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What is Technical Analysis?

What is Technical Analysis?

What you'll learn

  • The concept of volatility
  • Understand Moving Averages
  • Understand what Relative Strength Index

If you’ve read every article in Learncrypto’s section introducing how to trade cryptocurrency you should, by now, understand two key distinctions. Taking long term positions based on Fundamentals - as an Investor - and short term decisions based on Technical analysis as a Trader, looking to take advantage of crypto’s price volatility.

Technical Analysis requires interpreting price movement and volume. So far we’ve looked at the basics of price - where it comes from, the role of exchanges and the kind of basic information provided as part of the price formation process.

This led to exploring the most fundamental aid to analysing price - the price chart - through candlesticks and volume metrics. 

This layering of information allows you to view price history as a story and try and interpret the patterns and signals, to understand where the price narrative moves next. 

On their own, however, these basic tools cannot tell you the whole price story, and provide enough detail to predict future price, which is, after all, your objective.

So the next step is to start adding indicators to your trading tool kit to better quantify price movement, which means understanding volatility.

Measuring Volatility

Returning to bitcoin as our example, the amount by which its price goes up and down is measured by Volatility. Volatility is what determines the level of risk you take on in trying to make a successful trade. 

If you look at a daily bitcoin chart by eye, you’ll see peaks and troughs that look a bit like a seismograph, which is a useful analogy. Each movement is a reaction to the intensity of buyers and sellers, in the way a seismograph illustrates the intensity of tectonic activity. 

The literal definition of price volatility is the standard deviation of daily % changes. In simple terms, how much does the price deviate each day from the average.

Though it is important to understand how to calculate Bitcoin Volatility, measures are freely available online, here’s one example for 2020. The majority of the year the Volatility Index was somewhere between 2 and 4%, but with a huge spike in March/April, as it hit over 10%.

Returning to our earthquake analogy, this is like a 9 on the Richter scale, a major event. This was the reaction to the impact of Covid19 on the broader financial markets.

A Volatility Index of over 10% literally means theoretical returns of that size for daily trades within that period. For comparison, the volatility of gold averages around 1.2%, while other major currencies average between 0.5% and 1.0%.

The Volatility can be even greater when looking at an even shorter time frame, as it is simply an average, which means that on certain days the risks of trading are very high. 

The seismic event of Covid19 is virtually impossible to predict, but these kinds of market shocks must be expected. If you decide to trade regularly then there will be days when you are likely to experience significant swings in both directions.

As volatility works by looking at the variance in average bitcoin price, charts enable you to automatically plot what are known as moving averages, for standard periods, and overlay the spot price. 

Moving averages are one of the first indicators available within the technical analysis toolkit. They essentially allow you to view today’s price in a wider context. The longer moving average timeframe the more valuable the conclusion.

Moving Averages

A Moving Average is literally the average price measured for a fixed period that moves over time. It is best understood via an example.

Bitcoins seven day moving average will average the price for the previous seven days and update that over time. A price chart will plot the moving average alongside the actual price movement.

Moving averages start at short intervals such as five or seven days, then are calculated at longer intervals up to 200 days. Moving Averages for shorter time periods tend to be used for technical analysis, while the longer MAs are popular for fundamental analysis.

Moving averages are useful as indicators of resistance levels, essentially indicating likely floors or ceilings to price given the aggregate view they give of price over the longer term.

The slope of a Moving Average can be a useful guide to market direction, as it steepens it suggests that there is momentum in price, whereas a flattening MA might indicate upcoming bearish conditions.

The price chart below is from March 16th, 2021 plotting three moving averages against price. over a seven day period.

  • Price is blue
  • 7 Day Moving Average is yellow
  • 20 Day Moving Average is orange
  • 100 Day Moving Average is red

You can see from the chart that price and the short term Moving Averages are closely in sync, but for the longer term 100 day MA trends below them, suggesting that price was due the correction which happened on March 15th, bringing all these indicators into convergence.

Some of the strongest Moving Average indicators are where they cross:

  • A shorter Moving Average falling below a longer one is bearish
  • A shorter Moving Average rising above a longer one is bullish
  • The Death Cross is where the 50 day MA falls below the 200

An often quoted stat for Bitcoin for example, is that Bitcoin’s Monthly close has never been below the 200 week Moving Average - so an average which was first calculated when Bitcoin was 200 weeks old. 

The 200 WMA seems to increase like clockwork, and given the length of time it is calculated over, smooths all the volatility in that period and points to Bitcoin’s successful function as a store of value. 

Moving Averages are a useful tool when used in conjunction with Cost Averaging, as they provide a way to trim or increase regular purchases based on the slope of 200 day Moving Average.

As with all Technical Indicators, there are levels of complexity to Moving Averages. Experienced traders tend to using more sophisticated variants such as Exponential Moving Averages (giving more weight to more recent data) or Moving Average Convergence Divergence (MACD) which measures the relationship between two moving averages.

Another popular technical tool that serves a similar purpose to Moving Averages is the Relative Strength Index. 

Relative Strength Index (RSI)

Relative Strength Index, usually abbreviated to RSI is a useful indicator of whether a particular cryptocurrency is overbought - overvalued - or oversold - undervalued.

It is what is known as an Oscillating Index, as it returns a value on a scale from 0-100. An RSI value above 70 tends to suggest overbought conditions, while a value below 30 that a cryptocurrency is undervalued from excessive selling.

The RSI calculation is quite simple, essentially looking at days when the price gains in relation to those where price falls. It is calculated with this formula:

RSI = 100 – 100 / (1 + RS)

RS is the average increase in price over 14 unit periods / average decrease in price over the same period. A unit could be a day or hour.

In this way RSI is a measure of momentum in the market but if it was as simple as waiting for the RSI to hit 70 or 30 and sell or buy accordingly we would all be very wealthy.

Below is an example RSI seven day chart for BTC/USD on March 16th, 2021.

  • Notice the way that the linear price is in the top pane
  • RSI appears in a pane below with the key thresholds of 70 & 30 plotted
  • RSI correlates relatively closely to price and its highest point of 74 on March 14th acts as leading indicator for the subsequent drop in price.

Markets can support overbought and oversold conditions depending on other contributing factors so RSI shouldn’t be relied on in isolation. It is what is known as a Leading Indicator, an indicator of where price might be about to go.

Moving Averages are an example of a Lagging Indicator, an indication of historic pattern or confirmation of a trend. 

The next article in this section on how to trade cryptocurrency will look at leading and lagging indicators in more depth, including information specific to the functioning of cryptocurrencies and the wider ecosystem that provide useful information to inform trading.