Discussing the article: "Markov Chain-Based Matrix Forecasting Model"
Great job!!! Especially liked how you split into price, time and volume - that's a really smart approach. Tests on EUR/USD look promising.
But how will the model behave during sharp market changes like during Covid? If the transition matrix was built on historical data, how will it be able to adapt to such extreme conditions?
It would be interesting to know if the model was tested on pairs other than EUR/USD? Are there any built-in mechanisms of adaptation to sharp changes in volatility? Do you plan to take into account fundamental factors like macro news?
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Check out the new article: Markov Chain-Based Matrix Forecasting Model.
Andrey Markov, a prominent mathematician of the early 20th century, while working on probability theory, developed a concept that, a century later, became one of the cornerstones of modern financial mathematics. In developing the theory of stochastic processes, he studied sequences of events where the future depends only on the current state of the system, but not on previous history. This fundamental property — the absence of "memory" of the past beyond the current state — was called the "Markov property" and formed the basis of a whole class of models.
A Markov chain is a mathematical system that transitions from one state to another depending on probabilistic rules. If we imagine the possible states of a system as points in space, then the Markov chain describes the probabilities of movement between them. The stunning elegance of this concept lies in its ability to model incredibly complex processes through simple probabilistic mechanics.
Author: Yevgeniy Koshtenko