Surprises in scheduled releases: why do they move the bond market?

It is well known that information arrival has an impact on prices volatility, and trading volume in financial markets (see e.g., Goodhart and O?Hara 1997). Scheduled macroeconomic announcements, such as monthly employment figures, consumer prices, or building permits, stand out from the steady flow of information.1 Several studies (e.g. Fleming and Remolona 1997) show that these releases have a very distinct impact on prices. While most of these studies try to find out which releases are significant, considerably less effort has been devoted to the question what makes some releases so important in contrast to others that seem to attract no attention. Papers addressing this question emphasize the content of releases. For example, Edison (1996) discriminates between news related to unexpected inflation and those related to unexpected changes in economic activity. Investigating intraday T-bond futures price responses to surprises in scheduled macroeconomic releases, this paper presents evidence that the type of information is relevant. More specifically, the results suggest that the sequence of releases within a given content category helps to explain their relative importance. In other words, if market participants have already observed some figures on which they can base their assessment of a particular aspect of the economy, then the additional information of another related report should be small, and thus, its impact on prices. --Macroeconomic news,scheduled announcements,public information,price formation,Treasury bonds,futures market

The processing of non-anticipated information in financial markets: Analyzing the impact of surprises in the employment report

This paper delineates the simultaneous impact of non-anticipated information on mean and variance of the intraday return process by including appropriate variables accounting for the news flow into both the mean and the variance function. This allows us to differentiate between the consistent price reaction to surprising news and the traders’ uncertainty about the precise price impact of this information. Focussing on the US employment report, we find that headline information is almost instantaneously incorporated into T-bond futures prices. Nevertheless, large surprises, and ’bad’ news in particular, create considerable uncertainty. In contrast, if surprises in related headlines cross-validate each other, less room for differences of opinion is left, and hence volatility is decreased.high-frequency data, information processing, macroeconomic announcements, Treasury bond futures, trading process, volatility

Irrationality or efficiency of macroeconomic survey forecasts? Implications from the anchoring bias test

We analyze the quality of macroeconomic survey forecasts. Recent findings indicate that they are anchoring biased. This irrationality would challenge the results of a wide range of empirical studies, e.g., in asset pricing, volatility clustering or market liquidity, which rely on survey data to capture market participants' expectations. We contribute to the existing literature in two ways. First, we show that the cognitive bias is a statistical artifact. Despite highly significant anchoring coefficients a bias adjustment does not improve forecasts' quality. To explain this counterintuitive result we take a closer look at macroeconomic analysts' information processing abilities. We find that analysts benefit from the use of an extensive information set, neglected in the anchoring bias test. Exactly this information advantage drives the misleading anchoring bias test results. Second, we find that the superior information aggregation capabilities enable analysts to easily outperform sophisticated timeseries forecasts and therefore survey forecasts should clearly be favored. --macroeconomic announcements,efficiency of forecasts,anchoring bias,rationality of analysts

Do companies exploit accounting rules for broad stock opion plans?

Several studies indicate that stock option plans are becoming more and more a substantial part of compensation schemes in U.S. companies. This paper argues that for an employer the attractiveness of stock options arises from the U.S. Generally Accepted Accounting Principles (US-GAAP) which require no charge to earnings for specifically designed stock option plans if a company opts for footnote disclosure. This poses a substantial problem for security analysis since a firm's earnings may be considerably upward biased. Based on a case study of 20 companies out of the S&P 500 which rely heavily on employee stock options we arrive at the conclusion that the amount of hidden compensation cost can be significant. For some of the companies the misrepresentation of stated earnings exceeds usual immateriality limits by far. Therefore, we propose that the fair value method of Statement No. 123 Financial Accounting Standards Board should be made compulsory in order to restore the true and fair view which "income as stated" should provide.

