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Über dieses Buch

This book constitutes the proceedings of the 6th International Workshop on Enterprise Applications and Services in the Finance Industry, FinanceCom 2012, held in Barcelona, Spain, on June 10, 2012.

The workshop spans multiple disciplines, including technical, service, economic, sociological, and behavioral sciences. It reflects on technologically enabled opportunities, implications, and changes due to the introduction of new business models or regulations related to the financial services industry and the financial markets.

The seven papers presented were carefully reviewed and selected from numerous submissions. The topics covered are: news and text analysis; algorithmic and high-frequency trading; and the role and impact of technology.

Inhaltsverzeichnis

Frontmatter

News and Text Analysis

Frontmatter

Investigating the Impact of Media Sentiment and Investor Attention on Financial Markets

Abstract
Media sentiment has been shown to be related to stock returns. However, one prerequisite for this influence has not been taken into account yet: the question of whether investors actually pay attention to news and the related financial instruments. Within this study, we close this research gap by examining the interplay between media sentiment and investor attention. Thereby, we find that the positive impact of media sentiment on returns is increased when investor attention is high. Furthermore, we evaluate whether these variables can be used to forecast future market movements. Although our results reveal that the obtained forecasting accuracy cannot be achieved by chance, we conclude that further information has to be included in the forecasting model to obtain satisfying results.
Michael Siering

Towards Automated Event Studies Using High Frequency News and Trading Data

Abstract
Event studies have a long history in academic research and were used in disciplines as diverse as economics, law, information technology, marketing, and finance. One of the main challenges is that the process of undertaking such an event study is complex and many assumptions, trade-offs and design decisions need to be made. Based on Service-Oriented Computing principles, this paper proposes a business process on how to undertake and partly automate complex event studies on effects of (un)scheduled news on stocks prices using high frequency trading and news data. The proposed business process is illustrated using a case study that shows how to identify effects of unscheduled news on stock prices in the German DAX30 index.
Nicolai Bohn, Fethi A. Rabhi, Dennis Kundisch, Lawrence Yao, Tobias Mutter

The Role of Misbehavior in Efficient Financial Markets: Implications for Financial Decision Support

Abstract
The analysis of different data sources to support financial decision making has been a subject of research for several decades. While early approaches mostly focus on structured data, recent studies also take into account unstructured data. In this paper, we build upon these two research streams and explore potential benefits that can be achieved by combining both approaches. Therefore, we present an approach that integrates both data types. From a theoretical perspective, our research angle is based on two fundamental theories in Finance: while the Efficient Market Hypothesis states that capital markets are information efficient, Behavioral Finance theory stresses that market efficiency may be limited, e.g. due to irrational behavior of market participants or market barriers. While the two theories provide arguments for and against the functioning of our approach, we can illustrate its superiority compared to other approaches. The implications are discussed from a methodological and theoretical perspective.
Michael Siering, Jan Muntermann

Algorithmic and High Frequency Trading

Frontmatter

Humans vs. Algorithms – Who Follows Newcomb-Benford’s Law Better with Their Order Volume?

Abstract
Newcomb-Benford’s Law (NBL) is a well known regularity in the distribution of first significant digits (FSD) and therefore research in this field is manifold. As of 2012 research in the domain of financial markets is quite scarce, especially in the field of algorithmic trading. We pose the question whether order submission volumes of algorithmic traders and human traders follow NBL. Results in this context might help regulators to detect suspicious market activity and market participants to quantify the amount of algorithmic trading. Our findings indicate that the submitted order volumes of both groups follow NBL more than the uniform distribution. Comparing these two groups, we give a proof that algorithmic traders match NBL better than human traders, as human traders tend to overuse the FSD five.
Martin Haferkorn

The Effect of Single-Stock Circuit Breakers on the Quality of Fragmented Markets

Abstract
Since the May 6th, 2010 flash crash in the U.S., appropriate measures ensuring safe, fair and reliable markets become more relevant from the perspective of investors and regulators. Circuit breakers in various forms are already implemented for individual markets to ensure price continuity and prevent potential market failure and crash scenarios. However, coordinated inter-market safeguards have hardly been adopted, but are considered essential in a fragmented environment to prevent situations, where main markets halt trading but stock prices continue to decline as traders migrate to satellite markets. The objective of this paper is to empirically study the impact of circuit breakers in a single-market and inter-market setup. We find a decline in market volatility after the trading halt in the home and satellite market which come at the cost of higher spreads. Moreover, the satellite market’s quality and price discovery during CBs is weakened and only recovers as the other market restarts trading.
Peter Gomber, Martin Haferkorn, Marco Lutat, Kai Zimmermann

Technology Role and Impact

Frontmatter

A Case Study in Using ADAGE for Compute-Intensive Financial Analysis Processes

Abstract
The Ad hoc DAta Grid Environment (ADAGE) has been proposed as a framework to support analysis processes for large repositories of ad hoc data. Its use of a service-oriented architecture (SOA) brings the promise of flexibility, as well as enabling domain experts to define their own analysis processes at a high level of abstraction. However, these claims have not been verified empirically and the performance penalty of using additional abstract software layers has not been assessed on complex problems. This chapter describes a case study involving a realistic analysis process conducted by an expert user. It assesses the benefits and drawbacks of using the ADAGE approach versus conventional manual analysis processes. This chapter also outlines some avenues for future research to address existing limitations.
Lawrence Yao, Fethi A. Rabhi, Maurice Peat

XBRL: Impacts, Issues and Future Research Directions

Abstract
Only 13 years ago in April 1998 Charles Hoffman, a CPA investigated how XML could be used for the reporting of business and financial information. By now many researchers are dealing with this topic. The high (practical) relevance of XBRL is emphasized by several laws and a large number of regulatory requirements stipulating the use of XBRL for business and financial reporting. Giving an overview of conducted research is complicated due to the rich diversity of XBRL. On top, traditional literature reviews are focusing on the performed research, not including any indication of the relevance of the investigated topic. We will go one step further and include discussed impacts and issues weighted by their occurrence in literature. Based on this approach the paper concludes that frequently mentioned impacts and issues of XBRL are not yet researched but in turn minor research questions are well investigated.
Niels Müller-Wickop, Martin Schultz, Markus Nüttgens

Backmatter

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