Research
On-device research index

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

Trend · papers per month

50100150200 · May 202619922001200920172026
48 results for closing auctions

Study on heavy tails in closing auction returns, explaining imbalance through limit order submission.

problem Understanding heavy tails in closing auction return distributions.
method Used the stochastic call auction model of Derksen et al. (2020a) to derive and verify a relation between tail exponents.
result Large closing price fluctuations are not caused by large market orders, but by imbalance in limit orders.

MiFID II impacts European stock liquidity and price formation.

problem Impact of MiFID II on European stock liquidity and price formation.
method Analyzed effects of MiFID II on European stock markets, focusing on intraday and closing auction liquidity and tick size changes.
result Closing auction volumes increased and price formation became more efficient after MiFID II.

We first investigate the evolution of opening and closing auctions volumes of US equities along the years. We then report dynamical properties of pre-auction periods: the indicative match price is strongly mean-reverting because the imbalance is; the final auction price reacts to a single auction order placement or can…

2018-02-06abs ↗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.

A Deep Q-Learning framework tackles market-making by incorporating closing auctions.

problem Managing end-of-day risk in market-making models.
method Developed a Deep Q-Learning framework that anticipates closing auctions and continuously refines projected clearing prices.
result The Deep Q-Learning framework outperforms classical market-making models in simulations and real data.

Study adapts liquidity model to equity auctions, revealing accelerated event rates and reduced price impact.

problem Understanding and predicting price dynamics in equity auctions.
method Adapted latent/revealed order book framework to equity auctions, measuring order submissions, cancellations, and diffusion rates.
result Equity auctions exhibit accelerated event rates leading to reduced price impact and decreased volatility.

We propose a model for price formation in financial markets based on clearing of a standard call auction with random orders, and verify its validity for prediction of the daily closing price distribution statistically. The model considers random buy and sell orders, placed following demand- and supply-side valuation di…

2019-04-16abs ↗pdf ↗

This work optimizes bid strategies for online auctions using measure-valued optimization.

problem Optimizing bid strategies in first-price auctions to maximize expected surplus.
method Formulates the problem as convex optimization over the joint distribution of shading parameters, adapts the distribution after each auction using a Wasserstein-proximal update.
result The proposed algorithm encourages bids on values with high expected surplus.

We study the statistical regularities of opening call auction using the ultra-high-frequency data of 22 liquid stocks traded on the Shenzhen Stock Exchange in 2003. The distribution of the relative price, defined as the relative difference between the order price in opening call auction and the closing price of last tr…

2009-05-05abs ↗pdf ↗

We provide an exact analytical solution of the Nash equilibrium for kk- price auctions. We also introduce a new type of auction and demonstrate that it has fair solutions other than the second price auctions, therefore paving the way for replacing second price auctions.

2018-09-26abs ↗pdf ↗

The call auction is a widely used trading mechanism, especially during the opening and closing periods of financial markets. In this paper, we study a standard call auction problem where orders are submitted according to Poisson processes, with random prices distributed according to a general distribution, and may be c…

2014-07-16abs ↗pdf ↗

The study compares uniform-price and discriminatory auctions in terms of learning difficulty.

problem Comparing the learning difficulty of uniform-price and discriminatory multi-unit auctions.
method Characterization of learning difficulty through regret minimization in both full-information and bandit feedback settings.
result Regret scales similarly for both auction formats under full-information, but uniform-price auctions can achieve faster learning rates.

The ad-trading desks of media-buying agencies are increasingly relying on complex algorithms for purchasing advertising inventory. In particular, Real-Time Bidding (RTB) algorithms respond to many auctions -- usually Vickrey auctions -- throughout the day for buying ad-inventory with the aim of maximizing one or severa…

2015-11-26abs ↗pdf ↗

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.

Study on efficiency of Dutch auctions on blockchains considering various parameters.

problem Efficiency and fairness in Dutch auctions on blockchains.
method Modeling Dutch auctions with Poisson process and geometric Brownian motion, computing expected losses and time-to-fill.
result Tradeoff between speed and quality in Dutch auctions, useful for setting parameters.

Optimal bidding strategy for multi-platform ad auctions under budget constraints.

problem Optimizing ad placements for budget-constrained advertisers across multiple platforms.
method Developed an optimal bidding strategy for non-incentive-compatible auctions with budget constraints.
result Maximized total utility across auctions while satisfying budget constraints in expectation.

Proposes a framework for modeling RTB auctions using point processes.

problem Modeling and optimizing repeated auctions in the RTB ecosystem.
method Develops a stochastic framework using point processes to model and optimize RTB auctions.
result The proposed framework can be approximated to a Poisson point process, enabling the use of established properties.

