Sökning: "volatility prediction model"

Visar resultat 1 - 5 av 46 uppsatser innehållade orden volatility prediction model.

1. 1. Exploring the Idiosyncratic Volatility Anomaly in the Swedish Stock Market: An Empirical Analysis of its Impact on Returns

   Master-uppsats, Göteborgs universitet/Graduate School

   Författare :Anton Ahlqvist; Walter Uong; [2023-06-29]
   Nyckelord :;

   Sammanfattning : We examine the cross-sectional relationship between idiosyncratic volatility relative to the Fama-French three factor model and expected stock returns. We find that portfolios containing the firms with the lowest idiosyncratic risk offers excess returns in relation to the prediction of the Fama-French three factor model, while those with the highest idiosyncratic risk do not. LÄS MER

3. 2. Stock market analysis with a Markovian approach: Properties and prediction of OMXS30

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :Max Aronsson; Anna Folkesson; [2023]
   Nyckelord :Markov chain; OMXS30; Markov chain properties; voting ensemble model; markovkedja; OMXS30; egenskaper hos markovkedjor; ensemble-modell;

   Sammanfattning : This paper investigates how Markov chain modelling can be applied to the Swedish stock index OMXS30. The investigation is two-fold. Firstly, a Markov chain is based on index data from recent years, where properties such as transition matrix, stationary distribution and hitting time are studied. LÄS MER

4. 3. Aktiemarknadsprognoser: En jämförande studie av LSTM- och SVR-modeller med olika dataset och epoker

   Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

   Författare :Mads Nørklit Johansen; Jagtej Sidhu; [2023]
   Nyckelord :Stock Market Prediction; Long-Short Term Memory; Support Vector Regression; Prediction Accuracy; Financial Investments;

   Sammanfattning : Predicting stock market trends is a complex task due to the inherent volatility and unpredictability of financial markets. Nevertheless, accurate forecasts are of critical importance to investors, financial analysts, and stakeholders, as they directly inform decision-making processes and risk management strategies associated with financial investments. LÄS MER

5. 4. CryptoCurrency Time Series analysis : Comparative analysis between LSTM and BART Algorithm

   Uppsats för yrkesexamina på grundnivå, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Lakshmi Vyshnavi Nerella; Chiranjeevi Ponnada; [2023]
   Nyckelord :;

   Sammanfattning : Background: Cryptocurrency is an innovative digital or virtual form of money thatuses cryptographic techniques for secured financial transactions within a decentralized structure. Due to its high volatility and susceptibility to external factors, itis difficult to understand its behavior which makes accurate predictions challengingfor the investors who are trying to forecast price changes and make profitable investments. LÄS MER

7. 5. A Mixed Time-Series & Machine Learning Approach for Price Forecasting in the Swedish Ancillary Market

   Magister-uppsats, Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionen

   Författare :Daniel Arredondo; [2023]
   Nyckelord :Hybrid model; Volatility model; Machine learning model; Price spike prediction; Energy trading; Time series forecasting; Ancillary service market; Business and Economics;

   Sammanfattning : This study aims to forecast the Swedish FCR-D Down A2 market prices through a hybrid model combining a volatility model and a machine learning approach, and compares its performance with a standalone machine learning model. We further examine the impact of different lag orders (1-Hr vs. 24-Hr) on volatility estimates and forecast performance. LÄS MER