Tootfinder

This headline is a *bit* deceptive. Only visa holders from two countries in #Asia are impacted - #China and #NorthKorea
Of course, North Koreans can't get visas, so it really only applies to

Find alternatives to calling the #SantaBarbara Police Department.
The resources included here are limited to those that offer immediate assistance through emergency or crisis services.
These resources may be obligated to call police in the case of an immediate risk of harm to the caller or another, child abuse, or abuse of a vulnerable adult

Santa Barbara, CA - Don't Call The Police
Don't Call The Police - Community-based alternatives to calling the Santa Barbara Police Dept. or 911 in Santa Barbara, CA

Internal docs show Meta plans to use AI to automate up to 90% of its privacy and integrity risk assessments, including in sensitive areas like violent content (NPR)
https://www.npr.org/2025/05/31/nx-s1-5407870/meta-ai-facebook-instagram-risks…

Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG
Timothy B Mahoney, JingYang Liu, Huakun Xin, David B Grayden, Sam E John
https://arxiv.org/abs/2506.03452

Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG
Individuals with severe physical disabilities often experience diminished quality of life stemming from limited ability to engage with their surroundings. Brain-Computer Interface (BCI) technology aims to bridge this gap by enabling direct technology interaction. However, current BCI systems require invasive procedures, such as craniotomy or implantation of electrodes through blood vessels, posing significant risks to patients. Sub-scalp electroencephalography (EEG) offers a lower risk alternat…

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach
Arishi Orra, Aryan Bhambu, Himanshu Choudhary, Manoj Thakur, Selvaraju Natarajan
https://arxiv.org/abs/2505.03760

Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach
Portfolio optimization requires dynamic allocation of funds by balancing the risk and return tradeoff under dynamic market conditions. With the recent advancements in AI, Deep Reinforcement Learning (DRL) has gained prominence in providing adaptive and scalable strategies for portfolio optimization. However, the success of these strategies depends not only on their ability to adapt to market dynamics but also on the careful pre-selection of assets that influence overall portfolio performance. I…

masks at protests / demographics 2/n
I wonder about the influence of employment, as well. If you're at risk every work day, I could well imagine it seeming pointless to start being careful the rest of the time, and maybe just too cognitively dissonant to consider.
I remember in 2020, someone I knew was working at Waterstones, and they were forbidden to mask up at work - even though 2020 was before the whole "covid is over" thing.
I also remember reading about someone - maybe a nurse? that _kind_ of job, anyway - who'd started wearing a fitted mask while the default in their workplace was baggy blues, and iirc was formally rebuked. It wasn't allowed.
If for whatever reason you're unable to hold down a typical job, you might not have much cash for _getting_ things like masks, but you're also not under that same kind of economic pressure to put yourself at risk.
#masks #work #CovidIsntOver

Q&A with Tamara Bralo, the head of journalist safety at Radio Free Asia, on Trump's cuts, the future of at-risk visa holders, jailed staffers abroad, and more (Liam Scott/Columbia Journalism Review)
https://www.cjr.org/the_media_today/tamara

heise | heise Update vom 30. Mai 2025: Lesetipps fürs Wochenende
Der wöchentliche Newsletter von heise mit Schutz vor "Human Risk", Steuer-Apps, Deutschland-Stack, Synology-RAID nachbilden, Gefahr von Online-Glücksspiel

yeah my worst character trait is being too risk averse, over the last year ive been constantly doing things i should have done like 6 years ago

"Childhood cancer survivors have >2x risk of melanoma compared to the general population and those with an invasive melanoma have>2x risk of death."
https://ascopubs.org/doi/abs/10.1200/JCO-24-01519

Political turmoil in Washington has dried up job opportunities in what Professor Ladher calls
“the best research ecosystem in the world.”
Some decided they would now rather take their skills elsewhere, including Austria, Japan and Australia,
while others opted to stay in India.
As the Trump administration moves with abandon to deny visas,
expel foreign students and slash spending on research,
scientists in the United States are becoming increasingly alarm…

World Scientists Look Elsewhere as U.S. Labs Stagger Under Trump Cuts
With the welcome mat withdrawn for promising researchers from around the world, America is at risk of losing its longstanding pre-eminence in the sciences.

