Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series

Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series

A Master of Science thesis in Engineering Systems Management by Assia Lasfer entitled, "Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series," submitted in January 2013. Thesis advisor is Dr. Hazem El-Baz. Available are both soft and hard copies of the th...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Lasfer, Assia (author)
التنسيق:	doctoralThesis
منشور في:	2013
الموضوعات:	artificial neural networks (ANN) design of experiments (DOE) frontier emerging developed financial time series Stock price forecasting Mathematical models Neural networks (Computer science)
الوصول للمادة أونلاين:	http://hdl.handle.net/11073/5873
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة

Epicasting: An Ensemble Wavelet Neural Network for forecasting epidemics
حسب: Panja, Madhurima
منشور في: (2023)

Recurrent ensemble random vector functional link neural network for financial time series forecasting
حسب: Aryan Bhambu (18767731)
منشور في: (2024)

An overview of load demand and price forecasting methodologies
حسب: Kourtis, George
منشور في: (2011)

A Review on Membrane Fouling Prediction Using Artificial Neural Networks (ANNs)
حسب: Abuwatfa, Waad Hussein
منشور في: (2023)

Probabilistic AutoRegressive Neural Networks for Accurate Long-Range Forecasting
حسب: Panja, Madhurima
منشور في: (2023)

Randomized Deep Hopfield Network with Multiple Output Layers for Volatility Time Series Forecasting
حسب: Aryan Bhambu (18767731)
منشور في: (2025)

W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecasting
حسب: Sasal, Lena
منشور في: (2022)

An ensemble neural network approach to forecast Dengue outbreak based on climatic condition
حسب: Panja, Madhurima
منشور في: (2023)

Heteroscedastic ensemble deep random vector functional link neural network with multiple output layers for High Frequency Volatility Forecasting and Risk Assessment
حسب: Aryan Bhambu (18767731)
منشور في: (2025)

Deep random vector functional link transformer network with multiple output layers for significant wave height forecasting
حسب: Aryan Bhambu (18767731)
منشور في: (2025)

Stock Price Prediction via Sentiment Analysis on News Corpora
حسب: Al Watchi Al Hayek, Maher
منشور في: (2021)

One-Hour-Ahead Wind Power Forecast Using Hybrid Grey Models
حسب: Osman, Ahmed
منشور في: (2016)

Forecasting Emerging Stock Market Crashes via Machine Learning
حسب: Khan, Mohammad Osama
منشور في: (2023)

Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model
حسب: Chakraborty, Tanujit
منشور في: (2022)

Multimodal Learning Techniques for Time Series Forecasting in Renewable Energy Systems: A Comprehensive Survey
حسب: Majdi Mansouri (16869885)
منشور في: (2025)

A dual-stage deep learning approach for robust detection and identification of hardware trojans using monte-carlo dropout
حسب: Arash Golabi (21841484)
منشور في: (2025)

Forecasting CPI inflation under economic policy and geopolitical uncertainties
حسب: Sengupta, Shovon
منشور في: (2024)

Effect of Cooling Rate on the Mechanical Properties of Glass Fiber Polypropylene Composites
حسب: Kabbani, Mohammed S.
منشور في: (2017)

Predicting Stock Prices in Dubai Financial Market Using Neural Networks and the Polynomial Classifiers
حسب: Al-Salkhadi, Saeed Mohammed
منشور في: (2007)

Novel algorithms for accurate DNA base-calling
حسب: Mohammed, Omniyah Gul
منشور في: (2013)

High frequency volatility forecasting and risk assessment using neural networks-based heteroscedasticity model
حسب: Aryan, Bhambu
منشور في: (2025)

Short-term Wind Power Prediction
حسب: Marzbani, Fatemeh
منشور في: (2014)

Modelling the Impact of Bottlenecks on Arterial Travel Time Using Neural Networks
حسب: Abdallah, Azza
منشور في: (2012)

Artificial neural network algorithms. (c1999)
حسب: Ramadan, Samer N.
منشور في: (1999)

Stacked Ensemble Deep Random Vector Functional Link Network With Residual Learning for Medium-Scale Time-Series Forecasting
حسب: Ruobin Gao (16003195)
منشور في: (2025)

Air catalytic biomass (PKS) gasification in a fixed-bed downdraft gasifier using waste bottom ash as catalyst with NARX neural network modelling
حسب: Muhammad Shahbaz (772838)
منشور في: (2020)

Operational neural networks
حسب: Serkan Kiranyaz (3762058)
منشور في: (2020)

AttDCT: Attention-Based Deep Learning Approach for Time Series Classification in the DCT Domain
حسب: Amine Haboub (22392097)
منشور في: (2025)

Estimating Bridge Deterioration Age Using Artificial Neural Networks
حسب: AL HUSSEIN, ASEEL
منشور في: (2017)

Financial Technology, Customer Experience, Behaviour and Banks Financial Performance: The Case of United Arab Emirates
حسب: ALMASAFRI, AMAL HAZEEM SAEED HAZEEM
منشور في: (2022)

Energy markets restructure beyond 2022 and its implications on Qatar LNG sales strategy: Business forecasting and trend analysis
حسب: Noor Yusuf (15748120)
منشور في: (2024)

DCT-Based Channel Attention for Multivariate Time Series Classification
حسب: Amine Haboub (22392097)
منشور في: (2025)

Understanding the Intention to Use the Metaverse in IT Companies Using a Hybrid SEM-ANN Approach.
حسب: ZAMMAR, AHMAD KHALED
منشور في: (2023)

Forecasting the Direction of GCC Stock Indexes Using Support Vector Machine (SVM) Algorithm
حسب: Zeino, Yaser Abdullah
منشور في: (2014)

Artificial Intelligence Based Identification of the Attitude Dynamics for a Quadrotor UAV
حسب: Avdeev, Alexander
منشور في: (2014)

AI‐Enhanced PV Power Forecasting Using Cloud Thickness and Motion in Kayseri, Turkey
حسب: Levent Yavuz (22501784)
منشور في: (2025)

Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
حسب: Jafari, Reza
منشور في: (2005)

Neural Networks as a Convex Problem
حسب: Khalil, Baha
منشور في: (2016)

Using Linear Regression and Back Propagation Neural Networks to Predict Performance of Soiled PV Modules
حسب: Shapsough, Salsabeel Yousef
منشور في: (2019)

A Novel Discrete Time Series Representation With De Bruijn Graphs for Enhanced Forecasting Using TimesNet
حسب: Mert Onur Cakiroglu (22927777)
منشور في: (2025)