Essays about: "Financial Time Series Forecasting"

Showing result 1 - 5 of 55 essays containing the words Financial Time Series Forecasting.

1. 1. Artificial Neural Networks for Financial Time Series Prediction

   University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

   Author : Dana Malas; [2023]
   Keywords : artificial neural networks; time series analysis; deep learning; finance; long short-term memory; simple moving average;

   Abstract : Financial market forecasting is a challenging and complex task due to the sensitivity of the market to various factors such as political, economic, and social factors. However, recent advances in machine learning and computation technology have led to an increased interest in using deep learning for forecasting financial data. READ MORE

3. 2. CryptoCurrency Time Series analysis : Comparative analysis between LSTM and BART Algorithm

   University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Author : Lakshmi Vyshnavi Nerella; Chiranjeevi Ponnada; [2023]
   Keywords : ;

   Abstract : Background: Cryptocurrency is an innovative digital or virtual form of money thatuses cryptographic techniques for secured financial transactions within a decentralized structure. Due to its high volatility and susceptibility to external factors, itis difficult to understand its behavior which makes accurate predictions challengingfor the investors who are trying to forecast price changes and make profitable investments. READ MORE

4. 3. Credit Index Forecasting: Stability of an Autoregressive Model

   University essay from KTH/Matematik (Avd.)

   Author : Melker Wallén; Erik Grimlund; [2023]
   Keywords : Credit spreads; Time Series; Credit Risk; Index Modeling; Forecasting; Kreditspreadar; Tidsserier; Kreditrisk; Indexmodellering; Prognoser;

   Abstract : This thesis investigates the robustness and stability of total return series for credit bond index investments. Dueto the challenges which arise for financial institutes and investors in achieving these objectives, we aim to createa forecasting model which matches the statistical properties of historical data, while remaining robust, stable andeasy to calibrate. READ MORE

5. 4. Machine Learning Based Stock Price Prediction by Integrating ARIMA model and Sentiment Analysis with Insights from News and Information

   University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Author : Teja Sai Vaibhav Boppana; Joseph Sudheer Vinakonda; [2023]
   Keywords : Machine Learning; Market Trends; News; Headlines Stock Price Prediction; VADER.;

   Abstract : Background: Predicting stock prices in today’s complex financial landscape is asignificant challenge. An innovative approach to address this challenge is integrating sentiment analysis techniques with the well-established Autoregressive IntegratedMoving Average (ARIMA) model. READ MORE

6. 5. LSTM-based Directional Stock Price Forecasting for Intraday Quantitative Trading

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Isabella Mustén Ross; [2023]
   Keywords : Deep Learning; Long-Short-Term-Memory LSTM ; ARIMA; Financial Time Series Forecasting; Algorithmic Trading; Intraday Trading; Stock Prediction; Djupinlärning; LSTM; ARIMA; finansiella tidsserier; algoritmisk aktiehandel; intradagshandel; aktieprediktion;

   Abstract : Deep learning techniques have exhibited remarkable capabilities in capturing nonlinear patterns and dependencies in time series data. Therefore, this study investigates the application of the Long-Short-Term-Memory (LSTM) algorithm for stock price prediction in intraday quantitative trading using Swedish stocks in the OMXS30 index from February 28, 2013, to March 1, 2023. READ MORE