Finding seasonal spreads - forex trading systems for sale

Finding seasonal spreads ~ forex trading systems for sale

I am pleased to introduce guest blogger Paul Teetor for todays article.

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Finding Seasonal Spreads

By Paul Teetor

A seasonal spread is a spread which follows a regular pattern from year to year, such as generally falling in the Spring or generally rising in October. To find seasonal spreads, Ive been using ANOVA, which stands for analysis of variance. ANOVA is a well-established statistical technique which, given several groups of data, will determine if the groups have different averages. Importantly, it determines if the differences are statistically significantly.

I start with several years of spread data, compute the spreads daily changes, then group the daily changes by their calendar month, giving me 12 groups. The ANOVA analysis tells me if the groups (months) have significantly different averages. If so, I know the spread is seasonal since it is consistently up in certain months and consistently down in others.

The beauty is that I can automate the process, scanning my entire database for seasonal spreads. A recent scan identified the spread between crude oil (CL) and gasoline (RB), for example. The initial ANOVA analysis indicated the CL/RB spread is very likely to be seasonal. This bar chart of each months average daily change demonstrates the seasonality. (Click on the graph to enlarge it.)

The lines show the confidence interval for each months average. Notice how May and June are definitely "up" months because their confidence interval is entirely positive (above the axis). Likewise, November and December are definitely "down" months. For all other months, we cannot be certain because the confidence interval crosses zero, so the true average change could be either negative or positive. The conclusion: Be long the spread during May and June; be short during November and December.

For more details, please see my on-line paper regarding ANOVA and seasonal spreads.

- Paul Teetor

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Seasonal trades in natural gas and gasoline futures - forex day trading strategies work

Seasonal trades in natural gas and gasoline futures ~ forex day trading strategies work

In my book, I mentioned 2 seasonal trades in natural gas and gasoline futures that have been consistently profitable for 14 years. (Mentioned here and here also.) And not only in backtest: I paper-traded them in 2006, and actually traded them in 2007-8, and all 3 years were profitable. How did they fare in this recession year? Quite poorly.

Depending on your exact entry and exit points, the gasoline trade lost about $2,500 per contract of RB. The natural gas trade lost about $7,700 per contract of NG.

You may have heard that natural gas price is at a 6-year low. In fact, we are not seeing any increase in industrial demand for natural gas. Apparently, somebody has forgotten to tell the nations industrialists that an economic recovery is supposed to be under way.

Will I enter into these seasonal trades again next year? You bet I will.
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Seasonal trades in stocks - forex trading system best

Seasonal trades in stocks ~ forex trading system best

Readers of this blog have seen my discussions of various seasonal trades in commodities futures (e.g. see this article). Recently, Mark Hulbert of the NYTimes drew our attention to a seasonal trade in stocks. The strategy is very simple: each month, buy a number of stocks that performed the best in the same month a year earlier, and short the same number of stocks that performed poorest in that month a year earlier. The average annual return is more than 13% before transaction costs, and since it is market neutral, this already considerable return can be leveraged to 2 or 3 times higher. Also, since it turns over the stocks only once a month, transaction costs should not be a major problem. The strategy was developed by Profs. Steven Heston and Ronnie Sadka, and details can be found online here. Besides its simplicity, the strategy is not as affected by survivorship bias in the data set as a mean-reverting strategy, since survivorship bias would tend to lower its backtest performance by excluding very poorly performing stocks that we would short. All in all, it seems to be a market neutral strategy made for retail trading!
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