In the field of financial investment, accurate prediction of financial market values can increase investor profits. Investor personality affects specific portfolio solutions, which keeps them symmetrical in the process of investment competition. However, information is often asymmetric in financial markets, and this information bias often results in different future returns for investors. Nowadays, machine learning algorithms are widely used in the field of financial investment. Many advanced machine learning algorithms can effectively predict future market changes and provide a scientific basis for investor decisions. The purpose of this paper is to study the problem of optimal matching of financial investment by using machine learning alg...
Momentum or trend following investing refers to trading strategies constructed around the idea that ...
Investment strategies as rules for buy and sell are introduced as conditional statements involving i...
This thesis aims to examine the ARIMA model in predicting stock return for Finnish major banks: OP, ...
Gold and bitcoin are not new to us, but with limited cash and time, given only the past stream of th...
115 pagesQuantitative models are changing virtually every aspect of investment. In this thesis, we f...
In recent years, the bitcoin market has developed rapidly and has been recognized as a new type of g...
Machine Learning (ML) for finance is a fruitful approach to detect patterns in data. However, when i...
This project is looking for increasing return on investment, by presenting models based on artificia...
Gold-silver ratio (GSR) is a commonly followed ratio among investors. Investors use the ratio as an ...
In recent years, machine learning algorithms have been successfully employed to leverage the potenti...
Over the past four thousand years, numerous techniques have been developed and used to address probl...
Portfolio optimization is a very classical and challenging problem that is interested in many areas ...
Recently, with the development of Artificial Intelligence in finance, using it in stock market tren...
This thesis addresses several topics in finance and consists of two parts. The central theme is form...
Most financial firms use algorithms to buy and sell financial assets. It is possible for amateur inv...
Momentum or trend following investing refers to trading strategies constructed around the idea that ...
Investment strategies as rules for buy and sell are introduced as conditional statements involving i...
This thesis aims to examine the ARIMA model in predicting stock return for Finnish major banks: OP, ...
Gold and bitcoin are not new to us, but with limited cash and time, given only the past stream of th...
115 pagesQuantitative models are changing virtually every aspect of investment. In this thesis, we f...
In recent years, the bitcoin market has developed rapidly and has been recognized as a new type of g...
Machine Learning (ML) for finance is a fruitful approach to detect patterns in data. However, when i...
This project is looking for increasing return on investment, by presenting models based on artificia...
Gold-silver ratio (GSR) is a commonly followed ratio among investors. Investors use the ratio as an ...
In recent years, machine learning algorithms have been successfully employed to leverage the potenti...
Over the past four thousand years, numerous techniques have been developed and used to address probl...
Portfolio optimization is a very classical and challenging problem that is interested in many areas ...
Recently, with the development of Artificial Intelligence in finance, using it in stock market tren...
This thesis addresses several topics in finance and consists of two parts. The central theme is form...
Most financial firms use algorithms to buy and sell financial assets. It is possible for amateur inv...
Momentum or trend following investing refers to trading strategies constructed around the idea that ...
Investment strategies as rules for buy and sell are introduced as conditional statements involving i...
This thesis aims to examine the ARIMA model in predicting stock return for Finnish major banks: OP, ...