Gann Analysis: Experts Discuss the Future of Gann – Part 3

In Part 2 of our series talking to Gann experts we discussed how their understanding of Gann’s techniques has evolved over time, their favourite Gann strategies, and how they implement risk management into their systems.

This week we discuss Gann in an era of exponentially growing technology, such as AI, and the possible effects of using Gann’s methods on financial markets in the future.  

Before we dive into the not-too-distant future, I asked the experts what they say to detractors of Gann’s theories.

MH: Every trading strategy has its proponents and detractors, and Gann theory is no exception. What are some common misconceptions about Gann’s theories you’ve encountered, and what do you say to those who disregard it?

 

Alan Oliver: Many traders are focused and blindsided by the forecasting methods Gann kept private. If we remove this distraction and focus on the tools which do have clear or elementary instructions, we can make very lucrative profits from our efforts. It always seems to me the loudest detractors have spent little or no time at all on any meaningful research. Gann was adamant that numbers and letters have an underlying power, and it is only with dedicated time and effort can any individual hope to uncover these relationships.

Forecasting markets as Gann did would almost certainly create disbelief and incredulity today, and many experienced traders will not even mention this in passing. I wonder the fate of a fund manager who eluded that markets would decline because of the positions of Saturn and Jupiter? It would be a brave manager to expound this and he would almost certainly be knocked down in the rush to redeem funds from his care.

My personal view is that we must each make our own decisions based on actual research and ensuing results. Had I discounted the geometry theory of Gann using Time equal to Price I would never have placed a short trade on September 11, 2001 and would therefore have missed what eventually was a substantial profit.

 

Ian Flack: I find most Gann detractors have not studied Gann or read his books. The common misconception among Gann detractors is that it’s largely based on Forecasting.

I also find most people who are new to Gann go straight to the last chapters of his books and completely miss the most important chapters at the beginning focusing on Money Management, Trading Rules, and Position Sizing. Unfortunately, the boring parts are where the money is made.

 

Darren Wilson: The biggest one, and the one most often heard by me, is that in this day of algo-based trading methods and central bank interventions Gann’s rules are old and no longer apply today.

I have proven over and over to my satisfaction this statement is erroneous and incorrect.

It will almost always come from those who either don’t incorporate the ‘time’ aspects into trading or have never even thought to. At the end of the day, you want a strong back-tested plan that has a high win/loss ratio with low risk and can be scaled. Gann’s methods provide this, in any market condition.

To have this kind of trading plan you “must” incorporate the timing aspect. This is why Gann remains relevant today.

 

Jon Kirk: One common misconception about Gann’s theories is that he only used astrology. While Gann did use astrology as a layer of analysis, it was not the only thing he relied on. He primarily used mathematics with astrology as a supplement to his mechanical system. However, testing his forecasts against data and actual outcomes in relation to astrology alone raises questions.

Another misconception is that all the hidden secrets are contained in his book ‘The Tunnel Thru the Air’. While it does contain information on cycles, decoding it can be difficult without knowing what to look for. Gann taught the way he did for a reason, and using his mechanical system to trade and make money can help reveal the things in charts that relate to the book.

Lastly, some people claim Gann intentionally disguised his secrets with misinformation. However, Gann’s work is riddled with typographical errors, and it is unlikely he intentionally misled readers. Instead, the errors may have been a result of the reproduction process at the time. To those who disregard Gann’s work, it is important to respect it and move on to find tools that work for them. Having a trading plan tailored to one’s individual risk profile and drivers is key to success.

 

MH: The responses of our Gann experts reveal the existence of misconceptions surrounding Gann’s theories. It’s important to recognise every trading strategy is unique and personal, and there is no single approach that will work for everyone. To effectively use Gann, or any trading strategy, one must be receptive to its principles and willing to put in the required effort. If Gann’s methods don’t resonate with you, that’s okay—there are numerous alternative strategies to explore until you find the one that fits your needs. However, it would be a mistake to discount Gann’s theories simply because they don’t align with your approach. There are many successful traders who use Gann daily. 

In short, the key to success is to remain open-minded and find a trading plan that suits your individual risk profile and objectives.

 

My final question asked about the future of Gann theory.

We are seeing the emergence of AI more in our daily lives, including the financial markets. With Gann Theory being rooted in natural cycles and the patterns of human nature, what effect (if any) do you think this will have on the future of Gann-based analysis?

 

Darren Wilson: Gann theory will endure in my opinion. The introduction of AI is simply another cycle in itself. And if its been programmed by those ignorant of Gann’s work, my forecast is it gives those fluent in his theory an even greater chance of success. 

The incorporation of time and natural cycles can be, as it is today, an enduring market edge against even the best AI trading system should the above condition be met.

 

Jon Kirk: I’m old so my view on these things is probably jaded. But one of the things people forget is trade management is as much about form reading and emotion than it is about a mathematical formula. Markets run on emotion, that’s why most of the old pit traders never lasted in the transition to screen-based office trading. They have no gauge on the emotion of the day.

AI currently is probably good for getting a sense of history. If you have a cycle you are following, similar historical sentiment may help confirm the cycle or roadmap you have put together. As far as trading, I think if you have AI doing the trading and no human interference or operators it will be trading against itself, there will be no market to trade! Time will tell on this but in the meantime, for those prepared to do homework, Gann’s legacy lives on and is there for everyone to benefit from. There are no free lunches in trading.

 

Ian Flack: I believe the trading plans of most individuals are more effective if there is higher volume and liquidity in the markets. AI is providing increased volume and liquidity so can only be a benefit to traders. A study of economic cycles will display that natural cycles and patterns of human nature are as much a part of markets now as they have ever been.

 

Alan Oliver: Perhaps AI will become an important feature, just like new innovations like computers, the web, and cryptocurrencies, all of which have created new market conditions and opportunities. Today in existence we already have software that can analyse a market and enter and exit trades without any human intervention. I have met many traders who still persist with perfecting these software forms of trading and some have done well whilst others have not.

 Markets are not exact nor precise, and a cursory review of any chart will confirm this. I believe there may be a place in trading for AI, and it may become an important cog in the wheel. But my own personal view is that computers and AI will have a place but will not replace the brain, the instinct we have for investing. I suspect it will not entirely replace human intervention but become an adjunct or tool to decision-making processes. The future on this is indeed exciting but I don’t see an automated Gann robot any time soon.

MH: Predicting the future is always challenging, and with the frequency of advancements being announced by AI developers, it’s even more difficult to determine its potential impact. While it’s uncertain how AI will affect the markets, our experts believe Gann’s theories will continue to play a role in their strategies.

I tend to agree, given Gann’s theories have been in use for over a hundred years now, it has survived the introduction of computers, high-frequency trading, larger and more frequent government monetary interventions, and is successfully applied on markets such as FX and Crypto, neither of which existed in Gann’s time. 

I would like to express my gratitude to Alan, Jon, Darren, and Ian for sharing their insights with us over the past few weeks. It has been enlightening to see the similarities and differences in their perspectives, and gain further insight into Gann theory and application.

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