# Analyst builds a model to determine Bitcoin highs based on the golden ratio

Analyst Philip Swift published this week under the headline “Golden Ratio Multiplier – Uncovering the Mathematically Organic Nature of Bitcoin Spread.” According to him, the tool helps to understand the cyclical distribution of bitcoin as a technology and to determine the highs of the market both within cycles and for whole cycles separately..

According to Swift, the 350-day moving average has served as the axis around which the major cycles of Bitcoin have been built all this time. As soon as the price overcomes this level, the bullish trend is confirmed.

A curious picture emerges if you multiply the value of the moving average by other important quantities: the golden ratio (1.618) and the Fibonacci sequence (1, 2, 3, 5, 8, 13, 21).

This method allows you to determine most of the price highs within cycles on the historical data of the movement of the bitcoin rate, as well as the highs of each cycle separately.

Golden ratio multiplier (350MA x 1.6) – green line. Historically serves as important support and resistance.

In particular, it has become resistance during the current rally from the December 2018 lows. At the first contact, a failure occurred, due to which the price dropped by \$ 1,500.

By multiplying the moving average by 2 from the Fibonacci sequence, the analyst gets a red line, which serves as another important level of support and resistance and can be used by traders to predict short-term movements – for example, to determine when to take profit..

The next number is 3 – the purple line. It became strong resistance in the 2017 bull market and held the price back five times.

All three of these lines correspond to certain highs within the Bitcoin cycles. As we move further along the Fibonacci numbers (5, 8, 13, 21), the analyst finds the highs for each individual cycle, including the first bitcoin bubble in 2011.

• 350DMA x21 = 2011 maximum
• 350DMA x13 = 2013 maximum
• 350DMA x 8 = 2014 maximum
• 350DMA x5 = 2018 High

How to use this tool in practice? Swift points out that the Golden Ratio Multiplier should not be used in isolation, but it can help assess risks in specific situations. For example, historical data shows that by purchasing bitcoin at the time of the breakout of the 350-day moving average and then sequentially making a profit at the moment of the first contact with the levels x1.6, x2, x3, after which buying back the cryptocurrency at lower levels, it was possible to build a highly successful investment strategy that would culminate in a sale at the high of x5.

If the trend continues, the current cycle high will be found at x3 (purple line).

Why multiplying the 350-day moving average by these numbers gives such results? Swift explains this by the psychology of investors who tend to perceive the situation too pessimistic or too optimistic..

He cites a post by author Dima Vonko for Investopedia: “In many cases, it is believed that people subconsciously seek out the golden ratio. For example, it is psychologically uncomfortable for traders to observe trends that are too long. Graph analysis has a lot to do with nature, where things based on divine proportion are beautiful and well-built, while things that do not have it look ugly, seem suspicious and unnatural. This helps to understand why in the event of a strong deviation from the golden ratio, there is a feeling of an inappropriately long trend. “.

Swift doesn’t stop there. He added a 111-day moving average to the chart multiplied by 2,350-day moving average and got another indicator. When 350DMA x2 drops below 111DMA, Bitcoin price peaks for the current cycle. During the last three cycles, this happened three times, and the indicator was triggered within three days after the rate reached its maximum.

The analyst recommends that you watch this indicator closer to the expected end of the bullish cycle.

“Perhaps the main value of this tool lies not in the benefits for trading and investment, but in the ability to demonstrate that the spread of bitcoin and human herding behavior follow mathematical models,” concludes Swift..

You can play with the graph shown in the screenshots here.