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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.

168,657 papers · 148 categories

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1223 · Jun 201919922001200920172026
48 results for Broker

Strategic brokers exploit private information in broker-mediated markets, affecting informed traders' performance.

problem Strategic interactions and information leakage in broker-mediated markets.
method Study of strategic trading behavior and information leakage in a broker-mediated market.
result Brokers hold a strategic advantage over informed traders due to information leakage in trading flows.

An informed broker optimizes trading strategies in a market influenced by many traders.

problem Optimizing trading strategies for an informed broker in a market with many traders.
method Developed a mean-field game approach to derive equilibrium strategies for both the broker and traders.
result The broker's optimal strategy involves a Stackelberg equilibrium, leading and traders following.

Brokers and an informed trader compete for liquidity, affecting trading costs and inventory risk.

problem How brokers and an informed trader manage liquidity and trading costs.
method Sequential Stackelberg game, solving for trading strategies, numerical solutions.
result Equilibrium strategies and liquidity prices determined, not Pareto efficient.

A simple strategy optimizes broker-client trading, reducing price discounts for informed traders.

problem Optimizing broker-client trading to balance client flow and informed trader losses.
method Modelled as a stochastic control problem, derived optimal strategy in closed form, introduced algorithm.
result Optimal strategy reduces price discounts for informed traders, balancing client flow and informed trader losses.

We present an empirical study of the intertwined behaviour of members in a financial market. Exploiting a database where the broker that initiates an order book event can be identified, we decompose the correlation and response functions into contributions coming from different market participants and study how their b…

2011-04-04abs ↗pdf ↗

Traders buy and sell financial instruments in hopes of making profit, and brokers are responsible for the transaction. There are several hypotheses and conspiracy theories arguing that in some situations, brokers want their traders to lose money. For instance, a broker may want to protect the positions of a privileged …

2016-04-08abs ↗pdf ↗

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

problem Optimizing wealth in a game between brokers and informed traders with private signals.
method Closed-form solutions to a mean-field game using forward-backward SDEs.
result Optimal trading strategies for both brokers and informed traders are found.

Online trading platforms manipulate profits and losses, causing 82% of retail traders to lose money.

problem Manipulation of online trading platforms leading to financial losses for retail traders.
method Independent recording of trade details using REST API responses, comparison with broker reviews.
result 82% of retail traders lose money due to platform technical issues.

I derive practical formulas for optimal arrangements between sophisticated stock market investors (namely, continuous-time Kelly gamblers or, more generally, CRRA investors) and the brokers who lend them cash for leveraged bets on a high Sharpe asset (i.e. the market portfolio). Rather than, say, the broker posting a m…

2019-04-14abs ↗pdf ↗

Optimal order execution strategies for brokers under reference benchmarks.

problem Maximizing broker's utility of excess profit-and-loss subject to reference strategies.
method Formulated as a utility maximization problem, optimal strategies derived in closed form.
result General reference strategies can be approximated by piece-wise linear combinations of IS and TC orders.

The study examines how brokers' identity affects their trading strategies on the Toronto Stock Exchange.

problem Impact of anonymous trading on brokers' optimal execution strategies.
method Formulated a stochastic differential game and mean-field game to analyze the optimal execution problem of anonymous and identity-revealed trading.
result Obtained a closed-form solution for the optimal strategy under Almgren-Chris price impact framework.

This paper supplies two possible resolutions of Fortune's (2000) margin-loan pricing puzzle. Fortune (2000) noted that the margin loan interest rates charged by stock brokers are very high in relation to the actual (low) credit risk and the cost of funds. If we live in the Black-Scholes world, the brokers are presumabl…

2019-06-03abs ↗pdf ↗

Broker uses multi-task dynamic pricing to learn competitive prices in credit markets.

problem Lack of data and infrequent trading in credit markets.
method Two-Stage Multi-Task (TSMT) algorithm that leverages shared structure across securities.
result TSMT algorithm achieves a regret bound of O(TMd+Md)O(\sqrt{T M d} + M d), outperforming baselines.

