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Results for “auction tail” · papers 12 · wiki 2
Academic Papers · 12arXiv q-fin live 0 · desk corpus 12
OpenAlex · The Quarterly Journal of Economics · 2015 · cites 893

The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response *

Abstract The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed i

Eric Budish, Peter Cramton, John J. Shim
arXiv · arXiv · 2019

Transaction Cost Analytics for Corporate Bonds

The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Transaction Cost Analysis (TCA). One of the challenges in TCA is to build a realistic benchmark for the expected transaction cost and to characterize the price impact of each individual trade with given bond characteristics and market conditi

Xin Guo, Charles-Albert Lehalle, Renyuan Xu
arXiv · arXiv · 2014

Option Pricing, Historical Volatility and Tail Risks

We revisit the problem of pricing options with historical volatility estimators. We do this in the context of a generalized GARCH model with multiple time scales and asymmetry. It is argued that the reason for the observed volatility risk premium is tail risk aversion. We parametrize such risk aversion in terms of three coefficients: convexity, skew and kurtosis risk premium. We propose that option prices under the r

Samuel E. Vazquez
arXiv · arXiv · 2026

Retail Trader's Ruin: An Anatomy of Popular Signal Failure

We test whether five widely promoted retail signal families - trend, oscillator, candlestick, volume, and calendar rules - deliver a positive, economically meaningful, net-of-cost, and survivable edge. Practical viability is the conjunction of three predeclared gates: statistical edge after multiplicity correction, economic viability after trading costs, and finite-bankroll survival under leverage. Exposure-matched b

Adam Darmanin
arXiv · arXiv · 2026

Three-Currency HJM for Brazilian Credit Markets

This paper develops a three-currency Heath-Jarrow-Morton framework in which corporate credit is treated as a separate economy, connected to the nominal and real economies through synthetic inflation and credit exchange rates. The framework produces a testable identity. Under joint no-arbitrage, the credit spread of an issuer expressed over the inflation-rateindexed risk-free curve equals the same issuer's credit spre

Raphael Coelho
arXiv · arXiv · 2016

Funding, repo and credit inclusive valuation as modified option pricing

We take the holistic approach of computing an OTC claim value that incorporates credit and funding liquidity risks and their interplays, instead of forcing individual price adjustments: CVA, DVA, FVA, KVA. The resulting nonlinear mathematical problem features semilinear PDEs and FBSDEs. We show that for the benchmark vulnerable claim there is an analytical solution, and we express it in terms of the Black-Scholes for

Damiano Brigo, Cristin Buescu, Marek Rutkowski
arXiv · arXiv · 2026

Detecting unusual trading patterns on cryptocurrency exchanges by means of complexity measures

Artificial transaction generation remains an important source of potential market manipulation on cryptocurrency exchanges, as it may distort reported liquidity and reduce market transparency. This study proposes a diagnostic framework for detecting unusual trading patterns based on complexity and statistical-structure measures derived from high-frequency trade-level data. The analysis considers log-returns, trading

Jakub Zwydak, Marcin Wątorek, Jarosław Kwapień, Stanisław Drożdż
arXiv · arXiv · 2026

Diachronic Sample Integration: Robust Tail-Risk Estimation with Generative Models

Deep generative models are increasingly used as simulators for downstream decision-making under data scarcity, but in risk-sensitive applications their usefulness depends on rare adverse scenarios rather than typical samples. Standard generative objectives prioritize bulk distributional fidelity, leaving low-probability tails vulnerable to localized optimization noise and making tail-dependent functionals unstable un

Shuning Zhao, Patrick Wong, Leran Zhang, Xiaolin Hu
arXiv · arXiv · 2026

Model Predictive Control For Trade Execution

We address the problem of executing large client orders in continuous double-auction markets under time and liquidity constraints. We propose a model predictive control (MPC) framework that balances three competing objectives: order completion, market impact, and opportunity cost. Our algorithm is guided by a trading schedule (such as time-weighted average price or volume-weighted average price) but allows for deviat

Thomas P. McAuliffe, Samuel Liew, Yuchao Li, Andrey Ushenin, Chihang Wang
arXiv · arXiv · 2026

Quantifying Sub-Optimality in Routing for Automated Market Makers

We provide a large-scale empirical audit of DEX routing using 2.98 million WETH-USDC swaps on Ethereum. Comparing realized routes with optimized benchmarks, we measure an average shortfall of 2.02 bps per trade or \$24 million. To attribute losses, we introduce three reproducible optimal benchmarks: a Support-Constrained Optimum (SCO) that evaluates split quality conditional on the pools actually used; a Full-Venue O

Weiye Xi, Ciamac C. Moallemi
arXiv · arXiv · 2026

Application of parametric Shallow Recurrent Decoder Network to magnetohydrodynamic flows in liquid metal blankets of fusion reactors

Magnetohydrodynamic (MHD) phenomena play a pivotal role in the design and operation of nuclear fusion systems, where electrically conducting fluids (such as liquid metals or molten salts employed in reactor blankets) interact with magnetic fields of varying intensity and orientation, influencing the resulting flow dynamics. The numerical solution of MHD models entails the resolution of highly nonlinear, multiphysics

M. Lo Verso, C. Introini, E. Cervi, L. Savoldi, J. N. Kutz
arXiv · arXiv · 2026

Hybrid Hidden Markov Model for Modeling Equity Excess Growth Rate Dynamics: A Discrete-State Approach with Jump-Diffusion

Generating synthetic financial time series that preserve the statistical properties of real market data is essential for stress testing, risk model validation, and scenario design. Existing approaches struggle to simultaneously reproduce heavy-tailed distributions, negligible linear autocorrelation, and persistent volatility clustering. We developed a hybrid hidden Markov framework that discretized excess growth rate

Abdulrahman Alswaidan, Jeffrey D. Varner
Wiki Entities · 2
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