Sökning: "mariano"

Visar resultat 1 - 5 av 27 uppsatser innehållade ordet mariano.

1. 1. Volatility Forecasting - A comparative study of different forecasting models.

   Kandidat-uppsats,

   Författare :Emil Sturesson; Anton Wennström; [2023-06-29]
   Nyckelord :Volatility; GARCH; EGARCH; t-GAS; HAR-RV; Realized GARCH; Volatility Forecasting; Volatility Modelling;

   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

3. 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 School

   Författare :Johannes Marmdal; Adam Törnqvist; [2023-06-29]
   Nyckelord :Forecast; Volatility; Ether; GARCH; EWMA; SMA;

   Sammanfattning : 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

4. 3. NOWCASTING THE SWEDISH UNEMPLOYMENT RATE USING GOOGLE SEARCH DATA

   Magister-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Jacob Inganäs; [2023]
   Nyckelord :Google trends; unemployment; regARIMA; nowcast; forecast;

   Sammanfattning : In this thesis, the usefulness of search engine data to nowcast the unemployment rate of Sweden is evaluated. Four different indices from Google Trends based on keywords related  to unemployment are used in the analysis and six different regARIMA models are  estimated and evaluated. LÄS MER

5. 4. A comparison of forecasting techniques: Predicting the S&P500

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Axel Neikter; Nils Sjöberg; [2023]
   Nyckelord :Forecasting; machine learning; random forest; arima;

   Sammanfattning : Accurately predicting the S\&P 500 index means knowing where the US economy is heading. If there was a model that could predict the S\&P 500 with even some accuracy, this would be extremely valuable. Machine learning techniques such as neural network and Random forest have become more popular in forecasting. LÄS MER

7. 5. Forecasting monthly LME Copper returns

   Master-uppsats, Göteborgs universitet/Graduate School

   Författare :Nils Lervik; Philip Thorsell; [2022-06-29]
   Nyckelord :;

   Sammanfattning : We evaluate if monthly LOCADY returns on the London Metal Exchange can be accurately predicted one, two and three months ahead. In total ten models are constructed using time-varying parameters and bandwidth optimization. LÄS MER