Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Izumi Kiyoshi"'
Large Language Models (LLMs) have demonstrated exceptional capabilities across various machine learning (ML) tasks. Given the high costs of creating annotated datasets for supervised learning, LLMs offer a valuable alternative by enabling effective f
Externí odkaz:
http://arxiv.org/abs/2408.12326
This study demonstrates whether financial text is useful for tactical asset allocation using stocks by using natural language processing to create polarity indexes in financial news. In this study, we performed clustering of the created polarity inde
Externí odkaz:
http://arxiv.org/abs/2408.06585
Stock embedding is a method for vector representation of stocks. There is a growing demand for vector representations of stock, i.e., stock embedding, in wealth management sectors, and the method has been applied to various tasks such as stock price
Externí odkaz:
http://arxiv.org/abs/2408.02899
The gravity models has been studied to analyze interaction between two objects such as trade amount between a pair of countries, human migration between a pair of countries and traffic flow between two cities. Particularly in the international trade,
Externí odkaz:
http://arxiv.org/abs/2408.01938
What would happen if temperatures were subdued and result in a cool summer? One can easily imagine that air conditioner, ice cream or beer sales would be suppressed as a result of this. Less obvious is that agricultural shipments might be delayed, or
Externí odkaz:
http://arxiv.org/abs/2408.01748
In this paper, we attempt to summarize monthly reports as investment reports. Fund managers have a wide range of tasks, one of which is the preparation of investment reports. In addition to preparing monthly reports on fund management, fund managers
Externí odkaz:
http://arxiv.org/abs/2408.01744
Recently, Large Language Models (LLMs) have attracted significant attention for their exceptional performance across a broad range of tasks, particularly in text analysis. However, the finance sector presents a distinct challenge due to its dependenc
Externí odkaz:
http://arxiv.org/abs/2406.10811
Causality is fundamental in human cognition and has drawn attention in diverse research fields. With growing volumes of textual data, discerning causalities within text data is crucial, and causal text mining plays a pivotal role in extracting meanin
Externí odkaz:
http://arxiv.org/abs/2402.14484
This paper presents a new artificial market simulation platform, PAMS: Platform for Artificial Market Simulations. PAMS is developed as a Python-based simulator that is easily integrated with deep learning and enabling various simulation that require
Externí odkaz:
http://arxiv.org/abs/2309.10729
This study proposes a new generative adversarial network (GAN) for generating realistic orders in financial markets. In some previous works, GANs for financial markets generated fake orders in continuous spaces because of GAN architectures' learning
Externí odkaz:
http://arxiv.org/abs/2204.13338