Drowning in infosec news overload? Check out today's Metacurity for a concise rundown of the most critical developments you should know, including
--UK military will ramp up offensive cyber attacks against Russia and China
--Victoria's Secret hit by cyberattack,
--LexisNexis Risk Solutions breach affects 364K,
--Procurement database exposed Russian nuclear bases to attack,
--US gov't to mix DNA data of migrant children and sex offenders,
--ASUS …

UK military will ramp up offensive cyber attacks against Russia and China
Victoria's Secret hit by cyberattack, LexisNexis risk arm breach affects 364K, Procurement database exposed Russian nuclear bases to attack, US gov't to mix DNA data of migrant children and sex offenders, ASUS routers ensnared by novel botnet, APT41 exploited Google Calendar, much more

Investment Risk for Energy Infrastructure Construction Is Highest for #NuclearPower Plants, Lowest for #Solar

Investment Risk for Energy Infrastructure Construction Is Highest for Nuclear Power Plants, Lowest for Solar - CleanTechnica
A new study from the Boston University Institute for Global Sustainability finds that construction costs run over budget for more than 60% of energy infrastructure projects worldwide. By Laura Hurley Between now and 2050, the International Energy Agency projects that more than $100 trillion will be spent on building net-zero energy infrastructure globally. ... [continued]

The good news is, you won’t care….
Also, the study was only 55 people.
#cannabis
https://www.yahoo.com/news/smoking-marijuana-eating-cannab…

Smoking marijuana and eating cannabis gummies both linked to dangerous health risk, study finds
Experts warn of cardiovascular risks from chronic cannabis use, as a UC San Francisco study shows similar vascular effects to tobacco, urging caution.

This https://arxiv.org/abs/2504.10667 has been replaced.
link: https://scholar.google.com/scholar?q=a

Beyond Coordinates: Meta-Equivariance in Statistical Inference
Optimal statistical decisions should transcend the language used to describe them. Yet, how do we guarantee that the choice of coordinates - the parameterisation of an optimisation problem - does not subtly dictate the solution? This paper reveals a fundamental geometric invariance principle. We first analyse the optimal combination of two asymptotically normal estimators under a strictly convex trace-AMSE risk. While methods for finding optimal weights are known, we prove that the resulting op…

FPF and OneTrust launch updated Conformity Assessment under the EU AI Act: guide and infographic
https://fpf.org/blog/fpf-and-onetrust-launch-updated-conformity-assessment-under-the-eu-ai-act-guide-and-infographi…

masks at protests / demographics
Interestingly, at the May Day gathering I was the only one in a mask.
Thinking about the contrast with the trans protest the other week, where "good" (fitted not floppy) masks were dotted about throughout the crowd, and felt normalised.
Today's march was a less crowded event than the trans protest, so pretty low-risk for covid transmission anyway. But then when we got to the mini-fair after the march, indoors at the Friends' Meeting House, I didn't see anyone masking indoors either.
I wonder about the demographics of that difference. Seems like there's a traditional union/Labour left who share the mainstream denial of present-day covid, and a statistically more disabled & marginalised cohort where trans awareness and disability/illness awareness overlap.
#masks #CovidIsntOver

USB: A Comprehensive and Unified Safety Evaluation Benchmark for Multimodal Large Language Models
Baolin Zheng, Guanlin Chen, Hongqiong Zhong, Qingyang Teng, Yingshui Tan, Zhendong Liu, Weixun Wang, Jiaheng Liu, Jian Yang, Huiyun Jing, Jincheng Wei, Wenbo Su, Xiaoyong Zhu, Bo Zheng, Kaifu Zhang
https://arxiv.org/abs/2505.23793…

USB: A Comprehensive and Unified Safety Evaluation Benchmark for Multimodal Large Language Models
Despite their remarkable achievements and widespread adoption, Multimodal Large Language Models (MLLMs) have revealed significant security vulnerabilities, highlighting the urgent need for robust safety evaluation benchmarks. Existing MLLM safety benchmarks, however, fall short in terms of data quality and coverge, and modal risk combinations, resulting in inflated and contradictory evaluation results, which hinders the discovery and governance of security concerns. Besides, we argue that vulne…

