Exploring the financial indicators to improve the pattern recognition of economic data based on machine learning
X Wei, W Chen, X Li - Neural Computing and Applications, 2021 - Springer
Various economic data in the financial market need to be pattern-recognized to improve the
efficiency of economic data pattern recognition, further improve the accuracy of economic …
efficiency of economic data pattern recognition, further improve the accuracy of economic …
Highly Regarded Investors? Mining Predictive Value from the Collective Intelligence of Reddit's WallStreetBets
In 2021, the Reddit community of WallStreetBets (WSB) started making headlines in the
mainstream media as a source of risky investment ideas called YOLOs, and meme stocks …
mainstream media as a source of risky investment ideas called YOLOs, and meme stocks …
Techniques to preprocess the climate projections—a review
S Panjwani, SN Kumar - Theoretical and Applied Climatology, 2023 - Springer
Abstract Model-derived climate projections have been used by decision-makers for climate
change impact assessment, adaptation, and vulnerability studies at large scale. However …
change impact assessment, adaptation, and vulnerability studies at large scale. However …
Two-stage sector rotation methodology using machine learning and deep learning techniques
Market indicators such as CPI and GDP have been widely used over decades to identify the
stage of business cycles and also investment attractiveness of sectors given market …
stage of business cycles and also investment attractiveness of sectors given market …
A study of financial cycles and the macroeconomy in Taiwan
HL Cheng, NK Chen - Empirical Economics, 2021 - Springer
This paper studies the characteristics of financial cycles (credit and house prices) and their
interactions with business cycles in Taiwan. We employ multivariate structural time series …
interactions with business cycles in Taiwan. We employ multivariate structural time series …
Deep learning macroeconomics
RRS Guimaraes - arXiv preprint arXiv:2201.13380, 2022 - arxiv.org
Limited datasets and complex nonlinear relationships are among the challenges that may
emerge when applying econometrics to macroeconomic problems. This research proposes …
emerge when applying econometrics to macroeconomic problems. This research proposes …
A predictive framework for multi-horizon financial crises forecasting using macro-economic data
T Seth, V Chaudhary - … Conference on Big Data (Big Data), 2021 - ieeexplore.ieee.org
US economy is driven by complex dynamics and interplay, often stemming from consumer
spending, supply-demand associations, private market interactions, and government …
spending, supply-demand associations, private market interactions, and government …
Machine‐Learning and Deep‐Learning Techniques in Social Sciences
Social Science, also referred to as “Science of the Society,” is a branch of science that
encapsulates the study of societies and the relationships among individuals within societies …
encapsulates the study of societies and the relationships among individuals within societies …
An Empirical Study on the Effectiveness of Bi-LSTM-Based Industry Rotation Strategies in Thai Equity Portfolios
T Eiamyingsakul, S Tarnpradab… - … on Computational Science …, 2023 - Springer
Portfolio optimization poses a significant challenge due to asset price volatility caused by
various economic factors. Portfolio optimization typically aims to achieve a high risk-adjusted …
various economic factors. Portfolio optimization typically aims to achieve a high risk-adjusted …
臺灣景氣狀態之預測.
蕭宇翔， 林依伶 - Taiwan Economic Forecast & Policy, 2020 - search.ebscohost.com
摘要國發會認定並發布景氣循環峰谷時點存在一定時間的落後, 使施政單位不易即時掌握景氣
狀態變化, 鑑於近年臺灣經濟成長變動劇烈, 本文搜集大量國內, 外總體經濟變數, 預測2001 …
狀態變化, 鑑於近年臺灣經濟成長變動劇烈, 本文搜集大量國內, 外總體經濟變數, 預測2001 …