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Found 5 papers, 1 papers with code
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy
Privacy-preserving federated learning enables a population of distributed clients to jointly learn a shared model while keeping client training data private, even from an untrusted server.
The Importance of Low Latency to Order Book Imbalance Trading Strategies
There is a pervasive assumption that low latency access to an exchange is a key factor in the profitability of many high-frequency trading strategies.
Get Real: Realism Metrics for Robust Limit Order Book Market Simulations
Machine learning (especially reinforcement learning) methods for trading are increasingly reliant on simulation for agent training and testing.
Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency
In finance, the weak form of the Efficient Market Hypothesis asserts that historic stock price and volume data cannot inform predictions of future prices.
ABIDES: Towards High-Fidelity Market Simulation for AI Research
ABIDES is designed from the ground up to support AI agent research in market applications.
Multiagent Systems
