Discussing the article: "Analyzing Overbought and Oversold Trends Via Chaos Theory Approaches"

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Check out the new article: Analyzing Overbought and Oversold Trends Via Chaos Theory Approaches.

We determine the overbought and oversold condition of the market according to chaos theory: integrating the principles of chaos theory, fractal geometry and neural networks to forecast financial markets. The study demonstrates the use of the Lyapunov exponent as a measure of market randomness and the dynamic adaptation of trading signals. The methodology includes an algorithm for generating fractal noise, hyperbolic tangential activation, and moment optimization.

Imagine walking through the woods during a snowstorm. Snowflakes seem chaotic, their movement unpredictable. But if you look more closely, you will notice that they move along invisible air currents, following certain patterns. Like these snowflakes, prices in financial markets dance their own dance, which only looks random.

Chaos theory teaches us an amazing truth: deep patterns and structures are hidden in systems that seem completely unpredictable. Meteorologist Edward Lorenz discovered this when he was working with weather models and accidentally entered rounded data into his program. His discovery, later called the "butterfly effect," showed that even the slightest changes in the initial conditions can lead to radically different results.

"A system with a strange attractor may appear completely random, but there is a hidden order in it," Lorenz said. And just as weather systems have their own invisible patterns, financial markets follow certain regularities despite their apparent unpredictability.


Author: Yevgeniy Koshtenko

 
Very interesting article and interesting indicator. I would like to put it on the charts of the real account, in parallel with the traditional indicator of overbought, oversold and divergence RSI and compare the accuracy of the indicated signals of these two indicators. But as they say alas and ah! We old-timers of Forex work in the MQL4 language, which has long been mastered, reliable and understandable to a simple average statistical trader without higher IT-education. And we can't afford to change it for something new like MQL5. Please, ask the author to translate this indicator into MQL4. Thousands of practicing traders will be grateful, especially if this indicator will surpass our good old RSI in accuracy of trend change predictions. Thank you in advance.
 
stawros25 indicator of overbought, oversold and divergence RSI and compare the accuracy of the indicated signals of these two indicators. But as they say alas and ah! We old-timers of Forex work in the MQL4 language, which has long been mastered, reliable and understandable to a simple average statistical trader without higher IT-education. And we can't afford to change it for something new like MQL5. Please, ask the author to translate this indicator into MQL4. Thousands of practicing traders will be grateful, especially if this indicator will surpass our good old RSI in accuracy of trend change predictions. Thank you in advance.

Thank you very much. Ok, I will try to translate it to 4)

 
Hi,

I read your article - I really like the idea and the presentation. I wanted to share a small technical observation, maybe it will be interesting in the context of the topic.

In the text the Lyapunov exponent is mentioned in connection with market chaos, but in the code (CalculateLyapunovExponent()) the sensitivity of the model is actually calculated: two almost identical input samples are taken, passed through ForwardPass(), and then MathLog(distance / epsilon) is calculated. This gives a metric of the model, not of the market dynamics, which is quite logical, given that the "market" Lyapunov is almost impossible to estimate directly.

If you ever want to dig deeper into the "market" side of the question, there is an approach via Takens embedding: in essence, the phase space is reconstructed from the price, and there you can approximate the divergence of trajectories. This is purely as an interesting alternative, not as a suggestion to change anything - the article is already out and it was good.

Again, I found it interesting to read and thanks for the idea.

P.S.: I apologise if the translation from Spanish to Russian was unclear.
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