One of the concerns of investors in the bitcoin world is a huge selloff, which may happen. This happens when a death cross is formed, and people’s assets are sold. In this article, I will show a method that Medium writer randerson112358 used to analyze the death cross and golden cross. But what models the huge selloff bitcoin is the Python program used for analysis. So with this method, we can better predict the bitcoin price of 2021 and better understand the market.
If you like this analysis, then follow his Medium page for more price studies.
The death cross & golden cross
These two crosses are both on the coin. You should pay attention to both of them and probably check each one. The death cross is likely a huge selloff, and the golden cross is the opposite case. This indicator shows the probability of a huge upward turn in the market. So each of these indicators will examine these two probabilities in the bitcoin market.
“The death cross is a indicator that shows the possibility for a huge sell off of an asset. It is formed when the long-term moving average (usually 200 days) crosses above the short-term moving average (usually 50 days).”
randerson112358’s post
The golden cross is formed when the opposite of the death cross occurs, and the short-term moving average crosses above the long-term moving average. So it is in this way, the bitcoin index moves towards the golden cross, and a long-term bull market is formed.
How to model huge sell-off using Python
We can use the NumPy, Pandas, and Matplotlib libraries to fetch historical bitcoin price data. Then we can model the death cross and the huge bitcoin selloff, and finally, plot it on a line chart. This will show us whether bitcoin will sell well or not. The bitcoin price data we will be using will be from the dates 12-15-2016 to 07-08-2021.
Then by adding Long and Short Simple Moving Average and saving them in the data, we can create new columns on the table, which we can then plot to display the death cross. We can see that the death cross continues from 2021-06-19 until now. This is associated with where the LongSMA crosses above the ShortSMA.
What is SMA?
Each of the death cross & golden cross indicators will be calculated by averaging the value of closing the market on a certain period of time. In this case, SMA is derived from the two concepts of the short and long term. These moving averages can be used to get the cryptocurrency trend.
We can also see the number of death crosses and golden crosses in the bitcoin market.
As you can see, 3 golden crosses and 4 death crosses have occurred within the data set. These crosses have not been few during the bitcoin era and not a lot of bear market. This feature clearly shows when the death cross occurred. A good time has come to buy, and those who have taken advantage of this opportunity have been able to profit well in golden crosses after the BTC decrease. So this is where investors use the death cross, and their sales start. It can be said that this indicator shows the huge sell-off of BTC well.
Having a useful strategy
Finally, by using this indicator and other indicators, you can consider the price movement more accurately. The sum of these indicators can provide a more accurate analysis and a clearer pattern of bitcoin price movement.
This strategy can be easily used when the bitcoin is fixed, and the bitcoin trading trend is not clear. In this strategy, we can compare the support level of live bitcoin and make the right decision. Using Python and having insightful market experience, you can try this strategy and analyze it to improve your bitcoin price prediction.
In the end, what drives bitcoin’s huge selloff is a sales cycle in the market. What is clear is that in this volatile market, with the right and practical strategies and analysis, we can largely anticipate the buying and selling trend and use the market events to our advantage.
Disclaimer: The contents of this post should not be taken as investment advice. Use at your own risk. NotATether and staff are not responsible for financial decisions made as a result of following the article contents.
