Ethereum: Result is different than Binance technical analysis result

Ethereum Technical Analysis: A Story of Two Results

As a creator of technical analysis scripts using Go libraries, I have worked with various cryptocurrencies, including Ethereum. Recently, I analyzed Ethereum price movement using RSI (Relative Strength Index), Stoch RSI (Stochastic Oscillator RSI), Boler Band, and Moving Average Convergence Divergence (MACD). Although my script has been providing accurate results for some time, I have noticed a significant discrepancy between its predictions and the actual data from Binance.

In this article, I will outline the differences between my analysis and the actual performance of Ethereum on the Binance exchange. It is important to understand that technical analysis is not an exact science and that many factors affect market behavior. However, by comparing the results of my script with previous data, we can identify potential issues.

RSI: Bullish Indicator

My script uses RSI, which measures the size of price changes over time. I set the threshold at 70, which indicates overbought or oversold conditions. As expected, my results show that prices often find themselves in an “overbought” state, which results in false signals.

Stoch RSI: Oscillator

Stoch RSI is a momentum oscillator that calculates the difference between the current price and the 14-period average. My script shows that Stoch RSI tends to peak at 70-80%, which I call “overbought.” While this indicates potential buying pressure, there are other market factors to consider as well.

Boler Band: Trading Range

My Boler Band is a technical indicator that plots the upper and lower bands of a trading range. This script shows that prices often stay within ranges that I have labeled as “support” or “resistance.” While this suggests that prices are generally stable, it is important to monitor other indicators for potential divergences.

MACD: Moving Average Convergence and Divergence

My script uses the MACD line as a moving average with a 26-period EMA. I set the signal line at -12 and the crossovers above that level. As expected, my results show that prices often move in relation to the MACD line.

However, the
Signal Line is usually above zero, indicating strong buying pressure. This is where it gets interesting.

The Difference

Unlike Binance’s live data, which shows a different picture:

• Prices are not consistently overbought or oversold.

• Stoch RSI does not peak at 70-80% as often as my script predicts.

• The Boller Band is often shorter than expected, indicating higher volatility.

• The MACD line is not consistently above zero; in fact, it is often below zero.

Conclusion

While technical analysis can be an effective tool for investors, its accuracy has its limits. In this case, it appears that my script was making incorrect predictions due to a flaw in Binance’s data. There are several factors contributing to this discrepancy:

• Lack of historical context: My script does not take into account broader market trends or seasonal patterns.

• Limited trading volume: Actual trading volume on Binance may differ from my simulated data.

• Noise and sampling rate: Different time frames (e.g. 1-minute vs. 5-minute data) can result in noisy or inconsistent signals.

As a developer, it is essential to verify your technical analysis using real-world data to ensure its accuracy. If you rely solely on such simulations, be aware of the potential limitations and take them into account when making trading decisions.

Additional Recommendations

• Use More Accurate Indicators

  : Check out other technical indicators that have proven effective in the cryptocurrency market.

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BLOCKCHAIN PIONEERING FUTURE