Ridge regression is the method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. The method provides improved efficiency in parameters estimation problems in exchange for a tolerable amount of bias meanwhile Lasso (Least absolute shrinkage and selection operator) is a regression analysis method that performs both variable selection and regularization to enhance the prediction ...
The gray wolf algorithm is a metaheuristic stochastic swarm intelligence algorithm developed in 2014. Its idea is based on the gray wolf pack hunting model. There are four types of wolves: alpha, beta, delta and omega. Alpha has the most "weight" in decision making and managing the pack. Next come the beta and the delta, which obey the alpha and have power over the rest of the wolves. The omega wolf always obeys the rest of the dominant wolves. ...
For many years, the bee search methods were researched exclusively by biologists. However, the interest in applying swarm behavior in the development of new optimization algorithms was growing. In 2005, professor Dervis Karaboga became interested in the research results. He published a scientific article and was the first to describe the model of swarm intelligence mostly inspired by bee dance. The model was called the artificial bee colony. ...
Non-linear methods are widely used to handle financial time series. In particular, there are quite a few indicators in the MetaTrader trading platform that use non-linear approaches. All of them are actively used in trading. Non-linear indicators may be needed when certain characteristics of a signal are more important than general information. In addition, non-linear indicators can cope with situations, in which linear indicators are powerless. ...
Markov chains are a mathematical tool that can be used to model the behavior of financial markets. They are particularly useful because they allow traders to analyze the probability of future market states based on the current state of the market. One of the key benefits of using Markov chains in financial markets is that they allow traders to analyze and predict the evolution of market trends over time. Another benefit of Markov chains ...
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