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How many trades are needed for statistical validity?

Many traders ask how reliable is their track-record as far as statistical validity goes.

They may see some statistics on seasonal trades showing a market was up from April to June during 12 of the last 14 years.

They may have experience with their own trading system showing 8 of 9 winners following say a 5 unit moving average crossing over a 9 unit moving average.

None of these are valid from a statistical validity standpoint. That's because according to mathematical experts and statisticians a minimum of 30 occurrences are required for statistical validity.

Please keep this in mind when evaluation a trading system. Anything less than 30 samples is not statistically accurate.

Secrets of time durations of profitable & losing day-trades

Click-here for David Green's Blog

Most successful daytrades last approximately 7-minutes. That assumes the trader is using a reasonable profit objective and exiting the trade as his profit target gets hit.

Most losing daytrades last approximately 45-minutes. That’s because the trader relies on hope once he sees the trade appearing to fail. He hangs on to the losing trade hoping it will turn around, finally the trade loss becomes too big, forcing him to exit the losing trade, unfortuntely likely resulting in considerably more losing trades.

Secrets of why Seasonal Trades Frequently Fail

Most seasonal trades fail. I am sure you have seen all the fabulous statistics on so called “seasonal trades” by the seasonal trade experts who sell books and newsletters on this type of commodity trading. For example, statistics showing if you would buy April Live Cattle on a specific date in October and hold it until a specific date in February, it results in a nice profit 18 out of the last 20 years.

The truth is this type of trade is of dubious value and frequently fails. The reason is the dates used in the statistics are average dates based on computer analysis of the trades. This is very similar to optimization of technical indicators, something which is also of very dubious value. The dates may be off by a wide margin, either too early or too late depending on the year. This is why the trader finds it difficult, if not impossible, to make money on seasonal trades.


A Simple But Very Profitable Approach For Trading Commodity Futures

Click-here for CommodityDaytrading.com

We have been using this trading methodology to trade the commodity markets successfully for some time with the possibilty of achieving considerably more winning trades vs losses. The trading method is really quite simple and easy, but can be surprisingly profitable.

It involves buying higher swing-lows and selling lower swing-highs. Also known as pivot-points.

A definition of these swing-highs and swing-lows is appropriate here:

A swing-high is a high bar with lower bars on both sides of it.

A swing-low is a low bar with higher bars on both sides of it.

The more lower bars to the left of a swing-high the better.

The more higher bars to the left of the swing-low the better.

That makes them more significant and presumably more powerful swing points. However, only one bar on either side is acceptable (but two or more to the left are usually stronger signals).

My trading methodology requires two (or more) consecutive swings, with the second one being a higher swing-low than the preceding one for a buy. Alternately, the second swing-high must be a lower swing-high than the preceding one for a sell.

The actual long trade entry takes place on a buy-stop two ticks above the high price of the last bar (the bar following the swing-low pivot bar), for a buy.

The short trade takes place on a sell-stop at two-ticks under the low price of the last bar (the bar following the swing-high pivot bar), for a sell.

Your stop-loss order is placed 6-ticks under the lowest price of the last swing-low bar on a long trade.

The short trade stop goes 6-ticks above the highest price of the last swing-high bar. You can make some really outstanding money using this simple, but very effective commodities trading methodology. By David Stone

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