Moving averages (MAs) are one of the most widely indicators in Technical Analysis, or TA for short. In traditional stocks and cryptocurrencies like Bitcoin and Ethereum, TA utilizes existing data to make more informed decisions on when to buy and sell for traders.
Moving averages smooth out price charts and filters out noise to create an indicator that identifies trends.
The most popular types of moving averages are:
- Simple Moving Averages (SMAs) are calculated by averaging trailing prices (daily, hourly, weekly) for any past periods. The most popular SMAs are 10 day, 20 day for short term traders and 50 day and 200 day for longer term traders.
- Exponential Moving Averages (EMAs), unlike SMAs, assign more weight and value to recent prices. As a result, the EMAs are responsive to sudden price fluctuations and more favored by short term traders. The most popular short term EMAs are 12 day, 26 day, and 50 day. The formula for EMA is typically as follows:
EMA_TODAY = PRICE_TODAY * 2 / (1 + LENGTH_OF_PERIOD) + EMA_YESTERDAY * (1 - 2 / (1 + LENGTH_OF_PERIOD))
Using Moving Averages in Crossovers
Traders utilize moving average indicators to implement different rules-based trend trading strategies - the most favored among traders being crossover strategies. Crossovers occur when price of the asset (BTC, ETH) or another MA indicator moves from one side of the MA to the other. This crossover signal indicates a shift in momentum and determines when traders should exit or enter a position.
In addition to price, trader can utilize multiple MAs as crossover signals. For example, when a short term MA crosses a long term MA from below, traders refer to it as a golden cross as confirmation of a long term bullish market. When the opposite happens, traders refer to it as a death cross as confirmation of a long term bearish market.
MAs all use past prices and are subject to varying degrees of lag. Longer period MAs (past 100 days) will respond slowly to new information than shorter period MAs (past 20 days). Because of lag, traders use additional filters to avoid false positives, confirm trends, and minimize fees from constantly trading. These filters include tolerance around crossovers, confirmation periods, or minimum time interval between trades.
In a hypothetical example, if the price of ETH crosses over to below the 20 Day SMA, traders sell ETH to a stable asset to prevent further declines in the downtrend. To further reduce false positives, the trader may apply a filter of 6 hours to confirm the signal and minimum interval of 4 days to confirm trend reversals.
View the ETH20SMACO, the first Set that implements a crossover strategy on the 20 day simple moving average here.