Sökning: "Autoregressive Integrated Moving Average ARIMA"

Visar resultat 1 - 5 av 32 uppsatser innehållade orden Autoregressive Integrated Moving Average ARIMA.

  1. 1. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks

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

    Författare :Eddie Nevander Hellström; Johan Slettengren; [2023]
    Nyckelord :;

    Sammanfattning : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. LÄS MER

  3. 2. 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

  4. 3. Portfolio Risk Modelling in Venture Debt

    Master-uppsats, KTH/Matematisk statistik

    Författare :John Eriksson; Jacob Holmberg; [2023]
    Nyckelord :Startup Default Probability; Venture Debt; Gaussian Copula; Value-at-Risk; Expected Shortfall; Exposure at Default; Loss Given Default; Forecast; Linear Dynamic System; ARIMA Time Series; Monte Carlo Simulation; Linear Regression; Central Limit Theorem;

    Sammanfattning : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. LÄS MER

  5. 4. Predicting Waveforms with Machine Learning for Efficient Triggering in Monitoring Systems

    Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Amanda Rautio; [2023]
    Nyckelord :;

    Sammanfattning : Energy systems need to evolve to meet the requirements of the modern world and the future. Hence, substantial effort is needed at an academic and industrial level to develop valuable diagnostic techniques. LÄS MER

  7. 5. Inflation Index for the House and Content Portfolio : A Model to Calculate the Future Claim Costs for Trygg-Hansa

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Nadine Eklund; [2023]
    Nyckelord :Inflation Index; Claim Costs; Time Series Forecasting; Trygg-Hansa;

    Sammanfattning : Trygg-Hansa is a Swedish insurance company that specializes in business insurance, home insurance, vehicle insurance, and personal insurance. This work focuses on Trygg-Hansa’s House and Content portfolio, which insures customers’ homes, both the building itself and its contents. LÄS MER