Essays about: "MSE"
Showing result 1 - 5 of 106 essays containing the word MSE.
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1. Volatility Forecasting - A comparative study of different forecasting models.
University essay fromAbstract : 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. READ MORE
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2. Forecasting Volatility of Ether- An empirical evaluation of volatility models and their capacity to forecast one-day-ahead volatility of Ether
University essay from Göteborgs universitet/Graduate SchoolAbstract : 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. READ MORE
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3. Forecasting With Feature-Based Time Series Clustering
University essay from Jönköping University/Tekniska HögskolanAbstract : 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. READ MORE
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4. On modelling OMXS30 stocks - comparison between ARMA models and neural networks
University essay from Uppsala universitet/Matematiska institutionenAbstract : 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. READ MORE
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5. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning models
University essay from Högskolan i Skövde/Institutionen för informationsteknologiAbstract : 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). READ MORE
