The focus of the research is the profitability of using automated trading strategies. In other words, can trading strategies that are automatically executed in financial markets be profitable? In this study, three strategies are traded in a simulated environment under two different types of market conditions and on two different underlying assets. The trading strategies are based on a moving average crossover system with 5, 10, and 20 day moving averages. The first strategy uses only this moving average crossover system. The second strategy uses this same moving average system requiring increasing volume confirmation to make a trade. The final strategy uses this moving average crossover system but requires confirmation by a relative strengt...
Modernization in computers and Machine Learning have created new opportunities for improving the met...
This master’s thesis was born because of the interests of the author in Big Data, Machine Learning a...
Autonomous trading in stock markets is an area of great interest in both academic and commercial cir...
Honors (Bachelor's)StatisticsEconomicsUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/...
Electronic trading is relatively new to the long history of financial markets. The typical tradition...
The way in which financial markets operate has substantially been changed by the development of info...
Rapidly advancing algorithmic trading techniques and lagging financial market regulations have led t...
Problem statement: Despite widespread academic acceptance of the Efficient Markets Hypothesis, some ...
In an efficient market, prices of stocks reflect all relevant information. Efficient Market Hypothes...
This paper tests a few moving average technical trading rules for the NASDAQ Composite and Goldman S...
A general issue with moving average trading is the assumption that all buy/sell signals result in a ...
This study is motivated by the theoretical framework that suggests market timing and other algorithm...
This study examines whether the technical trading strategies can outperform the unconditional buy-an...
Artificial intelligence (AI) is one of the most discussed topics in finance. AI is expected to learn...
The goal of this Interactive Qualifying Project (IQP) is to test whether a diverse system of automat...
Modernization in computers and Machine Learning have created new opportunities for improving the met...
This master’s thesis was born because of the interests of the author in Big Data, Machine Learning a...
Autonomous trading in stock markets is an area of great interest in both academic and commercial cir...
Honors (Bachelor's)StatisticsEconomicsUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/...
Electronic trading is relatively new to the long history of financial markets. The typical tradition...
The way in which financial markets operate has substantially been changed by the development of info...
Rapidly advancing algorithmic trading techniques and lagging financial market regulations have led t...
Problem statement: Despite widespread academic acceptance of the Efficient Markets Hypothesis, some ...
In an efficient market, prices of stocks reflect all relevant information. Efficient Market Hypothes...
This paper tests a few moving average technical trading rules for the NASDAQ Composite and Goldman S...
A general issue with moving average trading is the assumption that all buy/sell signals result in a ...
This study is motivated by the theoretical framework that suggests market timing and other algorithm...
This study examines whether the technical trading strategies can outperform the unconditional buy-an...
Artificial intelligence (AI) is one of the most discussed topics in finance. AI is expected to learn...
The goal of this Interactive Qualifying Project (IQP) is to test whether a diverse system of automat...
Modernization in computers and Machine Learning have created new opportunities for improving the met...
This master’s thesis was born because of the interests of the author in Big Data, Machine Learning a...
Autonomous trading in stock markets is an area of great interest in both academic and commercial cir...