Results 31 to 40 of about 348,165 (301)
Multi-Asset Multi-Agent Reinforcement Learning for Portfolio Management
IEEE AccessPortfolio management reduces the risks and improves the profits of a portfolio comprising various asset classes (including stocks, bonds, commodities, and cash) that exhibit low correlations and distinct risk-return characteristics.
Sang-Ho Kim, Ki-Hoon Lee
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HeliyonThis paper investigates the impact of housing with both consumption and investment attributes on the risky financial asset allocation of households, constructs Probit and Tobit models using 2019 China Household Finance Survey (CHFS) data, and proceeds to
Lili Wu, Hui Yu
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Hopfield networks for asset allocation
Proceedings of the 5th ACM International Conference on AI in FinanceWe present the first application of modern Hopfield networks to the problem of portfolio optimization. We performed an extensive study based on combinatorial purged cross-validation over several datasets and compared our results to both traditional and deep-learning-based methods for portfolio selection.
Carlo Nicolini +3 more
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Molecular Oncology, EarlyView.Pre‐analytical handling critically determines liquid biopsy performance. This study defines practical best‐practice conditions for cell‐free DNA (cfDNA) and extracellular vesicle–derived DNA (evDNA), showing how processing time, storage conditions, tube type, and plasma input volume affect DNA integrity and mutation detection.
Jonas Dohmen +11 more
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Financial Innovation, 2021 The emergence and growing popularity of Bitcoins have attracted the attention of the financial world. However, few empirical studies have considered the inclusion of the newly emerged commodity asset in the global commodity market.
Yuze Li +3 more
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Molecular Oncology, EarlyView.Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch +13 more
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Simul-RL Portfolio Framework: Black-Scholes-Merton and Reinforcement Learning for Asset Allocation
IEEE AccessAsset allocation method using reinforcement learning is being actively researched. However, the existing asset allocation methods do not consider the following viewpoints in solving the asset allocation problem.
Jungyu Ahn, Hyoung-Goo Kang
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Digital twins to accelerate target identification and drug development for immune‐mediated disorders
FEBS Open Bio, EarlyView.Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
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Asset Allocation in Transition Economies [PDF]
SSRN Electronic Journal, 2002 Designing an investment strategy in transition economies is a difficult task, because stock markets opened through time, time series are short, and there is little guidance how to obtain expected returns and covariance matrices necessary for mean-variance asset allocation.
Jondeau, E., Rockinger, M.
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Cognitive Behavioral Therapy for Youth With Childhood‐Onset Lupus: A Randomized Clinical Trial
Arthritis Care &Research, EarlyView.Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐Onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham +29 more
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