Blog Profile: Automated Trading System, Trend Followers Dream Blog

This is a great place for all mechanical traders, especially those with an inclination for trend following methods.  As with many traders Jez Liberty faced many challenges and a big drawdown early in is trading life.

My main goal

My first priority now is to build a “simple” long-term end-of-day trend following system for futures while accumulating enough capital to trade it. And I intend to document that journey through this blog, hopefully connecting with or helping traders with similar interests.

Some of his noteworthy works include a monthly reporting of the state of trend following. This is where he gives a wrap up of all the common trend following techniques that is widely used and also constructs a composite index out from these strategies and reflects upon their performances.  In addition, he also follows a list of trend following hedge funds and checks on their performances too.

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Blog Profile: Falkenblog, Making sense of Risk

A former hedge fund manager who hasn’t been able to work due to his former employer, Telluride Asset Management in Minneapolis, suing him for stealing the firm’s trade secrets and violating its confidentiality agreement. Falkenstein had created trading algorithms for Telluride during his two and a half years on the job there, and the firm believed he was planning to use the same techniques to trade stocks for a fund he wanted to establish.  Hence instead, Eric Falkenstein has been devoting time to his blogging and research.

Amongst his research, I found the most interesting one being the one on risk. In his article “Why Take Risk?” he discusses that risking taking in general taking in general is not compensated.  He notes that:

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Blog Profile: The Psy-fi Blog, A Sideways Look at Psychology and Finance

A brazen no holds bars blog whereby the author highlights various behavourial biases of our financial markets and its participants.

Some common behavourial bias he notes are

1) Overconfidence and Over Optimism (We think that we are of above average ability and therefore will make more money compared to the average investor.)

2) Hindsight Bias (a believe that the event that we witness earlier was predictable than before it took place, for instance we think we can sidestep a financial crisis.)

3) Loss Aversion (we tend to more risk averse when protecting gains compared to chasing our recovering our losses, for instance we poorly manage risk when our portfolio head south and we are quick to take profits when  we see them.)

4) Regret (you regret missing a market surge? or have you ever regretted buying a particular stock that is going south?) Read more of this post

Blog Profile: Rajiv Sethi, Academic Reflections of Current Markets

A Professor of Economics, Barnard College, Columbia University & External Professor, Santa Fe Institute. Rajiv Sethi helps to tie in academic work with current market events. He seems to also be a rather open minded professors which engages the econblogosphere in a meaningful way and also supports them in their logic and well displayed ideas.

He has made some insightful on the recent flash crash on 7 May.

The point I was trying to make is this: the problem lies not so much with the method of trading (algorithmic or otherwise) but with the underlying strategies that are being implemented. Algorithmic trading allows technical strategies to profit and proliferate, and markets dominated by technical analysis will tend to be unstable. If destabilizing strategies are prevented from taking losses when they misfire, the result will be more frequent and significant departures of prices from fundamentals. Hence my concern over the cancellation of trades. Read more of this post

Blog Profile: CXO advisory, Comprehensive research on all forms of investing/trading

CXO Advisory is a wonderful place to get yourself started with investing and trading as they provide explore all quantifiable types of analysis be it being fundamental, technical, behavourial and many other forms of trading/ investing. Some of their noteworthy ideas are also featured here

An interesting section of the blog helps to track a large set of investment gurus from TV, newsletters and bloggers and tries to quantify their accuracies.  As mentioned in my earlier posts, talk is cheap, its easy to justify any direction of the markets be it up or down.  Results are the only way showing ones ability.

There is also a notable column, investing demons where it discusses whether financial market experts can beat the market. There are six aspects to this column

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Blog Profile: Macroresilience, Common Sense Economic Thought

A place of common sense and wisdom, Macroresilence helps to shed light and logic behind the problems of our financial system, and overview of  significant market events and explaining its complexities.  He was also cited by Rajiv Sethi as being an anonymous blogger that understood economics better than some professors.

Some of his suggestions for a better financial systems include paying off whistleblowers in order to uncover fraud:

The focus must be not to keep whistleblowers from losing their jobs but to compensate them sufficiently so that they never have to work again. As it happens, the scale of fraud in financial institutions means that this may even be achieved without spending taxpayer money. The whistleblower may be allowed to claim a small percentage of the monetary value of the fraud prevented from the institution itself, which should be more than sufficient for the purpose.

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Blog Profile: CSS Analytics, Adaptive Systematic Trading

The premier place when if you want to be learning about systematic trading.  Its interesting to note that the author David Varadi was formerly a research analyst who used to condemn technical analysis, but made a complete u-turn when he understood the basis of technical analysis.

One of his regular rants include his discussion on creating adaptive indicators.  Basically it means that no matter what your indicators you must include them they cannot be static and they must represent the current state of the market.  The most important part of such an algorithm should be:

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