Sökning: "Sentiment Forecasting"

Visar resultat 1 - 5 av 15 uppsatser innehållade orden Sentiment Forecasting.

  1. 1. Understanding Sales Performance Using Natural Language Processing - An experimental study evaluating rule-based algorithms in a B2B setting

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Angelica Smedberg; [2023]
    Nyckelord :NLP; Sentiment Analysis; Ruled-based algorithms; TextBlob; VADER; Naïve Bayes; Machine Learning;

    Sammanfattning : Natural Language Processing (NLP) is a branch in data science that marries artificial intelligence with linguistics. Essentially, it tries to program computers to understand human language, both spoken and written. Over the past decade, researchers have applied novel algorithms to gain a better understanding of human sentiment. LÄS MER

  3. 2. Unlocking the crystal ball: Deciphering recessions through dynamic relationships among leading indicators in Sweden

    Kandidat-uppsats, Jönköping University/IHH, Nationalekonomi

    Författare :Mariyan Traykov; Sina Mohseni; [2023]
    Nyckelord :VAR; analysis; economics; forecasting; recessions;

    Sammanfattning : Forecasting economic recessions has been a major topic of interest for economists, decisionmakers and the public alike. In this study we ventured to analyse how changes in economic output or GDP is related to changes in consumer sentiment and house prices in the Swedish economy. LÄS MER

  4. 3. Machine Learning Based Stock Price Prediction by Integrating ARIMA model and Sentiment Analysis with Insights from News and Information

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Teja Sai Vaibhav Boppana; Joseph Sudheer Vinakonda; [2023]
    Nyckelord :Machine Learning; Market Trends; News; Headlines Stock Price Prediction; VADER.;

    Sammanfattning : Background: Predicting stock prices in today’s complex financial landscape is asignificant challenge. An innovative approach to address this challenge is integrating sentiment analysis techniques with the well-established Autoregressive IntegratedMoving Average (ARIMA) model. LÄS MER

  5. 4. Volatility & The Black Swan : Investigation of Univariate ARCH-models, HARRV and Implied Volatility in Nasdaq100 amid Covid19

    Master-uppsats, Uppsala universitet/Nationalekonomiska institutionen

    Författare :Karl Tingstedt; [2022]
    Nyckelord :SV; ARCH; GARCH; TARCH; EGARCH; HARRV; IV; RV; Integrated Volatility; TINA;

    Sammanfattning : Covid19 hit the world’s financial markets by surprise in March 2020 and ensuing volatility marked an end to the prior low-volatility environment. This Black Swan engendered numerous publications establishing how the equity market responded to the exogenous shock. LÄS MER

  7. 5. A machine learning approach leveraging technical- and sentiment analysis to forecast price movements in major crypto currencies

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Ludvig Harting; Nils Åkesson; [2022]
    Nyckelord :Artifical Neural Network; Crypto; Sentiment Analysis; Twitter; Technical Analysis; Bitcoin; Ether; Litecoin; Artificiellt Neuronnät; Kryptovalutor; Sentimentsanalys; Twitter; Teknisk Analys; Bitcoin; Ether; Litecoin;

    Sammanfattning : This paper uses a back-propagating neural network (BPN) to predict the price movements of major crypto currencies, leveraging technical factors as well as measurements of collective sentiment derived from the micro-blogging network Twitter. Our dataset consists of daily, hourly and minutely price levels for Bitcoin, Ether and Litecoin along with 8 popular technical indicators, as well as all tweets with the currencies' cash tags during respective time periods. LÄS MER