We examine the Foreign Exchange (FX) spot price spreads with and without Last Look on the transaction. We assume that brokers are risk-neutral and they quote spreads so that losses to latency arbitrageurs (LAs) are recovered from other traders in the FX market. These losses are reduced if the broker can reject, ex-post…

2018-06-12abs ↗pdf ↗

In this paper, which is the third installment of the author's trilogy on margin loan pricing, we analyze 1,3671,367 monthly observations of the U.S. broker call money rate, which is the interest rate at which stock brokers can borrow to fund their margin loans to retail clients. We describe the basic features and mean-rev…

2019-06-03abs ↗pdf ↗

We present a formulation of the transaction cost analysis (TCA) in the Bayesian framework for the primary purpose of comparing broker algorithms using standardized benchmarks. Our formulation allows effective calculation of the expected value of trading benchmarks with only a finite sample of data relevant to practical…

2019-04-02abs ↗pdf ↗

Short-term incentives lead to riskier trading strategies.

problem Optimal execution with performance barriers.
method Analyzes the impact of short-term performance incentives on trading behavior.
result Short-term incentives result in more aggressive but less risky trading strategies in the short term, but poorer performance over long periods.

Suppliers (including companies and individual prosumers) may wish to protect their private information when selling items they have in stock. A market is envisaged where private information can be protected through the use of differential privacy and option contracts, while privacy-aware suppliers deliver their stock a…

2015-09-22abs ↗pdf ↗

We consider a broker who has to place a large order which consumes a sizable part of average daily trading volume. The broker's aim is thus to minimize execution costs he incurs from the adverse impact of his trades on market prices. By contrast to the previous literature, see, e.g., Obizhaeva and Wang (2005), Predoiu,…

2013-10-11abs ↗pdf ↗

Optimal execution strategy for merger & acquisition contracts with price impact.

problem Optimal execution and pricing of financial derivatives in M&A deals.
method Indifference utility arguments, considering linear and nonlinear contracts.
result Linear contracts are more expensive and vulnerable to manipulation.

FinRL-X unifies trading components for AI and rule-based strategies.

problem Inconsistent between research and live deployment in trading platforms.
method Modular architecture integrating data processing, strategy construction, backtesting, and execution.
result Unified protocol supports AI and rule-based trading components without altering execution.

Fink AGN classifier achieves high accuracy in classifying active galactic nuclei.

problem Classifying active galactic nuclei from astronomical data.
method Built features from photometric points and color estimation. Used active learning for optimized training sample. Applied traditional machine learning algorithms.
result Achieved 98.0% accuracy in classifying real alerts from ZTF.

Paper uses relaxation techniques to find optimal brokerage fees with private signals.

problem Finding optimal brokerage fees for clients with private trading signals.
method Relaxation techniques to establish contract existence in asymmetric information settings.
result Existence of optimal brokerage fees established in a market model with private signals.

I unravel the basic long run dynamics of the broker call money market, which is the pile of cash that funds margin loans to retail clients (read: continuous time Kelly gamblers). Call money is assumed to supply itself perfectly inelastically, and to continuously reinvest all principal and interest. I show that the rela…

2019-06-24abs ↗pdf ↗

We confirm the square-root law of market impact on Apple Inc. using a large dataset.

problem Testing the square-root law of market impact on a single U.S. large-cap equity.
method Using a full market-by-order feed, we reconstruct metaorders and calibrate impact using the square-root formula.
result The square-root law is confirmed with a prefactor of 0.34, consistent with worldwide data.

We study the problem of optimal execution of a trading order under Volume Weighted Average Price (VWAP) benchmark, from the point of view of a risk-averse broker. The problem consists in minimizing mean-variance of the slippage, with quadratic transaction costs. We devise multiple ways to solve it, in particular we stu…

2015-09-28abs ↗pdf ↗

A market fix serves as a benchmark for foreign exchange (FX) execution, and is employed by many institutional investors to establish an exact reference at which execution takes place. The currently most popular FX fix is the World Market Reuters (WM/R) 4pm fix. Execution at the WM/R 4pm fix is a service offered by FX b…

2015-01-30abs ↗pdf ↗

This paper optimizes brokerage contracts for multiple clients trading a single asset.

problem Optimizing brokerage contracts for multiple clients trading a single asset.
method Endogenously determines clients' reservation values and strategically chooses clients. Characterizes optimal portfolios computationally.
result Characterizes optimal portfolios of clients and their profits, showing dependence on price impact coefficients.

We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14,…

2018-02-16abs ↗pdf ↗