Behavioural biases and evolutionary dynamics in an agent-based financial market

This research is devoted to the study of financial market dynamics in a framework which combines agent-based modelling and concepts from behavioural finance. The thesis explores, in an agent-based financial market model, the interlinkage between investor heterogeneity, bounded rationality, behavioural biases and the aggregate market dynamics. We develop a dynamic equilibrium model of a financial market in the presence of heterogeneous, boundedly rational investors. The model combines a performance-driven strategy-switching mechanism of an adaptive belief system (Brock and Hommes, 1998) and an evolutionary finance model (Evstigneev, Hens and Schenk-Hopp´e, 2011). A key feature of this new model is that it contains a combination of passive and active learning dynamics. Passive learning refers to the market force by which wealth accumulates on investment strategies which have done relatively well. Active learning refers to the switching behaviour by which investors actively move their wealth into strategies which have performed well in the recent or distant past. This thesis extends the literature by examining the joint effect of passive and active learning in relation to the evolutionary dynamics of financial markets. By drawing in concepts from behavioural finance, we focus on the micro-level modelling of various heuristics and behavioural biases which may affect investors’ active learning and financial forecasting, such as overconfidence, recency bias, sentiment, etc. We quantify the macro-level market impact of these behavioural elements and study the evolutionary prospects of market dynamics. We show that the interaction between passive and active learning is crucial to understanding the market selection of dominant strategy or the survival of different strategies. Investors’ bounded rationality and behavioural biases in active learning and financial forecasting play an important role in shaping the market dynamics. Our findings point to the causes of the persistence of market inefficiencies and a variety of stylised facts of financial market. The added value of drawing together agent-based modelling and behavioural finance on the study of financial markets dynamics is demonstrated

The dependence of upper ocean gyres on wind and buoyancy forcing

A series of numerical simulations with different forcing conditions are carried out, to investigate the roles played by buoyancy and wind forcing on the upper ocean gyres, and to contrast the laminar and eddying regimes. Model experiments show that the buoyancy-driven eastward geostrophic flow tends to suppress the formation of the wind-driven subpolar gyre, but the northward eddy heat transport can homogenize the subpolar water and reduce the meridional temperature gradient by about two-third, thus counteracting the buoyancy effect and saving the subpolar gyre. For the subtropical gyre, its transport is enhanced by eddy mixing, and the role of buoyancy forcing is very sensitive to the choice of diapycnal diffusivity. Our results suggest that eddy effects must be considered in the dynamics of the subpolar gyre, and vertical diffusivity should be selected carefully in simulating the basin-wide circulations

Spatiotemporal-Augmented Graph Neural Networks for Human Mobility Simulation

Human mobility patterns have shown significant applications in policy-decision scenarios and economic behavior researches. The human mobility simulation task aims to generate human mobility trajectories given a small set of trajectory data, which have aroused much concern due to the scarcity and sparsity of human mobility data. Existing methods mostly rely on the static relationships of locations, while largely neglect the dynamic spatiotemporal effects of locations. On the one hand, spatiotemporal correspondences of visit distributions reveal the spatial proximity and the functionality similarity of locations. On the other hand, the varying durations in different locations hinder the iterative generation process of the mobility trajectory. Therefore, we propose a novel framework to model the dynamic spatiotemporal effects of locations, namely SpatioTemporal-Augmented gRaph neural networks (STAR). The STAR framework designs various spatiotemporal graphs to capture the spatiotemporal correspondences and builds a novel dwell branch to simulate the varying durations in locations, which is finally optimized in an adversarial manner. The comprehensive experiments over four real datasets for the human mobility simulation have verified the superiority of STAR to state-of-the-art methods. Our code will be made publicly available

Repressor Element 1 Silencing Transcription Factor (REST) Governs Microglia-Like BV2 Cell Migration via Progranulin (PGRN)

