Information Processing In Financial Markets
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| Author | : Jan-Philipp Matthewes |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 185 |
| Release | : 2015-01-28 |
| Genre | : Law |
| ISBN | : 3945021073 |
Financial analysts play an ambivalent role on financial markets: On the one hand investors and the media frequently follow their advice, on the other hand they are regularly discredited when their forecasts or recommendations prove to be erroneous. This cumulative thesis explores the informational content of financial analysts’ forecasts for investors by addressing three specific topics: Consensus size as a rudimentary investment signal, the association of analysts’ target prices with business sentiment, and the consistency of analysts’ different investment signals in the context of the 2008 financial crisis. Overall, the thesis provides additional evidence that investors can profit from analysts’ forecasts and recommendations. However, it is also shown that investors need to be very selective about which signal to rely on and in which context to use these because analysts’ investment signals can also be heavily biased and erroneous. About the author: Jan-Philipp Matthewes studied ‘Economics’ at the University of Cologne, Germany, and holds a Dean’s Award from the Faculty of Economics and Social Sciences. His research focus on financial analysts evolved while working in equity research at a leading German bank. The PhD-thesis was supervised by Prof. Dr. Martin Wallmeier, Finance and Accounting, at the University of Fribourg, Switzerland. Since 2013 Jan-Philipp Matthewes is the managing director of the boutique private equity firm ‘Matthewes Capital Invest GmbH’.
| Author | : M. Costantino |
| Publisher | : WIT Press |
| Total Pages | : 193 |
| Release | : 2008 |
| Genre | : Business & Economics |
| ISBN | : 1845641469 |
Professional financial traders are currently overwhelmed with news and extracting relevant information is a long and hard task, whilst trading decisions require immediate actions. Primarily intended for financial organizations and business analysts, this book provides an introduction to the algorithmic solutions to automatically extract the desired information from Internet news and obtain it in a well structured form. It places emphasis on the principles of the method rather than its numerical implementation, omitting the mathematical details that might otherwise obscure the text, and focuses on the advantages and on the problems of each method. The authors also include many practical examples with complete references and algorithms for similar problems, which may be useful in the financial field, and basic techniques applied in other information extraction fields which may be imported into the financial news analysis.
| Author | : Emilio Barucci |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 473 |
| Release | : 2012-12-06 |
| Genre | : Business & Economics |
| ISBN | : 1447100891 |
A presentation of classical asset pricing theory, this textbook is the only one to address the economic foundations of financial markets theory from a mathematically rigorous standpoint and to offer a self-contained critical discussion based on empirical results. Tools for understanding the economic analysis are provided, and mathematical models are presented in discrete time/finite state space for simplicity. Examples and exercises included.
| Author | : Ahmed Riahi-Belkaoui |
| Publisher | : Praeger |
| Total Pages | : 326 |
| Release | : 1989-06-23 |
| Genre | : Business & Economics |
| ISBN | : |
Ahmed Belkaoui focuses on the contributions human information processing research can make in the study of accounting decision-making. Both a review and synthesis of the current literature and a springboard for further research, Human Information Processing in Accounting explores the basic psychological concepts underlying human decision-making and their applications to accounting. As Belkaoui notes at the outset, accounting information is used primarily for decision-making. Human information processing in accounting is designed to understand, describe, evaluate, and--most importantly--improve the decision process used in an accounting or auditing context. Belkaoui's book provides accounting students and practitioners with the first comprehensive overview of the ways in which human information processing research has been used to study and enhance accounting decision-making. Divided into six parts, the volume begins by examining the policy-capturing process and the Brunswick Lens model used in this type of research. Subsequent chapters address the models of risky choice used to predict or describe how individuals make these types of choices, the application of probability elicitation and revision to accounting research and practice, the heuristics and biases individuals use to reduce complex cognitive processes to simpler judgmental operations, and the application of cognitive science to accounting. A number of chapters include appendices illustrating the type of accounting studies that exist for each of the human information processing paradigms presented. Taken as a whole, Belkaoui's work represents a pioneering attempt to focus and organize the field of human information processing in accounting.
| Author | : Ali N. Akansu |
| Publisher | : John Wiley & Sons |
| Total Pages | : 312 |
| Release | : 2016-04-21 |
| Genre | : Technology & Engineering |
| ISBN | : 1118745639 |
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.
