Topic: Trading Research. - page 4. (Read 800 times)

I believe many trading concepts are based on abstract assumptions and share a common origin, with some being outright misconceptions. Take Fibonacci levels, for example—waiting for a 50% retracement is essentially the same as waiting for a moving average crossover. When it comes to supply and demand, it’s complete nonsense in the context of BTC. While these concepts might apply to markets like grains or coffee, where seasonal supply and strategic demand are factors, BTC operates differently. Here, market makers provide liquidity 24/7, and market efficiency is their goal.

Risk management is another area that’s often misunderstood. The idea of risking 1% of your bankroll isn't efficient while 99% of it is not working. And strategies like risk-reward ratios of 1:3 can fail over time. Even in a vacuum, there are numerous combinations of losses that could eventually break you; it's only a matter of time.

The ICT approach is a compilation of these misconceptions, combining many flawed ideas into one.

As for historical data, numbers reflect specific states of affairs—quantitative aspects of reality as opposed to abstract ones. When combined with a deep understanding of market processes, this data can indeed help make more accurate predictions. You’ll see that the market is far from random. Statistics show that 95% of retail traders lose money. If you think that’s what randomness looks like, you’re mistaken—this is the result of misconceptions spreading and someone's well-executed market strategies.

You didn't give any example of any traditional trading method that has gone obsolete. Maybe mentioning them with a brief explanation would have helped explain your findings. I don't think all of these old methods are now out of date, maybe they have been advanced. Most of these traditional methods have been integrated with current technology making them easier and faster to apply.     

You wouldn't get the best analyst if the job is without financial benefits. There are some platforms where you can connect with people with the skills you seek. Members on those platforms might be open to free discussions or partnerships. You could also check the Service Board.     

These things still work because people don't change human instincts, greed and fear as well as consequent reactions in the market. Psychology cycle in the market is the same, from many different markets because people response in a same way with fear and greed, from stocks, real estates, gold to Bitcoin market.

Intelligent investors can apply nearly same principles like Warren Buffets uses in many decades. In different markets, you need to add some unique things in that market but generally there are many common things that related to human instinct.

You need the chart mostly for your investment and trading life.

Psychology of a market cycle


There is no free lunch. You can find available open source trading resources, scripts and use it if you want but if you proactively request it, it's not good. You need to pay other people to do works for you.

Can you cite an example of those traditional that is barely useful now for trading? Cause I only knew of basic trading concept and method but still employing up to now and it seems working fine for me.

So in your research what can you say about historical data does it help determine the potential future price for the market? As it seems many are reliable on this info as basis too.

Hello, community!

I've been involved in crypto since the beginning, but in recent years, I decided to dive into trading. After spending six months studying all available materials on the subject, I realized that many of the traditional methods are either outdated or irrelevant to today’s markets. So, I embarked on my own research journey.

As an economist with experience in big data analytics, I started working with historical data, focusing on price action. After a year of research, I’ve gained a deeper understanding of market processes but also recognized the limits of my own skills.

I’m now looking for a talented Data Scientist or Data Analyst to join me on a voluntary basis. If you excel in data export, analysis, and visualization, and are ready to invest some time in this research, please send me a message.

Discussions are also welcome!