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Archive for March, 2007

Make Money Online

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John Chow dot Com is a blog that helps you make money online. He is offering to link to your blog if you review his blog. If you want to learn a bit more on your opportunities as a blog owner, and have some fruits to your labor as a provider of quality content, I recommend paying him a visit.

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Efficient Market Hypothesis Continued - Weak Efficiency

In the last post, I talked about the three main categories of the Efficient Market hypothesis. In this post I’ll talk more about the weak form efficiency. To recap, the weak form efficiency basically says that current prices, reflect all past prices’ information. This means that techniques such Technical Analysis and Chart Reading can’t work.

Consider a game of heads and tails. If you get heads, you win 3.5% on your investment. Otherwise, you lose 2.5%.

headtails11.bmp

If you could play this game only once a day, how does such an investment look in the long run?

sp1.bmp

This is a very compelling graph. It shows that what people consider a trend may actually be a random event.

Studies have shown that there is no correlation between day to day returns. Could it be that trends do not exist and the market just follows what is called a random walk?

Although the above looks compelling, there are persistent statistical anomalies (although most are fading) that put doubts in the market efficiency. One, such as buying winners and selling losers, was already discussed. Another one is the weekend effect.

Studies have tried to determine the excess returns in different days of the week. A good speculation of the result would have to indicate higher returns on Mondays. This is because Monday returns would have to compensate for risk of having the stocks for the weekend. Moreover, we need to be compensated for the loss of alternative interest rate in the weekend. What were the results then?

weekend11.bmp

As you can see, Monday returns are actually lower! Although not lower enough to be able to make money, so the weak efficiency can still be a valid claim. You could still claim that the rationality hypothesis is not obsolete though, as seen in the above results.

In the next post, I’ll discuss in more detail the semi-strong efficiency. So stay tuned for coming updates.

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Financial Biases - What You Need to Watch Out For

Whether you are presented with some research claim or about to do some research yourself with financial data, there are certain biases you need to watch out for if you want to get accurate results. Not only that, when presented with financial research, you need to look into the little details, to see if the claim you are presented with is valid.

The most “popular” bias is called the survivorship bias. Here is a quick example: Suppose we want to check the claim that small caps companies have higher returns than large cap companies. We examine historical data, to further check the claim with our statistical models, and we might get to the conclusion, that small caps outperform large caps by 2% (This is a made up figure). There are a few problems though. When we are examining historical data of past prices, we would only examine companies that did not go bankrupt in the process, hence the name survivorship bias.

It is more likely that small caps companies would go bankrupt than large cap companies. It is also likely that the small caps companies who did not go bankrupt, had high returns. So in essence we took the best companies out there which result in higher returns for the small caps companies.

Another bias is the time intervals bias. This simply means that we take, consciensly or not, historical data in which different time intervals yield different results. This is actually done all the time consciensly, when hedge funds companies market their funds. They conviniently take a time interval in which they have the highest returns. If you are examining an hypothesis on past data, it’s always good to see what happens if you change the time intervals.

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