or the bullishness of the messages help to predict volatility? The first issue is, does the level of message activity or the bullishness of the messages successfully predict subsequent stock returns? This is the natural starting place because a very high proportion of the messages contain explicit assertions that the particular stock is either a good buy or a bad buy Of course, there are a great many previous empirical studies showing how hard it is to predict stock returns by enough to cover transactions costs We find that there is evidence of a small degree of negative predictability even after controlling for bid‐ask bounce When many messages are posted on a given day, there ∗ Both authors are at the Sauder School of Business, University of British Columbia We would

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Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards

Time-varying risk premia and forecastable returns in futures markets

Trade execution costs remain larger on Nasdaq as compared to the NYSE in the wake of new SEC-mandated order-handling rules and reductions in tick sizes, but the differential across markets is smaller than in earlier years. Cross-sectional regression analysis indicates that the differences in average trade execution costs are not explained by variation in observable economic factors. Quotations on both markets continue to cluster disproportionately on round fractions, and more so on Nasdaq than the NYSE, but quotation rounding appears not to be responsible or the greater Nasdaq execution costs. Preferencing agreements are highlighted as a likely reason that Nasdaq trade execution costs remain larger.

Trade Execution Costs on Nasdaq and the NYSE: A Post-Reform Comparison

Trade execution costs remain larger on NASDAQ compared to the NYSE in the wake of new SEC-mandated order-handling rules and reductions in tick sizes, but the differential across markets is smaller than in earlier years. Cross-sectional regression analysis indicates that the differences in average trade execution costs are not explained by variation in observable economic factors. Quotations on both markets continue to cluster disproportionately on round fractions, and more so on NASDAQ than the NYSE, but quotation rounding appears not to be responsible for the greater NASDAQ execution costs. Preferencing agreements are highlighted as a likely reason that NASDAQ trade execution costs remain larger.

https://www.jstor.org/stable/pdfplus/2676265.pdf

Trade Execution Costs on NASDAQ and the NYSE: A Post-Reform Comparison

Microstructure noise in security prices biases the results of empirical asset pricing specifications, particularly when security-level explanatory variables are cross-sectionally correlated with the amount of noise. We focus on tests of whether measures of illiquidity, which are likely to be correlated with the noise, are priced in the cross-section of stock returns, and document a significant upward bias in estimated return premia for an array of illiquidity measures in CRSP monthly return data. The upward bias is larger when illiquid securities are included in the sample, but persists even for NYSE/AMEX stocks after decimalization. We introduce a methodological correction to eliminate the biases that simply involves WLS rather than OLS estimation, and find evidence of smaller, but still significant, return premia for illiquidity after implementing the correction.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1453008_code358061.pdf?abstractid=891615

Liquidity Biases in Asset Pricing Tests

For decades, corporate bonds primarily traded in an opaque environment. Quotations, which indicate prices at which dealers are willing to transact, were available only to market professionals, most often by telephone. Prices at which bond transactions were completed were not made public. The U.S. corporate bond market became much more transparent with the introduction of the Transaction Reporting and Compliance Engine (TRACE) in July 2002. Beginning that date, bond dealers were required to report all trades in publicly issued corporate bonds to the National Association of Security Dealers, which in turn made transaction data available to the public. In this paper, we describe trading protocols in the corporate bond market and assess the impact of the increase in transparency on the market. We review how TRACE has affected the costs that corporate bond investors paid to bond dealers for their transactions. We canvass the opinions of a variety of finance professionals and consider articles in the trade press to obtain a broader view of the impact of transparency on the corporate bond market.

https://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.22.2.217

Hendrik Bessembinder

Papers

Time-varying risk premia and forecastable returns in futures markets

Trade Execution Costs on Nasdaq and the NYSE: A Post-Reform Comparison

Trade Execution Costs on NASDAQ and the NYSE: A Post-Reform Comparison

Liquidity Biases in Asset Pricing Tests

Markets : Transparency and the Corporate Bond Market