The role of scalp EEG recordings during cortical visual prosthesis testing https://onlinelibrary.wiley.com/doi/10.1111/aor.15023 "Given the known risk of cortical stimulation inducing seizures", "Scalp EEG can be valuable to alert researchers to impending…

Computer scientist Greg Nelson and I presented "Following AI's Footsteps from School to Society" at the 2025 UMaine Faculty Institute https://mycampus.maine.edu/web/uc-faculty-portal/faculty-institute-2025 including the IMPACT RISK framew…

Det här är samma grejer som Fredrik Nyström har kört med i flera år. https://youtu.be/0Fvn5QiMsOo
Det finns en ökad risk för flimmer hos de som tränar mycket, framför allt konditionsidrottare. Det innebär inte att det är en dålig idé för motionärer att ställa upp i olika lopp eller träna konditio…

A General Theory of Risk Sharing
Vasily Melnikov
https://arxiv.org/abs/2505.19276 https://arxiv.org/pdf/2505.19276

A General Theory of Risk Sharing
We introduce a new paradigm for risk sharing that generalizes earlier models based on discrete agents and extends them to allow for sharing risk within a continuum of agents. Agents are represented by points of a measure space and have potentially heterogeneous risk preferences modeled by risk measures. The existence of risk minimizing allocations is proved when constrained to satisfy economically convincing conditions. In the unconstrained case, we derive the dual representation of the value f…

Split the Yield, Share the Risk: Pricing, Hedging and Fixed rates in DeFi
Viraj Nadkarni, Pramod Viswanath
https://arxiv.org/abs/2505.22784 https://…

Split the Yield, Share the Risk: Pricing, Hedging and Fixed rates in DeFi
We present the first formal treatment of \emph{yield tokenization}, a mechanism that decomposes yield-bearing assets into principal and yield components to facilitate risk transfer and price discovery in decentralized finance (DeFi). We propose a model that characterizes yield token dynamics using stochastic differential equations. We derive a no-arbitrage pricing framework for yield tokens, enabling their use in hedging future yield volatility and managing interest rate risk in decentralized l…

COVID before or during pregnancy may confer 2 to 3 times the risk of miscarriage:
https://www.cidrap.umn.edu/covid-19/covid-or-during-pregnancy-may-confer-2-3-times-risk-miscarriage

Self-driving technologies need the help of the public: A narrative review of the evidence
Jonathan Smith, Siddartha Khastgir
https://arxiv.org/abs/2505.23472

Self-driving technologies need the help of the public: A narrative review of the evidence
If public trust is lot in a new technology early in its life cycle it can take much more time for the benefits of that technology to be realised. Eventually tens-of-millions of people will collectively have the power to determine self-driving technology success of failure driven by their perception of risk, data handling, safety, governance, accountability, benefits to their life and more. This paper reviews the evidence on safety critical technology covering trust, engagement, and acceptance. …

How I shorted $TRUMP coin (and got to have dinner with the President) | The Verge https://www.theverge.com/cryptocurrency/674327/trump-coin-short-sell-hedge-contest-dinner-winner

How I shorted $TRUMP coin (and got to have dinner with the President)
A crypto trader who won an invite to Trump’s exclusive dinner explains how he and many others shorted the meme coin to hedge his risk and still win the contest.

A new COVID subvariant spreads rapidly as Trump pivots away from vaccines
A new, highly transmissible COVID subvariant has been detected in California
— heightening the risk of a potential summer wave
as recent moves by the Trump administration threaten to make vaccines harder to get,
and more expensive,
for many Americans,
some health experts warn.
Health and Human Services Secretary Robert F. Kennedy Jr.
announced this week that he was resci…

COVID variant NB.1.8.1 spreads as Trump pivots away from vaccines
A new, highly transmissible COVID subvariant has been detected in California — heightening the risk of a summer wave as recent moves by the Trump administration threaten to make vaccines harder to get, and more expensive, for many Americans, some health experts warn.

