OLS beta VS. Robust beta

In financial context, $\beta$ is suppose to reflect the relation between a stock and the general market. A broad based index such as the S&P 500 is often taken as proxy for the general market. The $\beta$, without getting into too much detail, is estimated using the regression: $$stock_i = \beta_0+\beta_1market_i+e_i$$ A $\widehat{\beta_1}$ of say, 1.5 means that when the market goes up 1% the specific stock goes up 1.5%. (Ignoring all the biases at the moment!)

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Flash Crash

In his book, “A demon of our design”: [asa mytpl]0471227277[/asa] Richard Bookstaber talks about the concept of coupled systems. These are systems where, once launched, are impossible to shut down. One such process is a plain take off. Once started, the pilot has no way back, he cannot stop after getting off the ground, so the only way is up. Well, in financial markets, up is generally considered good,

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Reducing Portfolio Fluctuation

THIS IS NOT INVESTMENT ADVICE.  ACTING BASED ON THIS POST MAY, AND IN ALL PROBABILITY WILL, CAUSE MONETARY LOSS.

Most of us are risk averse, so in our portfolio, we prefer to have stocks that will protect us to some extent from market deterioration. Simply put, when things go sour we want to own solid companies. This will reduce return fluctuation and will help our ulcer index against large downwards market swings. Large caps are such stocks. But which large caps should we chose? The squared returns are often taken as a proxy for the volatility so, keeping simplicity in mind, I use those.

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Intra-day Volatility Pattern

When we speak about volatility we generally refer to the relative movement of an instrument, say stock, from its center, say average. So high volatility instrument means high swings in its price process. In recent years, with the increase in “fire power”, both in computing and information flow, there has been a spike in analysis of intra-day data. Data that describes the price within the day, as oppose to the more conventional, “open” (open price of the stock for the day) and “close” quotes.

We take a look at the pattern of “swings” from stock prices within the day.

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