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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 claims trading

Study claims trading to rescue banks in distress.

problem Rescue a bank in distress using claims trading.
method Formalize claims trading in financial networks, study decision and optimization problems, provide efficient algorithms for creditor-positive trades.
result No trade can strictly improve both banks' assets; provide efficient algorithms for creditor-positive trades.

We consider a general local-stochastic volatility model and an investor with exponential utility. For a European-style contingent claim, whose payoff may depend on either a traded or non-traded asset, we derive an explicit approximation for both the buyer's and seller's indifference price. For European calls on a trade…

2014-12-17abs ↗pdf ↗

In this paper, we provide a model-independent extension of the paradigm of dynamic hedging of derivative claims. We relate model-independent replication strategies to local martingales having a closed form which we can characterise via solutions of coupled PDEs. We provide a general framework and then apply it to a mar…

2018-09-01abs ↗pdf ↗

We shall provide in this paper good deal pricing bounds for contingent claims induced by the shortfall risk with some loss function. Assumptions we impose on loss functions and contingent claims are very mild. We prove that the upper and lower bounds of good deal pricing bounds are expressed by convex risk measures on …

2008-02-28abs ↗pdf ↗

New financial dataset and model detect claims affecting market returns.

problem Detecting analyst claims' impact on financial markets.
method Constructed new dataset, used weak-supervision model with SME knowledge.
result Outperformed existing models in claim detection and market analysis.

Study on hedging and valuation of basis risk in incomplete markets with partial information.

problem Hedging and valuation of European and American claims in an incomplete market with correlated assets and partial information.
method Stochastic control and partial information scenario, forward indifference valuation, dual representation, PDE approach.
result Derivation of optimal hedging strategy and forward indifference price representation for claims.

VAE struggles with distribution class sharpness, which can be learned dynamically.

problem VAE struggles with distribution class sharpness, leading to blurry reconstructions.
method Established that VAE fails if distribution class sharpness does not match data scale. Suggested learning distribution sharpness dynamically.
result Dynamic adjustment of distribution sharpness improves VAE performance, escaping local optima.

We study utility indifference prices and optimal purchasing quantities for a non-traded contingent claim in an incomplete semi-martingale market with vanishing hedging errors. We make connections with the theory of large deviations. We concentrate on sequences of semi-complete markets where in the nthn^{th} market, the …

2014-10-01abs ↗pdf ↗

Game contingent claims (GCCs) generalize American contingent claims by allowing the writer to recall the option as long as it is not exercised, at the price of paying some penalty. In incomplete markets, an appealing approach is to analyze GCCs like their European and American counterparts by solving option holder's an…

2017-07-28abs ↗pdf ↗

In this paper, we propose an equilibrium pricing model in a dynamic multi-period stochastic framework with uncertain income streams. In an incomplete market, there exist two traded risky assets (e.g. stock/commodity and weather derivative) and a non-traded underlying (e.g. temperature). The risk preferences are of expo…

2012-05-28abs ↗pdf ↗

We study contingent claims in a discrete-time market model where trading costs are given by convex functions and portfolios are constrained by convex sets. In addition to classical frictionless markets and markets with transaction costs or bid-ask spreads, our framework covers markets with nonlinear illiquidity effects…

2008-07-18abs ↗pdf ↗

This paper studies the optimal investment problem with random endowment in an inventory-based price impact model with competitive market makers. Our goal is to analyze how price impact affects optimal policies, as well as both pricing rules and demand schedules for contingent claims. For exponential market makers prefe…

2018-04-24abs ↗pdf ↗

Audit shows risk claims from distributional reinforcement learning agents are often false.

problem Evaluating the risk claims made by distributional reinforcement learning agents.
method Combines a decision-relevant screening metric, ground truth from Monte Carlo, and statistical methods to audit risk claims.
result 40-95% of the strongest risk claims are refuted, indicating the learned risk reflects a training artifact rather than environment stochasticity.