| Author | : William Bernhard |
| Publisher | : Cambridge University Press |
| Total Pages | : 237 |
| Release | : 2006-07-24 |
| Genre | : Political Science |
| ISBN | : 1107320992 |
The authors examine the conditions under which democratic events, including elections, cabinet formations, and government dissolutions, affect asset markets. Where these events have less predictable outcomes, market returns are depressed and volatility increases. In contrast, where market actors can forecast the result, returns do not exhibit any unusual behavior. Further, political expectations condition how markets respond to the political process. When news causes market actors to update their political beliefs, market actors reallocate their portfolios, and overall market behavior changes. To measure political information, Professors Bernhard and Leblang employ sophisticated models of the political process. They draw on a variety of models of market behavior, including the efficient markets hypothesis, capital asset pricing model, and arbitrage pricing theory, to trace the impact of political events on currency, stock, and bond markets. The analysis will appeal to academics, graduate students, and advanced undergraduates across political science, economics, and finance.
| Author | : Reinhold Decker |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 494 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3642572804 |
This volume contains revised versions of selected papers presented dur ing the 23rd Annual Conference of the German Classification Society GfKl (Gesellschaft fiir Klassifikation). The conference took place at the Univer sity of Bielefeld (Germany) in March 1999 under the title "Classification and Information Processing at the Turn of the Millennium". Researchers and practitioners - interested in data analysis, classification, and information processing in the broad sense, including computer science, multimedia, WWW, knowledge discovery, and data mining as well as spe cial application areas such as (in alphabetical order) biology, finance, genome analysis, marketing, medicine, public health, and text analysis - had the op portunity to discuss recent developments and to establish cross-disciplinary cooperation in their fields of interest. Additionally, software and book pre sentations as well as several tutorial courses were organized. The scientific program of the conference included 18 plenary or semi plenary lectures and more than 100 presentations in special sections. The peer-reviewed papers are presented in 5 chapters as follows: • Data Analysis and Classification • Computer Science, Computational Statistics, and Data Mining • Management Science, Marketing, and Finance • Biology, Genome Analysis, and Medicine • Text Analysis and Information Retrieval As an unambiguous assignment of results to single chapters is sometimes difficult papers are grouped in a way that the editors found appropriate.
| Author | : Andreas Storkenmaier |
| Publisher | : KIT Scientific Publishing |
| Total Pages | : 188 |
| Release | : 2014-08-22 |
| Genre | : Business & Economics |
| ISBN | : 3866446942 |
The last decades have seen dramatic changes in trading technology and the way that financial markets operate. As trading technology advances, news providers have kept pace and deliver news to market participants around the world within fractions of a second using electronic systems. Currently, most news is still interpreted by humans but news providers have started to offer newswire products with machine learning systems that specifically cater to algorithmic traders. In practice, newswire messagesmake up a major part of the public information set available to investors. This book studies how newswire messages impact modern electronic equity markets.
| Author | : Marie-Jeanne Lesot |
| Publisher | : Springer Nature |
| Total Pages | : 839 |
| Release | : 2020-06-05 |
| Genre | : Computers |
| ISBN | : 3030501531 |
This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.
| Author | : Mark Schindler |
| Publisher | : John Wiley & Sons |
| Total Pages | : 210 |
| Release | : 2007-04-04 |
| Genre | : Business & Economics |
| ISBN | : 9780470510339 |
On the trading floor, all action is based on news, therefore rumors in financial markets are an everyday phenomenon. Rumors are the oldest mass medium in the world and their nature is still difficult to grasp. Scientifically, not much is known about rumors, especially in the financial markets, where their consequences can have real money consequences. Rumors in Financial Markets provides a fresh insight to the topic, combining the theory of Behavioral Finance with that of Experimental Finance--a new and innovative scientific method which observes real decision makers in a controlled, clearly structured environment. Using the results from surveys and experiments, the author argues that rumors in the context of financial markets are built on three cornerstones: Finance, Psychology and Sociology. The book provides insights into how rumors evolve, spread and are traded on and provides explanations as to why volatility rockets, strong price movements, herding behavior for example, occur for apparently no good reason.
