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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.

168,695 papers · 148 categories

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144288431575 · Jun 202019922001200920172026
48 results for transactional efficiency

New method improves blockchain analysis by handling temporal changes and scalability.

problem Limited focus on evolving nature and scalability of blockchain transaction networks.
method Incremental approach with Metropolis-Hastings random walks.
result Comparable performance in node classification tasks with reduced computational overhead.

Sharp asymptotic lower bounds of the expected quadratic variation of discretization error in stochastic integration are given. The theory relies on inequalities for the kurtosis and skewness of a general random variable which are themselves seemingly new. Asymptotically efficient schemes which attain the lower bounds a…

2012-04-03abs ↗pdf ↗

Framework detects suspicious money laundering flows in large transaction graphs.

problem Detecting money laundering in large, complex transaction networks.
method Adapted framework for domain-specific constraints, including weighting method for edge significance.
result Framework outperforms state-of-the-art solutions in efficiency and effectiveness for large datasets.

With the explosive growth of e-commerce and the booming of e-payment, detecting online transaction fraud in real time has become increasingly important to Fintech business. To tackle this problem, we introduce the TitAnt, a transaction fraud detection system deployed in Ant Financial, one of the largest Fintech compani…

2019-06-18abs ↗pdf ↗

The paper tackles auction market design flaws by randomizing closing times and optimizing transaction fees.

problem Strategic traders exploit accumulated information to delay their orders, distorting auction efficiency.
method Randomizing auction closing times and designing optimal transaction fees policies.
result Policies encourage strategic traders to send orders earlier, improving auction market efficiency.

Bank transactions help predict macroeconomic indexes faster and more accurately.

problem Lag in macroeconomic index availability and autoregressive models' limitations in complex scenarios.
method Use financial transactions data to estimate macroeconomic indexes using neural networks and smart sampling.
result Neural network approach outperforms baseline methods on hand-crafted features based on transactions.

Onflow optimizes portfolio allocation with gradient flows, robust to transaction fees.

problem Optimizing portfolio allocation with transaction costs.
method Gradient flow reinforcement learning method for dynamic asset allocation.
result Onflow outperforms benchmarks in high transaction cost regimes.

This paper proposes a new method to optimize portfolio allocation with transaction costs using Wiener chaos expansion.

problem Optimizing portfolio allocation with transaction costs in multi-period settings.
method Wiener chaos expansion approach to represent and solve the optimization problem.
result The proposed method finds an optimal strategy for portfolio allocation with transaction costs.

Deep models for financial transactions are vulnerable to adversarial attacks, especially when adding transaction tokens.

problem Vulnerability of deep models to adversarial attacks on financial transaction records.
method Examine adversarial attacks and defenses on transaction records data, considering black-box attacks and adding transaction tokens.
result A few generated transactions can fool a deep-learning model, highlighting the need for robustness improvements.

In this article we consider the Merton problem in a market with a single risky asset and transaction costs. We give a complete solution of the problem up to the solution of a free-boundary problem for a first-order differential equation, and find that the form of the solution (whether the problem is well-posed, whether…

2016-12-02abs ↗pdf ↗

Hybrid model uses GNNs and pathfinding to optimize portfolio rebalancing costs.

problem Optimizing transaction costs in dynamic portfolio rebalancing.
method Combines GNNs for cost prediction and Dijkstra's algorithm for pathfinding.
result Significantly reduces transaction costs in financial asset graphs.

Proposes a robust and sparse portfolio selection model to reduce estimation errors and transaction costs.

problem Reduces impact of estimation errors and fixed transaction costs in portfolio selection.
method Develops an efficient algorithm to solve a mixed integer problem with an ellipsoidal uncertainty set.
result Proves the convergence of the algorithm to at least a local minimizer with a locally linear convergence rate.

Study optimizes rebate design in auction markets to enhance efficiency.

problem Designing optimal rebate policies in auction markets to improve efficiency.
method Formulated as a principal-agent problem, solved using Hamilton-Jacobi-Bellman equations and Deep BSDE method.
result Optimal transaction fees and rebates narrow the price spread, improving market efficiency.

AHEAD improves financial market efficiency through ad-hoc auctions.

problem Improving financial market efficiency and reducing transaction costs.
method Introducing a new matching design (AHEAD) for electronic markets where participants can trade at a fixed price and trigger auctions when unsatisfied.
result A Nash equilibrium is achieved in the market, and ad-hoc auctions are more relevant and efficient than periodic auctions and continuous limit order books.

TLMG4Eth combines language and graph models for Ethereum fraud detection.

problem Current fraud detection methods fail to consider semantic and similarity patterns in Ethereum transactions.
method TLMG4Eth uses a transaction language model and graph-based methods to capture semantic, similarity, and structural features.
result TLMG4Eth detects anomalies in Ethereum transactions more effectively than existing methods.

Study predicts stock transaction durations using LSTM and attention mechanism.

problem Estimating the probability density function of transaction durations in financial markets.
method Proposes a hybrid model combining LSTM networks and attention mechanism to extend ACD model.
result Demonstrates superior performance of the hybrid model on large-scale financial data.

Investment strategy optimized in markets with transaction costs and search delays.

problem Maximizing wealth in an illiquid market with transaction costs and search frictions.
method Characterized no-trade region and provided asymptotic expansions of value function for small transaction costs.
result The effects of transaction costs are more pronounced in illiquid markets.

Paper analyzes liquidity for everlasting options in DeFi, offering strategies to reduce costs.

problem Challenges of perpetual derivatives in decentralized finance markets.
method Dynamic proactive market maker model, simulations, hedging strategies.
result Liquidity providers can achieve net positive PnL with effective strategies.

New heuristic selects fewer assets for efficient portfolios, reducing costs.

problem High transaction costs and fees from including many assets in portfolios.
method Surrogate formulation to select assets, re-optimizes portfolio with fewer assets.
result Effective in constructing portfolios with fewer assets, reducing costs.

Model shows how price impact and transaction costs affect trading behavior and profits.

problem Analyzing trading behavior and profits in markets with transaction costs and price impact.
method Proves the existence of an equilibrium in a model with transaction costs and price impact.
result Existence of a strictly positive optimal transaction cost from the exchange's perspective.

The study examines pricing American options with both exogenous and endogenous transaction costs.

problem Pricing American options with transaction costs and liquidity risks.
method Modeling liquidity risks as a mean-reverting process and transaction costs as proportional to trading amount. Two nonlinear PDEs are used to characterize option values. Numerical solution via ADI method and model calibration using maximum likelihood estimation.
result The model incorporating liquidity risks significantly outperforms the Leland model.

Study reveals dynamic causal relationships between Ethereum transaction fees and economic subsystems.

problem Historical gas fee volatility caused economic disequilibria and stakeholder challenges.
method Time-varying Granger causality analysis using data on active wallets and transaction volume.
result Dynamic bidirectional causal relationships between transaction fees and economic subsystems across Ethereum.

Paper introduces a specialized text classification system for French Open Banking transactions.

problem Classifying specialized banking text data with high accuracy and efficiency.
method Data collection, labeling, preprocessing, modeling, and evaluation stages with language-specific techniques.
result Enhanced performance and efficiency compared to generic approaches.