Predicting financial markets is very complicated, and those who engage in frequent trading are unlikely to become profitable because the success rate is nearly zero. In September, I made one of the most important discoveries for predicting future prices and managed to achieve a winning rate of 70/90% depending on the time windows. Two months after the discovery, I connected everything to chaos theory and thus realized that I had solved determinism with some conjectures of chaos theory. I was only aware of the famous butterfly effect but not other concepts of the theory. From November to February, I conducted very thorough studies on chaos and complex systems and ultimately predicting future prices is like predicting the weather or earthquakes. I discovered that price formation is totally deterministic because it is influenced by a powerful attractor that I was able to find by executing a masterful exploit. As markets are a complex system, it is difficult to make predictions, but it is possible to find predictable time windows. In the "complex system" of price formation, we find dozens of non-linear chaotic dynamics, and if one can isolate or construct them externally, it is possible to search for attractors because by finding the attractors, we can understand towards what the system evolves. In these months, I identified another 11 simple but weak attractors, which obviously cannot be used to earn money but are useful for slightly improving predictions. With each attractor or more of them together, we will always have different time windows for predictions. Therefore, predicting future prices is extremely difficult due to the dozens of dynamics that influence its formation, and chaos theory already says everything about the limits of predictions. Chaos theory is a topic that is greatly underestimated in the financial field but studied much more in the fields of earthquakes and meteorology. Searching for strong attractors is easy because they are less subject to noise/distortion caused by other dynamics, while the weak ones are more difficult to identify. Everything is in plain sight, you just need to know how to search and use your brain. I can assert that noise/randomness in financial markets does not exist as everything is explainable by the various dynamics that compose it. In weather and earthquake predictions, it is easier because the dynamics are isolated, and for example, in weather, predictions are made on cells, while in financial markets, everything focuses on a single price that evolves second by second. Chaos theory is underestimated because many, including mathematicians/physicists, fail to grasp the essence of the theory, which is why it is underrated, but chaos theory is the basis of everything. Everything is predictable for the moment only in the macroscopic world, but in the future, we will see that determinism will also be found in quantum mechanics. The universe is a game based on continuous evolution. It collapses, bringing information with it, and regenerates to evolve in a better way.
The man outside with a bucket in the rain, will always catch more water then the man inside predicting the weather from a theoretical model.
I think you need to decide whether you want to become a trader or an academic. Traders don’t predict market, they buy and sell risk, they don’t care about theories, they manage risk. "In theory there is no difference between theory and practice - in practice there is" ~Yogi Berra~
Let's try to understand who operates in the financial markets and why liquidity providers are the "banker" that absorbs the losses of all participants. In the financial markets, there are: -Designated market makers who do not engage in proprietary trading but can carry out such activities due to the execution of client orders. Each client provides their instructions for the timing and methods of execution, allowing the equity market maker to continuously provide "liquidity." -Derivative market makers provide liquidity on derivatives, covering the underlying assets, and offload risk to other market participants. -Latency and statistical arbitrageurs: those who operate on latency improve the microstructure of financial markets and also earn from not particularly smart execution algorithms, with their risk solely tied to the investment in infrastructure. On the other hand, those focusing on statistical arbitrage (with numerous methods) believe they have an advantage, but the reality is they will always blow up, especially if they operate at low frequency. High-frequency statistical players capitalize on small advantages and the law of large numbers. -Liquidity providers, who are the real players in the markets because they supply the main liquidity through dynamic liquidity provision systems and can do this because they understand the underlying deterministic order. The other participants in the markets include: -Commercial companies that use financial markets solely for hedging purposes and not for speculation, especially in derivatives on commodities and currencies. -Portfolio managers who can make long-term investments with hedging or speculative activities. -Retail investors who can make long-term investments with hedging or speculative activities. Now that we've seen who the participants are, let's look at why independent liquidity supply companies absorb the money of those who engage in the markets for both hedging and speculative purposes. Given the complexity, it's impossible to make predictions, and every hedging or speculative movement made by managers and retail investors is detrimental. These hedging and speculative movements cause market fragility, and I agree with the fractal finance concept conceived by Mandelbrot. Therefore, every investment is better made for the long term, but since chaos theory speaks clearly, every long-term investment will eventually collapse, ending up with nothing.
We live in a world where we are blind, and this explains the use of supercomputers to try to solve complex problems, but it is not realized that everyone has processors at home to solve complex problems with modest computational power. Problems are not solved with brute force; it takes ingenuity, commitment, and elegance. For the time being, most "AI" models are "stupid" and elementary and cannot solve big things since they are currently focused on simple and "stupid" statistics and clustering. This explains why XTX still earns a mere billion a year. I think future AI models focused on chaos theory will solve great things. You don't find deterministic order with simple statistics because it takes unconventional search methods, and there are hundreds of methodologies. Artificial intelligence is nothing more than automatic research, but it is the architect who must know how to design the architecture well, and since there are hundreds of research methods, the experiments to be conducted are millions. The automation of "artificial intelligence" can reduce the "effort" of human beings in research. New HPC from TGS management. The main independent liquidity providers in the financial markets are Renaissance Technologies and TGS Management, so when you incur losses, you know where a significant portion of your money is going. Stochastic research leads nowhere, so my advice is to focus on determinism by seeking hidden model structures through unconventional methods. I hypothesize that there are 120/600 attractors influencing price formation. My current model, focused on a single attractor, can make predictions up to a week in advance with a 70% probability of success. However, on a weekly and monthly basis, there remains an underlying deterministic order, but it's not sufficient to devise a strategy because this underlying order weakens as other dynamics play a decisive role. In my opinion, it's easier to predict the prices of individual stocks, government bonds, and commodities to some extent, whereas making predictions on the stock market index becomes much more complex due to the increasing number of dynamics that impact formation. So, being everything deterministic, it is possible to assert that with advanced study, with complete data and knowledge, it is possible to make accurate predictions up to 95% for weeks or months into the future.
There is a subtle difference between knowing the past and present are wrong vs knowing/predicting the future.
Yes, here is one subtle difference: Most professional traders try to forecast the value of a variable in the future based on the past behaviour of that variable as well as the past behaviour of other variables that affect it. (edge with positive expectancy). On the other hand, when a trader makes a prediction, then often the ego gets involved because people like to be right. It is much better to react to the market then attempting to predict.
All good points except the part about collapse. I don't think it will happen anytime soon. Of course, in the limit, time =>> infinity, eventually the sun will run out of energy and life will not exist on earth.