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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.

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48 results for settlement manipulation

Prediction markets can be manipulated by traders who can move contract settlements, harming price discovery.

problem Manipulation of settlement times in prediction markets leads to unfair wealth transfer and harms price discovery.
method Developed a model showing how settlement manipulation transfers wealth and harms price discovery, and observed real-world effects on Polymarket's Bitcoin contract.
result Manipulators capture significant profits from retail traders, especially when settlement times are short.

This study reviews decentralized prediction markets, identifying key design variants and open problems.

problem Designing and implementing decentralized prediction markets with desirable properties.
method Modular workflow comprising eight stages: infrastructure, market topic, share structure, pricing, market initialization, trading, resolution, settlement, and archiving. Analysis of design variants and trade-offs.
result Identification of open problems for researchers in the field of decentralized prediction markets.

Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most socially and economically vulnerable people on the planet. Thus, understanding where these settlements are is of paramount importance to both gove…

2018-11-30abs ↗pdf ↗

The study analyzes how bonus-malus systems and delayed claims settlement affect insurance companies' financial stability.

problem Analyzing the impact of bonus-malus systems and delayed claims settlement on insurance companies' financial stability.
method Examined a discrete-time risk model with time-varying premiums, evaluating two types of claims and settlement delays.
result Delayed settlement of by-claims leads to lower ruin probabilities under specific assumptions.

PredictionMarketBench benchmarks trading agents on prediction markets.

problem Evaluating trading agents on prediction markets with realistic conditions.
method Deterministic replay of historical data, execution-realistic simulator, agent interface.
result Fee-aware algorithmic strategies outperform naive agents in volatile episodes.

Study cash-flow forecasting for derivatives, aligning with replication strategy and addressing timing frictions.

problem Inconsistencies in cash-flow forecasting under different measures and stochastic payment times.
method Use discounting sensitivities (funding-curve hedge ratios) for replication and propose a liquidity valuation adjustment.
result Aligns forecasting with replication strategy and avoids measure-mixing issues.

In his book with Alan Jolis, Vers un monde sans pauvreté (1997) Yunus gives the example of a microcredit loan of 1000BDT reimbursed via 50 weekly settlements of 22BDT and correctly claims that this corresponds to the annual interest rate of 20%. But this is without taking into account that if the borrower has good reas…

2013-12-08abs ↗pdf ↗

Paper introduces Cycles Protocol to integrate trade credit into market clearing.

problem Liquidity embedded in trade credit outside formal settlement infrastructures.
method Distributed, multilateral clearing mechanism based on double-entry accounting.
result Cycles Protocol maximizes balance sheet compression without redistributing counterparty risk.

AI learns market manipulation through simulation, suggesting regulation.

problem Regulating AI to prevent market manipulation.
method Used a genetic algorithm in an artificial market simulation.
result AI discovered market manipulation as an optimal strategy.

The paper analyzes how leverage affects manipulation in event-linked markets, offering new insights into regulation.

problem Manipulation and insider information in leveraged event-linked markets.
method Develops a two-axis manipulation taxonomy and analyzes leverage's effects on market-price and outcome manipulation.
result Leverage scales market-price manipulation linearly but shifts the cost-benefit threshold for outcome manipulation.

New model improves neural network robustness against input manipulations.

problem Improving neural network robustness against input manipulations.
method Causal view and deep causal manipulation augmented model (deep CAMA) with data augmentation and test-time fine-tuning.
result Deep CAMA shows superior robustness against unseen manipulations compared to traditional models.

This paper studies poisoning attacks in episodic RL and discovers their effectiveness depends on reward bounds.

problem Understanding security threats to RL algorithms through poisoning attacks.
method Examined two types of poisoning attacks: reward and action manipulation, in bounded and unbounded reward settings.
result The effectiveness of poisoning attacks depends on reward bounds, with different attack costs and success rates.

In this work we propose a model that can manipulate individual visual attributes of objects in a real scene using examples of how respective attribute manipulations affect the output of a simulation. As an example, we train our model to manipulate the expression of a human face using nonphotorealistic 3D renders of a f…

2019-01-28abs ↗pdf ↗

Manipulating data, such as weighting data examples or augmenting with new instances, has been increasingly used to improve model training. Previous work has studied various rule- or learning-based approaches designed for specific types of data manipulation. In this work, we propose a new method that supports learning d…

2019-10-28abs ↗pdf ↗

New method uses statistical physics to detect financial market manipulation.

problem Detecting financial market manipulation activities like spoofing and layering.
method Modeling order book dynamics as particle motion and using momentum measure.
result Method outperforms conventional Z-score-based anomaly detection.

This study categorizes RWA tokenization challenges and solutions.

problem Navigating the gap between on-chain deterministic code and off-chain probabilistic reality.
method Taxonomy and comparative analysis of RWA protocols, legal and technical standards.
result RWA tokenization requires overcoming legal and technical interoperability issues.

Framework detects covert financial market manipulation using LOB representations.

problem Detecting covert financial market manipulation (spoofing) from complex anomaly patterns in multilevel prices.
method Cascaded contrastive representation learning of LOB data.
result Transformer-based architectures achieve state-of-the-art results in detection performance.

Study reveals widespread manipulation of meme coins, leading to significant economic losses.

problem Widespread manipulation of meme coins leading to economic losses.
method Cross-chain analysis of 34,988 tokens across Ethereum, BNB Smart Chain, Solana, and Base.
result 82.8% of high-return tokens show evidence of artificial growth strategies.

A new method for robot manipulation tasks using imagined object goals.

problem Learning robot manipulation in sparse reward environments.
method Train objects to reach target positions, then use predictions to create a curriculum of tasks.
result Higher success rates in challenging learning scenarios compared to alternatives.

This work tackles force control for contact-rich manipulation tasks with rigid robots using RL.

problem Challenges in working with real robotic hardware, especially position-controlled robots.
method Combines RL with traditional force control techniques, implementing parallel position/force control and admittance control.
result Validated methods on both simulation and real robot (UR3 e-series) for force control.

Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a tradi…

2011-10-11abs ↗pdf ↗

Study on costs of manipulating AMM-based price oracles.

problem Cost of manipulation in AMM-based on-chain price oracles.
method Analyzes the robustness of AMM-based oracles to strategic manipulation, considering different aggregation methods and market conditions.
result Manipulation costs depend on the total quote depth and can be minimized by optimal liquidity weights.

Develop gradient boosting for estimating covariate-dependent GP distributions in insurance.

problem Estimating covariate-dependent Generalized Pareto distributions in insurance.
method Developing a statistical learning theory for gradient boosting.
result Deriving non-asymptotic error bounds for the boosting estimator.

Many problems in image processing and computer vision (e.g. colorization, style transfer) can be posed as 'manipulating' an input image into a corresponding output image given a user-specified guiding signal. A holy-grail solution towards generic image manipulation should be able to efficiently alter an input image wit…

2017-03-21abs ↗pdf ↗

Investigates optimal execution under time-varying liquidity, preventing price manipulation.

problem Optimal execution with time-varying liquidity impacts and price manipulation prevention.
method Almgren-Chriss framework, deterministic time variation, well-posedness, second-order conditions, price manipulation prevention.
result Sufficient conditions for a unique solution and prevention of price manipulation.

A new reward shaping method balances learning efficiency and effectiveness for robot manipulation.

problem Efficient and effective learning in robot manipulations with system uncertainty.
method Dense2Sparse reward shaping method combining dense and sparse rewards.
result Dense2Sparse method achieves higher expected reward and better system uncertainty tolerance.