The paper examines how builders in Ethereum auctions can defect and replicate winning MEV opportunities, affecting searchers' bidding strategies.

problem Commitment problem in Ethereum auctions where builders can defect and replicate winning MEV opportunities.
method Modeling and analysis of searchers' bidding strategies and the resulting equilibrium, using libMEV dataset.
result The equilibrium is piecewise, with the cost of imperfect commitment depending on replicability and competition. There is sharp heterogeneity across MEV types.

We consider a class of auctions (Lowest Unique Bid Auctions) that have achieved a considerable success on the Internet. Bids are made in cents (of euro) and every bidder can bid as many numbers as she wants. The lowest unique bid wins the auction. Every bid has a fixed cost, and once a participant makes a bid, she gets…

2010-07-24abs ↗pdf ↗

Optimizes reserve prices for first-price auctions to maximize revenue.

problem Optimizing reserve prices for first-price auctions in display advertising.
method Gradient-based algorithm to adaptively update and optimize reserve prices based on bidder responsiveness to experimental shocks.
result Revenue optimization in first-price auctions can be decomposed into demand and bidding components, and techniques are introduced to reduce variance of each.

We develop extensions to auction theory results that are useful in real life scenarios. 1. Since valuations are generally positive we first develop approximations using the log-normal distribution. This would be useful for many finance related auction settings since asset prices are usually non-negative. 2. We formulat…

2018-09-25abs ↗pdf ↗

Algorithm learns to bid optimally in repeated first-price auctions with censored feedback.

problem Learning to bid optimally in repeated first-price auctions with incomplete feedback.
method Developed an algorithm exploiting the specific feedback structure and payoff function of first-price auctions.
result Achieved a near-optimal O~(T)\widetilde{O}(\sqrt{T}) regret bound for first-price auctions.

Permutation-equivariant neural networks improve auction mechanisms by reducing regret and sample complexity.

problem Designing optimal auction mechanisms that balance revenue and bidders' regret.
method Introduced permutation-equivariant neural networks to auction mechanisms.
result Permutation-equivariant neural networks decrease expected ex-post regret and improve model generalizability.

Study learns optimal bidding strategy in auctions with dynamic values and aggregated feedback.

problem Optimizing bidding in auctions with time-dependent values and limited feedback.
method Combines plug-in estimators with differential-equation characterization of optimal policy.
result Achieves near optimal regret bounds for learning optimal policy.

This paper tackles optimal bidding strategies in adversarial first-price auctions.

problem How to bid optimally and efficiently in adversarial first-price auctions.
method Developed a minimax optimal online bidding algorithm leveraging expert-chaining structure and exploiting product structure.
result Achieved an O~(T)\widetilde{O}(\sqrt{T}) regret, superior to existing algorithms.

Study optimal auction formats for maximizing MEV on Ethereum.

problem Maximizing extractable value from Ethereum auctions.
method Empirical analysis of 2.2 million transactions, modeling affiliation among bidders.
result English and second-price sealed-bid auctions dominate other formats, with significant revenue losses.

New neural network architecture for auction design exploiting permutation symmetry.

problem Designing incentive-compatible auctions that maximize expected revenue.
method Constructed a permutation-equivariant neural network architecture.
result Permutation-equivariant architectures can perfectly recover optimal mechanisms.

This study evaluates price improvements in order flow auctions on Ethereum.

problem Improving trading outcomes in blockchain-based trading platforms.
method Utilized open-source tools to attribute price improvements to specific system inputs.
result Auction-enhanced interfaces can provide statistically significant improvements in trading outcomes, averaging 4-5 basis points.

We study a phenomenological model for the continuous double auction, equivalent to two independent M/M/1M/M/1 queues. The continuous double auction defines a continuous-time random walk for trade prices. The conditions for ergodicity of the auction are derived and, as a consequence, three possible regimes in the behavior …

2013-05-13abs ↗pdf ↗

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.

Efficient verified double auctions improve matching speed and detect errors.

problem Improving the efficiency and reliability of double auctions in financial markets.
method Formally verified implementation using Coq proof assistant, reducing time complexity and improving error detection.
result Improved efficiency with O(nlogn)O(n \log n) time complexity, reducing runtime from days to minutes.

This paper studies an environment of simultaneous, separate, first-price auctions for complementary goods. Agents observe private values of each good before making bids, and the complementarity between goods is explicitly incorporated in their utility. For simplicity, a model is presented with two first-price auctions …

2013-12-10abs ↗pdf ↗