CENNSurv models cumulative effects of time-dependent exposures on survival outcomes.
problem Challenges in modeling cumulative effects of time-dependent exposures on survival outcomes.
method CENNSurv, a novel deep learning approach that captures dynamic risk relationships from time-dependent data.
result CENNSurv reveals multi-year lagged and short-term behavioral shifts in survival outcomes.
The paper clarifies long-horizon investment and DCA, showing no risk reduction but different exposure profiles.
problem Misleading claims about reducing risk with longer investment horizons and DCA.
method Unified probabilistic framework, defining risk and uncertainty, and introducing effective investment exposure.
result Different investment timing strategies can lead to distinct exposure profiles over time, affecting risk and uncertainty.
New risk metric for AI systems reduces safety risks with minimal data.
problem Risk assessment in multi-agent AI systems.
method Free Energy Principle applied to risk metrics, introducing Cumulative Risk Exposure.
result Gatekeepers improve system safety in autonomous vehicle fleets.
Stocks of more resilient firms outperformed during the pandemic, reflecting disaster risk.
problem The impact of social distancing on firms' operations and stock performance.
method Cross-sectional analysis of firms' resilience and stock performance, controlling for risk factors.
result Stocks of more resilient firms are expected to yield significantly lower returns than less resilient ones, reflecting disaster risk.
The study analyzes ETFs' portfolio optimization and tail-risk management.
problem Analyzing the performance of actively managed ETFs in managing risk and diversification.
method Daily Bloomberg data for 30 funds, evaluating various strategies under long-only and long-short constraints.
result Tangency-type portfolios generally outperform buy-and-hold benchmarks, while minimum-variance and CVaR-minimizing portfolios sacrifice upside for downside control.
Paper introduces a new method for efficient portfolio risk quantification.
problem Efficiently quantify risk in large portfolios with many trades and few dominant risk factors.
method Combines Fourier-cosine series with tensor decomposition techniques for dimension reduction.
result Achieves relative errors below 0.1% with significant runtime improvement.
Study shows short exposure and systematic risk exposure affect disposition effect asymmetries.
problem Understanding disposition effect in short vs long exposure positions and systematic risk.
method Generalized Odean measures, introduced Value metric, implemented dispositionEffect R package.
result Short positions exhibit weaker disposition effect than long positions under narrow framing, reversing in integrated framing.
This paper optimizes multi-channel sequential advertising to maximize cumulative revenue.
problem Maximizing cumulative revenue in multi-channel sequential advertising under a budget constraint.
method Formulated as a dynamic knapsack problem, proposed a bilevel optimization framework with action space reduction.
result Significantly improved cumulative revenue compared to state-of-the-art baselines.
We propose an interacting particle system to model the evolution of a system of banks with mutual exposures. In this model, a bank defaults when its normalized asset value hits a lower threshold, and its default causes instantaneous losses to other banks, possibly triggering a cascade of defaults. The strength of this …
Deep learning approximates Bermudan option exposures and future values.
problem Computing accurate expected and future exposures for high-dimensional Bermudan options.
method Neural network-based approach combining Deep Optimal Stopping and regression.
result Neural network approximations of pathwise option values are more accurate.
Counterparty Risk FAQ: Credit VaR, PFE, CVA, DVA, Closeout, Netting, Collateral, Re-hypothecation, WWR, Basel, Funding, CCDS and Margin Lendingq-fin.PR We present a dialogue on Counterparty Credit Risk touching on Credit Value at Risk (Credit VaR), Potential Future Exposure (PFE), Expected Exposure (EE), Expected Positive Exposure (EPE), Credit Valuation Adjustment (CVA), Debit Valuation Adjustment (DVA), DVA Hedging, Closeout conventions, Netting clauses, Collateral …
Measurement and management of credit concentration risk is critical for banks and relevant for micro-prudential requirements. While several methods exist for measuring credit concentration risk within institutions, the systemic effect of different institutions' exposures to the same counterparties has been less explore…
Paper optimizes neural networks for Bermudan option pricing with faster convergence and risk management tools.
problem Efficiently pricing Bermudan options with static hedging and risk management.
method Monte-Carlo-based artificial neural network framework with novel optimisation algorithm.
result The proposed neural network accelerates convergence and provides improved risk management tools.
Systemic risk arises as a multi-layer network phenomenon. Layers represent direct financial exposures of various types, including interbank liabilities, derivative- or foreign exchange exposures. Another network layer of systemic risk emerges through common asset holdings of financial institutions. Strongly overlapping…
Study analyzes crypto asset risk exposures using a divide-and-conquer approach.
problem Lack of high-frequency macro-financial proxies for estimating risk.
method Two-stage divide-and-conquer approach: first stage estimates idiosyncratic and market risk, second stage identifies latent economy-wide factors.
result Heterogeneous exposures to idiosyncratic and systematic risk across crypto assets.
