Spatio-temporal momentum: Jointly learning time-series and cross-sectional strategies
We introduce Spatio-Temporal Momentum strategies, a class of models that unify both time-
series and cross-sectional momentum strategies by trading assets based on their cross …
series and cross-sectional momentum strategies by trading assets based on their cross …
Transfer ranking in finance: applications to cross-sectional momentum with data scarcity
Cross-sectional strategies are a classical and popular trading style, with recent high
performing variants incorporating sophisticated neural architectures. While these strategies …
performing variants incorporating sophisticated neural architectures. While these strategies …
Multi-agent model based proactive risk management for equity investment
D Mita, A Takahashi - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Developing and applying new artificial intelligence (AI) techniques in finance has become
popular and one of the growing areas. Although many studies focus on return prediction and …
popular and one of the growing areas. Although many studies focus on return prediction and …
[HTML][HTML] The cross-sectional stock return predictions via quantum neural network and tensor network
N Kobayashi, Y Suimon, K Miyamoto… - Quantum Machine …, 2023 - Springer
In this paper, we investigate the application of quantum and quantum-inspired machine
learning algorithms to stock return predictions. Specifically, we evaluate the performance of …
learning algorithms to stock return predictions. Specifically, we evaluate the performance of …
Fast training of a transformer for global multi-horizon time series forecasting on tensor processing units
JL García-Nava, JJ Flores, VM Tellez… - The Journal of …, 2023 - Springer
Abstract Time Series Forecasting (TSF) is essential to key domains, and the Transformer
neural network has advanced the state-of-the-art on global, multi-horizon TSF benchmarks …
neural network has advanced the state-of-the-art on global, multi-horizon TSF benchmarks …
The Equity Fund Risk Predictions Via Quantum-Classical Hybrid Neural Networks
P Wang, Q Zhu, H Wu, X Li, S Yang, S Yang - International Conference on …, 2023 - Springer
Among the recent studies on the use of machine learning methods to study fund stocks,
there are few studies on the use of quantum-classical hybrid models. In this paper, we …
there are few studies on the use of quantum-classical hybrid models. In this paper, we …
Sequential asset ranking in nonstationary time series
We extend the research into cross-sectional momentum trading strategies. Our main result is
our novel ranking algorithm, the naive Bayes asset ranker (nbar), which we use to select …
our novel ranking algorithm, the naive Bayes asset ranker (nbar), which we use to select …
[PDF][PDF] Test Case Generation Evaluator for the Implementation of Test Case Generation Algorithms Based on Learning to Rank
Z Guo, X Xu, X Chen - cdn.techscience.cn
In software testing, the quality of test cases is crucial, but manual generation is time-
consuming. Various automatic test case generation methods exist, requiring careful …
consuming. Various automatic test case generation methods exist, requiring careful …