While I was getting my MBA I developed a strong interest in quantitative finance. I doubt I'll ever pursue a career in this field but I continue to enjoy reading about it in my spare time as part of a larger, general interest in applied mathematics (more about that in a future post).
Needless to say, I was eager to read the paper Algorithmic Trading: A Primer published in the summer 2009 issue of The Journal of Trading.
Unfortunately, I apparently misinterpreted the title as instead of discussing the algorithms themselves, the article covered the high-level points that clients of algorithmic trading firms should be aware of. To this end the article did cover some important points including:
- The desire (nay need) for algorithms to increase trader productivity
- The importance of Regulation NMS and why it favors electronic trading (which I must admit was new to me).
- The basic framework of algorithmic trading systems such as performance benchmarks, assumptions, etc.
- The rationale for and limitations of using log-normal models for price fluctuations.
- The importance of avoiding trades that signal the market and may therefore invalidate the algorithm's model.
- The importance of using the right algorithms at the right time to achieve the intended goals.
So, although the article didn't cover the topics I had initially hoped for I did find it a useful read anyway.
