کنفرانس مهندسی برق ایران

صفحه اصلی / سی و دومین کنفرانس بین المللی مهندسی برق

Machine Learning-based Fundamental Stock Prediction Using Companies’ Financial Reports

نویسندگان :

Hossein Rezaei¹ Kamran Abdi² Mohsen Hooshmand³

1- دانشگاه تحصیلات تکمیلی علوم پایه زنجان 2- دانشگاه تحصیلات تکمیلی علوم پایه زنجان 3- دانشگاه تحصیلات تکمیلی علوم پایه زنجان

کلمات کلیدی :

Stock market prediction،Fundamental feature analysis،Dataset generation،Machine learning،Time series،Statistical conversion

چکیده :

Portfolio management is a significant and crucial goal in investments. Therefore, the efficient prediction of the shares and securities plays an important role in highly profitable incomes. The fundamental stock analysis is a powerful and fruitful method of predicting the long-term of shares. However, further investigation in this area suffers from the lack of online fundamental features. This paper provides a fundamental feature dataset from TSE. Its features are extracted from the financial reports of companies and its prediction targets are both the return and risk values of each share. Moreover, this work investigates the effect of utilizing time dependency, absent in a vast majority of machine learning methods, on the prediction performance. Last, we propose machine-learning methods, i.e., logistic regression and gradient boosting to analyze the performance of fundamental stock prediction.

لیست مقالات

لیست مقالات بایگانی شده

Network-based functional connectivity in MDD with suicide ideation before and after TMS: An fMRI case study

Moslem Khafi - Morteza Fattahi - Hamid Soltanian-Zadeh - Reza Rostami

A brief review of methods for improving the performance of virtual synchronous generators under unbalnced conditions

Mohammad Hossein Mousavi - Hassan Moradi CheshmehBeigi

Analyzing, simulating and measuring the effects of stirrers and walls on the performance of the RTS60 reverberation chamber

Mojtaba Basravi - Zakerhossein Firouzeh - Hadi Aliakbarian

A Single-Fed Circularly-Polarized Elliptical Slot Antenna for S-Band applications

Sina Rezaee - Mahdi Janforooz - Behnam Rasoulpour

Exploring Different Machine Learning-based Methods for Learning the Language of Shepna Stock Price

Zoreh Ansari - Jalal Raeisi Gahruei - Mansoor Khademi

A Novel Approach to Pulmonary Embolism Segmentation: Increasing an Attention-based U-Net

Hanie Arabian - Alireza Karimian - Hosein Arabi - Marjan Mansourian

Modeling, estimation, and model predictive control for Covid-19 pandemic with finite security duration vaccine

Abolfazl Delavar - Reza Rahimi Baghbadorani

Using a Novel Connection Triangle as a Classifier to Discriminate between Different Faults in the Frequency Response Analysis

Mohammad Hamed Samimi

کنترل بازوی ربات دو درجه آزادی با کنترل‌کننده مود لغزشی مرتبه کسری فازی-تطبیقی پایانه‌ای

مائده نفیسی فر - متین جزءاسلامی - ابوالفضل جلیلوند - سمیرا نریمان پور - فرهاد بیات

On the Interaction Between Meteorological Conditions and Performance Optimization in MISO Free-Space Optical Communication

Meysam Ghanbari - Mahdis Saghaee Jahed - Seyed Mohammad Sajad Sadough

بیشتر

ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.0.4