The market is constantly evolving; as a market participant – whether you’re a long-term investor or a trader – your investing education is an ongoing process. Today, I wanted to tell you about a recent book that offers to close the gap between aspiring stock market operators and profitable algorithmic traders…
There’s been a lot of attention on algorithmic trading in 2010. Much of that attention has come from the massive profits hedge funds and bulge-bracket investment banks – like Renaissance Technologies or Goldman Sachs – have made from algorithmic trading systems. It’s estimated that as the market crumbled in 2008, algorithmic traders took home profits of $21 billion. Today, the majority of trading volume comes from these automated black-box systems…
But not a whole lot of focus has been paid to how retail investors can harness the power of algorithmic trading for their own accounts. I recently got ahold of Dr. Ernest Chan’s book, Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading, $60), and I thought that it’d be valuable to share some insights from it…
In Quantitative Trading, Chan breaks down how retail investors and aspiring professionals can build a profitable algorithmic trading system without needing the resources of a major financial institution.
Essentially, algorithmic trading uses computer programs to determine which stocks to trade, when to buy and when to sell. In some cases, these systems can execute round-trip trades without needing any human input at all. And despite the fact that there’s substantial competition from trading firms, Chan points out that there are still a number of exploitable strategies out there that the institutions are too big to touch.
In an industry where it normally pays to be opaque about your strategies, Dr. Chan actually shares a substantial amount of knowledge about algorithmic trading. From divulging MATLAB and Excel codes readers can use to test out their own strategies, to the library of backtested results available on the book’s companion site, this certainly is not one of those investing books that leaves you wondering what to do next.
Despite its relatively small size, Quantitative Trading is an involved read. In the book, Chan goes into detail about everything from finding a quantitative strategy to structuring an algorithmic trading business. For those reasons, the book gets relatively technical at times, particularly for those who haven’t taken a math class in a while. That said, it’s a book that most aspiring traders should find accessible if they take the time to understand the concepts presented.
Whether you’re interested in algorithmic trading for your own account, or you just want to build a better understanding of the high-frequency strategies being used by major Wall Street firms, Quantitative Trading is a good resource for any trading library…
Have a good weekend,
Jonas Elmerraji
Managing Editor, Penny Sleuth
December 4, 2010
Book Review: How to Build Your Own Algorithmic Trading Business was originally featured in the Penny Sleuth.
There’s been a lot of attention on algorithmic trading in 2010. Much of that attention has come from the massive profits hedge funds and bulge-bracket investment banks – like Renaissance Technologies or Goldman Sachs – have made from algorithmic trading systems. It’s estimated that as the market crumbled in 2008, algorithmic traders took home profits of $21 billion. Today, the majority of trading volume comes from these automated black-box systems…
But not a whole lot of focus has been paid to how retail investors can harness the power of algorithmic trading for their own accounts. I recently got ahold of Dr. Ernest Chan’s book, Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading, $60), and I thought that it’d be valuable to share some insights from it…
In Quantitative Trading, Chan breaks down how retail investors and aspiring professionals can build a profitable algorithmic trading system without needing the resources of a major financial institution.
Essentially, algorithmic trading uses computer programs to determine which stocks to trade, when to buy and when to sell. In some cases, these systems can execute round-trip trades without needing any human input at all. And despite the fact that there’s substantial competition from trading firms, Chan points out that there are still a number of exploitable strategies out there that the institutions are too big to touch.
In an industry where it normally pays to be opaque about your strategies, Dr. Chan actually shares a substantial amount of knowledge about algorithmic trading. From divulging MATLAB and Excel codes readers can use to test out their own strategies, to the library of backtested results available on the book’s companion site, this certainly is not one of those investing books that leaves you wondering what to do next.
Despite its relatively small size, Quantitative Trading is an involved read. In the book, Chan goes into detail about everything from finding a quantitative strategy to structuring an algorithmic trading business. For those reasons, the book gets relatively technical at times, particularly for those who haven’t taken a math class in a while. That said, it’s a book that most aspiring traders should find accessible if they take the time to understand the concepts presented.
Whether you’re interested in algorithmic trading for your own account, or you just want to build a better understanding of the high-frequency strategies being used by major Wall Street firms, Quantitative Trading is a good resource for any trading library…
Have a good weekend,
Jonas Elmerraji
Managing Editor, Penny Sleuth
December 4, 2010
Book Review: How to Build Your Own Algorithmic Trading Business was originally featured in the Penny Sleuth.
