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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,291 papers · 148 categories

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1122 · Mar 202619922001200920182026
10 results for EURUSD

This study finds similarities between currency exchange dynamics and supercooled systems.

problem Understanding the dynamics of currency exchange markets.
method Comparing EURUSD price fluctuations to colloidal dynamics and using models for arrested physical systems.
result EURUSD price fluctuations exhibit two-step dynamics similar to supercooled systems.

Unified model explains volatility memory in stocks and forex.

problem Understanding the components of volatility memory in financial markets.
method Developed a three-dimensional decomposition of volatility memory into level, shape, and tempo.
result Unified model shows that volatility memory is state-dependent, with different gates prevailing in equities and forex.

Proposes a new framework for invariant quadratic P&L predictions in option books.

problem Inconsistent second-order P&L predictions across different factor parameterizations.
method Local, model-agnostic framework using covariant Hessian defined by an affine connection.
result Coordinate-invariant quadratic P&L predictions that match desk targets.

Paper presents a modular RL framework for Forex trading, addressing limitations of prior studies.

problem Challenges in applying RL to Forex trading, including unrealistic environments, simplified rewards, and restricted action spaces.
method Integrates three components: a friction-aware execution engine, a decomposable reward architecture, and a discrete action interface.
result Empirical evaluation shows strong non-monotonic reward interactions and optimal Sharpe ratio with the full reward configuration.

Novel method for estimating currency option parameters with improved accuracy.

problem Improving currency option pricing accuracy and calibration process.
method Develops approximate formulas for two parameters in stochastic volatility models with exponentially-affine characteristic functions.
result Superior accuracy in parameter estimation for currency options.

Study finds Bitcoin market efficient, no exploitable inefficiencies with neural networks.

problem Investigating market inefficiencies in Bitcoin using neural networks.
method Used a feedforward neural network with various asset-related input features.
result Adding more features does not improve prediction accuracy, and one feature set outperforms a buy-and-hold strategy.