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Full-Text Articles in Finance and Financial Management
Deep Reinforcement Learning Pairs Trading, Andrew Brim
Deep Reinforcement Learning Pairs Trading, Andrew Brim
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
This research applies a deep reinforcement learning technique, Deep Q-network, to a stock market pairs trading strategy for profit. Artificial intelligent methods have long since been applied to optimize trading strategies. This work trains and tests a DQN to trade co-integrated stock market prices, in a pairs trading strategy. The results demonstrate the DQN is able to consistently produce positive returns when executing a pairs trading strategy.
The Performance Of Military Defense Contracted Companies After September 11th, 2001: The Case Of Politically Connected Companies, Derek J. Larsen
The Performance Of Military Defense Contracted Companies After September 11th, 2001: The Case Of Politically Connected Companies, Derek J. Larsen
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
This paper examines the effect that the terrorist attacks on September 11th, 2001 had on the stock prices of companies within the military defense industry. In addition, this paper studies the effect of the defense firms’ political engagement (through lobbying activities) and how this affected the stock price response to the terrorist attacks. Our study finds that the cumulative abnormal returns of these companies are positively significant and that companies who lobbied experienced higher returns relative to those who did not lobby.
Predictive Distributions Via Filtered Historical Simulation For Financial Risk Management, Tyson Clark
Predictive Distributions Via Filtered Historical Simulation For Financial Risk Management, Tyson Clark
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Filtered historical simulation with an underlying GARCH process can be used as a valuable tool in VaR analysis, as it derives risk estimates that are sensitive to the distributional properties of the historical data of the produced predictive density. I examine the applications to risk analysis that filtered historical simulation can provide, as well as an interpretation of the predictive density as a poor man’s Bayesian posterior distribution. The predictive density allows us to make associated probabilistic statements regarding the results for VaR analysis, giving greater measurement of risk and the ability to maintain the optimal level of risk per …
The Stock Return Changes Of Chinese Adr Before And After Trump's Election And Imposed Tariff On Chinese Goods, Suyao Liu
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
This study examines the stock return changes of Chinese ADR company likely be affected by Trump’s election on November 9, 2016, the signing of tariff Chinese goods bill on March 8, 2018, and the tariff bill takes into act on March 23, 2018. The results show that, relative to the entire market, the stock prices of Chinese ADR companies underperform. Our analysis provides evidence that it’s hard to find that these three events would affect a particular industry of Chinese ADR the most.