Essays about: "Stock Movement Prediction"

Showing result 1 - 5 of 11 essays containing the words Stock Movement Prediction.

  1. 1. A Markovian Approach to Financial Market Forecasting

    University essay from KTH/Matematisk statistik

    Author : Kevin Sun Wang; William Borin; [2023]
    Keywords : Markov chain; Markov model; stock market prediction; Laplace smoothing; steady-state; forecasting; trading strategy; stochastic; trading algorithm; Markovkedjor; Markovmodell; prediktion; Laplace-jämning; stationär fördelning; tradingstrategi; stokastisk; trading algoritm;

    Abstract : This thesis aims to investigate the feasibility of using a Markovian approach toforecast short-term stock market movements. To assist traders in making soundtrading decisions, this study proposes a Markovian model using a selection ofthe latest closing prices. READ MORE

  3. 2. Predicting Stock Market Movement Using Machine Learning : Through r/wallstreetbets sentiment & Google Trends, Herding versus Wisdom of Crowds

    University essay from Uppsala universitet/Företagsekonomiska institutionen

    Author : Niklas Norinder; [2022]
    Keywords : Sentiment Analysis; Machine Learning; Stock Movement Prediction; r wallstreetbets; Google Trends;

    Abstract : Stock market analysis is a hot-button topic, especially with the growth of online communities surrounding trading and investment. The goal of this paper is to examine the sentiment of r/wallstreetbets and the Google Trends score for a number of stocks – and then understanding whether the herding nature of investors on r/wallstreetbets is better at predicting the movement of the stock market than the WOC nature of Google Trends scores. READ MORE

  4. 3. Short Term Stock Price Prediction Using Machine Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Olov Rahm; Alexander Wikström; [2022]
    Keywords : Machine Learning; Long Short-Term Memory; Recurrent Neural Network; Stock Price Prediction; NASDAQ;

    Abstract : This report assesses different machine learning models’accuracies to predict whether a stock will go up or down invalue in a short term. The models that is used is linear regression,LSTM and Elman RNN. These models was trained on historicalprice data from the Nasdaq Stock Exchange. READ MORE

  5. 4. A Neural Network Approach for Generating Investors’ Views in the Black-Litterman Model

    University essay from KTH/Matematik (Avd.)

    Author : Rafael Lavatt; [2022]
    Keywords : Black-Litterman; Neural Networks; Portfolio Optimization; Black-Litterman; Neurala nätverk; portföljoptimering;

    Abstract : This thesis investigates how neural networks can be used to produce investors' views for the Black-Litterman market model. The study uses two data sets, one with global stock market indexes and one with stock market data from the S&P 500. READ MORE

  6. 5. Sentiment building from textual data content in quarterly reports

    University essay from Lunds universitet/Nationalekonomiska institutionen

    Author : Tarek Jelassi; [2021]
    Keywords : Textual analysis; Python Programming Language; Modeling; Return Forecast; Sentiment building.; Business and Economics;

    Abstract : Textual analysis is increasingly becoming a reliable tool for pattern assessing and forecasting especially statistically. Implementing such techniques in the financial field is still in an infantry stage and it represents a novel research area. READ MORE