Essays about: "Stock indices"
Showing result 6 - 10 of 156 essays containing the words Stock indices.
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6. An Evaluation of Leading Indicators in the Context of a Swedish Recession
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : The aim of this paper is to evaluate potential leading indicators of a recession in Sweden. To answer the question potential leading indicators are first identified with previous findings in literature and with the current state of the Swedish financial system as background. READ MORE
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7. A comparison of forecasting techniques: Predicting the S&P500
University essay from Uppsala universitet/Statistiska institutionenAbstract : Accurately predicting the S\&P 500 index means knowing where the US economy is heading. If there was a model that could predict the S\&P 500 with even some accuracy, this would be extremely valuable. Machine learning techniques such as neural network and Random forest have become more popular in forecasting. READ MORE
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8. Swedish Stock and Index Price Prediction Using Machine Learning
University essay from Mälardalens universitet/Akademin för utbildning, kultur och kommunikationAbstract : Machine learning is an area of computer science that only grows as time goes on, and there are applications in areas such as finance, biology, and computer vision. Some common applications are stock price prediction, data analysis of DNA expressions, and optical character recognition. READ MORE
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9. Copula approach to fitting bivariate time series
University essay from Lunds universitet/Matematisk statistikAbstract : We apply the GARCH-copula method to estimate Value at Risk (VaR) for European and Stockholm stock indices. First, marginal distributions are estimated by the ARMA-GARCH model with normal, Student-t, and skewed t distributions. READ MORE
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10. Forest Aboveground Biomass Monitoring in Southern Sweden Using Random Forest Modelwith Sentinel-1, Sentinel-2, and LiDAR Data
University essay from Högskolan i Gävle/SamhällsbyggnadAbstract : Monitoring carbon stock has emerged as a critical environmental problem among several worldwide organizations and collaborations in the context of global warming and climate change. This study seeks to provide a remote sensing solution based on three types of data, to explore the feasibility and reliability of estimating aboveground biomass (AGB) in order to improve the efficiency of monitoring carbon stock. READ MORE