financial data mining


Economic globalization and evolution of information technology has in recent times accounted for huge volume of financial data being generated and accumulated at an unprecedented pace. Data mining techniques have been used to extract hidden patterns and predict future trends and behaviours in financial markets.

Discovering golden nuggets: data mining in financial application
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With the increase of economic globalization and evolution of information technology, financial data are being generated and accumulated at an unprecedented pace. As a result, there has been a critical need for automated approaches to effective and efficient utilization

Forecasting fraudulent financial statements using data mining
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This paper explores the effectiveness of machine learning techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. To this end, a number of experiments have been conducted using

Financial stock market forecast using data mining techniques
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The automated computer programs using data mining and predictive technologies do a fare amount of trades in the markets. Data mining is well founded on the theory that the historic data holds the essential memory for predicting the future direction. This technology is

The importance of simplicity and validation in genetic programming for data mining in financial data
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A genetic programming system for data mining trading rules out of past foreign exchange data is described. The system is tested on real data from the dollar/yen and dollar/DM markets, and shown to produce considerable excess returns in the dollar/yen market

Financial statement fraud detection by data mining
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-ABSTRACT- Financial losses due to financial statement frauds (FSF) are increasing day by day in the world. The industry recognizes the problem and is just now starting to act

Study of Data Mining Techniques used for Financial Data Analysis
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This paper describes about different data mining techniques used in financial data analysis. Financial data analysis is used in many financial institutes for accurate analysis of consumer data to find defaulter and valid customer. For this different data mining techniques can be

Data mining as a financial auditing tool
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In recent years, the volume and complexity of accounting transactions in major organizations have increased dramatically. To audit such organizations, auditors frequently must deal with voluminous data with rather complicated data structure. Consequently, auditors no longer

Financial data mining using genetic algorithms technique: Application to KOSPI 200
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This study intends to mine reasonable trading rules using genetic algorithms for Korea Stock Price Index 200 (KOSPI 200) futures. We have found trading rule which would have yielded the highest return over a certain time period using historical data . Simulated results of

Data mining for analysis of rare events: A case study in security, financial and medical applications
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We are drowning in the deluge of data that are being collected world-wide, while starving for knowledge at the same time Despite the enormous amount of data , particular events of interest are still quite rare Rare events are events that occur very infrequently, ie their

Detecting financial fraud using data mining techniques: a decade review from 2004 to 2015
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Objective: Financial fraud has been a big concern for many organizations across industries; billions of dollars are lost yearly because of this fraud. So businesses employ data mining techniques to address this continued and growing problem. This paper aims to review

Examples of the use of data mining in financial applications
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This article considers building mathematical models with financial data by using data mining techniques. In general, data mining methods such as neural networks and decision trees can be a useful addition to the techniques available to the financial analyst. However, the

Basic Principles of Financial Process Mining A Journey through Financial Data in Accounting Information Systems.
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Auditors and process managers often face a huge amount of financial entries in accounting information systems. For many reasons like auditing the internal control system a process- oriented view would be more helpful to understand how a set of transactions produced

Feature weighting of support vector machines based on derivative saliency analysis and its application to financial data mining
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This paper proposes a novel feature weighting approach based on derivative saliency analysis, which can specifically display to what extent the output of support vector regression machines varies with the features (ie the components of the input vector). The empirical

Detection of fraudulent financial statements through the use of data mining techniques
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This paper explores the effectiveness of Data Mining (DM) classification techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. In accomplishing the task of management fraud

Data mining in finance: Report from the post-nncm-96 workshop on teaching computer intensive methods for financial modeling and data analysis
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The conference Neural Networks in the Capital Markets was followed by a workshop at Caltech on November 23, 1996. The purpose of the workshop was to bring people together to share their experiences and ideas on designing and teaching new courses in financial

Application of Artificial Intelligence and Data Mining Techniques to Financial Markets.
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Mining Financial Data with Scheduled Discovery of Exception Rules
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This paper shows preliminary results, on financial data , of an algorithm for discovering pairs of an exception rule and a common sense rule under a prespecified schedule. An exception rule, which represents a regularity of exceptions to a common sense rule, often exhibits This paper examines stock prices forecasting and trading strategies development with means of computational intelligence (CI), addressing the issue of an artificial neural network (ANN) topology dependency. Simulations reveal optimal network settings. Optimality of

Analysis of the impact of financial development on foreign direct investment: A data mining approach
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Several empirical studies have tried to examine the links between Foreign Direct Investment, financial development and economic growth. However, little work has been done to examine the direct relationship between FDI and financial development. Thus, through this study we

ANALYZING RISKS FOR HOME LOANS DURING FINANCIAL CRISIS OF 2008 USING DATA MINING .
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Freddie Macs single family loan data provide ample information on historical single family loan originations and performances throughout the loan periods. We analyzed these datasets to answer a critical question for the secondary mortgage market: Were there


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