Agent-based model with multi-agent RL shows market-maker profitability trends upward overall with rising aggregate market informedness as price-discovery benefits offset adverse-selection costs.
Journal of Financial Economics , volume =
3 Pith papers cite this work. Polarity classification is still indexing.
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PTMC is a proposed Monte Carlo estimator that generates market-outcome distributions by simulating continuous double-auction interactions among persona-conditioned neural-policy bots whose heterogeneity is drawn from a learned distribution.
Value of information to informed traders equals price-order flow covariance and totals 0.04% of market cap, much less than active management fees.
citing papers explorer
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Market Informedness and Market-Maker Profitability: The Trade-Off Between Adverse Selection and Price Discovery
Agent-based model with multi-agent RL shows market-maker profitability trends upward overall with rising aggregate market informedness as price-discovery benefits offset adverse-selection costs.
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Persona-Trained Monte Carlo: Estimating Market-Outcome Distributions via Swarms of Persona-Conditioned Neural Policy Bots in a Limit Order Book
PTMC is a proposed Monte Carlo estimator that generates market-outcome distributions by simulating continuous double-auction interactions among persona-conditioned neural-policy bots whose heterogeneity is drawn from a learned distribution.
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The Value of Information: A Puzzle
Value of information to informed traders equals price-order flow covariance and totals 0.04% of market cap, much less than active management fees.