Sökning: "volatility forecasting"
Visar resultat 1 - 5 av 153 uppsatser innehållade orden volatility forecasting.
1. Volatility Forecasting - A comparative study of different forecasting models.
Kandidat-uppsats,Sammanfattning : This study evaluates the out-of-sample forecasting performance of different volatility mod- els. When applied to XACT OMXS30, we use GARCH(1,1), EGARCH(1,1), and t- GAS(1,1) to forecast squared daily returns while Realized GARCH(1,1) and HAR-RV are used to forecast Realized Variance. LÄS MER
2. Forecasting Volatility of Ether- An empirical evaluation of volatility models and their capacity to forecast one-day-ahead volatility of Ether
Master-uppsats, Göteborgs universitet/Graduate SchoolSammanfattning : This study evaluates the performance of volatility models in forecasting one-day-ahead volatility of the cryptocurrency Ether. The selected models are: GARCH, EGARCH, GJR-GARCH, SMA9, SMA20, and EWMA. We investigate both in-sample performance and out-of-sample performance. LÄS MER
3. Forecasting Volatility of Electricity Intraday Log Returns with Generalized Autoregressive Score Models
Master-uppsats, Göteborgs universitet/Graduate SchoolSammanfattning : We forecast volatility of electricity intraday log returns with Generalized Autoregressive Score (GAS) models. We extend our GAS models with variables representing the difference between the public’s expectation of weather and energy load and the actual outcome using a restricted ARMA(4,4) model. LÄS MER
4. On Predicting Price Volatility from Limit Order Books
Master-uppsats, Uppsala universitet/Matematiska institutionenSammanfattning : Accurate forecasting of stock price movements is crucial for optimizing trade execution and mitigating risk in automated trading environments, especially when leveraging Limit Order Book (LOB) data. However, developing predictive models from LOB data presents substantial challenges due to its inherent complexities and high-frequency nature. LÄS MER
5. Aktiemarknadsprognoser: En jämförande studie av LSTM- och SVR-modeller med olika dataset och epoker
Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)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