A market that is trending up should have higher peaks and higher valleys. The majority of bars should also have higher highs and higher lows. In a down trend the market should have lower valleys and lower peaks and the majority of bars should have lower lows and lower highs.

When a market is in consolidation (bracketing/flat) the price will generally oscillate in a broad range. Traders who are watching for the breakout will monitor the security for a qualified break. They may place a straddle traded to catch the move regardless of whether it breaks up or down.

There are traders who specialize in trading consolidation. I don't however recommend it to new traders simply because they get whipsawed too much.

The changing prices of a security from tick to tick, day to day or whatever time period you are looking at may seem random, but there are ways to smooth out this randomness. One way trader's look to make sense from this seemingly unpredictable sea is moving averages.

If you are going to trade professionally it is vital that you can identify trading opportunities. To this end the concept of moving averages is a very useful tool to understand.

A moving average (MA) is a way to try and eliminate or minimize the fluctuations of the numerical value of price fluctuations we are observing.

This will help us identify the underlying value. Moving averages are generally calculated using the closing price.

What, in effect, the moving average does, is to eliminate the fluctuation of price in all time periods below the number which is chosen for the average. i.e. a 4-day or 9-week moving average eliminates the presence of price fluctuations for periods up to 4 days or 9 weeks respectively.

A 200-day moving average eliminates the presence of daily price fluctuations for periods below 200 days. This smoothing effect of price change increases as you use longer and longer periods as the average.

There are four commonly used moving averages: simple, smoothed, weighted and exponential.

Simple moving averages give equal weighting to each time period's price.

In an attempt to give more importance to more recent prices, different types of moving averages have been developed. These include smoothed, weighted and exponential moving averages.

I won't go into their complex mathematical derivations of these. Why not? Because detailed retrospective studies of their use has shown that the simple moving average statistically outperforms or equals the use of these newer, biased moving averages.

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