V.13:09 (375-376): Detecting the Minimum Tradable Cycle by Robert Wayman
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TRADING TECHNIQUES Detecting The Minimum Tradable Cycle by Robert Wayman
Cycle theorists will tell you that there may be tradable cycles within market data. Before looking for those cycles, though, you must determine the noise level within the data. Here are some methods to do so in this, the first of two parts.
The simple moving average (SMA) is the most basic of what can be done to a pricing datastream, whether for stocks, futures, options or other financial instruments. The simple moving average is easy to calculate and allows us to quickly interpret what prices are doing. If prices are above the moving average, then the pricing data series must be advancing; if prices are below the moving average, then the pricing datastream must be declining.
But the simple moving average needs cyclic variations to do its job, and some cycles are more tradable than others. Recently, I completed a study of the cycle-driven SMA that casts light on its operation and some of its drawbacks. By looking at the SMA and determining its weaknesses, we should be able to gain insight into the operation of indicators related to the SMA as well.
When we think of trading an instrument (as opposed to buy and hold), we are implicitly thinking of cycles in the pricing series. By using a mathematical procedure called a Fourier transform, we can find out the frequencies at which this cycle's energy lies.
Cycle theorists will tell you that there may be tradable cycles within market data. Before looking for those cycles, though, you must determine the noise level within the data. Here are some methods to do so in this, the first of two parts.
The simple moving average (SMA) is the most basic of what can be done to a pricing datastream, whether for stocks, futures, options or other financial instruments. The simple moving average is easy to calculate and allows us to quickly interpret what prices are doing. If prices are above the moving average, then the pricing data series must be advancing; if prices are below the moving average, then the pricing datastream must be declining.
But the simple moving average needs cyclic variations to do its job, and some cycles are more tradable than others. Recently, I completed a study of the cycle-driven SMA that casts light on its operation and some of its drawbacks. By looking at the SMA and determining its weaknesses, we should be able to gain insight into the operation of indicators related to the SMA as well.
When we think of trading an instrument (as opposed to buy and hold), we are implicitly thinking of cycles in the pricing series. By using a mathematical procedure called a Fourier transform, we can find out the frequencies at which this cycle's energy lies.
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