Bitcoin Trading Strategies

Moving Averages

As I mentioned in previous articles, the best trading systems usually contain the fewest number of rules. Based on my four decades of trading and investing, I have discovered that complicated systems with complex mathematical formulas rarely produce long-term profitable results. Instead, the most consistently profitable systems are based on simple trading methods with very few rules. For example, moving averages have produced reliable performance results for many years. What is a moving average and why is it one of the most popular trading systems? Let’s discuss the details.

A moving average is a mathematical tool used to identify the trend of a financial asset. It helps to smooth out price data by creating a constantly updated average price. For example, the impact of a large, short-term price fluctuation can be reduced by calculating a moving average on a daily basis. It helps filter out the day-to-day “noise” that often occurs in speculative assets.

Moving averages are most commonly used with stocks, commodities, precious metals, forex and cryptocurrencies. The indicator is popular because it provides traders with an easy way to determine the underlying trend of the market. Despite its popularity, the indicator is certainly not perfect. The biggest drawback is the fact that moving averages are lagging indicators, which means that all of the collected data is based on past prices. Therefore, a moving average has no predictive ability to forecast future price movement. Instead, the indicator can only be used to study previous price behavior.

Most traders are willing to overlook the shortcomings of the moving average because it is one of the easiest ways to determine the trend of the market. As a general rule, traders prefer simple tools and indicators. This explains why moving averages are so popular.

There are three types of moving averages: simple moving average (SMA), exponential moving average (EMA) and weighted moving average (WMA). Let’s briefly discuss each moving average.

Simple Moving Average (SMA) is also known as an arithmetic moving average. It is calculated by computing the average price of a security over a specific number of periods. For example, a 5-day SMA is the sum of closing prices divided by five. Old data is dropped as new data becomes available. As an example, let’s review the 5-day simple moving average of gold.

In order to calculate the simple moving average, we must collect five days of price data. At the end of the day on 4 May, the moving average is calculated by simply adding the closing price of the previous five days and dividing by five ($9,285.1 / 5 = $1857.0). Calculating the moving average for 5 May, requires us to drop the closing price from 28 April and replace it with the closing price for 5 May. This will give us a new 5-day SMA for 5 May.

Exponential Moving Average (EMA) is a slightly different variation of a simple moving average. The distinguishing characteristic of EMA is the fact that it places more importance on recent price data. For example, when EMA is calculated, it places a higher weighting on today’s closing price versus the closing price from five days ago. This is the main difference between SMA and EMA. SMA gives an equal weighting to each day within the selected time period. For example, with SMA, today’s closing price is just as important as the closing price from five days ago.

Weighted Moving Average (WMA) is fairly similar to EMA. However, the main difference between WMA and EMA is based on the fact that WMA assigns a specific weighting to each closing price used in the moving average calculation. The most recent closing price has the highest weighting, while each prior closing price has progressively less weight. This type of calculation has the effect of allocating a greater level of importance to the most recent trading days in comparison to previous trading days. Consequently, WMA tracks the current price level much more closely than other types of moving averages.

Chart #1 contains six months of trading activity for silver. The chart displays SMA, EMA and WMA. At first glance, you will notice that all three moving averages are fairly correlated. In other words, they are all moving in the same direction with very little divergence between each moving average. This is an indication that all moving averages are conceptually designed in the same manner.

My moving average system is based on SMA. Please review the rules for my SMA system.

SMA Trading System

  • Buy signal occurs when the price trades above SMA for two consecutive days.
  • Sell signal occurs when the price trades below SMA for two consecutive days.
  • Protective stop is 50% of the trading range on the day of entry.
  • Liquidate the trade when SMA generates a new signal.

Chart #2 displays six months of trading activity for BTC. The green line represents the 20-day SMA. A buy signal was triggered on 4 October, when the price remained above the SMA for two consecutive days. The trade was liquidated on 18 November, after the SMA system generated a reversal signal.

SMA Buy Signal

  • Buy at $49,021 on 5 October (on the opening)
  • Protective stop = $47,775
  • $49,475 – $46,982 = $2,493 x 50% = $1,246 ($49,021 – $1,246 = $47,775)
  • Trade was liquidated on 18 November on $60,088
  • Profit = 11,067 points ($60,088 – $49,021 = $11,067)

SMA Sell Signal

  • Sell @ $60,088 on 18 November (on the opening)
  • Protective stop = $61,316
  • $61,077 – $58,621 = $2,456 x 50% = $1,228 + $60,088 = $61,316
  • The short position is still active
  • The system will remain short until SMA produces a reversal signal

As you can see from Chart #2, the SMA system is very profitable when the price of the underlying asset is trending in the same direction for an extended period of time. BTC has been drifting lower since mid-November. The system has captured the majority of this move.

The SMA system is a good example of how the trading community can benefit from using moving averages. Traders have been using moving averages for 120 years. Despite its inability to accurately forecast future price direction, the global trading community still loves to use this technical indicator. Most likely, the popularity of moving averages will continue well into the future.

Profitable Trading Does Not Require A High Winning Percentage

During the past four decades, I have read many books about trading and investing. My favorite investing book is Market Wizards by Jack D Schwager. In this book, Schwager interviews several of the world’s most successful traders. While conducting his interviews, Schwager discovered that the overwhelming majority of these traders had a winning percentage of approximately 35%, which means that 65% of the trades are losers.

These numbers are nearly identical to my own personal results. Since I began trading in 1989, my winning percentage is approximately 40%. Of course, this means that I lose money on 60% of my trades. The numbers are even worse during the past five years. Since 2017, 75% of my trades are losers. I cut my losses very quickly, which means that very few trades will generate a profit.

Despite my low winning percentage, I still manage to generate a decent profit. Therefore, please remember that it’s not necessary to have a high winning percentage in order to become a successful trader.

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