Sökning: "ARIMA modeller"

Visar resultat 11 - 15 av 34 uppsatser innehållade orden ARIMA modeller.

1. 11. A Comparison of Recurrent Neural Networks Models and Econometric Models for Stock Market Predictions

   Master-uppsats, Umeå universitet/Institutionen för fysik

   Författare :Johan Keskitalo; [2020]
   Nyckelord :Neural Network; Stock market Predictions;

   Sammanfattning : It is well known that the stock market is highly volatile, so stock price prediction is a very challenging task. However, in order to make a profit or to understand the equity market, many investors and researchers use various statistical, econometric, and neural network models to make the best stock price predictions possible. LÄS MER

3. 12. Adding external factors in Time Series Forecasting : Case study: Ethereum price forecasting

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :José María Vera Barberán; [2020]
   Nyckelord :Time-series; Forecasting; Pattern-based models; ARIMA; LSTM; Tidsserier; Prognoser; Mönsterbaserade modeller; ARIMA; LSTM;

   Sammanfattning : The main thrust of time-series forecasting models in recent years has gone in the direction of pattern-based learning, in which the input variable for the models is a vector of past observations of the variable itself to predict. The most used models based on this traditional pattern-based approach are the autoregressive integrated moving average model (ARIMA) and long short-term memory neural networks (LSTM). LÄS MER

4. 13. ARIMA Modeling : Forecasting Indices on the Stockholm Stock Exchange

   Kandidat-uppsats, Karlstads universitet/Handelshögskolan (from 2013)

   Författare :Philip Jansson; Hugo Larsson; [2020]
   Nyckelord :Forecasting; ARIMA; Index; MPE; MAPE; Förutspå; ARIMA; Index; MPE; MAPE;

   Sammanfattning : The predictability of the stock market has been discussed over a long period of time and is of great interest to anyone investing in the stock market. Some people argue that the stock market is impossible to predict, while others believe that the market is somewhat predictable. LÄS MER

5. 14. Generative Adversarial Networks and Natural Language Processing for Macroeconomic Forecasting

   Master-uppsats, KTH/Matematisk statistik

   Författare :David Evholt; Oscar Larsson; [2020]
   Nyckelord :Machine learning; natural language processing; generative adversarial nets; GAN; LSTM; CNN; macroeconomics; S P500; unemployment; forecasting; Machine learning; natural language processing; generative adversarial nets; GAN; LSTM; CNN; macroeconomics; S P500; unemployment; forecasting;

   Sammanfattning : Macroeconomic forecasting is a classic problem, today most often modeled using time series analysis. Few attempts have been made using machine learning methods, and even fewer incorporating unconventional data, such as that from social media. In this thesis, a Generative Adversarial Network (GAN) is used to predict U.S. LÄS MER

7. 15. Modeling of non-maturing deposits

   Master-uppsats, KTH/Matematisk statistik

   Författare :Fredrik Stavrén; Nikita Domin; [2019]
   Nyckelord :Financial mathematics; time series analysis; replicating portfolio; risk management; risk analysis; econometric anaylsis; non-maturing deposits; SARIMA; Random forest regression; EBA; BCBS; Finansiell matematik; tidsserieanalys; replikeringsportfölj; riskhantering; riskanalys; Ekonometrisk analys; Icke-tidsbunden inlåning; ARIMA; SARIMA; SARIMAX; Random Forest Regression; EBA; BCBS;

   Sammanfattning : The interest in modeling non-maturing deposits has skyrocketed ever since thefinancial crisis 2008. Not only from a regulatory and legislative perspective,but also from an investment and funding perspective.Modeling of non-maturing deposits is a very broad subject. LÄS MER