Automatic Categorization of Announcements on the Australian Stock Exchange

نویسندگان

  • Rafael A. Calvo
  • Ken Williams
چکیده

This paper compares the performance of several machine learning algorithms for the automatic categorization of corporate announcements in the Australian Stock Exchange (ASX) Signal G data stream. The article also describes some of the applications that the categorization of corporate announcements may enable. We have performed tests on two categorization tasks: market sensitivity, which indicates whether an announcement will have an impact on the market, and report type, which classifies each announcement into one of the report categories defined by the ASX. We have tried Neural Networks, a Näıve Bayes classifier, and Support Vector Machines and achieved good results.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Impact of Official Publication of Information in Tehran Stock Exchange on Shares Prices: A GMM Approach

Released information in stock markets plays an important role in making decisions by agents like brokers, investors and other market activists. Rational decision-making in these markets will be possible if relevant and significant information is being released on-time. Otherwise, transparency and equality in the market is compromised. This study aims to respond to the question of whether offici...

متن کامل

The Effectiveness of the Automatic System of Fuzzy Logic-Based Technical Patterns Recognition: Evidence from Tehran Stock Exchange

The present research proposes an automatic system based on moving average (MA) and fuzzy logic to recognize technical analysis patterns including head and shoulder patterns, triangle patterns and broadening patterns in the Tehran Stock Exchange. The automatic system was used on 38 indicators of Tehran Stock Exchange within the period 2014-2017 in order to evaluate the effectiveness of technical...

متن کامل

Does Disclosure Lead to Lower Informed Trading and Symmetric Order-follow Shocks in the Tehran Stock Exchange?

In financial markets, the symmetry of information and the homogeneous interpretation of information among traders is one of the main conditions for market efficiency, but these conditions are in fact violated. In this paper first; we accurately estimated the dynamic measures of trades stemming from information asymmetry and diverse opinions among investors indices by a hidden Markov model. Ther...

متن کامل

Stock Price Prediction using Machine Learning and Swarm Intelligence

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...

متن کامل

The Effect of Asymmetric Fluctuations of Exchange Rate and Oil Price on Stock Index of Tehran Stock Exchange

The aim of this study was to investigate the asymmetric effects of exchange rate fluctuations on Stock index of Tehran Stock Exchange. For this purpose, we first calculated the exchange rate fluctuations using model General Autoregressive Conditional Heteroskedastic (GARCH), and then the effect of these fluctuations on the Stock index of Tehran Stock Exchange was estimated using the Generalized...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002