Masters Oral Defense: "Algorithmic Trading with Prior Information"

Abstract: Traders utilize different strategies by using different mix of market and limit orders to generate profits. There are different types of traders in the market, some has the prior information and can learn from changes in prices to tweak her strategy continuously, while some do not have the ability to learn. The traders who are well informed are called 'informed traders' (IT) or 'algorithmic traders', while others are called 'uninformed traders' (UT).

Alvaro Cartea, Sebastian Jaimungal and Damir Kinzebulatov created a model for algorithmic traders in 2014. The traders can use the model to decide which strategy to use. The model considered the distribution of the prices in the future, the spread of the bid and ask prices and also the capital appreciation of inventories. I implemented the model for the case when the trader can only learn from one asset and take positions in one asset. Compared to the uninformed traders, the IT using the proposed model can generate higher and more certain profits.If the prices has high volatility, the trader's ability of learning from price innovations can be impaired. However, the problem can be avoided by leaning from more than one asset that co-moves. 

Hosts: Nan Lin & Jose Figueroa-Lopez