Abstract
Abstract
Authors
Institutions
No ROR-resolved institution is linked to this work yet.
Provenance
crossref
Confidence 100%
pubmed
Confidence 98%
europepmc
Confidence 96%
unpaywall
Confidence 95%
doaj
Confidence 92%
datacite
Confidence 0%
No local reference links have been materialized yet.
Unresolved referenced work
2017
Unresolved referenced work
2015
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
An agent-based computational model for china’s stock market and stock index futures market
2014
A fractional reaction-diffusion description of supply and demand
2018
10.1145/2492002.2482577
10.1145/2492002.2482577
Agent-based simulation in finance: design and choices
2014
The use of agent-based financial market models to test the effectiveness of regulatory policies
10.1515/jbnst-2008-2-305 · 2008
Tipping points in macroeconomic agent-based models
10.1016/j.jedc.2014.08.003 · 2015
10.2139/ssrn.1411462
10.2139/ssrn.1411462
10.1007/978-3-319-00723-6
10.1007/978-3-319-00723-6 · 2014
Imaging-based parcellations of the human brain
10.1038/s41583-018-0071-7 · 2018
Over a Decade of Neuroeconomics: What Have We Learned?
2016
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
10.1126/science.aar6404 · 2018
Behavioural and neural characterization of optimistic reinforcement learning
10.1038/s41562-017-0067 · 2017
Contextual modulation of value signals in reward and punishment learning
2015
More than the sum of its parts: A role for the hippocampus in configural reinforcement learning
10.1016/j.neuron.2018.03.042 · 2018
The successor representation in human reinforcement learning
10.1038/s41562-017-0180-8 · 2017
In the mind of the market: Theory of mind biases value computation during financial bubbles
10.1016/j.neuron.2013.07.003 · 2013
Deep reinforcement learning in agent based financial market simulation
2020
Unresolved referenced work
Kept as external metadata until matched
Building an artificial stock market populated by reinforcement?learning agents
10.3846/1611-1699.2009.10.329-341 · 2009
Coordination through social learning in a general equilibrium model
10.1016/j.jebo.2017.05.020 · 2017
10.2139/ssrn.290140
10.2139/ssrn.290140
Reinforcement learning in economics and finance
2021
Unresolved referenced work
Kept as external metadata until matched
10.2139/ssrn.2507826
10.2139/ssrn.2507826
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
1997
Performance functions and reinforcement learning for trading systems and portfolios
10.1002/(sici)1099-131x(1998090)17:5/6<441::aid-for707>3.0.co;2-# · 1998
Learning to trade via direct reinforcement
10.1109/72.935097 · 2001
10.1109/adprl.2007.368193
10.1109/adprl.2007.368193
Unresolved referenced work
Kept as external metadata until matched
Reinforcement learning in financial markets
10.3390/data4030110 · 2019
10.1109/intellisys.2017.8324237
10.1109/intellisys.2017.8324237
Improving financial trading decisions using deep q-learning: Predicting the number of shares, action strategies, and transfer learning
10.1016/j.eswa.2018.09.036 · 2019
10.1145/3383455.3422540
10.1145/3383455.3422540
A multiagent approach to q-learning for daily stock trading
10.1109/tsmca.2007.904825 · 2007
Momentum and autocorrelation in stock returns
10.1093/rfs/15.2.533 · doi-reference
The behavior of stock-market prices
10.1086/294743 · doi-reference
The empirical relationship between trading volume, returns and volatility
10.1111/j.1467-629x.1996.tb00300.x · doi-reference
Arch models
10.1016/s1573-4412(05)80018-2 · doi-reference
Trading volume and serial correlation in stock returns
10.2307/2118454 · doi-reference
On a universal mechanism for long-range volatility correlations
10.1088/1469-7688/1/2/302 · doi-reference
10.1007/978-3-540-34625-8_10
10.1007/978-3-540-34625-8_10 · doi-reference
10.2139/ssrn.1365229
10.2139/ssrn.1365229 · doi-reference
Empirical properties of asset returns: stylized facts and statistical issues
10.1080/713665670 · doi-reference
10.1017/cbo9780511755767
10.1017/cbo9780511755767 · doi-reference
Multi-agent-based order book model of financial markets
10.1209/epl/i2006-10139-0 · doi-reference
A general version of the fundamental theorem of asset pricing
10.1007/bf01450498 · doi-reference
10.1371/journal.pone.0170766
10.1371/journal.pone.0170766 · doi-reference
Noise
10.2307/2328481 · doi-reference
The beneficial role of random strategies in social and financial systems
10.1007/s10955-013-0691-2 · doi-reference
Herd behavior and aggregate fluctuations in financial markets
10.1017/s1365100500015029 · doi-reference
Bayesian interactions and collective dynamics of opinion: Herd behavior and mimetic contagion
10.1016/0167-2681(95)00035-6 · doi-reference
A theory of fads, fashion, custom, and cultural change as informational cascades
10.1086/261849 · doi-reference
Confirmation bias in human reinforcement learning
10.1371/journal.pcbi.1005684 · doi-reference
A drunk and her dog
10.1080/00031305.1994.10476017 · doi-reference
10.1007/978-3-319-09946-0
10.1007/978-3-319-09946-0 · doi-reference
Efficient capital markets: A review of theory and empirical work
10.2307/2325486 · doi-reference
The econometrics of financial markets
10.1016/0927-5398(95)00020-8 · doi-reference
Modelling and measuring the irrational behaviour of agents in financial markets: Discovering the psychological soliton
10.1016/j.chaos.2015.12.015 · doi-reference
Testing the causality of hawkes processes with time reversal
10.1088/1742-5468/aaac3f · doi-reference
Private information in futures markets: An experimental study
10.1002/mde.2868 · doi-reference
10.1007/978-3-030-55190-2_19
10.1007/978-3-030-55190-2_19 · doi-reference
10.1145/3383455.3422570
10.1145/3383455.3422570 · doi-reference
10.1007/978-3-030-60990-0_12
10.1007/978-3-030-60990-0_12 · doi-reference
A multi-agent deep reinforcement learning framework for algorithmic trading in financial markets
10.1016/j.eswa.2022.118124 · doi-reference
Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications
10.1109/tcyb.2020.2977374 · doi-reference
10.1002/9781119424444
10.1002/9781119424444 · doi-reference