There has been a lot of research on the application of data mining and knowledge discovery technologies into financial market prediction area. However, most of the existing research focused on mining structured or numeric data such as financial reports, historical quotes, etc. Another kind of data source – unstructured data such as financial news articles, comments on financial markets by exper...

Financial market prediction on the basis of online sentiment tracking has drawn a lot of attention recently. However, most results in this emerging domain rely on a unique, particular combination of data sets and sentiment tracking tools. This makes it difficult to disambiguate measurement and instrument effects from factors that are actually involved in the apparent relation between online sen...

A successful financial prediction system presents many challenges. Some are encountered over again, and though an individual solution might be system-specific, general principles still apply. Using them as a guideline might save time, effort, boost results, as such promoting project’s success. This paper remarks on a prediction system development stemming from author’s experiences and published...

As the era of knowledge economy is prevalent in U.S. during 1992, knowledge economy plays an important role around the world. The value and competition of the traditional companies accounted on tangible assets. However, in the era of knowledge economy, the value and continuing operation of the companies accounted on intangible assets. It is not sufficient in estimating the value of a company on...

Market-makers have been used by global stock exchanges as well as prediction markets to maintain liquidity and orderly price transitions in the financial markets. We use an agent-based model of the financial markets to analyze the behavior of market-makers employing various strategies. We empirically evaluate the performance of the market-makers in the financial market to demonstrate the streng...

Financial news contains useful information on public companies and the market. In this paper we apply the popular word embedding methods and deep neural networks to leverage financial news to predict stock price movements in the market. Experimental results have shown that our proposed methods are simple but very effective, which can significantly improve the stock prediction accuracy on a stan...

---------------------------------------------------------------------Abstract------------------------------------------------------------------Now a day’s investors invest money in financial products. Financial operations are not local but wide-ranging to all the countries in the world. Stock Market is the market for security where organized issuance and trading of Stocks take place either thro...

A new bootstrap procedure to obtain prediction densities of returns and volatilities of GARCH processes is proposed. Financial market participants have shown an increasing interest in prediction intervals as measures of uncertainty. Furthermore, accurate predictions of volatilities are critical for many financial models. The advantages of the proposed method are that it allows incorporation of ...

Enterprise Credit Risk becomes important issue in financial and accounting. It includes bankruptcy prediction, financial distress, corporate performance clustering / prediction and credit risk estimation. This research aims to provide a state-of-the art review of the relative literature and indicate relevant research opportunities. We found that the current research trends are necessary a metho...