Essays about: "stock return prediction"

Showing result 6 - 10 of 29 essays containing the words stock return prediction.

  1. 6. Predicting Stock Price Direction for Asian Small Cap Stocks with Machine Learning Methods

    University essay from KTH/Matematik (Avd.)

    Author : Tina Abazari; Sherwin Baghchesara; [2021]
    Keywords : Machine Learning; Classification; Classification Trees; Random Forest; Support Vector Machine; Logistic Regression; Stocks; Stock Market; Asset Management; Investments; Asia; Small Cap; Micro Cap; Maskininlärning; Klassificering; Klassificeringsträd; Random Forest; Support Vector Machine; Logistisk Regression; Aktier; Aktiemarknad; Fondförvaltning; Investeringar; Asien; Småbolag; Mikrobolag.;

    Abstract : Portfolio managers have a great interest in detecting high-performing stocks early on. Detecting outperforming stocks has for long been of interest from a research as well as financial point of view. Quantitative methods to predict stock movements have been widely studied in diverse contexts, where some present promising results. READ MORE

  3. 7. Financial statement information and abnormal stock returns : a test of increased market efficiency over time in the Swedish stock market

    University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi; Handelshögskolan i Stockholm/Institutionen för redovisning och finansiering

    Author : David Axelsson; Markus Elmgärde; [2021]
    Keywords : Financial statement analysis; Fundamental valuation; Abnormal returns; Market mispricing;

    Abstract : This study revisits the question of whether publicly available financial statement information can be used to generate abnormal returns. The study tests the hypothesis that the Swedish stock market has become increasingly efficient over time with respect to publicly available financial statement information, suggested by Skogsvik and Skogsvik (2010), by applying their investment strategy, combining the estimated probability of an increase in mid-term ROE with the implied market expectations for future mid-term ROE estimated from a RIV-model. READ MORE

  4. 8. Portfolio optimization using factor models

    University essay from Lunds universitet/Matematisk statistik

    Author : Ville Ekelund; [2020]
    Keywords : Mathematics and Statistics;

    Abstract : In this thesis model predictive control (MPC) is used to dynamically optimize a portfolio where data is sampled at the closing price. Previous research has shown that MPC optimization applied on financial data can yield a portfolio that exceeds the value of traditional portfolio strategies. READ MORE

  5. 9. Spectral Portfolio Optimisation with LSTM Stock Price Prediction

    University essay from KTH/Matematisk statistik

    Author : Nancy Wang; [2020]
    Keywords : Artificial Neural Network; LSTM; Spectral factor model; Portfolio optimisation; Stock price prediction; Time series analysis; Risk estimation; Spectral risk; Frequency-specific beta decomposition; Artificiella neurala nätverk; LSTM; Spektralfaktormodell; Portföljoptimering; Aktieprispredikering; Tidsserieranalys; Riskestimering; Spektra risk; Frekvensspecifik beta dekomposition;

    Abstract : Nobel Prize-winning modern portfolio theory (MPT) has been considered to be one of the most important and influential economic theories within finance and investment management. MPT assumes investors to be riskaverse and uses the variance of asset returns as a proxy of risk to maximise the performance of a portfolio. READ MORE

  6. 10. Politics, Artificial Intelligence, Twitter and Stock Return : An Interdisciplinary Test for Stock Price Prediction Based on Political Tweets

    University essay from Jönköping University/IHH, Företagsekonomi

    Author : Reamflar Elvio Estebano Troeman; Lisa Fischer; [2020]
    Keywords : Stock Price Prediction; Politics; Efficient Market Hypothesis; Twitter; Artificial Intelligence; Sentiment Analysis; Event Study;

    Abstract : As the world is gravitating toward an information economy, it has become more and more critical for an investor to understand the impact of data and information. One of the sources of data that can be converted into information are texts from microblogging platforms, such as Twitter. READ MORE