This https://arxiv.org/abs/2505.18422 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

A Task-Driven Human-AI Collaboration: When to Automate, When to Collaborate, When to Challenge
According to several empirical investigations, despite en-hancing human capabilities, human-AI cooperation fre-quently falls short of expectations and fails to reach true synergy. We propose a task-driven framework that reverses prevalent approaches by assigning AI roles according to how the task's requirements align with the capabilities of AI technology. Three major AI roles are identified through task analysis across risk and complexity dimensions: au-tonomous, assistive/collaborative, and a…

Replication of Reference-Dependent Preferences and the Risk-Return Trade-Off in the Chinese Market
Penggan Xu
https://arxiv.org/abs/2505.20608 https://

Replication of Reference-Dependent Preferences and the Risk-Return Trade-Off in the Chinese Market
This study replicates the findings of Wang et al. (2017) on reference-dependent preferences and their impact on the risk-return trade-off in the Chinese stock market, a unique context characterized by high retail investor participation, speculative trading behavior, and regulatory complexities. Capital Gains Overhang (CGO), a proxy for unrealized gains or losses, is employed to explore how behavioral biases shape cross-sectional stock returns in an emerging market setting. Utilizing data from 1…

Machine learning approach to stock price crash risk
Abdullah Karasan, Ozge Sezgin Alp, Gerhard-Wilhelm Weber
https://arxiv.org/abs/2505.16287 https://

Machine learning approach to stock price crash risk
In this study, we propose a novel machine-learning-based measure for stock price crash risk, utilizing the minimum covariance determinant methodology. Employing this newly introduced dependent variable, we predict stock price crash risk through cross-sectional regression analysis. The findings confirm that the proposed method effectively captures stock price crash risk, with the model demonstrating strong performance in terms of both statistical significance and economic relevance. Furthermore,…

Agent-based Liquidity Risk Modelling for Financial Markets
Perukrishnen Vytelingum, Rory Baggott, Namid Stillman, Jianfei Zhang, Dingqiu Zhu, Tao Chen, Justin Lyon
https://arxiv.org/abs/2505.15296

Agent-based Liquidity Risk Modelling for Financial Markets
In this paper, we describe a novel agent-based approach for modelling the transaction cost of buying or selling an asset in financial markets, e.g., to liquidate a large position as a result of a margin call to meet financial obligations. The simple act of buying or selling in the market causes a price impact and there is a cost described as liquidity risk. For example, when selling a large order, there is market slippage -- each successive trade will execute at the same or worse price. When th…

This https://arxiv.org/abs/2307.10800 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Contagious McKean--Vlasov problems with common noise: from smooth to singular feedback through hitting times
We consider a family of McKean--Vlasov equations arising as the large particle limit of a system of interacting particles on the positive half-line with common noise and feedback. Such systems are motivated by structural models for systemic risk with contagion. This contagious interaction is such that when a particle hits zero, the impact is to move all the others toward the origin through a kernel which smooths the impact over time. We study a rescaling of the impact kernel under which it conv…

Identifying Heart Attack Risk in Vulnerable Population: A Machine Learning Approach
Subhagata Chattopadhyay, Amit K Chattopadhyay
https://arxiv.org/abs/2505.21139

Identifying Heart Attack Risk in Vulnerable Population: A Machine Learning Approach
The COVID-19 pandemic has significantly increased the incidence of post-infection cardiovascular events, particularly myocardial infarction, in individuals over 40. While the underlying mechanisms remain elusive, this study employs a hybrid machine learning approach to analyze epidemiological data in assessing 13 key heart attack risk factors and their susceptibility. Based on a unique dataset that combines demographic, biochemical, ECG, and thallium stress-tests, this study categorizes distinc…

What has ... DRM (?!) ever done for us?
https://infosec.exchange/@dangoodin/114546912959367470

Risk spillovers between rare earths, green bonds, and clean energy https://www.sciencedirect.com/science/article/pii/S014098832500386X @…

UK 2025 #Publication
Severe Space Weather Impacts on UK Critical National Infrastructure
A Space weather instrumentation, measurement, modelling and risk (#SWIMMR) Project Report
Priority Recommendation CS6 : "That government and other policymakers ensure that s…

