Essays about: "Multivariate Financial Time Series"
Showing result 6 - 10 of 13 essays containing the words Multivariate Financial Time Series.
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6. Scenario Creation for Stress Testing Using Copula Transformation
University essay from Umeå universitet/Institutionen för fysikAbstract : Due to turbulence in the financial market throughout history, stress testing has become a growing part of the risk analysis performed by clearing houses. Events connected to previous crises have increased the demand for prudent risk exposure, and in this thesis we investigate regulators view on how CCPs should construct risk scenarios to meet best practice for stress testing their members’ composite portfolios. READ MORE
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7. LSTM Neural Network Models for Market Movement Prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Interpreting time varying phenomena is a key challenge in the capital markets. Time series analysis using autoregressive methods has been carried out over the last couple of decades, often with reassuring results. READ MORE
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8. A Multivariate Data Stream Anomaly Detection Framework
University essay from KTH/Skolan för elektro- och systemteknik (EES)Abstract : High speed stream anomaly detection is an important technology used in many industry applications such as monitoring system health, detecting financial fraud, monitoring customer's unusual behavior and so on. In those scenarios multivariate data arrives in high speed, and needs to be calculated in real-time. READ MORE
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9. Multivariate Financial Time Series and Volatility Models with Applications to Tactical Asset Allocation
University essay from KTH/Matematisk statistikAbstract : The financial markets have a complex structure and the modelling techniques have recently been more and more complicated. So for a portfolio manager it is very important to find better and more sophisticated modelling techniques especially after the 2007-2008 banking crisis. READ MORE
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10. Deep learning for multivariate financial time series
University essay from KTH/Matematisk statistikAbstract : Deep learning is a framework for training and modelling neural networks which recently have surpassed all conventional methods in many learning tasks, prominently image and voice recognition. This thesis uses deep learning algorithms to forecast financial data. The deep learning framework is used to train a neural network. READ MORE