Moving average crossover trading Definition
The concept of moving average is a subject of historical data and solely indicate the average price over a specific interval. MA crossovers are a common strategy a trader can employ for trading exits and entries. While the MA crossover is a trend following strategy, it can also show areas of inherent resistance or support. With every moving trend strategy, you have two moving averages, a faster moving average such as the 50days moving average and slower moving average like the 200days moving average. And when these two moving average crosses, it’s called a crossover.
Moving average crossover strategy
The MA strategy is one that focuses on locating the middle of a trend.
The simple reason most people use the 50- and 200-days moving averages is that they are the most popular moving averages.
When the 50 days moving averages rises above the 200 days moving averages, it is called a golden cross, and when the 50 days moving average falls below the 200 days moving average, it is called a death cross.
Simple moving average crossover strategy
The basic rules are:
- Buy (go 100% long) when the market’s 50-day moving average crosses above the 200day moving average;
- Sell (go 100% cash) when the market’s 50 day moving average crosses below its 200day moving average.
In summary, you want to be bullish when the 50 days moving average crosses above the 200days moving average, and you want to be bearish when it crosses below the 200days moving average strategy.
The 200day simple moving average is slower to react as it still “remembers” the prices 200 days ago, which lags further behind than more recent price action. On the other hand, the 50day simple moving average only has price data for the last 50 days, and so reacts very quickly and ‘hugs’ the current price action more closely. A simple moving average can be used to signal current price trends and the potential for a change in an established trend. The most straightforward use of an SMA in the analysis is to quickly identify if a security is in an uptrend or down-trend.
In a simple moving average, each day’s value takes equal weight, and the effect of high values dropping out of the calculation as the average moves can undeservedly affect the result, or skew the result in a way that may not be desirable.
[quote]A downside of the simple moving average is that data must be maintained for the entire period covered by the average. For the standard 200-day moving average, this can become quite cumbersome.[/quote]Do not backtest a strategy such as the moving average crossover on just 20yeras or fewer data. You need to backtest any strategy, including the moving average strategy on as much data as possible. Because the market goes through different environments, there are some decades in which the market trends very strongly, and then there are particular decades in which the market doesn’t trend very strongly. You should not limit your backtest if you have more historical data at your disposal.
Daily Moving Average
Moving averages are an incredibly powerful momentum indicator and can be used to capture profitable trends. Moving average crossover strategy is mainly for swing traders but can also be applied to day trading if some adjustments are made.
According to a research by ETF HQ, a total of 300 years’ worth of daily and weekly data from a total of 16 different global indices were used to determine which two moving averages would produce the highest gains for crossover traders. The research revealed that among the short-term and long-term Exponential moving average, trading the crossover of 13day and 48.5day averages yield the highest returns.
The longer the period for the moving average, the clearer the simple moving average. In the end, you find a shorter timeframe moving average to be more volatile, but its reading is closer to the source data.
Moving Average Indicator
More often than not, moving crossovers serve as an indicator to buy and sell. A trader does this by either watching for price to cross whatever moving average you are using or by running two moving averages of the same price index, one faster than the other and watching for a golden cross.
Exponential Moving Average (EMA) usually serves as a bedrock in more complex technical indicators such as MACD, GMMA, and many more. The primary function of these indicators is to identify either the trend, strength of the trend, or pinpoint the time to buy or sell. Sometimes on their own, moving average crossover underperform buy and hold; this is particularly true in the US stock market. Moving average crossover are a trend following strategy, and almost all trend following strategies tends to underperform a little bit in a bull market. So almost all the outperformance happens in a bear market.
There is nothing special about the 5o and 200-day moving averages, rather than using a 50-day moving average, you can use 47, 48, 49, 51, 52, 53, 54, 55 … day moving averages, and instead of using a 200-day moving average, you can use the 197, 198, 199, 201, 202, 203, 204 ... day moving averages. There isn’t much of a difference among various moving average crossovers.
Moving Average Calculation
There are three main types of moving average: simple, weighted, and exponential. Moving average takes the averages of a specific period. For example, a 50-day moving average moves so that it always represents the average of the last 50 days.
A calculation of some of the moving averages is shown below:
Simple moving average (sma)
The simple moving average is calculated by data of whatever stock or futures contract you are following, then divide the result by the period. For example, a 20day SMA would be calculated from the most recent price (P1) to the oldest price (P20) thus:
- SMA = (P1+P2+P3…P18+P19+P20)/20
The simple moving average can be calculated on a different time frame.
Weighted moving average (wma)
The weighted moving average places more emphasis on recent prices as opposed to past prices.
The formula is shown below:
- WMA1 = (P1×P2×P3…P18×P19×P20)/(20+19+18…+3+2+1)
Weighted moving average moves a lot faster than simple moving average because of its emphasis on recent prices.
Exponential moving average (ema)
This is the most complicated calculation of all the moving average calculations: An example of a 10-day EMA calculation is shown below.
- EMA1 = P1 + (1-2/(10+1)) × P2 + (1-2/(10+1))2 × P3 × +… + (1-2/(10+1))9 × P10 1 + (1-2/(10+1)) + (1-2/(10+1))2 + … + (1-2/(10+1))9
The primary function of moving averages is to give smooth data to make trends more transparent, discernable, and they are used to construct market indicators and assist in the interpretation of price charts.
It is worthy of note that exponential moving averages (EMAs), which weight most recent prices heavier than earlier prices, perform better overall than Simple Moving Averages (SMAs), which weight all prices in the timeframe equally.
Other moving averages are:Triangular moving average
Triangular moving averages emphasize the weight in the middle part of the price series. They help to further smothen a simple moving average. The time frame (periods) used in the triangular moving average varies, depending on whether or not an odd or even number of periods is used.
It is calculated thus:
- Add 1 to the number of periods selected in the moving average (e.g., 10 plus 1 is 11);
- Divide the sum from Step 1 above by 2 (e.g., 11 / 2 is 5.5);
- Approximate the result of Step 2 to the nearest integer (e.g., round 5.5 to 6);
- Using the value from Step 3 (i.e., 6), calculate a simple moving average of the closing prices (i.e., a 6-period SMA);
- Using the value from Step 3 (i.e., 6), calculate a simple moving average of the moving average calculated in Step 4 (i.e., a moving average of a moving average).
Variable moving average
A variable moving average is an EMA that automatically utilizes the volatility of data to adjusts the smoothing percentage.
Most moving average calculation methods do not consider trading range versus trending markets. During trading ranges (when prices swing sideways in a narrow range), shorter-term moving averages tend to produce numerous false signals. In trending markets (when prices swing upward or downward over an extended period), longer-term moving averages are generally slow to respond to reversals in trend. The automatic process of adjusting the smoothing constant allows a variable moving average to adjust its sensitivity. Hence, it performs better in both types of markets.
A variable moving average is calculated thus:
- (0.078 (VR) × Close) + (1 – 0.078 (VR) × previous day’s Moving Avg.)
- VR = The Volatility Ratio
Conclusion
Even the simplest of strategy can be super effective in the right conditions. But, in the wrong condition, they are useless. The key to having a successful strategy is to assess the market condition and use the strategy that suits the market conditions. It is important to note that the moving average crossover is essentially a trend following strategy, and trend strategy does better when the market is in a powerful trending position, and does worse when the market is not trending.
