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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.

169,051 papers · 148 categories

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48 results for Cash-in risk

Central bank optimizes bailout cash injection to limit defaults.

problem Optimizing cash injection to limit defaults in a system of mutual obligations.
method Proved convergence and solved a drift controlled Stefan problem using mean field control and policy gradient methods.
result Optimal strategies involve subsidizing banks with equity values in a time-dependent region.

Social Security and other public policies can be viewed as a series of cash in and outflows that depend on parameters such as the age distribution of the population and the retirement age. Given forecasts of these parameters, policies can be designed to be financially stable, i.e., to terminate with a zero balance. If …

2012-01-30abs ↗pdf ↗

Examines various types of cryptocurrencies and their economic properties.

problem Understanding the economic characteristics of different cryptocurrencies.
method Characterization and analysis of different classes of cryptocurrencies using balance sheet operations.
result Different types of cryptocurrencies have distinct economic properties, ranging from commodities to liabilities of central banks.

Optimal control of reserve assets for stablecoins to maintain peg stability.

problem Balancing immediate liquidity and yield on reserve assets for stablecoin peg maintenance.
method Developed a stochastic model predictive control framework with moment closure for event intensities, incorporating a soft-thresholding structure for rebalancing.
result Optimal policy shifts predictably toward cash as expected outflows intensify or windows lengthen, preserving most bill carry in calm markets and quickly building cash during stress.

We propose a new approach to utilities that is consistent with state-dependent utilities. In our model utilities reflect the level of consumption satisfaction of flows of cash in future times as they are valued when the economic agents are making their consumption and investment decisions. The theoretical framework use…

2006-03-14abs ↗pdf ↗

The ad-trading desks of media-buying agencies are increasingly relying on complex algorithms for purchasing advertising inventory. In particular, Real-Time Bidding (RTB) algorithms respond to many auctions -- usually Vickrey auctions -- throughout the day for buying ad-inventory with the aim of maximizing one or severa…

2015-11-26abs ↗pdf ↗

Paper simplifies complex AI exploration by predicting future rewards.

problem Training machines to optimally gather complex information.
method Developed a denser reward structure using cross-value to decouple exploration and exploitation.
result Demonstrated successful learning of challenging tasks without shaping or bonuses.

Optimizes cash management in ATM networks to reduce costs and increase revenue.

problem Minimizing cash costs while ensuring adequate funds in a network of ATMs.
method Developed a discrete optimal control model using forecasting techniques and control theory.
result The proposed model outperforms classical inventory management models, earning 30% more revenue.

Develops a new method for risk diversification using dynamic risk measures.

problem Dynamic risk diversification in investment portfolios.
method Introduces dynamic risk contributions and a recursive optimization approach for coherent dynamic distortion risk measures.
result Dynamic risk budgeting strategies can be solved using deep learning.

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.

Optimal risk sharing found for heterogeneous risk attitudes using distortion risk measures.

problem Risk sharing in economies with diverse risk attitudes.
method Modeling preferences with distortion risk measures, using comonotonic and counter-monotonic principles.
result Optimal risk sharing strategies identified based on risk attitudes, reducing the nn-agent problem to a two-agent formulation.

This paper extends risk parity to continuous-time, solving risk budgeting problems.

problem Achieving robust risk across different assets in continuous-time.
method Characterizing risk contributions and solving risk budgeting problems using continuous-time terminal variance.
result Risk contributions and risk budgets can be represented as predictable processes in continuous-time.

Approximate Incremental Value-at-Risk formulae provide an easy-to-use preliminary guideline for risk allocation. Both the cases of risk adding and risk pooling are examined and beta-based formulae achieved. Results highlight how much the conditions for adding new risky positions are stronger than those required for ris…

2002-04-28abs ↗pdf ↗

New set-valued star-shaped risk measures introduced for better risk assessment.

problem Improving risk assessment in financial contexts.
method Developed new set-valued star-shaped risk measures and proved their representation theorems.
result Set-valued star-shaped risk measures can be represented as unions of set-valued convex risk measures.

Study risk sharing among agents with varying risk preferences.

problem Risk sharing among agents with heterogeneous risk measures.
method Derive explicit solutions for inf-convolution and counter-monotonic inf-convolution under varying risk seeking.
result Explicit solutions for inf-convolution and counter-monotonic inf-convolution can be represented by a generalization of distortion risk measures.

The article develops a model for skewness risk in risk parity portfolios.

problem Managing skewness risk in asset allocation models.
method Modeling asset returns with skewness and jumps, deriving analytical formulas for risk contributions.
result Skewness-based risk parity portfolios outperform volatility-based portfolios in managing jump risks.

The paper establishes a connection between different risk measures and their risk contributions.

problem Understanding the relationship between conditional coherent and deviation risk measures.
method Axiomatic framework and continuous-time risk contribution analysis.
result Risk contributions of time-consistent risk measures are also time-consistent.