Equilibrium Policy on Dividend and Capital Injection under Time-inconsistent Preferences
Sang Hu, Zihan Zhou
https://arxiv.org/abs/2505.23511 https://

Equilibrium Policy on Dividend and Capital Injection under Time-inconsistent Preferences
This paper studies the dividend and capital injection problem under a diffusion risk model with general discount functions. A proportional cost is imposed when injecting capitals. For exponential discounting as time-consistent benchmark, we obtain the closed-form solutions and show that the optimal strategies are of threshold type. Under general discount function which leads to time-inconsistency, we adopt the definition of weak equilibrium and obtain the extended HJB equation system. An explic…

This https://arxiv.org/abs/2505.22598 has been replaced.
initial toot: https://mastoxiv.page/@arX…

On the performance of machine-learning assisted Monte Carlo in sampling from simple statistical physics models
Recent years have seen a rise in the application of machine learning techniques to aid the simulation of hard-to-sample systems that cannot be studied using traditional methods. Despite the introduction of many different architectures and procedures, a wide theoretical understanding is still lacking, with the risk of suboptimal implementations. As a first step to address this gap, we provide here a complete analytic study of the widely-used Sequential Tempering procedure applied to a shallow MA…

This https://arxiv.org/abs/2502.14479 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Modelling the term-structure of default risk under IFRS 9 within a multistate regression framework
The lifetime behaviour of loans is notoriously difficult to model, which can compromise a bank's financial reserves against future losses, if modelled poorly. Therefore, we present a data-driven comparative study amongst three techniques in modelling a series of default risk estimates over the lifetime of each loan, i.e., its term-structure. The behaviour of loans can be described using a nonstationary and time-dependent semi-Markov model, though we model its elements using a multistate regress…

2/3
🔹 Pros:
✅ Truly passive income
✅ Wealth grows exponentially over time
✅ Maximum financial security & freedom
🔹 Cons:
❌ Requires capital to start
❌ Knowledge & risk management are crucial
❌ Returns aren’t instant – patience is key

This https://arxiv.org/abs/2505.09619 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Predictive Models for Chronic Heart Failure
The management of chronic Heart Failure (HF) presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of exacerbations, and personalized treatment strategies. In this paper, we present a predictive model founded on Machine Learning (ML) techniques to identify patients at HF risk. This model is an ensemble learning approach, a modified stacking technique, that uses two specialized models leveraging clinical and echocardiographic features and then a m…

Multi-period Mean-Buffered Probability of Exceedance in Defined Contribution Portfolio Optimization
Duy-Minh Dang, Chang Chen
https://arxiv.org/abs/2505.22121

Multi-period Mean-Buffered Probability of Exceedance in Defined Contribution Portfolio Optimization
We investigate multi-period mean-risk portfolio optimization for long-horizon Defined Contribution plans, focusing on buffered Probability of Exceedance (bPoE), a more intuitive, dollar-based alternative to Conditional Value-at-Risk (CVaR). We formulate both pre-commitment and time-consistent Mean-bPoE and Mean-CVaR portfolio optimization problems under realistic investment constraints (e.g., no leverage, no short selling) and jump-diffusion dynamics. These formulations are naturally framed as …

This https://arxiv.org/abs/2501.12926 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Comparative Statics for the Subjective
I study robust comparative statics for risk-averse subjective expected utility (SEU) maximizers. Starting with a finite menu of actions totally ordered by sensitivity to risk, I identify the transformations of her menu that lead a decision-maker to take a lower action, regardless of her particular utility function or belief. My main results reveal that a robust decrease in the action selected is guaranteed by an intuitive steepening/tilting of the actions' payoffs and necessitates a slightly we…

This https://arxiv.org/abs/2501.17490 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Pricing Carbon Allowance Options on Futures: Insights from High-Frequency Data
Leveraging a unique dataset of carbon futures option prices traded on the ICE market from December 2015 until December 2020, we present the results from an unprecedented calibration exercise. Within a multifactor stochastic volatility framework with jumps, we employ a three-dimensional pricing kernel compensating for equity and variance components' risk to derive an analytically tractable and numerically practical approach to pricing. To the best of our knowledge, we are the first to provide an…

