Essays about: "tradingstrategi"

Found 3 essays containing the word tradingstrategi.

  1. 1. A Markovian Approach to Financial Market Forecasting

    University essay from KTH/Matematisk statistik

    Author : Kevin Sun Wang; William Borin; [2023]
    Keywords : Markov chain; Markov model; stock market prediction; Laplace smoothing; steady-state; forecasting; trading strategy; stochastic; trading algorithm; Markovkedjor; Markovmodell; prediktion; Laplace-jämning; stationär fördelning; tradingstrategi; stokastisk; trading algoritm;

    Abstract : This thesis aims to investigate the feasibility of using a Markovian approach toforecast short-term stock market movements. To assist traders in making soundtrading decisions, this study proposes a Markovian model using a selection ofthe latest closing prices. READ MORE

  3. 2. Algorithmic Trading and Prediction of Foreign Exchange Rates Based on the Option Expiration Effect

    University essay from KTH/Matematisk statistik

    Author : Sina Mozayyan Esfahani; [2019]
    Keywords : Option expiration effect; option relevance coefficient; algorithmic trading; time series analysis; GARCH-X.; Effekten av optioners förfall; optionsrelevanskoefficient; algoritmisk handel; tidsserieanalys; GARCH-X.;

    Abstract : The equity option expiration effect is a well observed phenomenon and is explained by delta hedge rebalancing and pinning risk, which makes the strike price of an option work as a magnet for the underlying price. The FX option expiration effect has not previously been explored to the same extent. READ MORE

  4. 3. Bayesian Neural Networks for Financial Asset Forecasting

    University essay from KTH/Matematisk statistik

    Author : Alexander Back; William Keith; [2019]
    Keywords : Bayesian neural networks; variational inference; Markov chain Monte Carlo; dropout; systematic trading; futures contracts; Bayesianska neurala nätverk; variational inference; Markov chain Monte Carlo; dropout; systematisk trading; terminskontrakt;

    Abstract : Neural networks are powerful tools for modelling complex non-linear mappings, but they often suffer from overfitting and provide no measures of uncertainty in their predictions. Bayesian techniques are proposed as a remedy to these problems, as these both regularize and provide an inherent measure of uncertainty from their posterior predictive distributions. READ MORE