You Analyze, I Analyze, We Analyze. But we disagree (Part 2)

Having discussed about the Economists and Analysts and their frailties, I would like to discuss how we can approach analysis. But before i get started I would like to highlight a great article from AR, it basically sums up the lack of transparency of punditry. They hence made a suggestion.

Given these two eternal truths, pundit scorecards are a necessary feature that would allow viewers to help judge the credibility of pundits.  However scorecards are not sufficient.  Until we are allowed to, as they say in math class, see the work, we will be somewhat at a loss when those predictions turn out true or false.

Hence do not accept anybody’s forecast or analysis unless they show you their results and most importantly their underlying hypothesis behind their ideas.  Although it is unlikely anyone will give you their full details but knowing its underlying philosophy can help one to judge whether its feasible or not.  Its also a good idea to track what they are saying. For instance at CXO advisory they track, investing gurus and how they are performing based on public available information.

Some may use quantitative methods, whilst other might use qualitative ones. The qualitative analysts will always try to point out that heck, these mathematicians and there formulas will never be able to quantify everything that is happening around and I have a better ‘feel’ of the markets.  That statement, is hundred percent true, but note the only way to have a traceable performance is to at least know about a persons returns year on year.   In addition, quantitative methods allows people who are fresh to the style or way of trading to understand its peculiarities by testing it under various circumstances. Hence I do believe that quantitative work is important to get things started and the gain perspective. However it is not to say that qualitative work is not important,  I will touch on that later. But for now I give a brief start to quant work.

For every quant work you are starting off with a hypothesis and list of assumptions.  For instance you suggest that momentum drives stock prices higher. Well that might be true but for what time frame? Is it the same for all stocks or asset classes, are other factors that work together indicators or factors. You see its not enough to come up with a strategy or idea, the point here is to test it under different conditions. For instance Cam Hui pointed out in one of his articles where he discussed about research on timing models based on seasonality across various asset classes that

Don’t use a single tool indiscriminately
A number of years ago I did some research into seasonality effects on selected industries. We found that there was a weak seasonal effect for US retailers around Black Friday. In addition, turn-of-year effects have been cited by many researchers in many markets around the world. CXO Advisory recently did some work on gold and gold stock seasonality, their conclusion was that you get very different conclusions depending on what test period you chose.

Seasonality is a tool that can be used in certain circumstances, but it’s not a universal tool. Don’t fall into the trap that if you have a hammer, every problem looks like a nail.

It boils down to once again, common sense. Do not simply believe your regression model, it must fit logic in the real world.  Sometimes two contradictory techniques can even come together. For instance on one hand with momentum which says strong stocks will continue higher, and we have mean reversion which states that strong stocks tend to get overbought and hence will pullback when it gets overbought. In some research it showed that momentum works in the longer term whilst mean reversion works in the shorter term.  Hence this neatly reconciles opposing views another article goes on to state that actually the momentum factor has a six month lag where it momentum 6 months ago actually drives a stock more meaningfully . This is important as there many ways to invest or trade therefore two systems with a great track record a can have opposing positions on the same instrument.  But most important still is to check for the validity and logicality of such ideas.

Having discussed about quant studies, now we move on to branch out to two schools of thought technical analysis and fundamental analysis. Both fall under quant studies as they can be quantified the only difference is that the first uses data from historical price and volume was the latter using information from the balance sheet.  CSS analytics has done well stating the case for both technical and fundamental analysis and where they work and their limitations.  In essence he states that technical analysis works well because of feedback loop in bull or bear markets, hence price action captures the mood and sentiment of the market. However at extremes of a bull or bear markets fundamentals and possibly sentiment indicators triumph because it reveals the overshooting of expectation by its participants. Interestingly a recent paper has even revealed that by combining both fundamental and technical analysis can improve results even better.

To wrap up I will touch on qualitative analysis, I still believe that it is important especially when identifying sentiment tops and bottoms.  For instance back in late 2007 someone pointed out that they saw kitchen bowl washers rushing to the stock exchange to open accounts to trade.  This kind of euphoria highlights extreme optimistic sentiment and we all know what happens next.  Meanwhile the doom and gloom that surrounded late 2008 and early 2009 allowed for a chance to wash out weak hands and for crazy market surge, this kind of sentiment was very well documented by Carl Futia.   In addition, Dr Brett has time and time again pointed out the importance of intuition in his short term trading.  What does all this mean, can intangibles be useful, the short answer is yes. However to get that kind of feel, one must experience the market many times to finally get the feel, for instance Dr Brett points out how sportsman make their movements second nature after repeated practice, that is how they achieve optimum performance in real life. So if sportsmen are training to better themselves. Should investors or traders do the same before entering the market?

Part 1

Part 3


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3 Responses to You Analyze, I Analyze, We Analyze. But we disagree (Part 2)

  1. Pingback: Sunday links: market repetition Abnormal Returns

  2. Pingback: You Analyze, I Analyze, We Analyze. And we disagree. « Financialfreezeframe's Blog

  3. Pingback: Blog Profile: CXO advisory « Financialfreezeframe's Blog

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