Week 3 Update

I organised regular Weekly meetings with my supervisors on Thursdays 5-6pm.

This week my supervisors encouraged me to read material by Hendershott as he is the best expert in Algorithmic Trading.

Also, we discussed the idea of trying to identify rules for algorithms that instigated responses in the market for the topic of my thesis. For example, predicting the volatility of the market based on how an algorithm is behaving at the moment. According to Andrew this is a major point of interest in Finance these days.

I also read the book "Option Theory with Stochastic Analysis" in order to learn about how to analyse data. This topic brought up the concept of Brownian Motion, Inverse Gaussian Aggregation and Logarithmic Returns to stocks.

Week 2 Update

 I have studied the article "Algorithmic Trading Strategy Optimization Based on Mutual Information Entropy Based Clustering" in depth and presented it at the research group meetings that Sanjay Chawla holds weekly for all of his research students.

I had to teach myself Information Theory in order to understand this article.

I found many mathematical errors as well as a lack of explanation for why the authors did certain things. As a consequence, my supervisors and I dismissed it as a Tier C article with too many flaws to be taken seriously.

However, I still consider it to have been a good learning experience as it taught me how to understand an academic article.

I read these two resources to help me out in how to read an academic article:

"Evaluating Research Articles From Start to Finish" by Ellen R. Girden
"The Research Student's Guide to Success" by Pat Cryer.

At this stage I have still not decided what my question is going to be in my thesis and am still reading articles to understand what the area of algorithmic trading is all about.

Here are some other articles that I have studied, though not in as much depth as the one mentioned above:
"Data Stream Mining For Market Neutral Algorithmic Trading"
"Efficient Trade Execution Using A Genetic Algorithm in an Order Book Based Artificial Market"
"Efficient Event Processing through Reconfigurable Hardware for Algorithmic Trading"

I also organized an interview with an undisclosed financial institution's algorithmic trading team member to discuss how they use algorithmic trading and how they will be able to help me in my research thesis-Contact me for more information if interested.

Week 1 Update

Hello! This is my first blog for my ELEC 4712 Research thesis.

It is already Week 1  of Semester 1, 2011 and I spent my first week and holidays reading the following articles:

Chaboud, A. , Chiquoine, B. , Hjalmarsson, E., and Vega, C., 2009, Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market, International Finance Discussion Papers: Board of Governors of the Federal Reserve System Number 980, 1-46


Hendershott, T., Jones, C.M., and  Menkveld, A.J., Does Algorithmic Trading Improve Liquidity?

Gsell, M., Assessing the impact of algorithmic trading on markets: a simulation approach.

Domowitz, I.,  and Yegerman, H., 2005, The cost of algorithmic trading: A first look at comparative performance

I have also attended preliminary informal meetings with Sanjay Chawla and Andrew Lepone to ask them about being my joint supervisor and they have agreed. However, I will be getting their signatures on Wednesday and Thursday respectively so that I can hand in my topic registration form. Have already got Rafa Calvo as my SEIE supervisor.