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Showing 1 to 13 of 13 for “"Market prediction"”.

  1. Selective machine learning for stock market prediction

    Applying state-of-the-art machine learning models to predicting stock returns has been a common focus of research for practitioners. However, these models often face challenges due to the inclusion of a wide universe of stocks, leading to performance degradation caused by significant noise. In this …

    texas Repository record for Selective machine learning for stock market prediction (opens in a new tab)

  2. Applications of twitter emotion detection for stock market prediction

    … emotion categorization to predict future stock market performance.

    mit Repository record for Applications of twitter emotion detection for stock market prediction (opens in a new tab)

  3. Flags of Caution for Future Downturns in the Housing Market Prediction Using the Markov Chain Model

    The recent downturn in the United States housing market yielded a period of time akin to that of the Great Depression. Since the 1930s, there has never been an economic downturn in this country as close as that of the Great Depression era. The Depression experienced similarities to the current …

    twu Repository record for Flags of Caution for Future Downturns in the Housing Market Prediction Using the Markov Chain Model (opens in a new tab)

  4. Analyzing Causality between Actual Stock Prices and User-weighted Sentiment in Social Media for Stock Market Prediction

    … the proposed algorithm can contribute to stock prediction. The proposed sentiment analysis algorithm reflects the factors of Twitter which are relevant to users’ authority to calculate sentiment weight of each message that is different from existing sentiment analysis algorithms. Linear and …

    calgary Repository record for Analyzing Causality between Actual Stock Prices and User-weighted Sentiment in Social Media for Stock Market Prediction (opens in a new tab)

  5. Artificial neural networks to predict share prices on the Johannesburg stock exchange

    … use of historical data to build models for stock market prediction has been extensively researched. Artificial Neural Networks (ANNs) bring new opportunities for predicting stock markets, and is now one of the leading techniques used for time series and specifically stock market prediction. This …

    cape-town Repository record for Artificial neural networks to predict share prices on the Johannesburg stock exchange (opens in a new tab)

  6. Gene expression programming for Efficient Time-series Financial Forecasting

    Stock market prediction is of immense interest to trading companies and buyers due to high profit margins. The majority of successful buying or selling activities occur close to stock price turning trends. This makes the prediction of stock indices and analysis a crucial factor in the determination …

    de-montfort Repository record for Gene expression programming for Efficient Time-series Financial Forecasting (opens in a new tab)

  7. NEUROEVOLUTION AND AN APPLICATION OF AN AGENT BASED MODEL FOR FINANCIAL MARKET

    <p>Market prediction is one of the most difficult problems for the machine learning community. Even though, successful trading strategies can be found for the training data using various optimization methods, these strategies usually do not perform well on the test data as expected. Therefore, …

    cuny Repository record for NEUROEVOLUTION AND AN APPLICATION OF AN AGENT BASED MODEL FOR FINANCIAL MARKET (opens in a new tab)

  8. Soft computing techniques in power system analysis

    … industrial plants, pattern recognition, market prediction, patient diagnosis, logistics and of course power system analysis and prediction. However in all these fields its application is comparatively new and research is being carried out continuously in many universities and research …

    vu-aus Repository record for Soft computing techniques in power system analysis (opens in a new tab)

  9. A Behavioural Data Approach Towards Predicting Direct Real Estate Markets in the United Kingdom

    In recent years, modern prediction models have evolved to include behavioural data such as user-generated search query data that capture market sentiment and reach beyond the grasp of established macroeconomic indicators. These applications had considerable success in predicting a wide range of …

    cambridge Repository record for A Behavioural Data Approach Towards Predicting Direct Real Estate Markets in the United Kingdom (opens in a new tab)

  10. News and financial market

    News can influent the market. It has been proven that using text mining techniques, financial news can be used to predict market trend and volatility. In this thesis, we study some existing prediction algorithms that are based on Naive Bayes Classifier and Adjusted Document Frequency-Inverse …

    uiuc Repository record for News and financial market (opens in a new tab)

  11. Robust and cheating-resilient power auctioning on Resource Constrained Smart Micro-Grids

    … per critical section invocation (auction market execution). Our CDA algorithm scales better and avoids the single point of failure problem associated with centralised CDAs (which could be used to adversarially provoke a break-down of the grid marketing mechanism). In addition, the …

    cape-town Repository record for Robust and cheating-resilient power auctioning on Resource Constrained Smart Micro-Grids (opens in a new tab)