Sökning: "ARIMA"
Visar resultat 11 - 15 av 162 uppsatser innehållade ordet ARIMA.
11. Portfolio Risk Modelling in Venture Debt
Master-uppsats, KTH/Matematisk statistikSammanfattning : 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
12. Evaluating machine learning models for time series forecasting in smart buildings
M1-uppsats, KTH/Hälsoinformatik och logistikSammanfattning : Temperature regulation in buildings can be tricky and expensive. A common problem when heating buildings is that an unnecessary amount of energy is supplied. This waste of energy is often caused by a faulty regulation system. LÄS MER
13. Forecasting Monthly Swedish Air Traveler Volumes
Kandidat-uppsats, Uppsala universitet/Statistiska institutionenSammanfattning : In this paper we conduct an out-of-sample forecasting exercise for monthly Swedish air traveler volumes. The models considered are multiplicative seasonal ARIMA, Neural network autoregression, Exponential smoothing, the Prophet model and a Random Walk as a benchmark model. LÄS MER
14. Do Inflation Expectations Granger Cause Inflation? A VEC Model Approach
D-uppsats, Handelshögskolan i Stockholm/Institutionen för nationalekonomiSammanfattning : Being able to accurately predict future inflation is of great importance for a wide range of actors in the economy, as well as for the effectiveness of monetary policy decisions. In this thesis, we examine whether survey measures of inflation expectations contribute to more accurate inflation forecasts in Sweden. LÄS MER
15. Predicting Waveforms with Machine Learning for Efficient Triggering in Monitoring Systems
Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : 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