Bayesian Learning in Financial Markets: Testing for the Relevance of Information Precision in Price Discovery

An important claim of Bayesian learning and a standard assumption in price discovery models is that the strength of the price impact of unanticipated information depends on the precision of the news. In this paper, we test for this assumption by analyzing intra-day price responses of CBOT T-bond futures to U.S. employment announcements. By employing additional detail information besides the widely used headline figures, we extract release-specific precision measures which allow to test for the claim of Bayesian updating. We find that the price impact of more precise information is significantly stronger. The results remain stable even after controlling for an asymmetric price response to 'good' and 'bad' news.Bayesian learning; information precision; macroeconomic announcements; asymmetric price response; ¯nancial markets; high-frequency data

Optimal leverage, its benefits, and the business cycle

We study the effect of the business cycle on optimal capital structure choice and the benefit to leverage. We propose a regime switching model with a state-dependent cash flow process to capture macroeconomic risk in a firm's cash flow. Our model is parsimonious but still realistic and allows for a wide range of analysis. We find pro-cyclical optimal leverage ratios, benefits to leverage, and costs of operating at a non-optimal leverage. If macroeconomic risk decreases, i.e. earnings become more stable and growth rates less volatile, optimal leverage and its benefits increase due to lower default risk. The regime switching property of EBIT traces observed EBIT paths closely and is applicable to a wide range of corporate valuation models. Our model offers novel empirically testable implications, such as higher tax benefits after the change in macroeconomic risk since the late 1980s and common capital structure adjustments in recessions and around turning points. --capital structure,macroeconomic risk,regime switching,benefit to leverage

A mean variance king? Creation and resolution of uncertainty under the employment report's reign

This paper delineates the simultaneous impact of non-anticipated information on first and second moments of the intraday price process by including appropriate variables accounting for the news flow into both the mean and the variance function. This allows us to differentiate between the consistent price reaction to surprising news and traders? uncertainty about the precise price impact of this information. Analyzing the US employment report, we find that headline information is almost instantaneously incorporated into T-bond futures prices. Nevertheless, large surprises create considerable uncertainty, in particular ?bad? news. In contrast, if surprises in related headlines cross-validate each other, less room for differences of opinion is left, and hence volatility is decreased. --Information processing,trading process,volatility,macroeconomic announcements,Treasury bond futures,high-frequency data

Accounting for stock-based compensation: an extended clean surplus relation

Residual income valuation is based on the assumption that the clean surplus relation holds. As pointed out by Ohlson (2000), among others, the standard clean surplus relation is frequently violated. Moreover, standard residual income valuation models rest on the implicit assumption that future stated earnings belong to current shareholders only. This is clearly invalid for companies granting employee options. In order to overcome these deficiencies, this paper establishes an extension of the clean surplus relation and derives simple analytical solutions for the value of outstanding stocks in terms of already known accounting information. --Residual income valuation,clean surplus accounting,US-GAAP,employee stock option programs

New economy accounting : why are broad-based stock option plans so attractive?

Several studies indicate that stock option plans are becoming more and more a substantial part of compensation schemes in U.S. companies. This paper shows the tax implications and accounting rules for stock option plans. By comparison of the tax and accounting rules for different compensation schemes we show that the popularity of stock options may be mainly due to the U.S. Generally Accepted Accounting Principles (US-GAAP) which require no charge to earnings for speciffically designed stock option plans if a company opts for footnote disclosure. Thus, for these companies the stated earnings are higher than their economical situations justify. Based on a case study of 20 companies out of the S&P 500 which rely heavily on employee stock options we arrive at the conclusion that the amount of hidden compensation cost can reach economically signifficant amounts. Since this topic seems to be widely neglected it is questionable whether stock prices reflect these hidden cost. --Accounting,US-GAAP,stock option programs

Price adjustment to news with uncertain precision

Bayesian learning provides the core concept of processing noisy information. In standard Bayesian frameworks, assessing the price impact of information requires perfect knowledge of news’ precision. In practice, however, precision is rarely dis- closed. Therefore, we extend standard Bayesian learning, suggesting traders infer news’ precision from magnitudes of surprises and from external sources. We show that interactions of the different precision signals may result in highly nonlinear price responses. Empirical tests based on intra-day T-bond futures price reactions to employment releases confirm the model’s predictions and show that the effects are statistically and economically significant