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Trading Opportunities (trading + opportunity)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	50%

Selected Abstracts

Empowering Automated Trading in Multi-Agent Environments

COMPUTATIONAL INTELLIGENCE, Issue 4 2004
David W. Ash
Trading in the financial markets often requires that information be available in real time to be effectively processed. Furthermore, complete information is not always available about the reliability of data, or its timeliness,nevertheless, a decision must still be made about whether to trade or not. We propose a mechanism whereby different data sources are monitored, using Semantic Web facilities, by different agents, which communicate among each other to determine the presence of good trading opportunities. When a trading opportunity presents itself, the human traders are notified to determine whether or not to execute the trade. The Semantic Web, Web Services, and URML technologies are used to enable this mechanism. The human traders are notified of the trade at the optimal time so as not to either waste their resources or lose a good trading opportunity. We also have designed a rudimentary prototype system for simulating the interaction between the intelligent agents and the human beings, and show some results through experiments on this simulation for trading of the Chicago Board Options Exchange (CBOE) options. [source]

Identifying and Attracting the "right" Investors: Evidence on the Behavior of Institutional Investors

JOURNAL OF APPLIED CORPORATE FINANCE, Issue 4 2004
Brian Bushee
This article summarizes the findings of research the author has conducted over the past seven years that aims to answer a number of questions about institutional investors: Are there significant differences among institutional investors in time horizon and other trading practices that would enable such investors to be classified into types on the basis of their observable behavior? Assuming the answer to the first is yes, do corporate managers respond differently to the pressures created by different types of investors, and, by implication, are certain kinds of investors more desirable from corporate management's point of view? What kinds of companies tend to attract each type of investor, and how does a company's disclosure policy affect that process? The author's approach identifies three categories of institutional investors: (1) "transient" institutions, which exhibit high portfolio turnover and own small stakes in portfolio companies; (2) "dedicated" holders, which provide stable ownership and take large positions in individual firms; and (3) "quasi-indexers," which also trade infrequently but own small stakes (similar to an index strategy). As might be expected, the disproportionate presence of transient institutions in a company's investor base appears to intensify pressure for short-term performance while also resulting in excess volatility in the stock price. Also not surprising, transient investors are attracted to companies with investor relations activities geared toward forward-looking information and "news events," like management earnings forecasts, that constitute trading opportunities for such investors. By contrast, quasi-indexers and dedicated institutions are largely insensitive to shortterm performance and their presence is associated with lower stock price volatility. The research also suggests that companies that focus their disclosure activities on historical information as opposed to earnings forecasts tend to attract quasi-indexers instead of transient investors. In sum, the author's research suggests that changes in disclosure practices have the potential to shift the composition of a firm's investor base away from transient investors and toward more patient capital. By removing some of the external pressures for short-term performance, such a shift could encourage managers to establish a culture based on long-run value maximization. [source]

Presidential Address: Asset Price Dynamics with Slow-Moving Capital

THE JOURNAL OF FINANCE, Issue 4 2010
DARRELL DUFFIE
ABSTRACT I describe asset price dynamics caused by the slow movement of investment capital to trading opportunities. The pattern of price responses to supply or demand shocks typically involves a sharp reaction to the shock and a subsequent and more extended reversal. The amplitude of the immediate price impact and the pattern of the subsequent recovery can reflect institutional impediments to immediate trade, such as search costs for trading counterparties or time to raise capital by intermediaries. I discuss special impediments to capital formation during the recent financial crisis that caused asset price distortions, which subsided afterward. After presenting examples of price reactions to supply shocks in normal market settings, I offer a simple illustrative model of price dynamics associated with slow-moving capital due to the presence of inattentive investors. [source]

NETWORK EXTERNALITIES AND COMPARATIVE ADVANTAGE

BULLETIN OF ECONOMIC RESEARCH, Issue 4 2007
Toru Kikuchi
D43; F12; L13 ABSTRACT In this article, I examine how the network externalities of communications activities and trading opportunities interact to determine the structure of comparative advantage. These interactions are examined by constructing a two-country, three-sector model of trade involving a country-specific communications network sector. The role of the connectivity of network providers, which allows users of a network to communicate with users of another network, is also explored. [source]