Algorithmic Trading

My own trading revolves around the algorithmic trading of horse races. In particular, I am looking to get ahead of the crowd through low-latency trading, following trends caused by the flow of late-breaking information, statistical arbitrage across markets, non-fundamental pricing algorithms, spoofing, bot baiting, synthetic bets and so on. Research is always on-going as strategies can lose their edge and new strategies evolve.

There is a lot of commonality between what I do and what goes on in the financial markets. Namely, I am looking for an edge in any way that I can but without any fundamental analysis. A lot of the time, in this zero sum game, you are preying on the mistakes and naivety of others.

As I am not a fundamental trader I don't read the horse racing news. I have watched the Grand National a few times when Red Rum was running, one or two Epsom derbies and a few Royal Ascot meetings, mainly through boredom rather than any desire to see horses run.
What I do read is how quants trade financial markets. I have no desire to trade in the financial markets myself and have the HFT (high-frequency trading) firms leading me by the nose. I read books about financial algorithmic trading and architect similar methodologies for sports trading markets.

Some of the books that have assisted me in building an algorithmic trading platform are listed here.

The basis of any algorithmic trading platform is the black box through which a portfolio of trades is assembled and executed. In Inside The Black Box you are given the architecture of a black box; the alpha model (the money making strategy), the risk model (minimisation of drawdown), the transaction cost model (trading cost efficiently) and the portfolio construction model (taking the portfolio of positions from the current position to a more profitable one).

The book describes order execution algorithms, the importance of data when creating new strategies, researching new strategies, quant strategy evaluation and a discussion on high-frequency trading. Although the book obviously discusses this in a financial trading context, the information within is an excellent guide to creating a black box for trading sports betting markets.

Amazon - Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading

Building Winning Algorithmic Trading Systems is written from the viewpoint of a highly successful independent trader, Kevin Davey. His methods are similar to mine in his use of data to create strategies and Monte Carlo simulations to test them.

The book takes you from the beginning of the author's trading career and his demonstration of why not to trade under psychological stress. Davey was still trading a week after two traumatic deaths in his family. Trading on whim he invested in live cattle futures the day before the US announced its first case of BSE, a fine example of a black swan event (see The Black Swan: The Impact of the Highly Improbable).

After dabling with other beginner's mistakes such as simplistic that were not sufficiently tested, Davey started chasing his losses by averaging down, in the hope that the market would turn only to compound his losses yet further. Davey re-evaluated all that he thought he knew and started again. He learned how to create strategies that were devoid of human interaction and properly tested so that none of his frailties affected his trades. This results were impressive, two seconds and a first in the World Championship of Futures Trading.

For more than twenty years Davey has created thousands of systems, tested them using walk-forward analysis and then determined the optimal position size using Monte Carlo simuations. All of which is detailed in this book. Because Davey's approach is so similar to mine I need only recommend his book and not have to tell you myself.

Amazon - Building Winning Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading

Programming for Betfair is written by the author of this website. The book is a guide to creating applications for direct access to Betfair's exchange and will therefore be useful to those wishing to implement an algorithmic trading set up using the other books listed here.

No previous programming experience is necessary to build the applications in the book. After completing the programming exercises the reader will have a powerful tool for gathering prices for database creation, strategy building and algorithmic trade placement. Beginner programmers and experienced programmers have informed me that the book is easy to understand and that it has assisted them in creating algorithmic trading platforms.

Amazon - Programming for Betfair: A Guide to Creating Sports Trading Applications with API-NG

Without winning trading strategies your algorithmic trading operation is not going to be profitable. The Encyclopedia of Trading Strategies is a complete guide to many of the methods used in optimising and statistically analysing trading systems. Models for trade entries are covered through breakout models, moving average models, oscillators, cycles, neural networks and genetic algorithms. Exits are then covered with AI approaches included. There is even some whacky lunar and solar rhythms included but we won't talk about that.

Again, the book is entirely geared towards financial trading and it is up to the sports trader to filter out relevant information.

Amazon - The Encyclopedia of Trading Strategies

If you want to use machine learning for the optimisation of your trading systems then Biologically Inspired Algorithms for Financial Modelling is a book dedicated to that task. Covering neural networks, evolutionary computation (genetic algorithm, genetic programming, evolutionary algorithms etc.), swarm, ant colony and immune system models the book exaplains how these methods work and their applicability to the creation of trading rules.

The second part of the book details model development from project goals, through data collection, to optimising for trade entries, exits and money management. Part three of the book contains case studies of index prediction and trading. A book for the more advanced quants amongst us.

Amazon - Biologically Inspired Algorithms for Financial Modelling

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