Research
On-device research index

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

Trend · papers per month

97194290387 · Jun 202019922001200920172026
48 results for Freight Rate Risk

This research proposes a method to hedge freight rate risk in shipping markets under model uncertainty.

problem Managing freight risk in shipping markets under model uncertainty.
method The approach uses Wasserstein barycenter for modeling freight rates dynamics and optimal hedging strategy selection.
result The proposed method provides robust hedging strategies even in high noise cases.

Empirical study shows carriers ignore past shippers' behavior, focusing only on current actions.

problem Opportunistic behavior by shippers and carriers in dynamic freight markets.
method Empirical analysis of carrier reciprocity in US truckload transportation sector.
result Carriers do not remember shippers' past behaviors but respond to current actions.

The paper introduces risk consistency properties for credit ratings.

problem Promoting prudent investment decisions in credit ratings.
method Introducing and studying risk consistency properties in the framework of Choquet rating criteria.
result Characterization of Choquet risk measures and rating criteria satisfying risk consistency properties.

We define risk-free portfolios using three gauge invariant differential operators that require such portfolios to be insensitive to price changes, to be self-financing, and to produce a zero real return so there are no risk-free profits. This definition identifies the risk-free rate as the return of an infinitely diver…

2016-05-11abs ↗pdf ↗

Study examines risk premium convergence rates in risk sharing contracts.

problem Analyzing risk premium convergence rates in risk sharing contracts.
method Examines the limiting behavior of risk premium associated with Pareto optimal risk sharing contracts under general law-invariant risk measures.
result Risk premium convergence rate is typically n1/2n^{1/2}, not nn.

Paper bounds convergence rate of adversarial surrogate risk.

problem Vulnerability of binary classification models to adversarial attacks.
method Characterizes conditions for adversarial consistency and provides surrogate risk bounds.
result Surrogate risk bounds quantify the rate of convergence of adversarial classification risk.

This paper improves credit risk analysis by incorporating state-dependent recovery rates into a factor model.

problem Accurate default forecasting in credit risk analysis.
method Extends a one-factor Gaussian copula model to include state-dependent recovery rates and a common factor.
result The proposed model outperforms other models in default prediction, especially during hectic periods.

Develops a bi-variate stochastic framework to model mortality and interest rates with long-range dependence.

problem Captures long-range dependence and instantaneous correlation in mortality and interest rates.
method Mixed fractional Brownian motions, analytical solutions, risk-neutral measure, sequential parameter estimation.
result Explicit pricing of zero-coupon bonds and extreme mortality bonds, practical implications for pricing and risk management.

The geometric Lévy model (GLM) is a natural generalisation of the geometric Brownian motion model (GBM) used in the derivation of the Black-Scholes formula. The theory of such models simplifies considerably if one takes a pricing kernel approach. In one dimension, once the underlying Lévy process has been specified, th…

2011-11-09abs ↗pdf ↗

Model estimates LIBOR rates and finds COVID-19 spread spike due to credit risk.

problem Estimating LIBOR rates and understanding the factors affecting them.
method Developed a joint model for various LIBOR-related rates and used it to decompose spreads.
result Credit risk mainly caused the spike in LIBOR-OIS spread during the COVID-19 onset, with equal contributions from credit and funding-liquidity risks on average.

Model trains passing events on a bridge using multilevel Gaussian process.

problem Represent aggregate train-passing events from a bridge monitoring system.
method Formulate a combined model with low-rank approximation hierarchical Gaussian process, incorporating domain expertise as constraints.
result Allow for simulation of previously unobserved train types.

The paper analyzes insurance risks using stochastic models.

problem Interest rate and variance risks in unit-linked insurance policies.
method General stochastic volatility models and stochastic interest rates are used to price unit-linked life insurance contracts.
result A perfect hedging strategy is provided and compared with the Black-Scholes model.

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated by a maximum likelihood approach using historical rating transitions and heurist…

2009-11-19abs ↗pdf ↗

Unified framework for ESG-inclusive portfolio optimization and pricing.

problem Incorporating ESG ratings into dynamic asset pricing theory.
method Introducing ESG-valued return as a linear transformation of financial and ESG scores, preserving traditional risk aversion with an ESG affinity parameter.
result Developed a more complex portfolio optimization problem in a space governed by reward, risk, and ESG score.