The study reveals unspanned risks in equity option risk premiums, explaining negative premiums for certain options.

problem Explaining negative risk premiums for certain equity option types.
method Developed a decomposition of equity option risk premiums, operationalized the pricing kernel process, and incorporated unspanned risks.
result Empirical evidence supports the presence of unspanned risks, explaining negative risk premiums for certain options.

Paper introduces new risk measures for default risk and model uncertainty.

problem Model uncertainty and default risk in rating systems.
method Introduces default risk measures and discusses their properties and impacts.
result Different default risk measures and margins of conservatism affect risk-weighted assets.

Diversified risk parity strategies outperform equally-weighted portfolios in various asset universes.

problem Finding optimal portfolio allocations that balance risk and reward.
method Integrates various reward-risk measures and generic allocation rules into diversified risk parity.
result Diversified reward-risk parity strategies exhibit higher average returns, Sharpe ratios, and Calmar ratios compared to equally-weighted risk portfolios.

Study risk-sensitive reinforcement learning with Lipschitz dynamic risk measures, establishing regret bounds.

problem Risk-sensitive reinforcement learning in Markov decision processes.
method Two model-based algorithms for Lipschitz dynamic risk measures, focusing on regret bounds.
result Upper bounds demonstrate optimal dependencies on actions and episodes, reflecting risk sensitivity vs. sample complexity trade-off.

Examines optimal risk sharing with realistic risk attitudes, finding risk seeking in certain subdomains.

problem Optimal risk sharing with empirically realistic risk attitudes.
method Allows for risk-seeking agents, generalizes expected utility, and uses counter-monotonic improvement theorem.
result First empirical results on optimal risk sharing with realistic risk attitudes.

The paper models and prices cyber insurance risks, distinguishing idiosyncratic, systematic, and systemic risks.

problem Modeling and pricing cyber insurance policies, especially for systemic risks.
method Distinguishes three types of cyber risks and proposes methods for their valuation.
result Complex methods are needed for systemic cyber risks, including risk-neutral valuation and monetary risk measures.

Spectral risk measures are attractive risk measures as they allow the user to obtain risk measures that reflect their risk-aversion functions. To date there has been very little guidance on the choice of risk-aversion functions underlying spectral risk measures. This paper addresses this issue by examining two popular …

2011-03-29abs ↗pdf ↗

Study combines intra-risk and contagion risk for SME bankruptcy prediction.

problem Predicting bankruptcy risk of SMEs considering both intra-risk and contagion risk.
method Proposes a novel model using Graph Neural Networks to combine intra-risk and contagion risk.
result Model outperforms state-of-the-art methods in bankruptcy prediction.

This paper shows how to calculate risk measures for sums of two counter-monotonic risks.

problem Calculating risk measures for sums of two counter-monotonic risks.
method Using a fixed distortion function and expressing the risk measure of a sum as the sum of two related measures of the marginals.
result The risk measure of a sum of two counter-monotonic risks can be expressed as the sum of two related distortion risk measures of the marginals.

Copulas outperform marginal models in multivariate risk forecasting, reducing model risk by narrowing down the set of models.

problem Model risk in multivariate risk forecasting, especially during crises.
method Comprehensive empirical study comparing Copula-GARCH models with fixed marginals, copulas, or neither.
result Model risk is almost entirely due to copula choice, not marginal models.

Study uses TV news to measure climate risks affecting clean energy firms.

problem Understanding how climate risks impact clean energy firms' financial stability.
method Developed climate risk measures from TV news coverage and analyzed their effects on clean energy firms' risks.
result Increased TV news coverage of climate risks correlates with higher systematic risk and lower idiosyncratic risk for clean energy firms.

Develops a statistical framework for coherent risk estimation.

problem Constructing coherent risk estimators with sound financial and statistical properties.
method Inspired by axiomatic risk measure theory, defines coherent risk estimators through robust representations linked to LL-estimators.
result Demonstrates that coherence of a risk measure does not necessarily carry over to its estimators and shows alternative weight structures can lead to different outcomes.

The paper calculates VaR and CTE for extreme and aggregate risks using FGM copula.

problem Estimating risk measures for extreme and aggregate risks of dependent and independent markets.
method Used FGM copula to model dependence, exponential and pareto distributions for marginal risks.
result Effect of dependency on VaR and CTE of extreme and aggregate risks analyzed.

Develops a risk-sensitive reinforcement learning framework for uncertain environments.

problem Learning in uncertain environments with varying risk preferences.
method Integrates utility functions and risk measures into reinforcement learning, tuning risk preference with parameter β.
result Risk-averse, risk-neutral, and risk-taking behaviors can be achieved and compared.