Dec

1

Taming time, from Sushil Kedia

December 1, 2006 |

A market moving through an entire day repeatedly between two prices, roughly encapsulating a daily normal volatility range, could imply a relatively quiet day for a long term investment manager, while the same market could mean an extremely volatile patch for a position trader over a few days, and yet also imply a great profit making spot for a scalper.

Does that not bring one to the question whether volatility is really different for different people? If indeed volatility were the same for all participants one could not have traded it in the form of a contract. What we are trading in the name of volatility is actually the price of volatility, the value of volatility similar to the value of the underlying is different for each.

If true, then to estimate an applicable calculation of volatility for oneself, one needs to first assess which layers of market flow one is most comfortable in. If markets were a giant ocean then am I most comfortable catching the long currents or am I more profitable surfing the waves that are arising from near the shores? Or am I more comfortable playing up in the waters that are getting thrusted in between a row of rocks?

Rather than define volatility over units of time, as measured in the real world over days weeks and months, am I better placed in assessing the length of moves that I am able to measure most, and what degree of variations over those lengths of moves are upsetting my plans — hence the defining unit of volatility for me? The whole issue of timing markets while not having a scientifically applicable definition of time itself to differentiate security price series is saddening. Does the approach of looking at different volatilities for different market objectives have a way of eliminating the indefinable time out?

If I do not understand time my approaches at timing are only partially rigorous attempts. Eliminating time and studying price versus price appeals as a method of timeless timing. This thought took over my mind recently yet again taking me back to reviewing all of the popular ways of plotting prices on the charts. One age old approach, not finding much favor at this moment however, is actually relying on not plotting prices against time but only against prices — it is the Point & Figure method. What possible improvements can one make on this loosely defined way of charting that takes into account a few logical constructs relating to one’s understanding or lack thereof, of volatility?

A lot of words I know, without a single formula, equation or quantifiable expression. But then a fog only turns into a raining cloud as electrical charge is induced. I am submitting this haze to the more electrical minds on the list, and hoping for a downpour.

Steve Ellison adds:

Mr. Bollingerr’s book presents an innovative approach to point and figure charting, building on earlier work by Frederick Macaulay and Arthur Merrill.

I find the point and figure approach a fertile source of ideas. For example, the forecasting literature generally argues that changes in stock prices cannot be forecast with accuracy; put another way, the best forecast of a future stock price is the current price. However, if one represents the price history as a series of moves, rather than a series of prices, one redefines the forecasting challenge to whether the next move will be up or down. Unchanged is not an option.

Point and figure data has much in common with a Galton box. For example, what is the probability that a ball that has moved three jumps to the right of its starting point will move X jumps farther to the right before moving three jumps to the left?

Since June 6, there have been 53 movements of 1% in the S&P 500 futures, 31 moves up and 22 moves down. After the 22 down moves, 14 of the next moves were up and 8 were down. After the 30 up moves excluding the most recent, 17 of the next moves were up, 13 were down.


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