How Much Do the Central Bank Announcements Matter on Financial Market? Application of the Rule-Based Trading System Approach

This paper proposes a rule-based trading system to investigate how much the central bank’s announcements matter on a financial market. We design a novel investment strategy and we simulate trades in order to quantify their profitability in the out–of–sample period using the data from a broad financial market in Poland spanning across 3 segments: stock market, foreign exchange market and bonds market. Our results show that the individual transactions delivered profits in 72.7% cases. The overall profitability across all events and all trading horizons was positive in as many as 63.6% cases. Although the financial market in Poland was only moderately sensitive to the NBP central bank’s communication, the identified types of the monetary policy announcements are economically significant and very useful for the investors, who can trade based on them and exploit them directly in the design of the rule-based trading strategies

IQ Classification via Brainwave Features: Review on Artificial Intelligence Techniques

Intelligence study is one of keystone to distinguish individual differences in cognitive psychology. Conventional psychometric tests are limited in terms of assessment time, and existence of biasness issues. Apart from that, there is still lack in knowledge to classify IQ based on EEG signals and intelligent signal processing (ISP) technique. ISP purpose is to extract as much information as possible from signal and noise data using learning and/or other smart techniques. Therefore, as a first attempt in classifying IQ feature via scientific approach, it is important to identify a relevant technique with prominent paradigm that is suitable for this area of application. Thus, this article reviews several ISP approaches to provide consolidated source of information. This in particular focuses on prominent paradigm that suitable for pattern classification in biomedical area. The review leads to selection of ANN since it has been widely implemented for pattern classification in biomedical engineering

Design and Applications of an Intelligent Financial Reporting and Auditing Agent with Net Knowledge (FRAANK)

This paper discusses the use of intelligent Internet agents as essential tools for automating financial analysis functions in the virtual world. Several important characteristic features of intelligent agents are discussed, including autonomy, communication ability, collaboration, and mobility. This paper focuses on developing a new intelligent agent called FRAANK – Financial Reporting and Auditing Agent with Net Knowledge. The prototype of FRAANK described in this paper provides intelligent access to, and processing and integration of rapidly changing financial information available from various sources on the Internet. FRAANK is an example of an agent that provides a value-added service that can be used for extracting data from natural text financial statements and converting them into XBRL-tagged statements, can potentially be utilized in an auditing practice, or used by investors and creditors in making their decisions

Auditing Symposium XII: Proceedings of the 1994 Deloitte & Touche/University of Kansas Symposium on Auditing Problems

Discussant\u27s response to The Acme Financial Statement Insurance Company Inc: A case study / Dan A. Simunic; Behavioral-economics approach to auditors\u27 risk assessments / William S. Waller; Discussant\u27s response to A Behavioral-economics approach to auditors\u27 risk assessments / Peter R. Gillett; Auditing for fraud: Perception vs reality / Alan J. Winters, John B. Sullivan; What we can learn from Yogi Berra: Discussant\u27s response to Auditing for fraud: Perception vs reality / Karen V. Pincus; What\u27s really wrong with the accounting profession? / A. A. Sommer; Client acceptance and continuation decisions / Stephen Asare, Karl Hackenbrack, W. Robert Knechel; Discussant\u27s response to Accounting and auditing history: Major developments in England and the United States from ancient roots through the mid-twentieth century / G. William Graham ; Exploratory analysis of the determinants of audit engagement resource allocations / Timothy B. Bell, W. Robert Knechel, John J. Willingham; Discussant\u27s response to An Exploratory analysis of the determinants of audit engagement resource allocations / Jane F. Mutchler; Investigation of adaptability in evidential planning / Janice D. DiPietro, Theodore J. Mock, Arnold Wright; Accounting and auditing history: Major developments in England and the United States from ancient roots through the mid-twentieth century / Howard Stettler; Discussant\u27s response to An Investigation of adaptability in evidential planning / Norman R. Walker; Acme Financial Statement Insurance Company Inc: A case study / Stephen J. Aldersleyhttps://egrove.olemiss.edu/dl_proceedings/1011/thumbnail.jp

Quantum Monte Carlo simulations for estimating FOREX markets: A speculative attacks experience

The foreign exchange markets, renowned as the largest financial markets globally, also stand out as one of the most intricate due to their substantial volatility, nonlinearity, and irregular nature. Owing to these challenging attributes, various research endeavors have been undertaken to effectively forecast future currency prices in foreign exchange with precision. The studies performed have built models utilizing statistical methods, being the Monte Carlo algorithm the most popular. In this study, we propose to apply Auxiliary-Field Quantum Monte Carlo to increase the precision of the FOREX markets models from different sample sizes to test simulations in different stress contexts. Our findings reveal that the implementation of Auxiliary-Field Quantum Monte Carlo significantly enhances the accuracy of these models, as evidenced by the minimal error and consistent estimations achieved in the FOREX market. This research holds valuable implications for both the general public and financial institutions, empowering them to effectively anticipate significant volatility in exchange rate trends and the associated risks. These insights provide crucial guidance for future decision-making processes

A Defect-Based Approach for Detailed Condition Assessment of Concrete Bridges

Bridge condition assessment is one of the most essential elements of Bridge Management Systems (BMS). This is owing to the fact that available inputs from assessment reports are constantly interpreted for maintenance decisions and budget allocation to critical bridges within a region’s inventory. Thus, performing effective bridge assessment is vital to ensure safety and sustainability of the bridge infrastructure. In practice, the evaluation of concrete bridges is mostly conducted on the basis of visual inspection, which is associated with considerable subjectivity and uncertainty inherent in human judgments. Additionally, current bridge assessment practices were found to be oversimplified, with conclusions being often drawn in absence of in-depth review and consideration of critical factors. To remediate the existing shortcomings and ameliorate the bridge assessment process, this study proposes a fuzzy Hierarchical Evidential Reasoning (HER) approach for detailed condition assessment of concrete bridges under uncertainty. The essence of the suggested framework addresses the treatment and aggregation of uncertain measurements of detected bridge defects, in a systematic manner, to establish an enhanced platform for reliable and detailed bridge assessment. The significant features of this methodology can be summarized in the following points. First, the proposed approach utilizes a generic hierarchy that models the several levels of a concrete bridge under assessment; namely: bridge components, elements, and measured defects. Second, the proposed model is set to account for relative importance weights of all assessment factors in the hierarchical breakdown. Third, a novel HER assessment belief structure is employed to grip probabilistic uncertainty (ignorance) in bridge evaluation, whereas fuzzy uncertainty (subjectivity) is processed through a set of collectively exhaustive fuzzy linguistic variables. Forth, Dempster-Shafer (D-S) theory is eventually applied under the proposed HER framework for the purpose of accumulating supporting pieces of evidence in a comprehensive manner. The suggested model is implemented to arrive at detailed and informative bridge element condition ratings through data acquired from two case study bridges in Canada. As it benefits from a data oriented and structured algorithm, the developed defect-based model is believed to introduce a great deal of objectivity in an otherwise subjective area of infrastructure assessment. This falls within the ultimate goal of enhancing overall public safety and well-being