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This was posted on Decisionpoint.com as a sample.
The point that grabbed my attention was that systems give more false signals
because of increased volatility even though more opportunities are created.
Comments?
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JOHN BOLLINGER'S CAPITAL GROWTH LETTER
3/10/00
Capital Growth Topics #316: Volatility
On the lower right-hand corner of the front page of Wednesday's Investor's
Business Daily there was a chart depicting volatility on the NASDAQ. The
methodology was to calculate the average daily range for the NASDAQ
Composite for each year from 1982 to date. In the period 1982 to 1995
volatility ran near or just below 1%. Starting in 1996 it broke out of that
range and has steadily risen to 3%, a tripling of the prior normal range.
A study conducted by us of the S&P looking at a 10-week average of the
weekly ranges shows a similar pattern with volatility increasing by about
0.4% per year. A study of the NASDAQ Composite shows a slightly higher
annual rate of increase, 0.6% per year.
The IBD chart gives the impression of an exponential increase in
volatility--that is a to say a rate of increase that is growing every year.
Our study suggests that this is not the case. I suspect that this illusion
is largely due to the last period, 2000, which includes only two months of
extremely volatile data in the average. A larger sample will most likely
bring the average range lower and more in line with the linear rate of
increase observed for the S&P.
The increase in volatility has many implications. To point to a few:
Traders have more opportunities.
Investors are more nervous.
Stops loss orders are hit far more often in the course of "normal" trading.
The signal-to-noise ratio is increasing. (This makes analysis harder.)
Indicators behave differently than they have in the past.
Systems give more "false" signals.
There is more to talk about on CNBC.
Market makers find their jobs harder and more profitable.
One example of the changes demanded by increased volatility is the
EquityTrader risk-adjustment procedure. In the past we calculated positive
and negative betas. These measure a stock's responsiveness to up and down
moves in the market. (Normal = 1.0) We then used negative betas greater than
one to penalize the ranking of stocks whose downside volatility was greater
than the markets. Well, as volatility has risen betas have risen too and our
risk-adjustments became too great. So, we had to go to an adjustment
procedure that looks at the differential between positive and negative betas
rather than the negative beta on its own.
For a long time my forecast has been for increasing volatility and that
remains my forecast. Be careful out there!
John Bollinger, CFA, CMT
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