News site Forex Magnates brings to light another entrant in the social trading arena called ForexGlobes. I signed up to see if this site has anything new to offer in the increasingly-competitive social trading world. Unfortunately, it’s still in beta, so some critical components appeared to be missing (or at least, I could not find them): it doesn’t appear that signal providers will be compensated for their signals, so sharing trades is purely for bragging rights at this stage. In addition, while ForexGlobes claims to be partnered with several forex brokers, I could not for the life of me figure out how to link my live account. In addition, it has a strong resemblance to Tradeo in look and feel, so the jury is still out as to how ForexGlobes intends to differentiate itself. In any case, here’s the bottom line from Forex Magnates:
MIT will run an experiment to see if social media investing improves performance. It’s doing so by giving $100 each to 10,000 Asians to trade forex on eToro by following high-performing traders and copying their trades.
Over at Abnormal Returns is an interview that Tadas Viskanta had with Dr. Wesley Gray of Turnkey Analyst about his book, Quantitative Value. It makes a great case for systematic investing (i.e. investing based on rules, not intuition) and why removing emotion from the investing process is really the best way to success in the investment world. However, he goes a step farther by differentiating between investing based on logic and based on empirical data. The argument focuses on value investing, but I think the case presented is applicable to all styles of investment.
Jay Kaeppel at Optionetics.com has a semi-humorous post about a new algorithmic trading system that he invented today (appropriately called JK Today). On the surface, at least, it appears to be a viable system with good profit potential. In short, he uses the 4% Zweig swing as a directional indicator, and semiconductor to inverse Nasdaq-100 ratio as an overbought/oversold indicator. Again, see the post for the details and his calculations. However, the real point of his post is to show some of the thought process involved in developing a set of rules for a trading system, and what is required of the trader to ensure that the trading system is a success. Here are the performance stats, just to entice you to read it all.
Matt Radtke at Tradingmarkets.com has a nice 6 part series on how to build a trading strategy, from conceptualization to implementation. This is a great place to start for those just beginning to learn about the world of algorithmic trading. Make sure to try out the techniques detailed by writing down your trading rules or testing them on data in Excel.
- Central Thesis
- Defining a Universe
- Additional filters
- Exit methods and stop losses
You can download historical stock data from Yahoo Finance to get started.
I recently came across a great blog run by fellow Collective2 system developer Sanz Prophet with a treasure trove of information for those just starting out with algorithmic trading. Check out the following posts:
- A quick survey of backtesting tools, including Amibroker, Quantshare, Multicharts, and IQBroker.
- Backtesting a multi-strategy algorithm in Quantopian.
- Running Quantshare in the cloud (Amazon EC2).
- An intro to Amibroker.
A great resource. Visit his blog for more.