A case-control study in twins, from Denmark: "Tattoo ink exposure is associated with lymphoma and skin cancers"
BMC Public Health
https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-025-21413-3

Tattoo ink exposure is associated with lymphoma and skin cancers – a Danish study of twins - BMC Public Health
Background We aim to study the potential association between tattoo ink exposure and development of certain types of cancers in the recently established Danish Twin Tattoo Cohort. Tattoo ink is known to transfer from skin to blood and accumulate in regional lymph nodes. We are concerned that tattoo ink induces inflammation at the deposit site, leading to chronic inflammation and increasing risk of abnormal cell proliferation, especially skin cancer and lymphoma. Methods We conducted two designs…

On the performance of machine-learning assisted Monte Carlo in sampling from simple statistical physics models
Luca Maria Del Bono, Federico Ricci-Tersenghi, Francesco Zamponi
https://arxiv.org/abs/2505.22598

On the performance of machine-learning assisted Monte Carlo in sampling from simple statistical physics models
Recent years have seen a rise in the application of machine learning techniques to aid the simulation of hard-to-sample systems that cannot be studied using traditional methods. Despite the introduction of many different architectures and procedures, a wide theoretical understanding is still lacking, with the risk of suboptimal implementations. As a first step to address this gap, we provide here a complete analytic study of the widely-used Sequential Tempering procedure applied to a shallow MA…

Logarithmic resilience risk metrics that address the huge variations in blackout cost
Arslan Ahmad, Ian Dobson
https://arxiv.org/abs/2505.12016 https://

Logarithmic resilience risk metrics that address the huge variations in blackout cost
Resilience risk metrics must address the customer cost of the largest blackouts of greatest impact. However, there are huge variations in blackout cost in observed distribution utility data that make it impractical to properly estimate the mean large blackout cost and the corresponding risk. These problems are caused by the heavy tail observed in the distribution of customer costs. To solve these problems, we propose resilience metrics that describe large blackout risk using the mean of the log…

Martingale Consumption
Peter Holm Nielsen
https://arxiv.org/abs/2505.20504 https://arxiv.org/pdf/2505.20504

Martingale Consumption
We propose martingale consumption as a natural, desirable consumption pattern for any given (proportional) investment strategy. The idea is to always adjust current consumption so as to achieve level expected future consumption under the arbitrarily chosen investment strategy. This approach avoids the formulation of an optimization objective based on preferences towards risk, intertemporal consumption, habit formation etc. We identify general explicit solutions in deterministic-coefficient mode…

2/3
🔹 Pros:
✅ Truly passive income
✅ Wealth grows exponentially over time
✅ Maximum financial security & freedom
🔹 Cons:
❌ Requires capital to start
❌ Knowledge & risk management are crucial
❌ Returns aren’t instant – patience is key

[2025-05-30 Fri (UTC), no new articles found for q-fin.RM Risk Management]
#toXiv_bot_toot

Shortermism and excessive risk taking in optimal execution with a target performance
Emilio Barucci, Yuheng Lan
https://arxiv.org/abs/2505.15611 https://…

Shortermism and excessive risk taking in optimal execution with a target performance
We deal with the optimal execution problem when the broker's goal is to reach a performance barrier avoiding a downside barrier. The performance is provided by the wealth accumulated by trading in the market, the shares detained by the broker evaluated at the market price plus a slippage cost yielding a quadratic inventory cost. Over a short horizon, this type of remuneration leads, at the same time, to a more aggressive and less risky strategy compared to the classical one, and over a long hor…

This https://arxiv.org/abs/2505.09619 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Predictive Models for Chronic Heart Failure
The management of chronic Heart Failure (HF) presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of exacerbations, and personalized treatment strategies. In this paper, we present a predictive model founded on Machine Learning (ML) techniques to identify patients at HF risk. This model is an ensemble learning approach, a modified stacking technique, that uses two specialized models leveraging clinical and echocardiographic features and then a m…

