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Ethereum technical analysis: a story of two results
As a developer of technical analysis scripts using libraries like Go, I work with various cryptocurrencies, including Ethereum. Recently, I analyzed the price movement of Ethereum using RSI (Relative RSSI Strength), Stoch RSI (RSI stochastic oscillator), Boler and Divergence of Mobile Average Convergence (MacD). While my script has produced precise results for some time, I noticed a significant difference between its forecasts and the live data live from Binance.
In this article, I will denounce the differences between my analysis and the real performance of Ethereum on the exchange of Binance. It is essential to understand that technical analysis is not an exact science, and there are various factors influencing market behavior. However, by examining the production of my script against historical data, we can identify potential problems.
RSI: the Haussier indicator
My script uses RSI, which measures the extent of price changes over time. I fixed the threshold at 70, indicating over -racket or occurrence conditions. As expected, my results show that prices are often in a “surbough” state, which leads to false signals.
Stoch RSI: the oscillator
The Stoch RSI is a momentum oscillator which calculates the difference between the current price and its average of 14 periods. My script shows that Stoch RSI generally cultivates around 70 to 80%, which I labeled as “overbush”. Although this indicates potential purchase pressure, it is essential to consider other market factors.
BOLD BAND: The trading fork
My BOLER strip is a technical indicator that draws the upper and lower bands with a trading range. This script shows that prices often remain in these ranges, which I have marketed as “support” or “resistance”. Although it suggests that prices are generally stable, it is crucial to monitor other potential gap indicators.
MacD: the divergence of Mobile average convergence
My script uses the MacD line as a mobile average, with an EMA of 26 periods. I set the signal line to -12 and the crossings above this level. As expected, my results show that prices often evolve in tandem with the MacD line.
However, the
signal line is generally greater than zero, indicating high purchase pressure. This is where things become interesting.
The difference
In the real -time data contract of Binance, which shows a different image:
- Prices are not systematically exaggerated or occurred.
- The Stoch RSI does not peak at 70 to 80% as often as my script predicts it.
- The mud band is often shorter than expected, indicating more volatility.
- The MacD line is not systematically greater than zero; In fact, it is often below zero.
Conclusion
Although technical analysis can be a powerful tool for investors, there are limits to its precision. In this case, my script seems to have made incorrect forecasts due to the inherent nature of binance exchange data. There are several factors that contribute to this divergence:
* Lack of historical context : My script does not take into account wider market trends or seasonal models.
* Limited trading voluties
: the real trading volume on Binance may be different from my simulated data.
* Noise and sampling rate : Different time intervals (for example, data of 1 minute against 5 minutes) can cause noisy or inconsistent signals.
As a developer, it is essential to validate your technical analysis using real data to guarantee precision. If you are only counting on simulations like this, be aware of potential limits and take them into consideration when taking negotiation decisions.
Additional recommendations
- Use more precise indicators : Explore other technical indicators that are well established on the cryptocurrency market.
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