Essays about: "Directional long-short"

Showing result 1 - 5 of 10 essays containing the words Directional long-short.

1. 1. 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

3. 2. Forecasting Efficiency in Cryptocurrency Markets : A machine learning case study

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

   Author : Erik Persson; [2022]
   Keywords : Cryptocurrencies; Financial time-series; Multi step-ahead forecasting; Machine Learning; Feature selection; Kryptovalutor; Finansiella tidsserier; Flerstegsprognoser; Maskininlärning; variabelselektion;

   Abstract : Financial time-series are not uncommon to research in an academic context. This is possibly not only due to its challenging nature with high levels of noise and non-stationary data, but because of the endless possibilities of features and problem formulations it creates. READ MORE

4. 3. Energy Predictions of Multiple Buildings using Bi-directional Long short-term Memory

   University essay from Högskolan i Halmstad/Akademin för informationsteknologi

   Author : Anton Gustafsson; Julian Sjödal; [2020]
   Keywords : Deep Learning; LSTM; Recurrent Neural Network; Transfer Learning; Predict; Building Energy Consumption;

   Abstract : The process of energy consumption and monitoring of a buildingis time-consuming. Therefore, an feasible approach for using trans-fer learning is presented to decrease the necessary time to extract re-quired large dataset. The technique applies a bidirectional long shortterm memory recurrent neural network using sequence to sequenceprediction. READ MORE

5. 4. Link blockage modelling for channel state prediction in high-frequencies using deep learning

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

   Author : Shreya Krishnama Chari; [2020]
   Keywords : Radio link blockage; mmwave communications; sub-6GHz communications; 5G; Long short-term memory network; Deep neural network; Blockering av radiolänkar; mmwave-kommunikation; sub-6GHzkommunikation; 5G; Long short-term memory nätverk; Deep neural nätverk;

   Abstract : With the accessibility to generous spectrum and development of high gain antenna arrays, wireless communication in higher frequency bands providing multi-gigabit short range wireless access has become a reality. The directional antennas have proven to reduce losses due to interfering signals but are still exposed to blockage events. READ MORE

6. 5. Emotion Classification with Natural Language Processing (Comparing BERT and Bi-Directional LSTM models for use with Twitter conversations)

   University essay from Lunds universitet/Matematisk statistik

   Author : Nathaniel Joselson; Rasmus Hallén; [2019]
   Keywords : Mathematics and Statistics;

   Abstract : We have constructed a novel neural network architecture called CWE-LSTM (concatenated word-emoji bidirectional long short-term memory) for classify- ing emotions in Twitter conversations. The architecture is based on a combina- tion of word and emoji embeddings with domain specificity in Twitter data. READ MORE