The study models mortgage prepayment risk, accounting for behavioral uncertainty, and provides replication strategies.
problem Modeling and replicating the prepayment option of mortgages with behavioral uncertainty.
method Modeling behavioral uncertainty as a non-hedgeable risk factor, proving its impact on exposure value, and using IRSs and swaptions for replication.
result Including behavioral uncertainty reduces the exposure's value, and swaptions are necessary for optimal replication.
A risk-averse agent hedges her exposure to a non-tradable risk factor U using a correlated traded asset S and accounts for the impact of her trades on both factors. The effect of the agent's trades on U is referred to as cross-impact. By solving the agent's stochastic control problem, we obtain a closed-form expr…
The paper tackles robust design selection for online experiments under uncertain interference mechanisms.
problem Designing experiments in ads, recommendations, and member-experience systems when interference mechanisms are unknown.
method Formulates the problem as robust design selection over uncertain exposure mechanisms. Compares designs by worst-case planning risk over an ambiguity set combining various factors.
result Develops a geometry-aware guarantee and robust selector theorem with excess-risk control, exact recovery under separation, and certified shortlists when the risk surface is flat.
We study the risk criterion for investments based on the drawdown from the maximal value of the capital in the past. Depending on investor's risk attitude, thus his risk exposure, we find that the distribution of these drawdowns follows a general power law. In particular, if the risk exposure is Kelly-optimal, the expo…
Paper uses neural networks to compress large portfolios of options, reducing risk and capital requirements.
problem Managing risk and capital requirements for large portfolios of financial options.
method Artificial neural network framework for portfolio compression, static hedging, and risk management.
result The compressed portfolio's risk profiles align closely with the target portfolio's, reducing capital requirements.
Sparse grids reduce xVA exposure evaluations by up to 6000 times.
problem Efficiently computing exposures for xVA in large portfolios with many risk factors.
method Sparse Grid Method combined with Stochastic Collocation and Smolyak's extension.
result Significant reduction in the number of portfolio evaluations, up to 6000 times.
We present an approach to derivative exposure management based on subjective and implied probabilities. We suggest to maximize the valuation difference subject to risk constraints and propose a class of risk measures derived from the subjective distribution. We illustrate this process with specific examples for the two…
The paper calculates bounds for risk metrics and entropies under partial information constraints.
problem Analyzing risk metrics and entropies for unimodal, symmetric distributions with limited information.
method Develops lower and upper bounds for worst-case distortion riskmetrics and weighted entropy for unimodal, symmetric distributions with known mean and variance.
result Sharp upper bounds for distortion riskmetrics and weighted entropy for symmetric distributions.
Management of systemic risk in financial markets is traditionally associated with setting (higher) capital requirements for market participants. There are indications that while equity ratios have been increased massively since the financial crisis, systemic risk levels might not have lowered, but even increased. It ha…
Develops regression trees for estimating cumulative incidence curves in competing risks.
problem Estimating cumulative incidence functions in competing risks settings.
method Uses augmented estimators of the Brier score risk to build and prune regression trees.
result Demonstrates the utility of the proposed methods through simulation studies and real data.
The study tests a functional-form restriction on risk exposure dynamics using margin debt data.
problem Understanding risk exposure dynamics under capital constraints and slack.
method Testing a regime-conditional functional-form restriction on aggregate risk-exposure dynamics implied by VaR-constrained intermediary models.
result The contraction and growth of exposures under capital constraints and slack are observed and tested.
This research develops a new framework to measure AI investment returns considering both gains and risks.
problem Traditional ROI calculations fail to account for AI's dual impact on risk reduction and new exposures.
method Integrates ISO 42001 and regulatory exposure into a comprehensive financial framework using risk quantification methods.
result Accurate AI investment evaluation requires modeling both productivity gains and risk exposures.
We consider thin incomplete financial markets, where traders with heterogeneous preferences and risk exposures have motive to behave strategically regarding the demand schedules they submit, thereby impacting prices and allocations. We argue that traders relatively more exposed to market risk tend to submit more elasti…
Develops a climate risk model for asset managers.
problem Climate-related risks affecting asset performance and productivity.
method Uses the Vasicek model with downward jumps to represent climate impacts on asset dynamics.
result Expected losses increase over time due to climate-related extreme events.
Financial markets are exposed to systemic risk, the risk that a substantial fraction of the system ceases to function and collapses. Systemic risk can propagate through different mechanisms and channels of contagion. One important form of financial contagion arises from indirect interconnections between financial insti…
The paper analyzes worst-case distortion risk metrics and weighted entropy under partial information.
problem Analyzing worst-case distortion risk metrics and weighted entropy with limited information.
method General distributions, partial information (mean and variance), various entropies and risk measures.
result Provides worst-case results for distortion risk metrics and weighted entropy.
