Reyat Yilmaz

1. Introduction Financial forecasting aims to empower decision makers to anticipate market movements and asset prices. Price forecasts are crucial in economic decisions and serves as a cornerstone for portfolio construction, risk analysis, and investment strategy development. Accurate price predictions enhance the efficiency and transparency of the financial markets.

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4.2. Experimental Results The balanced dataset was divided as a training set and test set through the 10-fold cross-validation technique with the aim of applying the proposed LMT forest method to it. According to this approach, the results of each fold are separately given in Table 4. As can be seen, our proposed model outperformed the well-known random forest method [81] in terms of classification accuracy.