Forecasting the Tehran Stock market by Machine Learning Methods using a New Loss Function
Stock market forecasting has attracted so many researchers and investors that many studies have been done in this field. These studies have led to the development of many predictive methods, the most widely used of which are machine learning-based methods. In machine learning-based methods, loss function has a key role in determining the model weights. In this study a new loss function is introduced, that has some special features, making the investing in the stock market more accurate and profitable than other popular techniques. To assess its accuracy, a two-stage experiment has been designed using data of Tehran Stock market. In the first part of the experiment, we select the most accurate algorithm among some of the well-known machine learning algorithms based on artificial neural network, ANN, support vector machine, SVM. In the second stage of the experiment, the various popular loss functions are compared with the proposed one. As a result, we introduce a new neural network using a new loss function, which is trained based on genetic algorithm. This network has been shown to be more accurate than other well-known and common networks such as long short-term memory (LSTM) for both train and test data.
Prediction of stock market is a long-time attractive topic to researchers from different fields. In particular, numerous studies have been conducted to predict the movement of stock market using machine learning algorithms such as support vector machine (SVM) and reinforcement learning. In this project, we propose a new prediction algorithm that exploits the temporal correlation among global st...متن کامل
In order to have effective agricultural production the impacts of drought must be mitigated. An important aspect of mitigating the impacts of drought is an effective method of forecasting future drought events. In this study, three methods of forecasting short-term drought for short lead times are explored in the Awash River Basin of Ethiopia. The Standardized Precipitation Index (SPI) was the ...متن کامل
In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators...متن کامل
Forecasting Stock Price using Hybrid Model based on Wavelet Transform in Tehran and New York Stock Market
Forecasting financial markets is an important issue in finance area and research studies. On one hand, the importance of prediction, and on the other hand, its complexity, have led to huge number of researches which have proposed many forecasting methods in this area. In this study, we propose a hybrid model including Wavelet Transform, ARMA-GARCH and Artificial Neural Network (ANN) for single-...متن کامل
conditional copula-garch methods for value at risk of portfolio: the case of tehran stock exchange market
ارزش در معرض ریسک یکی از مهمترین معیارهای اندازه گیری ریسک در بنگاه های اقتصادی می باشد. برآورد دقیق ارزش در معرض ریسک موضوع بسیارمهمی می باشد و انحراف از آن می تواند موجب ورشکستگی و یا عدم تخصیص بهینه منابع یک بنگاه گردد. هدف اصلی این مطالعه بررسی کارایی روش copula-garch شرطی در برآورد ارزش در معرض ریسک پرتفویی متشکل از دو سهام می باشد و ارزش در معرض ریسک بدست آمده با روشهای سنتی برآورد ارزش د...
The paper briefly analysis the methods used in forecasting of the stock market quotations, from the classic methods, used by the fundamentalists and chartist annalists, to the newest methods. The practical situations, where the analyzed methods are suitable, are also indicated.متن کامل
دوره 6 شماره 2
صفحات 1- 24
تاریخ انتشار 2021-04-01
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