We introduce a new method to calculate the credit exposure of European and path-dependent options. The proposed method is able to calculate accurate expected exposure and potential future exposure profiles under the risk-neutral and the real-world measure. Key advantage of is that it delivers an accuracy comparable to …
The paper proposes using function approximations to reduce the computational burden in measuring counterparty credit exposure.
problem The need for regular exposure calculations in finance, balancing between computational cost and risk simplification.
method Replacing derivative pricers with function approximations, proving error bounds, and using Chebyshev interpolation for convergence.
result Derives probabilistic and finite sample error bounds, showing significant run-time reductions and asymptotic efficiency gains.
We develop a methodology for index tracking and risk exposure control using financial derivatives. Under a continuous-time diffusion framework for price evolution, we present a pathwise approach to construct dynamic portfolios of derivatives in order to gain exposure to an index and/or market factors that may be not di…
A new method uses counterfactual learning to improve recommendation system evaluation.
problem Inconsistent results in recommender systems due to exposure mechanisms.
method Proposes a minimax empirical risk formulation with an adversarial game to account for exposure.
result Shows improved learning bounds and effectiveness over various recommendation settings.
Employs granular data to create a multilayer network for euro area banks, revealing distinct risk patterns.
problem Lack of comprehensive, granular data integration for systemic risk assessment in euro area banks.
method Constructs an empirically grounded multilayer network integrating various supervisory and statistical datasets, each layer representing a distinct transmission channel.
result Cross-layer heterogeneity in connectivity and centrality reveals economically relevant structure and misidentifies systemically important institutions.
Paper converts quantiles to cumulative distribution functions to simplify risk measures.
problem Technical assumptions in risk measure calculations.
method Invention of converting integrated quantiles to integrated cumulative distribution functions.
result Avoids the need for probability density function existence.
In spite of the growing theoretical literature on cascades of failures in interbank lending networks, empirical results seem to suggest that networks of direct exposures are not the major channel of financial contagion. In this paper we show that networks of interbank exposures can however significantly amplify contagi…
This paper maps the insurability of AI risks across various insurance products.
problem Emerging AI risks and their implications for insurance coverage.
method Coding 55 AI threat classes against 26 insurance products using public carrier materials and threat catalogs.
result Identification of a four-tier insurability frontier: affirmatively insured, silent-AI exposures, actively excluded, and unstructured perils.
TradingAgents uses LLM-powered multi-agent framework for financial trading.
problem Lack of collaborative dynamics in multi-agent financial trading systems.
method Inspired by real-world trading firms, TradingAgents features specialized LLM-powered agents and a risk management team.
result Framework outperforms baseline models in trading performance metrics.
Proposes a new method to assess Wrong-Way Risk in cross-currency swaps.
problem Addressing Wrong-Way Risk (WWR) in cross-currency swaps with stochastic correlation modeling.
method Proposes a stochastic correlation approach to model the dependency between exposure and counterparty credit risk, capturing tail dependence.
result The impact of stochastic correlation on calculated CVA is substantial, providing a promising method to model WWR.
The kind of realized mission inflows the sensitivity to risk. Among other factors, the risk results from decision about liquid assets investment level and liquid assets financing. The higher the risk exposure, the higher the level of liquid assets. If the specific risk exposure is smaller, the more aggressive could be …
Adaptive rerouting reshapes impacts of maritime chokepoint disruptions
problem How disruptions to shipping traffic at chokepoints affect global economy
method Empirically calibrated full-scale agent-based model of global commercial shipping fleet
result Rerouting changes arrival losses under chokepoint closures
In this work we consider adversarial contextual bandits with risk constraints. At each round, nature prepares a context, a cost for each arm, and additionally a risk for each arm. The learner leverages the context to pull an arm and then receives the corresponding cost and risk associated with the pulled arm. In additi…
Currency carry trade is the investment strategy that involves selling low interest rate currencies in order to purchase higher interest rate currencies, thus profiting from the interest rate differentials. This is a well known financial puzzle to explain, since assuming foreign exchange risk is uninhibited and the mark…
Efficiently models Wrong-Way Risk in FVA without full Monte Carlo.
problem Assessing Wrong-Way Risk in Funding Valuation Adjustments (FVA) without extensive simulations.
method Splitting exposure into independent and WWR-driven parts; approximating WWR-driven part using Gaussian stochastic factor.
result An efficient and robust method to include WWR in FVA modelling.
Defines SETR to measure carbon transition risk for investors.
problem Difficulty in measuring the magnitude of carbon transition risk for investors.
method Defines Single Event Transition Risk (SETR) and illustrates its use.
result SETR can approximate the magnitude of low-carbon transition risk.
Optimal reinsurance and dividend strategy for insurance companies in a finite time.
problem Maximizing dividends while managing risk in a finite time horizon.
method Dynamic control problem with Hamilton-Jacobi-Bellman equation, penalty approximation method.
result Smoothness of the value function and comparison principle for its gradient.