How to recognize opportunities: Heterarchical search in a Wall Street trading room

Our task in this paper is to analyze the organization of trading in the era of quantitative finance. To do so, we conduct an ethnography of arbitrage, the trading strategy that best exemplifies finance in the wake of the quantitative revolution. In contrast to value and momentum investing, we argue, arbitrage involves an art of association - the construction of equivalence (comparability) of properties across different assets. In place of essential or relationa l characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else - associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.Arbitrage, trading, heterarchy

Repurchasing Shares on a Second Trading Line

This paper studies a unique buyback method allowing firms to reacquire their own shares on a separate trading line where only the firm is allowed to buy shares. This temporary trading platform is opened concurrently with the original trading line on the stock exchange. This share repurchase method is called the Second Trading Line and has been extensively used by Swiss companies since 1997. This type of repurchase is unique for two reasons. First, unlike open market programs, the repurchasing company does not trade under the cover of anonymity. Second, all transactions made by the repurchasing firm are publicly available in real time to every market participant. This is a case of instantaneous disclosure which contrasts sharply with other markets characterized by delayed or no disclosure. Using actual repurchase data from all buybacks implemented through second trading lines, we find that managers exhibit timing ability for the majority of programs. We also document that the daily repurchase decision is statistically associated with short-term price changes. However, we reject the opportunistic repurchase hypothesis and find no evidence that managers exploit their information advantage when reacquiring shares. We also find that repurchases on the second trading line have a beneficial impact on the liquidity of repurchasing firms (i.e., higher trading volumes, smaller bid-ask spreads, and thicker total depths). Exchanges and regulators may consider the second trading line an attractive share reacquisition mechanism because of its transparency and positive liquidity effects.Share Repurchases;Disclosure Environment;Information Asymmetry;Liquidity

Why is order flow so persistent?

Order flow in equity markets is remarkably persistent in the sense that order signs (to buy or sell) are positively autocorrelated out to time lags of tens of thousands of orders, corresponding to many days. Two possible explanations are herding, corresponding to positive correlation in the behavior of different investors, or order splitting, corresponding to positive autocorrelation in the behavior of single investors. We investigate this using order flow data from the London Stock Exchange for which we have membership identifiers. By formulating models for herding and order splitting, as well as models for brokerage choice, we are able to overcome the distortion introduced by brokerage. On timescales of less than a few hours the persistence of order flow is overwhelmingly due to splitting rather than herding. We also study the properties of brokerage order flow and show that it is remarkably consistent both cross-sectionally and longitudinally.Comment: 42 pages, 15 figure

EURACE: A Massively Parallel Agent-Based Model of the European Economy

EURACE is a major European attempt to construct an agent-based model of the European economy with a very large population of autonomous, purposive agents interacting in a complicated economic environment. To create it, major advances are needed, in particular in terms of economic modeling and software engineering.In this paper, we describe the general structure of the economic model developed for EURACE and present the Flexible Large-scale Agent Modeling Environment (FLAME) that will be used to describe the agents and run the model on massively parallel supercomputers. Illustrative simulations with a simplifiedmodel based on EURACE's labour market module are presented.Agent-based Computational Economics; X-Machines; Parallelcomputation.

Bayesian forecasting and scalable multivariate volatility analysis using simultaneous graphical dynamic models

The recently introduced class of simultaneous graphical dynamic linear models (SGDLMs) defines an ability to scale on-line Bayesian analysis and forecasting to higher-dimensional time series. This paper advances the methodology of SGDLMs, developing and embedding a novel, adaptive method of simultaneous predictor selection in forward filtering for on-line learning and forecasting. The advances include developments in Bayesian computation for scalability, and a case study in exploring the resulting potential for improved short-term forecasting of large-scale volatility matrices. A case study concerns financial forecasting and portfolio optimization with a 400-dimensional series of daily stock prices. Analysis shows that the SGDLM forecasts volatilities and co-volatilities well, making it ideally suited to contributing to quantitative investment strategies to improve portfolio returns. We also identify performance metrics linked to the sequential Bayesian filtering analysis that turn out to define a leading indicator of increased financial market stresses, comparable to but leading the standard St. Louis Fed Financial Stress Index (STLFSI) measure. Parallel computation using GPU implementations substantially advance the ability to fit and use these models.Comment: 28 pages, 9 figures, 7 table

The intraindustry effects of going concern audit reports

This paper investigates the effect of a going concern opinion (GCO) on the equity value of the announcing firm’s competitors. On average, GCOs increase the value of a value-weighted portfolio of rivals by 0.37% at the event date. This positive effect is significantly larger when the announcing firm is relatively more profitable, the industry is more concentrated, and when rivals and event firms have distinct assets in place and growth opportunities. Additional tests reveal that such competitive effect is not a mere short-term phenomenon as investors can earn up to 1.54% on a risk-adjusted basis over the first postGCO month. This finding is especially interesting as we show that for the industry rivals the one-year and six-month preGCO riskadjusted equity returns are, on average, strongly negative. Our results highlight the impact of mandatory accounting information on market prices at both the firm and industry levels.Audit reports; Going concern; Competitive effect; Contagion effect.

History of Value-at-Risk: 1922-1998

value-at-risk history

APPLICATIONS: Financial risk and financial Risk Management Technology (RMT): Issues and advances

Methods for sound risk management are of increasing interest among Wall Street investment banking and brokerage firms in the aftermath of the October 1987 crash of the stock market. As the knowledge of advanced technology applications in risk management increases, financial firms are finding innovative ways to use them practically, in order to insulate themselves. The recent development in models, the software and hardware, and the market data to track risk are all considered advances in Risk Management Technology (RMT). -. These advances have affected all three stages of risk management: the identification, the measurement, and the formulation of strategies to control financial risk. This article discusses the advances made in five areas of RMT: communication software, object-oriented programming, parallel processing, neural nets and artificial intelligence. Systems based on any of these areas may be used to add value to the business of a firm. A business value linkage analysis shows how the utility of advanced systems can be measured to justify their costs.Information Systems Working Papers Serie