Sökning: "MSE"

Visar resultat 1 - 5 av 118 uppsatser innehållade ordet MSE.

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. Forecasting With Feature-Based Time Series Clustering

   Master-uppsats, Jönköping University/Tekniska Högskolan

   Författare :Conrad Tingström; Johan Åkerblom Svensson; [2023]
   Nyckelord :demand forecasting; time series prediction; time series clustering;

   Sammanfattning : Time series prediction plays a pivotal role in various areas, including for example finance, weather forecasting, and traffic analysis. In this study, time series of historical sales data from a packaging manufacturer is used to investigate the effects that clustering such data has on forecasting performance. LÄS MER

5. 4. On modelling OMXS30 stocks - comparison between ARMA models and neural networks

   Master-uppsats, Uppsala universitet/Matematiska institutionen

   Författare :Irina Zarankina; [2023]
   Nyckelord :ARMA; ARIMA; LSTM; time series; statistics;

   Sammanfattning : This thesis compares the results of the performance of the statistical Autoregressive integrated moving average (ARIMA) model and the neural network Long short-term model (LSTM) on a data set, which represents a market index. Both models are used to predict monthly, daily, and minute close prices of the OMX Stockholm 30 Index. LÄS MER

7. 5. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning models

   Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Divya Chedayan; Harry Geo Fernandez; [2023]
   Nyckelord :machine learning; lettuce yield prediction; Regression; SVR; RF; DNN; MAE; MSE; RMSE; R-squared; Adjusted R-squared;

   Sammanfattning : A key challenge for maximizing the world’s food supply is crop yield prediction. In this study, three machine models are used to predict the fresh weight (yield) of lettuce plants that are grown inside indoor farms hydroponically using the vertical farming infrastructure, namely, support vector regressor (SVR), random forest regressor (RFR), and deep neural network (DNN). LÄS MER