2/3
🔹 Examples: Gig work (Uber, TaskRabbit), freelancing (writing, graphic design), tutoring, part-time jobs.
🔹 Pros:
✅ Low-risk & easy to start
✅ Immediate income potential
✅ No need to build systems or invest upfront
🔹 Cons:
❌ Limited scalability – you only earn when you work
❌ No leverage – time is still your biggest constraint
❌ Taxed at the highest rate (active personal income)

This https://arxiv.org/abs/2410.10239 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Sample Average Approximation for Portfolio Optimization under CVaR constraint in an (re)insurance context
We consider optimal allocation problems with Conditional Value-At-Risk (CVaR) constraint. We prove, under very mild assumptions, the convergence of the Sample Average Approximation method (SAA) applied to this problem, and we also exhibit a convergence rate and discuss the uniqueness of the solution. These results give (re)insurers a practical solution to portfolio optimization under market regulatory constraints, i.e. a certain level of risk.

[2025-05-29 Thu (UTC), no new articles found for q-fin.RM Risk Management]
#toXiv_bot_toot

2/3
🔹 Examples: Gig work (Uber, TaskRabbit), freelancing (writing, graphic design), tutoring, part-time jobs.
🔹 Pros:
✅ Low-risk & easy to start
✅ Immediate income potential
✅ No need to build systems or invest upfront
🔹 Cons:
❌ Limited scalability – you only earn when you work
❌ No leverage – time is still your biggest constraint
❌ Taxed at the highest rate (active personal income)

[2025-05-28 Wed (UTC), no new articles found for q-fin.RM Risk Management]
#toXiv_bot_toot

Predictive Models for Chronic Heart Failure
Pietro Cassieri, Aiman Faiz, Anna Maria De Roberto, Claudio Pascarelli, Gianvito Mitrano, Gianluca Fimiani, Marina Garofano, Christiancarmine Esposito, Genoveffa Tortora, Alessia Bramanti, Giuseppe Scanniello
https://arxiv.org/abs/2505.09619

Predictive Models for Chronic Heart Failure
The management of chronic Heart Failure (HF) presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of exacerbations, and personalized treatment strategies. In this paper, we present a predictive model founded on Machine Learning (ML) techniques to identify patients at HF risk. This model is an ensemble learning approach, a modified stacking technique, that uses two specialized models leveraging clinical and echocardiographic features and then a m…

This https://arxiv.org/abs/2409.06289 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Automate Strategy Finding with LLM in Quant Investment
We present a novel three-stage framework leveraging Large Language Models (LLMs) within a risk-aware multi-agent system for automate strategy finding in quantitative finance. Our approach addresses the brittleness of traditional deep learning models in financial applications by: employing prompt-engineered LLMs to generate executable alpha factor candidates across diverse financial data, implementing multimodal agent-based evaluation that filters factors based on market status, predictive quali…

excellent description of executive functioning predicaments
... in a thread at Ask a Manager about ADHD.
I wouldn't recommend the whole comments section this time, because there was too much "well _I_ manage" and missing the point, but I thought this comment from "Han about town" laid out the essence of it really well. Here's a snippet on the challenge of consistently filling out timesheets:
"Monetary penalties or privileges have zero effect on the behaviour, because the behaviour is not moderated by risk, reward, or consequences. It’s moderated by how well I’m able to perform a very rote, boring, *consistent* task on a repeated basis, which is very poorly."
#ADHD #neurodivergence #ExecutiveFunction #rewards

This https://arxiv.org/abs/2505.13185 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Filtering in a hazard rate change-point model with financial and life-insurance applications
This paper develops a continuous-time filtering framework for estimating a hazard rate subject to an unobservable change-point. This framework arises naturally in both financial and insurance applications, where the default intensity of a firm or the mortality rate of an individual may experience a sudden jump at an unobservable time, representing, for instance, a shift in the firm's risk profile or a deterioration in an individual's health status. By employing a progressive enlargement of filt…

