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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.

168,695 papers · 148 categories

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23466891 · Jun 202019922001200920172026
48 results for swap regret

Paper solves no-swap regret minimization for combinatorial bandits with polylogarithmic dependence on N.

problem Design efficient no-swap regret algorithms for combinatorial bandits with exponentially large action space.
method Introduces a no-swap-regret learning algorithm with polylogarithmic dependence on N and demonstrates efficient implementation.
result Achieves no-swap regret with polylogarithmic dependence on N, resolving an open problem.

The paper improves on existing algorithms for minimizing different types of regret in online learning.

problem Minimizing external, internal, and swap regret in online learning with multiple experts.
method Develops a single algorithm using φ-regret minimization and Haar-wavelet-inspired matrix features to achieve optimal bounds in various scenarios.
result Achieves optimal bounds for external, internal, and swap regrets in different expert scenarios.

New insights link no-regret learning to online conformal prediction in adversarial settings.

problem Understanding the relationship between no-regret learning and online conformal prediction in adversarial environments.
method Analysis of existing algorithms and new connections between no-regret learning and conformal prediction.
result No-regret learning algorithms can provide group-conditional coverage guarantees in adversarial settings.

We introduce CSE for MLSF games and devise online learning algorithms for achieving no-external Stackelberg-regret.

problem Learning equilibrium in leader-follower games with noisy bandit feedback.
method Proposed Correlated Stackelberg Equilibrium (CSE) and online learning algorithms balancing exploration and exploitation.
result Achieves no-external Stackelberg-regret, converging to approximate CSE.

Algorithm minimizes regret and converges to equilibria in Markov games.

problem Regret minimization and convergence to equilibria in general-sum Markov games under adversarial opponents.
method Decentralized algorithm that uses policy optimization and controls path length to achieve sublinear regret.
result Sublinear regret guarantees for convergence to correlated equilibrium in Markov games.

New algorithm achieves online calibration in polynomial time for high-dimensional problems.

problem Online calibration of high-dimensional probability distributions over many days.
method Randomly selects among sub-forecasters, each predicting empirical outcome frequency over recent time windows.
result Achieves asymptotically calibrated strategies after polynomial number of rounds, resolving open questions.

Debt swaps improve financial networks by optimizing clearing payments and stability.

problem Improving financial network stability and efficiency through debt swaps.
method Analyzing computational complexity of debt swaps, focusing on semi-positive swaps and v-improving swaps.
result Polynomial length of sequences of semi-positive v-improving swaps for ranking-based clearing, but NP-hard for arbitrary v-improving swaps.

We derive an arbitrage free relationship between recovery swap rates, digital default swap spreads and conventional CDS spreads, and argue that the fair forward recovery rate used in recovery swaps must contain a convexity premium over the expected recovery value.

2010-01-05abs ↗pdf ↗

The paper extends the market price of risk for electricity swap contracts, incorporating jump risk.

problem Pricing electricity swap contracts with consideration of jump risk.
method Introducing a Merton type model with jumps and transferring to the physical measure, comparing arithmetic and geometric averaging.
result A decomposition of swap's market price of risk into classical and market price of risk components.

Improved bounds for multicalibration and omniprediction in online and distributional settings.

problem Achieving efficient multicalibration and omniprediction in fairness and loss minimization.
method Proposed an efficient algorithm achieving improved rates for multicalibration and omniprediction.
result Achieved O(T13)O(T^{\frac{1}{3}}) 2\ell_{2}-swap multicalibration error for convex Lipschitz functions.

A variance swap is a derivative with a path-dependent payoff which allows investors to take positions on the future variability of an asset. In the idealised setting of a continuously monitored variance swap written on an asset with continuous paths it is well known that the variance swap payoff can be replicated exact…

2011-04-20abs ↗pdf ↗

The SABR model is shortly presented and the volatility swap explained. The fair value for a volatility swap is then computed using the usual theory in financial mathematics. An analytical solution using confluent hypergeometric functions is found. The solution is then verified using Rama Cont's functional calculus.

2013-03-25abs ↗pdf ↗

Paper examines pricing and hedging for cross-currency swaps referencing backward-looking rates.

problem Pricing and hedging cross-currency swaps with backward-looking rates.
method Uses interest rate and currency futures for hedging, analyzes arbitrage-free multi-curve setting.
result Explicit pricing and hedging results for CCBS with backward-looking rates.

This paper proposes swaps on two important new measures of generalized variance, namely the maximum eigen-value and trace of the covariance matrix of the assets involved. We price these generalized variance swaps for financial markets with Markov-modulated volatilities. We consider multiple assets in the portfolio for …

2019-08-11abs ↗pdf ↗

We study the fair strike of a discrete variance swap for a general time-homogeneous stochastic volatility model. In the special cases of Heston, Hull-White and Schobel-Zhu stochastic volatility models we give simple explicit expressions (improving Broadie and Jain (2008a) in the case of the Heston model). We give condi…

2013-05-30abs ↗pdf ↗

Paper explores volatility swaps in rough volatility models.

problem Understanding volatility swaps in rough volatility models.
method Examines the relationship between forward start volatility swaps and implied volatilities in rough volatility models.
result The leading term approximation error in the correlated case does not depend on the time to forward start date.

New algorithm for online omniprediction with strong guarantees for continuous hypothesis classes.

problem Online adversarial learning with continuous hypothesis classes.
method Developed an oracle-efficient online multicalibration algorithm for infinite benchmark classes.
result First efficient online omnipredictor with strong guarantees for Lipschitz convex loss functions.

We develop robust pricing and hedging of a weighted variance swap when market prices for a finite number of co--maturing put options are given. We assume the given prices do not admit arbitrage and deduce no-arbitrage bounds on the weighted variance swap along with super- and sub- replicating strategies which enforce t…

2010-01-15abs ↗pdf ↗

The rank nn swapping algebra is the Poisson algebra defined on the ordered pairs of points on a circle using the linking numbers, where a subspace of (Kn×Kn)r/GL(n,K)(\mathbb{K}^n \times \mathbb{K}^{n*})^r/\operatorname{GL}(n,\mathbb{K}) is its geometric mode. In this paper, we find an injective Poisson homomorphism from the Poisso…

2019-04-15abs ↗pdf ↗

Interest rate market models, like the LIBOR market model, have the advantage that the basic model quantities are directly observable in financial markets. Inflation market models extend this approach to inflation markets, where zero-coupon and year-on-year inflation-indexed swaps are the basic observable products. For …

2015-03-17abs ↗pdf ↗

Proposes a new method for completing swap cycles in decentralized exchanges.

problem Completing swap cycles in decentralized exchanges efficiently and without slippage.
method Introduces an asset matrix formulation to verify and complete CoW cycles using graph traversal and imbalance correction.
result Demonstrates efficient discovery and insertion of synthetic orders for atomic cycle closure.

Empirical study finds variance swap rate is affine in spot variance for S&P500 data.

problem Investigating the relationship between variance swap rate and spot variance.
method Empirical analysis using S&P500 data from 2006-2018, testing different models.
result Affine relationship between variance swap rate and spot variance is supported.