Study tests five popular trading signal families and finds four refuted, one inconclusive, and one not refuted.

problem Testing the viability of five popular trading signal families for generating a positive edge.
method Statistical edge testing, economic viability assessment, and finite-bankroll survival under leverage using exposure-matched benchmarks, stationary-bootstrap confidence intervals, and hierarchical Benjamini-Yekutieli control.
result Four out of five signal families are refuted, one is inconclusive, and one is not refuted.

We respond to the issues discussed by Farmer and Lillo (FL) related to our proposed approach to understanding the origin of power-law distributions in stock price fluctuations. First, we extend our previous analysis to 1000 US stocks and perform a new estimation of market impact that accounts for splitting of large ord…

2004-03-02abs ↗pdf ↗

Study shows subordinated Cramér-Lundberg model increases ruin probability.

problem Analyzing the impact of subordinated time-changed claims on insurance ruin probability.
method Examined a compound Poisson process modified by a Lévy subordinator.
result Probability of ruin decreases slowly with initial capital, despite unchanged total claim amount.

EBM improves car insurance claim severity and frequency prediction while maintaining interpretability.

problem Balancing predictive accuracy and interpretability in insurance claim modeling.
method Combines GAM and cyclic gradient boosting, providing interpretable predictions.
result EBM outperforms benchmark models in claim severity and frequency prediction.

The paper solves a utility-based hedging problem with quadratic costs.

problem Optimal trading strategy for hedging European contingent claims with quadratic transaction costs.
method Duality theory applied to exponential utility maximization problem.
result Explicit computation of optimal trading strategy for quadratic payoffs.

In this paper we investigate discrete time trading under integer constraints, that is, we assume that the offered goods or shares are traded in integer quantities instead of the usual real quantity assumption. For finite probability spaces and rational asset prices this has little effect on the core of the theory of no…

2017-08-25abs ↗pdf ↗

We develop a framework for computing the total valuation adjustment (XVA) of a European claim accounting for funding costs, counterparty credit risk, and collateralization. Based on no-arbitrage arguments, we derive backward stochastic differential equations (BSDEs) associated with the replicating portfolios of long an…

2016-08-09abs ↗pdf ↗

We study the pricing and the hedging of claim ψ which depends on the default times of two firms A and B. In fact, we assume that, in the market, we can not buy or sell any defaultable bond of the firm B but we can only trade defaultable bond of the firm A. Our aim is then to find the best price and hedging of ψ using o…

2012-09-26abs ↗pdf ↗

Unified comparison of gradient boosting algorithms for insurance claims.

problem Improving predictive accuracy and computational efficiency in insurance claim prediction.
method Unified notation and comprehensive numerical study comparing 12 gradient boosting algorithms on 5 datasets.
result No trade-off between model adequacy and predictive accuracy.

Develops a hedging method for multi-asset derivatives with correlation risk.

problem Hedging multi-asset derivatives exposed to correlation and covariance risk.
method Combines dynamic trading with static hedging instruments using Galtchouk--Kunita--Watanabe decomposition.
result Explicit semi-static replication formulas for covariance swaps and geometric dispersion trades.

The paper prices and replicates various financial contracts on a risky asset with stochastic volatility and jumps.

problem Pricing and replicating financial contracts on assets with stochastic volatility and jumps.
method Develops pricing and hedging formulas for various financial contracts, independent of the volatility process dynamics.
result Pricing and hedging formulas for financial contracts are derived without dependence on the volatility process dynamics.

We study a continuous-time financial market with continuous price processes under model uncertainty, modeled via a family P\mathcal{P} of possible physical measures. A robust notion NA1(P){\rm NA}_{1}(\mathcal{P}) of no-arbitrage of the first kind is introduced; it postulates that a nonnegative, nonvanishing claim cannot …

2014-10-18abs ↗pdf ↗

With globalization, countries are more connected than before by trading flows, which currently amount to at least 36 trillion dollars. Interestingly, approximately 30-60 percent of global exports consist of intermediate products. Therefore, the trade flow network of a particular product with high added values can be re…

2014-01-14abs ↗pdf ↗