Microglia activation contributes to Alzheimer’s disease (AD) etiology, and microglia migration is a fundamental function during microglia activation. The repressor element-1 silencing transcription factor (REST), a powerful transcriptional factor, was found to play a neuroprotective role in AD. Despite its possible role in disease progression, little is known about whether REST participates in microglia migration. In this study, we aimed to explore the function of REST and its molecular basis during microglia migration under Aβ1-42-treated pathological conditions. When treated by Aβ1-42 REST was upregulated through JAK2/STAT3 signal pathway in BV2 cells. And transwell coculture system was used to evaluate cell migration function of microglia-like BV2. Small interfering RNA (siRNA) targeting progranulin (PGRN) were delivered into BV2 cells, and results showed that PGRN functions to promote BV2 migration. REST expression was inhibited by sh-RNA, which induced BV2 cell migration obviously. On the contrary, REST was overexpressed by REST recombinant plasmid transfection, which repressed BV2 cell migration, indicating that REST may act as a repressor of cell migration. To more comprehensively examine the molecular basis, we analyzed the promoter sequence of PGRN and found that it has the potential binding site of REST. Moreover, knocking-down of REST can increase the expression of PGRN, which confirms the inhibiting effect of REST on PGRN expression. Further detection of double luciferase reporter gene also confirmed the inhibition of REST on the activity of PGRN promoter, indicating that REST may be an inhibitory transcription factor of PGRN which governs microglia-like BV2 cell migration. In conclusion, the present study demonstrates that transcription factor REST may act as a repressor of microglia migration through PGRN

Aβ-Induced Repressor Element 1-Silencing Transcription Factor (REST) Gene Delivery Suppresses Activation of Microglia-Like BV-2 Cells

Compelling evidence from basic molecular biology has demonstrated the crucial role of microglia in the pathogenesis of Alzheimer’s disease (AD). Microglia were believed to play a dual role in both promoting and inhibiting Alzheimer’s disease progression. It is of great significance to regulate the function of microglia and make them develop in a favorable way. In the present study, we investigated the function of repressor element 1-silencing transcription factor (REST) in Aβ1-42-induced BV-2 cell dysfunction. We concluded that Aβ1-42 could promote type I activation of BV-2 cells and induce cell proliferation, migration, and proinflammation cytokine TNF-α, IL-1β, and IL-6 expression. Meanwhile, REST was upregulated, and nuclear translocalization took place due to Aβ1-42 stimulation. When REST was knocked down by a specific short hairpin RNA (sh-RNA), BV-2 cell proliferation, migration, and proinflammation cytokine expression and secretion induced by Aβ1-42 were increased, demonstrating that REST may act as a repressor of microglia-like BV-2 cell activation

Synthesis of all-biomass-derived carbon nanofibers for dual-functional filtration membranes and oxygen evolution reaction electrocatalysts

We report a facile and eco-friendly approach to the synthesis of carbon nanofibers (CNFs), using cornstalks as carbon precursors and pinewood-derived carbon powders with inherent rough surfaces as catalytic substrates during chemical vapor deposition. Then, we annealed the CNFs in the presence of ammonia to impart them nitrogen doping (NCNFs), large surface areas, hydrophilicity and underwater oleophobicity. As a result, the NCNF networks achieved via vacuum filtration could work as oil/dye dual-functional filtration membranes for simultaneous removal of crude oil droplets, methylene blue and reactive violet K-3R from water with high flux up to 4950 L m-2 h-1, high efficiency of 99.82% and excellent recyclability. Finally, cobalt oxide (CoxOy) nanoparticles were deposited on NCNFs to prepare CoxOy/NCNF composites, which exhibited higher electrocatalytic activity (overpotential at current density of 10 mA cm-2: 290 mV) and better durability towards the oxygen evolution reaction than the state-of-the-art precious iridium oxide catalysts. This may be attributable to nitrogen doping, synergistic effect between CoxOy and NCNFs, as well as the superior structural and compositional stability of the CoxOy/NCNF composites.(c) 2022 Elsevier B.V. All rights reserved

偏極陽子標的の為の高温動的核偏極

京都大学0048新制・課程博士博士(理学)甲第6969号理博第1865号新制||理||1015(附属図書館)UT51-97-S281京都大学大学院理学研究科物理学第二専攻(主査)教授 政池 明, 教授 今井 憲一, 教授 薮崎 努学位規則第4条第1項該当Doctor of ScienceKyoto UniversityDFA