arXiv research

Optimal linear contracts are possible even with memory in Gaussian settings.

Let $X$ be a proper CAT(0) space and let $G$ be a cocompact group of isometries of $X$ which acts properly discontinuously. Charney and Sultan constructed a quasi-isometry invariant boundary for proper CAT(0) spaces which they called the contracting boundary. The contracting boundary imitates the Gromov boundary for $δ…

The paper prices weather contracts using a complex temperature model.

New framework for learning policies that converge in out-of-sample regions.

New formulations capture aversion to ambiguity about volatility.

Study optimal contracts for pandemic risk, offering fixed shares and prevention mechanisms.

Hamiltonian dynamics-based algorithms achieve deterministic and accelerated convergence for convex optimization.

Derives pricing formulas for perpetual futures contracts.

Study on nonsmooth contractive SA with constant stepsize and Q-learning.

In this paper we analyzed dependencies in commodity markets investigating correlations of future contracts for commodities over the period 1998.09.01 - 2007.12.14. We constructed a minimal spanning tree based on the correlation matrix. The tree provides evidence for sector clusterization of investigated contracts. We a…

The paper develops a valuation framework for GLWB-LTC contracts with Levy dynamics and stochastic interest rates.

In this paper, we combine modern portfolio theory and option pricing theory so that a trader who takes a position in a European option contract and the underlying assets can construct an optimal portfolio such that at the moment of the contract's maturity the contract is perfectly hedged. We derive both the optimal hol…

This study examines lead-lag relationships in Chinese futures markets using high-frequency data.

Optimizes capital structure for life insurance companies with surplus participation.

Predicts short-term futures contract direction using neural networks and order flow data.

We give a sharp lower bound for the number of geometrically distinct contractible periodic orbits of dynamically convex Reeb flows on prequantizations of symplectic manifolds that are not aspherical. Several consequences of this result are obtained, like a new proof that every bumpy Finsler metric on $S^n$ carries at l…

Study optimizes smart contract adoption under high demand variability using Negative Binomial models.

Study on convex ordering in stochastic control for swing contracts, proving value function convexity.

Develops a new volatility model for prediction markets.

Two algorithms learn Gaussian graphical models from Glauber dynamics trajectories.

We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary independent increments process for the low-frequency dynamics, and model the la…

Study risk-controlling prediction sets for single trajectory data from dynamical systems.

This work studies the contraction coefficients of Schrödinger bridge problems in linear systems.

This study compares microscopic and macroscopic models for commodity index derivatives pricing.

Based on a new coupling approach, we prove that the transition step of the Hamiltonian Monte Carlo algorithm is contractive w.r.t. a carefully designed Kantorovich (L1 Wasserstein) distance. The lower bound for the contraction rate is explicit. Global convexity of the potential is not required, and thus multimodal targ…

Study develops smart contract framework for procurement under demand variability.

Voluntary insurance contracts constitute a puzzle because they increase the expectation value of one party's wealth, whereas both parties must sign for such contracts to exist. Classically, the puzzle is resolved by introducing non-linear utility functions, which encode asymmetric risk preferences; or by assuming the p…

Reinsurance counterparty credit risk (RCCR) is the risk of a loss arising from the fact that a reinsurance company is unable to fulfill her contractual obligations towards the ceding insurer. RCCR is an important risk category for insurance companies which, so far, has been addressed mostly via qualitative approaches. …

We consider a contracting problem in which a principal hires an agent to manage a risky project. When the agent chooses volatility components of the output process and the principal observes the output continuously, the principal can compute the quadratic variation of the output, but not the individual components. This…

Let $X$ be a proper geodesic metric space and let $G$ be a group of isometries of $X$ which acts geometrically. Cordes constructed the Morse boundary of $X$ which generalizes the contracting boundary for CAT(0) spaces and the visual boundary for hyperbolic spaces. We characterize Morse elements in $G$ by their fixed po…

We analyze the counterparty risk embedded in CDS contracts, in presence of a bilateral margin agreement. First, we investigate the pricing of collateralized counterparty risk and we derive the bilateral Credit Valuation Adjustment (CVA), unilateral Credit Valuation Adjustment (UCVA) and Debt Valuation Adjustment (DVA).…

Proposes a regularization approach to model German power derivative market, identifying significant risk spillovers.

New method improves sampling efficiency in complex stochastic systems.

Develops a new volatility model for prediction markets.

This paper introduces a method to improve GNN stability and robustness.

We describe a general method to construct completely bounded idempotent mappings on operator spaces, starting from amenable semigroups of completely bounded mappings. We then explore several applications of that method to injective operator spaces, fixed points of completely contractive mappings, Toeplitz operators, dy…

New Q-learning method achieves optimal sample complexity for average-reward problems.

Study develops a smart contract framework for efficient and fair resource allocation.

Investigates optimal withdrawal strategies in VA contracts with tax and ratchet mechanisms.

The paper values reinsurance contracts for dynamic catastrophe claims without arbitrage.

We propose a new non-parametric framework for learning incrementally stable dynamical systems x' = f(x) from a set of sampled trajectories. We construct a rich family of smooth vector fields induced by certain classes of matrix-valued kernels, whose equilibria are placed exactly at a desired set of locations and whose …

Gibbs sampler contracts entropy under strong log-concavity, improving mixing time.

We study the problem of dynamically trading multiple futures contracts with different underlying assets. To capture the joint dynamics of stochastic bases for all traded futures, we propose a new model involving a multi-dimensional scaled Brownian bridge that is stopped before price convergence. This leads to the analy…

Stochastic differential equation approximation for linear TD(0) under Markovian noise

Paper proposes a new descriptor for early trajectory characterization in matrix iterations.

We consider a continuous time Principal-Agent model on a finite time horizon, where we look for the existence of an optimal contract both parties agreed on. Contrary to the main stream, where the principal is modelled as risk-neutral, we assume that both the principal and the agent have exponential utility, and are ris…

New bounds for SGLD show error decreases with more data.

In commodity and energy markets swing options allow the buyer to hedge against futures price fluctuations and to select its preferred delivery strategy within daily or periodic constraints, possibly fixed by observing quoted futures contracts. In this paper we focus on the natural gas market and we present a dynamical …