This https://arxiv.org/abs/2309.15511 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Measuring risk contagion in financial networks with CoVaR
The stability of a complex financial system may be assessed by measuring risk contagion between various financial institutions with relatively high exposure. We consider a financial network model using a bipartite graph of financial institutions (e.g., banks, investment companies, insurance firms) on one side and financial assets on the other. Following empirical evidence, returns from such risky assets are modeled by heavy-tailed distributions, whereas their joint dependence is characterized b…

[2025-05-27 Tue (UTC), 1 new article found for q-fin.RM Risk Management]
#toXiv_bot_toot

Filtering in a hazard rate change-point model with financial and life-insurance applications
Matteo Buttarazzi, Claudia Ceci
https://arxiv.org/abs/2505.13185

Filtering in a hazard rate change-point model with financial and life-insurance applications
This paper develops a continuous-time filtering framework for estimating a hazard rate subject to an unobservable change-point. This framework arises naturally in both financial and insurance applications, where the default intensity of a firm or the mortality rate of an individual may experience a sudden jump at an unobservable time, representing, for instance, a shift in the firm's risk profile or a deterioration in an individual's health status. By employing a progressive enlargement of filt…

[2025-05-26 Mon (UTC), no new articles found for q-fin.RM Risk Management]
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NewsNet-SDF: Stochastic Discount Factor Estimation with Pretrained Language Model News Embeddings via Adversarial Networks
Shunyao Wang, Ming Cheng, Christina Dan Wang
https://arxiv.org/abs/2505.06864

NewsNet-SDF: Stochastic Discount Factor Estimation with Pretrained Language Model News Embeddings via Adversarial Networks
Stochastic Discount Factor (SDF) models provide a unified framework for asset pricing and risk assessment, yet traditional formulations struggle to incorporate unstructured textual information. We introduce NewsNet-SDF, a novel deep learning framework that seamlessly integrates pretrained language model embeddings with financial time series through adversarial networks. Our multimodal architecture processes financial news using GTE-multilingual models, extracts temporal patterns from macroecono…

This https://arxiv.org/abs/2504.15268 has been replaced.
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Beating the Correlation Breakdown: Robust Inference, Flexible Scenarios, and Stress Testing for Financial Portfolios
We live in a multivariate world, and effective modeling of financial portfolios, including their construction, allocation, forecasting, and risk analysis, simply is not possible without explicitly modeling the dependence structure of their assets. Dependence structure can drive portfolio results more than the combined effects of other parameters in investment and risk models, but the literature provides relatively little to define the finite-sample distributions of dependence measures in useabl…

[2025-05-23 Fri (UTC), no new articles found for q-fin.RM Risk Management]
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This https://arxiv.org/abs/2408.13266 has been replaced.
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Impact of Climate transition on Credit portfolio's loss with stochastic collateral
The aim of this work is to propose an end-by-end modeling framework to evaluate the risk measures of a bank's portfolio of collateralized loans in an economy subject to the climate transition. The economy, organized in sectors, is driven by a multidimensional Ornstein-Uhlenbeck (OU) productivity process while the climate transition is declined thanks to continuous deterministic carbon price and intensities processes. We thus derive the dynamics of macroeconomic variables for each scenario. By c…

[2025-05-22 Thu (UTC), no new articles found for q-fin.RM Risk Management]
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[2025-05-21 Wed (UTC), 1 new article found for q-fin.RM Risk Management]
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[2025-05-20 Tue (UTC), 1 new article found for q-fin.RM Risk Management]
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Foundation Time-Series AI Model for Realized Volatility Forecasting
Anubha Goel, Puneet Pasricha, Martin Magris, Juho Kanniainen
https://arxiv.org/abs/2505.11163

Foundation Time-Series AI Model for Realized Volatility Forecasting
Time series foundation models (FMs) have emerged as a popular paradigm for zero-shot multi-domain forecasting. These models are trained on numerous diverse datasets and claim to be effective forecasters across multiple different time series domains, including financial data. In this study, we evaluate the effectiveness of FMs, specifically the TimesFM model, for volatility forecasting, a core task in financial risk management. We first evaluate TimesFM in its pretrained (zero-shot) form, follow…

[2025-05-14 Wed (UTC), 1 new article found for q-fin.RM Risk Management]
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