Sökning: "price predictions"

Visar resultat 16 - 20 av 112 uppsatser innehållade orden price predictions.

  1. 16. The Effects of ETS & CBAM on Cost Differences in the European Steel Industry : A Case Study on Swedish and German Long Engineering Steel Manufacturers

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Tim Fahlstedt; Oliver Håkansson; [2022]
    Nyckelord :ETS; CBAM; Carbon Leakage; Steel; EAF; Scrap; Cost Predictions.; ETS; CBAM; Koldioxidläckage; Stål; Ljusbågsugn; Skrot; Kostnadsanalys.;

    Sammanfattning : To combat anthropogenic climate change and comply with the Paris Agreement, the EU has previously introduced its Emissions Trading System (ETS) and has now also proposed a Carbon Border Adjustment Mechanism (CBAM). While these tools may reduce emissions within the EU, and in some cases, even in other countries, they can also affect European industries in unpredictable and sometimes negative ways. LÄS MER

  3. 17. Signal detection of FX Fixing events

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskap

    Författare :Anton Sjöström; [2022]
    Nyckelord :Machine learning; Deep learning; Trading; Time series;

    Sammanfattning : This master thesis investigates the price dynamics of two currency pairs, GBP/USD and EUR/GBP, during the event called the “London 4 PM Fix”, which is a daily event. The dynamics of this event is understood by first creating a mathematical model to find the theoretical optimal trading strategy given a number of assumptions. LÄS MER

  4. 18. Spatial Statistical Modelling of Insurance Claim Frequency

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Daniel Faller; [2022]
    Nyckelord :Insurance risk; claim frequency; Markov chain Monte Carlo MCMC ; Riemann manifold Metropolis adjusted Langevin algorithm MMALA ; spatial statistics; Gaussian Markov random field GMRF ; preconditioned Crank Nicolson Langevin algorithm pCNL ; Gibbs sampling; Bayesian hierarchical modelling; high dimensional; shrinkage prior; horseshoe prior; regularisation.; Mathematics and Statistics;

    Sammanfattning : In this thesis a fully Bayesian hierarchical model that estimates the number of aggregated insurance claims per year for non-life insurances is constructed using Markov chain Monte Carlo based inference with Riemannian Langevin diffusion. Some versions of the model incorporate a spatial effect, viewed as the relative spatial insurance risk that originates from a policyholder's geographical location and where the relative spatial insurance risk is modelled as a continuous spatial field. LÄS MER

  5. 19. Forecasting Efficiency in Cryptocurrency Markets : A machine learning case study

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

    Författare :Erik Persson; [2022]
    Nyckelord :Cryptocurrencies; Financial time-series; Multi step-ahead forecasting; Machine Learning; Feature selection; Kryptovalutor; Finansiella tidsserier; Flerstegsprognoser; Maskininlärning; variabelselektion;

    Sammanfattning : Financial time-series are not uncommon to research in an academic context. This is possibly not only due to its challenging nature with high levels of noise and non-stationary data, but because of the endless possibilities of features and problem formulations it creates. LÄS MER

  7. 20. Favourable Opportunities in Sports Betting - A Statistical Approach to Football Goals in the Premier League

    Kandidat-uppsats, KTH/Matematisk statistik

    Författare :Fredrik Lindau; Gustaf Carle; [2022]
    Nyckelord :statistics; Poisson distribution; Negative Binomial distribution; Bayesian regression; football; Premier League; sports betting; market efficiency; probability theory; estimations; statistik; Poisson fördelning; Negativ Binomial fördelning; Bayesiansk regression; fotboll; Premier League; betting; marknadseffektivitet; sannolikhetsteori; skattningar;

    Sammanfattning : The premise of this report is to delve into sports betting and whether favourable opportunities can be found, more specifically focusing on over and under odds for number of goals scored in football games of the Premier League. Using historical data from football matches several models are developed, the characteristics of goals warranting the use of probability based Poisson and Negative Binomial models, as well as Bayesian Poisson regression for goal predictions. LÄS MER