The paper models exchange rate risk premium using mean-reverting dynamics.

problem Empirical failure of uncovered interest parity (UIP).
method Modeling risk premium using Ornstein-Uhlenbeck (OU) process embedded in stochastic differential equation for exchange rate.
result The model shows strong predictive performance at short and long horizons, but underperforms at intermediate horizons.

Study extreme-case Value-at-Risk under IFR distributions, providing guidance for risk management.

problem Understanding extreme-case risk measures under distributional ambiguity and increasing failure rate.
method Characterized extreme-case range Value-at-Risk under mean and variance constraints with increasing failure rate.
result Characterized specific characteristics of extreme-case distributions under IFR constraints.

MILLION framework optimizes portfolio risk and return efficiently.

problem Optimizing risk and return in AI for FinTech portfolio management.
method Two phases: return maximization with auxiliary objectives and risk control with portfolio interpolation and improvement.
result Framework achieves fine-grained risk control and improved return rates.

Study on estimating invertible functions with minimax analysis.

problem Minimizing risk of estimating invertible functions on a plane.
method Introduce two types of L2L^2-risks, derive lower and upper rates for minimax values, develop an asymptotically almost everywhere invertible estimator.
result Invertibility does not reduce the complexity of the estimation problem in terms of the rate.

Copula models for sovereign ratings improved by incorporating climate risk.

problem Modeling nonlinear dependence and clustering in sovereign rating migrations.
method Mixed-difference transformation, MAGMAR(1,1) copula process, consistent and asymptotically normal estimators.
result Gumbel MAGMAR(1,1) specification outperforms other models in empirical performance.

We provided an analytical representation of the price of a barrier option with one type of special moving barrier. We consider the case that risk free rate, dividend rate and stock volatility are time dependent. We get a pricing formula and put call parity for barrier option when the moving barrier has a special relati…

2013-03-06abs ↗pdf ↗

The paper uses stochastic control to analyze interest rate markets with roll-over risk.

problem Analyzing interest rate markets with roll-over risk without classical arbitrage assumptions.
method Stochastic optimal control problems with power-type objective functionals.
result Endogenously determined funding-liquidity spread.

Algorithm minimizes risk for multiclass classification of stochastic diffusion paths.

problem Multiclass classification of stochastic diffusion paths with distinct drift functions.
method Empirical risk minimization using L2 risk.
result Achieves fast rates of convergence under margin assumption.

Aggregate and systemic risk in complex systems are emergent phenomena depending on two properties: the idiosyncratic risks of the elements and the topology of the network of interactions among them. While a significant attention has been given to aggregate risk assessment and risk propagation once the above two propert…

2017-11-21abs ↗pdf ↗

Convolutional neural networks improve image classification accuracy.

problem Improving accuracy in image classification.
method Analyzing the convergence rate of misclassification risk for image classifiers.
result A rate of convergence independent of image dimension proves the effectiveness of CNNs.

Analysis finds no evidence of banks managing deposit run risk prior to 2023 Regional Banking Crisis.

problem Determining factors for deposit run risk management before a regional banking crisis.
method Cross-sectional analysis of interest rate and equity use by banks.
result No evidence of banks managing deposit run risk via their balance sheet.

Exact risk and learning rate curves derived for adaptive SGD on high-dimensional problems.

problem Analyzing risk and learning rate dynamics in high-dimensional optimization problems.
method Developed a framework to give exact expressions for risk and learning rate curves using ODEs.
result Exact expressions for risk and learning rate curves, with detailed analysis of two adaptive learning rates.

Measures financial resilience using BSDEs and their properties.

problem Measuring financial resilience in dynamic risk environments.
method Developed stochastic calculus for BSDEs with jumps, revealing resilience rate as expectation of generator.
result Resilience rate can be represented as expectation of BSDE generator, revealing properties of dynamic risk measures.

The paper studies estimation of parameters of diffusion market models from historical data. The standard definition of implied volatility for these models presents its value as an implicit function of several parameters, including the risk-free interest rate. In reality, the risk free interest rate is unknown and need …

2013-03-20abs ↗pdf ↗

The paper proposes a new method to estimate interest rates consistently under both risk-neutral and real-world measures.

problem Consistent estimation of interest rates under both risk-neutral and real-world measures.
method Proposes a framework using progressive and square-integrable functions to specify the change of measure, and introduces two time-dependent candidates: step and linear functions.
result The proposed methods produce more stable and realistic long-term interest rate forecasts compared to using a constant function.