Tootfinder

Variable selection for minimum-variance portfolios
Guilherme V. Moura, Andr\'e P. Santos, Hudson S. Torrent
https://arxiv.org/abs/2508.14986 https://ar…

Variable selection for minimum-variance portfolios
Machine learning (ML) methods have been successfully employed in identifying variables that can predict the equity premium of individual stocks. In this paper, we investigate if ML can also be helpful in selecting variables relevant for optimal portfolio choice. To address this question, we parameterize minimum-variance portfolio weights as a function of a large pool of firm-level characteristics as well as their second-order and cross-product transformations, yielding a total of 4,610 predicto…

Eigen Portfolios: From Single Component Models to Ensemble Approaches
ZhengXiang Zhou, Yuqi Luan
https://arxiv.org/abs/2508.15586 https://arxiv.org/pdf/250…

Eigen Portfolios: From Single Component Models to Ensemble Approaches
The increasing integration of data science techniques into quantitative finance has enabled more systematic and data-driven approaches to portfolio construction. This paper investigates the use of Principal Component Analysis (PCA) in constructing eigen-portfolios - portfolios derived from the principal components of the asset return correlation matrix. We begin by formalizing the mathematical underpinnings of eigen-portfolios and demonstrate how PCA can reveal latent orthogonal factors driving…

Through the Looking Glass: Bitcoin Treasury Companies
B K Meister
https://arxiv.org/abs/2507.14910 https://arxiv.org/pdf/2507.14910

Through the Looking Glass: Bitcoin Treasury Companies
Bitcoin treasury companies have taken stock markets by storm amassing billions of dollars worth of tokens. More than a hundred companies active in various crypto-tokens, not just Bitcoin, are listed. The ability to generate leverage, for example stemming from borrowing collateralized by stock portfolios, helps to understand this phenomenon. In addition, the extension of the binary-choice Kelly criterion to incorporate uncertainty in the form of the Kullback-Leibler divergence or more generall…

Challenges in GenAI and Authentication: a scoping review
Wesley dos Reis Bezerra, Lais Machado Bezerra, Carlos Becker Westphall
https://arxiv.org/abs/2507.11775

Challenges in GenAI and Authentication: a scoping review
Authentication and authenticity have been a security challenge since the beginning of information sharing, especially in the context of digital information. With the advancement of generative artificial intelligence, these challenges have evolved, demanding a more up-to-date analysis of their impacts on society and system security. This work presents a scoping review that analyzed 88 documents from the IEEExplorer, Scopus, and ACM databases, promoting an analysis of the resulting portfolio thro…

Recently a friend asked me why I don't publish my videos on Youtube. I'd get more views.
So I checked my views - and know what: RIGHT, I don't get a lot of views - but most of the #videos on #Peertube show *more* views than I got on Youtube.
Well, the YT algorithm never love…

From Chaos to Automation: Enabling the Use of Unstructured Data for Robotic Process Automation
Kelly Kurowski, Xixi Lu, Hajo A. Reijers
https://arxiv.org/abs/2507.11364

From Chaos to Automation: Enabling the Use of Unstructured Data for Robotic Process Automation
The growing volume of unstructured data within organizations poses significant challenges for data analysis and process automation. Unstructured data, which lacks a predefined format, encompasses various forms such as emails, reports, and scans. It is estimated to constitute approximately 80% of enterprise data. Despite the valuable insights it can offer, extracting meaningful information from unstructured data is more complex compared to structured data. Robotic Process Automation (RPA) has ga…

When a video from #Peertube appears in my feed here in #Mastodon, it only shows the title and the URL, nothing more. This is not really helpful.
Would it be possible, that Mastodon shows something like the first 300 characters from the description (500 characters minus 120 for the peertube …

If anyone I have a connection with has any thoughts on part or full time design/illustration roles, I would LOVE to hear from you.
18 years experience and am open to new challenges!
#lookingforwork #getfedihired
My most recently uploaded work can be found in my portfolio at https://www.andycarolan.com
If you wish to find out more about me as a person, my strengths, skills and what I'm like to work with, please take a look at my personal user manual at https://www.andycarolan.com/myusermanual
CV/Resume on request

Chemical transformation of CO in evolving protoplanetary discs across stellar masses: a route to C-rich inner regions
Andrew D. Sellek, Ewine F. van Dishoeck
https://arxiv.org/abs/2507.11631

Chemical transformation of CO in evolving protoplanetary discs across stellar masses: a route to C-rich inner regions
Protoplanetary discs around Very Low Mass Stars (VLMS) show hydrocarbon-rich MIR spectra indicative of C/O>1 in their inner discs, in contrast to discs around higher-mass hosts which mostly show O-bearing species. One scenario proposed to elevate C/O in VLMS inner discs is the advection of O-depleted gas from the outer disc. However, if CO gas remains abundant, C/O can be at most ~1. We test if chemical transformation of CO into other species allows this transport scenario to produce C/O signif…

Causal Negative Sampling via Diffusion Model for Out-of-Distribution Recommendation
Chu Zhao, Eneng Yang, Yizhou Dang, Jianzhe Zhao, Guibing Guo, Xingwei Wang
https://arxiv.org/abs/2508.07243

Causal Negative Sampling via Diffusion Model for Out-of-Distribution Recommendation
Heuristic negative sampling enhances recommendation performance by selecting negative samples of varying hardness levels from predefined candidate pools to guide the model toward learning more accurate decision boundaries. However, our empirical and theoretical analyses reveal that unobserved environmental confounders (e.g., exposure or popularity biases) in candidate pools may cause heuristic sampling methods to introduce false hard negatives (FHNS). These misleading samples can encourage the …