Mood in foreign exchange trading: Cognitive processes and performance☆☆☆

Dynamic capabilities and firm performance

Despite the different nature of financial engineering and electrical engineering, both areas are intimately connected on a mathematical level. The foundations of financial engineering lie on the statistical analysis of numerical time series and the modeling of the behavior of the financial markets in order to perform predictions and systematically optimize investment strategies. Similarly, the foundations of electrical engineering, for instance, wireless communication systems, lie on statistical signal processing and the modeling of communication channels in order to perform predictions and systematically optimize transmission strategies. Both foundations are the same in disguise. It is often the case in science that the same or very similar methodologies are developed and applied independently in different areas. A Signal Processing Perspective of Financial Engineering is about investment in financial assets treated as a signal processing and optimization problem. It explores such connections and capitalizes on the existing mathematical tools developed in wireless communications and signal processing to solve real-life problems arising in the financial markets in an unprecedented way. A Signal Processing Perspective of Financial Engineering provides straightforward and systematic access to financial engineering for researchers in signal processing and communications so that they can understand problems in financial engineering more easily and may even apply signal processing techniques to handle some financial problems.

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A Signal Processing Perspective on Financial Engineering

This study proposes a technique based upon Fuzzy C-Means (FCM) classification theory and related fuzzy theories for choosing an appropriate value of the Variable Precision Rough Set (VPRS) threshold parameter (@b) when applied to the classification of continuous information systems. The VPRS model is then combined with a moving Average Autoregressive Exogenous (ARX) prediction model and Grey Systems theory to create an automatic stock market forecasting and portfolio selection mechanism. In the proposed mechanism, financial data are collected automatically every quarter and are input to an ARX prediction model to forecast the future trends of the collected data over the next quarter or half-year period. The forecast data are then reduced using a GM(1,N) model, classified using a FCM clustering algorithm, and then supplied to a VPRS classification module which selects appropriate investment stocks in accordance with a pre-determined set of decision-making rules. Finally, a grey relational analysis technique is employed to weight the selected stocks in such a way as to maximize the rate of return of the stock portfolio. The validity of the proposed approach is demonstrated using electronic stock data extracted from the financial database maintained by the Taiwan Economic Journal (TEJ). The portfolio results obtained using the proposed hybrid model are compared with those obtained using a Rough Set (RS) selection model. The effects of the number of attributes of the RS lower approximation set and VPRS @b-lower approximation set on the classification are systematically examined and compared. Overall, the results show that the proposed stock forecasting and stock selection mechanism not only yields a greater number of selected stocks in the @b-lower approximation set than in the RS approximation set, but also yields a greater rate of return.

Application of VPRS model with enhanced threshold parameter selection mechanism to automatic stock market forecasting and portfolio selection

The growth of individuals investing in the stock of publicly traded companies in the late 1990s coincided with the development of new media outlets for equivocal financial data. Discussion board participants enact an assortment of messages, experience a number of texts simultaneously and therefore are always immersed within a multiplicity of discourses. One such cyberspace was examined to investigate participants’ sensemaking related to their financial holdings. Through the use of Weick’s double interact, discussion board participants make sense of and organize equivocal messages. For business communication practitioners, these sensemaking processes call for the creation of dialogic texts that engage readers on multiple levels. Limitations and future possibilities for research are surveyed.

Stockholders in Cyberspace: Weick’s Sensemaking Online

Five-Sigma Event The Two Wise Men Mr.Market and the Lemmings Buying a Business Permanent Holdings Fixed-Income Marketable Securities Equity Marketable Securities A Few More Good Stocks An Unreasonable Man Appendix Notes Index.

Robert G Hagstrom

Papers

The Warren Buffett Way - Investment Strategies of the World's Greatest Investor Mass Market