arXiv research

Speed bumps reduce but do not fully eliminate investment in fast trading technology.

DEX allows HFTs to quickly acquire speed, improving price discovery without sacrificing liquidity.

Study shows time matters in automated trading, improving simple strategies over complex ones.

Faster trading algorithms aren't always better, as shown in simulated financial markets.

Study shows HFT benefits large traders under certain conditions.

Both the scientific community and the popular press have paid much attention to the speed of the Securities Information Processor, the data feed consolidating all trades and quotes across the US stock market. Rather than the speed of the Securities Information Processor, or SIP, we focus here on its accuracy. Relying o…

Optimal execution method uses rough path signatures for approximate solutions.

We study the optimal execution of market and limit orders with permanent and temporary price impacts as well as uncertainty in the filling of limit orders. Our continuous-time model incorporates a trade speed limiter and a trader director to provide better control on the trading rates. We formulate a stochastic control…

Fragmented exchanges arise due to speed advantages in high-activity regions.

Flexible deep learning models for dynamic accuracy and speed trade-offs.

Research optimizes C++ patterns for HFT, reducing latency and improving profitability.

Paper improves financial trading models using GPU parallelism.

Game theory models how agents trade in a risky asset considering price impact and a common signal.

Trading system uses NP-hard optimization to select stocks for high Sharpe ratio trading.

High-frequency trading strategy boosts battery storage profits.

Develops a new trading strategy for statistical arbitrage with path-dependent signals.

Non-autoregressive method speeds up protein folding prediction 23 times.

MATCHA speeds up decentralized SGD by parallelizing communication.

Quantum algorithms improve high-frequency trading efficiency.

Modeling vessel speed to balance efficiency and environmental risks in Arctic shipping.

Nearly one-half of all trades in financial markets are executed by high-speed, autonomous computer programs -- a type of trading often called high-frequency trading (HFT). Although evidence suggests that HFT increases the efficiency of markets, it is unclear how or why it produces this outcome. Here we create a simple …

Modern physics has demonstrated that matter behaves very differently as it approaches the speed of light. This paper explores the implications of modern physics to the operation and regulation of financial markets. Information cannot move faster than the speed of light. The geographic separation of market centers means…

Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult to satisfy real-time constraints. There is a trade-off between the speed (because of model complexity) and accuracy. Inspired by the reject…

Diffusion models' speed-accuracy relations derived from thermodynamics.

Optimizes trading trajectories for large portfolios quickly.

Solves a game between brokers and informed traders using stochastic differential equations.

The possibility of latency arbitrage in financial markets has led to the deployment of high-speed communication links between distant financial centers. These links are noisy and so there is a need for coding. In this paper, we develop a gametheoretic model of trading behavior where two traders compete to capture laten…

In this paper we propose a mathematical framework to address the uncertainty emergingwhen the designer of a trading algorithm uses a threshold on a signal as a control. We rely ona theorem by Benveniste and Priouret to deduce our Inventory Asymptotic Behaviour (IAB)Theorem giving the full distribution of the inventory …

Adaptive workflow combines fast amortized inference with MCMC for many datasets.

This paper studies four trading algorithms of a professional trader at a multilateral trading facility, observing a realistic two-sided limit order book whose dynamics are driven by the order book events. The identity of the trader can be either internalizing or regular, either a hedge fund or a brokery agency. The spe…

High-frequency traders can act as either small informed traders or round-trippers, affecting price discovery and liquidity.

The paper calculates optimal trading turnover in terms of asset liquidity and alpha autocorrelation.

Paper develops models for better HFT and algorithmic trading.

We propose and evaluate new techniques for compressing and speeding up dense matrix multiplications as found in the fully connected and recurrent layers of neural networks for embedded large vocabulary continuous speech recognition (LVCSR). For compression, we introduce and study a trace norm regularization technique f…

In this paper, we present a multi-period trading model in the style of Kyle (1985)'s inside trading model, by assuming that there are at least two insiders in the market with long-lived private information, under the requirement that each insider publicly discloses his stock trades after the fact. Based on this model, …

Model shows advantageous position in trade networks leads to success.

Investigates market dynamics with informed traders and high-frequency traders.

New measures detect HFT activity, revealing its impact on stock prices.

This paper compares FAISS and FENSHSES for nearest neighbor search in Hamming space.

Bayesian optimization offers the possibility of optimizing black-box operations not accessible through traditional techniques. The success of Bayesian optimization methods such as Expected Improvement (EI) are significantly affected by the degree of trade-off between exploration and exploitation. Too much exploration c…

QTNet uses deep reinforcement learning to automate trading strategies.

Quantum algorithm reduces qubit usage for Monte Carlo simulations.

Approximate multipliers boost CNN training speed, power, and area at slight accuracy cost.

Unified model improves sampling speed and quality.

Dynamic econometric models improve trading signals in momentum strategies.

We reconsider the problem of optimal trading in the presence of linear and quadratic costs, for arbitrary linear costs but in the limit where quadratic costs are small. Using matched asymptotic expansion techniques, we find that the trading speed vanishes inside a band that is narrower than in the absence of quadratic …

We extend Kyle's model to include stochastic liquidity and multiple assets.

Bayesian theory explains market impact of large trades.