Tootfinder

BAGELS: Benchmarking the Automated Generation and Extraction of Limitations from Scholarly Text
Ibrahim Al Azher, Miftahul Jannat Mokarrama, Zhishuai Guo, Sagnik Ray Choudhury, Hamed Alhoori
https://arxiv.org/abs/2505.18207

BAGELS: Benchmarking the Automated Generation and Extraction of Limitations from Scholarly Text
In scientific research, limitations refer to the shortcomings, constraints, or weaknesses within a study. Transparent reporting of such limitations can enhance the quality and reproducibility of research and improve public trust in science. However, authors often a) underreport them in the paper text and b) use hedging strategies to satisfy editorial requirements at the cost of readers' clarity and confidence. This underreporting behavior, along with an explosion in the number of publications, …

Academic Research Output Derivatives: Structuring Futures and Options on Research Output Index
Amarendra Sharma
https://arxiv.org/abs/2505.20492 https://…

Academic Research Output Derivatives: Structuring Futures and Options on Research Output Index
This paper explores an innovative financial concept--Academic Research Output Futures (AROFs)--which aim to bring the tools of market-based finance into the realm of academic research. At the heart of this idea lies a cash-settled futures contract tethered to a composite Research Output Index (ROI), a metric designed to quantify the research productivity of universities and research institutions. By allowing investors to take positions--speculative or hedging--on the projected trajectory of aca…

Robust Hedging of American Options via Aggregated Snell Envelopes
Marco Rodrigues
https://arxiv.org/abs/2506.14553 https://arxiv.org/…

Robust Hedging of American Options via Aggregated Snell Envelopes
We construct an aggregator for a family of Snell envelopes in a nondominated framework. We apply this construction to establish a robust hedging duality, along with the existence of a minimal hedging strategy, in a general semi-martingale setting for American-style options. Our results encompass continuous processes, or processes with jumps and non-vanishing diffusion. A key application is to financial market models, where uncertainty is quantified through the semi-martingale characteristics.

Optimal hedging of an informed broker facing many traders
Philippe Bergault, Pierre Cardaliaguet, Wenbin Yan
https://arxiv.org/abs/2506.08992 https://

Optimal hedging of an informed broker facing many traders
This paper investigates the optimal hedging strategies of an informed broker interacting with multiple traders in a financial market. We develop a theoretical framework in which the broker, possessing exclusive information about the drift of the asset's price, engages with traders whose trading activities impact the market price. Using a mean-field game approach, we derive the equilibrium strategies for both the broker and the traders, illustrating the intricate dynamics of their interactions. …

Having an absolutely awful time with the notion that the most recent pivot/s to video are hedging the bet that people won’t be able to fucking read anymore

How Pete Carroll and his philosophy impacted a trio of NFL head coaches https://www.raiders.com/news/pete-carroll-coaching-tree-dan-quinn-dave-canales-brian-schottenheimer

Benchmark-Neutral Risk-Minimization for insurance products and nonreplicable claims
Michael Schmutz, Eckhard Platen, Thorsten Schmidt
https://arxiv.org/abs/2506.19494

Benchmark-Neutral Risk-Minimization for insurance products and nonreplicable claims
In this paper we study the pricing and hedging of nonreplicable contingent claims, such as long-term insurance contracts like variable annuities. Our approach is based on the benchmark-neutral pricing framework of Platen (2024), which differs from the classical benchmark approach by using the stock growth optimal portfolio as the numéraire. In typical settings, this choice leads to an equivalent martingale measure, the benchmark-neutral measure. The resulting prices can be significantly lower …

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…

Hedging Deposit Run Risk Prior to the 2023 Regional Banking Crisis
Matt Brigida, Kathleen Maceyka
https://arxiv.org/abs/2506.03344 https://

Hedging Deposit Run Risk Prior to the 2023 Regional Banking Crisis
In this analysis we determine factors driving the cross-sectional variation in uninsured deposits during the interest rate raising cycle of 2022 to 2023. The goal of our analysis is to determine whether banks proactively managed deposit run risk prior to the hiking cycle which produced the 2023 Regional Banking Crisis. We find evidence that interest rate forward, futures, and swap use affected the change in a bank uninsured deposits over the period. Interest rate option use, however, has no eff…

How Pete Carroll and his philosophy impacted a trio of NFL head coaches https://www.raiders.com/news/pete-carroll-coaching-tree-dan-quinn-dave-canales-brian-schottenheimer

This https://arxiv.org/abs/2503.01148 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Dynamic spillovers and investment strategies across artificial intelligence ETFs, artificial intelligence tokens, and green markets
This paper investigates the risk spillovers among AI ETFs, AI tokens, and green markets using the R2 decomposition method. We reveal several key insights. First, the overall transmission connectedness index (TCI) closely aligns with the contemporaneous TCI, while the lagged TCI is significantly lower. Second, AI ETFs and clean energy act as risk transmitters, whereas AI tokens and green bond function as risk receivers. Third, AI tokens are difficult to hedge and provide limited hedging ability …

This https://arxiv.org/abs/2402.01820 has been replaced.
link: https://scholar.google.com/scholar?q=a

Signature volatility models: pricing and hedging with Fourier
We consider a stochastic volatility model where the dynamics of the volatility are given by a possibly infinite linear combination of the elements of the time extended signature of a Brownian motion. First, we show that the model is remarkably universal, as it includes, but is not limited to, the celebrated Stein-Stein, Bergomi, and Heston models, together with some path-dependent variants. Second, we derive the joint characteristic functional of the log-price and integrated variance provided t…

This https://arxiv.org/abs/2505.22784 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

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…

Market power abuse in wholesale electricity markets
Alice Lixuan Xu, Jorge S\'anchez Canales, Chiara Fusar Bassini, Lynn H. Kaack, Lion Hirth
https://arxiv.org/abs/2506.03808 …

Market power abuse in wholesale electricity markets
In wholesale electricity markets, prices fluctuate widely from hour to hour and electricity generators price-hedge their output using longer-term contracts, such as monthly base futures. Consequently, the incentives they face to drive up the power prices by reducing supply has a high hourly specificity, and because of hedging, they regularly also face an incentive to depress prices by inflating supply. In this study, we explain the dynamics between hedging and market power abuse in wholesale el…

Model-Free Deep Hedging with Transaction Costs and Light Data Requirements
Pierre Brugi\`ere, Gabriel Turinici
https://arxiv.org/abs/2505.22836 https://

Model-Free Deep Hedging with Transaction Costs and Light Data Requirements
Option pricing theory, such as the Black and Scholes (1973) model, provides an explicit solution to construct a strategy that perfectly hedges an option in a continuous-time setting. In practice, however, trading occurs in discrete time and often involves transaction costs, making the direct application of continuous-time solutions potentially suboptimal. Previous studies, such as those by Buehler et al. (2018), Buehler et al. (2019) and Cao et al. (2019), have shown that deep learning or reinf…

This https://arxiv.org/abs/2209.10166 has been replaced.
link: https://scholar.google.com/scholar?q=a

Chaotic Hedging with Iterated Integrals and Neural Networks
In this paper, we derive an $L^p$-chaos expansion based on iterated Stratonovich integrals with respect to a given exponentially integrable continuous semimartingale. By omitting the orthogonality of the expansion, we show that every $p$-integrable functional, $p \in [1,\infty)$, can be approximated by a finite sum of iterated Stratonovich integrals. Using (possibly random) neural networks as integrands, we therefere obtain universal approximation results for $p$-integrable financial derivative…