TY - GEN
T1 - VTCGAN
T2 - 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023
AU - Mtetwa, Joseph Tafataona
AU - Ogudo, Kingsley
AU - Pudaruth, Sameerchand
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper presents a novel coupled Generative Adversarial Network (GAN) for the optimization of algorithmic trading techniques, termed Visio- Temporal Conditional Generative Adversarial Network (VTCGAN). The termed Visio- Temporal Conditional Generative Adversarial Network combines an Image Generative Adversarial Network and a Multivariate Time Series Generative Adversarial Network, offering an innovative approach for producing realistic and high-quality financial time series and chart patterns. By utilizing the generated synthetic data, the resilience and flexibility of algorithmic trading models can be enhanced, leading to improved decision-making and decreased risk exposure. Although empirical analyses have not yet been conducted, the termed Visio- Temporal Conditional Generative Adversarial Network shows promise as a valuable tool for optimizing algorithmic trading techniques, potentially leading to better performance and generalizability when applied to actual financial records.
AB - This paper presents a novel coupled Generative Adversarial Network (GAN) for the optimization of algorithmic trading techniques, termed Visio- Temporal Conditional Generative Adversarial Network (VTCGAN). The termed Visio- Temporal Conditional Generative Adversarial Network combines an Image Generative Adversarial Network and a Multivariate Time Series Generative Adversarial Network, offering an innovative approach for producing realistic and high-quality financial time series and chart patterns. By utilizing the generated synthetic data, the resilience and flexibility of algorithmic trading models can be enhanced, leading to improved decision-making and decreased risk exposure. Although empirical analyses have not yet been conducted, the termed Visio- Temporal Conditional Generative Adversarial Network shows promise as a valuable tool for optimizing algorithmic trading techniques, potentially leading to better performance and generalizability when applied to actual financial records.
KW - Algorithmic Trading
KW - Financial Time Series
KW - Image GAN
KW - Multivariate Time Series Simulation GAN
KW - Synthetic Data
KW - VTCGAN
UR - http://www.scopus.com/inward/record.url?scp=85171972555&partnerID=8YFLogxK
U2 - 10.1109/icABCD59051.2023.10220544
DO - 10.1109/icABCD59051.2023.10220544
M3 - Conference contribution
AN - SCOPUS:85171972555
T3 - 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings
BT - 6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings
A2 - Pudaruth, Sameerchand
A2 - Singh, Upasana
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 August 2023 through 4 August 2023
ER -