The key to universal seasonality was that it was a seasonal advance. You cannot use the results in a backtest of the period in which you are trying to discover seasonality.

The problem with this type of seasonal study is the assumptions that must be made in the analysis. Suppose a market rises in price in the selected time period in 21 of the 23 years from 1980 to 2002. Would a trader have known to make these seasonal trades based on the information he had at the time a trade was to be made? operation? Let’s say, for example, in 1985, five years after the carefully selected period, that the market had appreciated during this particular time period in only six of the 10 years from 1975 to 1984. Few traders would have taken the trade then, even though in the original analysis 1985 may have been the most profitable year.

Even assuming the same trades would have taken place, using a static seasonal relationship in a forward simulation is a flawed approach. The correct way to study seasonality is with a pure seasonal dynamic of advance. It is necessary to use all previous years or a window of previous years to operate the current year and then move the window forward. It is also important to use the same rules to define seasonality and make business decisions for each market.

This package contains multiple types of seasonal calculations from the simplest average return over the next N bars to my Ruggiero/Barna Seasonal that I developed in 1996. This amazing indicator still works well today.

Two unique measures in this package are seasonal for both trend and volatility. I originally studied this in 1996 and it was a very powerful market trend around the same time each year.

Herramientas Estacionalidad - Quantified Models

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This package contains multiple types of seasonal calculations from the simplest average return over the next N bars to my Ruggiero/Barna Seasonal that I developed in 1996. This amazing indicator still works well today.

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