Prediction markets can be manipulated by traders who can move contract settlements, harming price discovery.
arXiv research
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Graph learning categorizes DeFi services into similar functionalities.
Develops theory of relatively Anosov representations using flow examples.
Two methods for pricing swing contracts using neural networks or explicit functions.
Let B be a thick spherical building equipped with its natural CAT(1) metric and let M be a proper, convex subset of B. If M is open or if M is a closed ball of radius pi/2, then the maximal subcomplex supported by the complement of M is spherical and non contractible.
The action dimension of a group G is the minimal dimension of a contractible manifold that G acts on properly discontinuously. We show that if G acts properly and cocompactly on a thick Euclidean building, then the action dimension is bounded below by twice the dimension of the building. We also compute the action dime…
This work studies the contraction coefficients of Schrödinger bridge problems in linear systems.
In this paper we provide a valuation formula for different classes of actuarial and financial contracts which depend on a general loss process, by using the Malliavin calculus. In analogy with the celebrated Black-Scholes formula, we aim at expressing the expected cash flow in terms of a building block. The former is r…
Paper proposes new Langevin samplers for sampling from log-concave distributions with superlinear gradient growth.
The main purpose of this paper is to formalize the modelling process, analysis and mathematical definition of corruption when entering into a contract between principal agent and producers. The formulation of the problem and the definition of concepts for the general case are considered. For definiteness, all calculati…
This paper introduces a method to improve GNN stability and robustness.
We propose a general notion of algebraic gauge theory obtained via extracting the main properties of classical gauge theory. Building on a recent work on transferring curved -structures we show that, under certain technical conditions, algebraic gauge theories can be transferred along chain contractions. Sp…
The paper improves energy contract pricing models by incorporating jumps and varying parameters.
Study random walks on CAT(0) spaces with contracting elements, proving limit laws.
Develops a Gaussian model to compute the Alexander polynomial of knots.
Quantum crypto-economics models price risks in blockchain technology.
Finite type for 3-manifolds with boundary.
Improved AMM protocol supports diverse loan maturities in DeFi.
We show that if K: P \to R is an autonomous Hamiltonian on a symplectic manifold (P,Ω) which attains 0 as a Morse-Bott nondegenerate minimum along a symplectic submanifold M, and if c_1(TP)|_M vanishes in real cohomology, then the Hamiltonian flow of K has contractible periodic orbits with bounded period on all suffici…
New complex surfaces found with interesting geometric properties.
Contracts for Difference (CfDs) are forwards on the spread between an area price and the system price. Together with the system price forwards, these products are used to hedge the area price risk in the Nordic electricity market. The CfDs are typically available for the next two months, three quarters and three years.…
This paper studies the stochastic modeling of market drawdown events and the fair valuation of insurance contracts based on drawdowns. We model the asset drawdown process as the current relative distance from the historical maximum of the asset value. We first consider a vanilla insurance contract whereby the protectio…
In this paper we study a model-based approach to calculating approximately optimal policies in Markovian Decision Processes. In particular, we derive novel bounds on the loss of using a policy derived from a factored linear model, a class of models which generalize numerous previous models out of those that come with s…
Tensor CANDECOMP/PARAFAC (CP) decomposition has wide applications in statistical learning of latent variable models and in data mining. In this paper, we propose fast and randomized tensor CP decomposition algorithms based on sketching. We build on the idea of count sketches, but introduce many novel ideas which are un…
We study a stochastic control approach to managed futures portfolios. Building on the Schwartz 97 stochastic convenience yield model for commodity prices, we formulate a utility maximization problem for dynamically trading a single-maturity futures or multiple futures contracts over a finite horizon. By analyzing the a…
The paper explores coalescent contractions in contractible spaces, providing criteria and examples.
We will survey the work on the topology of in the last 20 years or so. Much of the development is driven by the tantalizing analogy with mapping class groups. Unfortunately, is more complicated and less well-behaved. Culler and Vogtmann constructed Outer Space , the analog of Teichmüller spac…
Paper proposes new methods for improving interatomic potentials.
Computable contracts simplify financial transactions and reduce legal costs.
This paper provides a methodology for fast and accurate pricing of the long-dated contracts that arise as the building blocks of insurance and pension fund agreements. It applies the recursive marginal quantization (RMQ) and joint recursive marginal quantization (JRMQ) algorithms outside the framework of traditional ri…
In an online contract selection problem there is a seller which offers a set of contracts to sequentially arriving buyers whose types are drawn from an unknown distribution. If there exists a profitable contract for the buyer in the offered set, i.e., a contract with payoff higher than the payoff of not accepting any c…
Optimal execution strategy for merger & acquisition contracts with price impact.
This paper develops a method to select a reference contract for multi-contract quoting to minimize execution risk.
A recurring problem when building probabilistic latent variable models is regularization and model selection, for instance, the choice of the dimensionality of the latent space. In the context of belief networks with latent variables, this problem has been adressed with Automatic Relevance Determination (ARD) employing…
Proposes a probabilistic framework for smart contract risk quantification.
We consider a general framework of optimal mechanism design under adverse selection and ambiguity about the type distribution of agents. We prove the existence of optimal mechanisms under minimal assumptions on the contract space and prove that centralized contracting implemented via mechanisms is equivalent to delegat…
In case of the heat flow on the free loop space of a closed Riemannian manifold non-triviality of Morse homology for semi-flows is established by constructing a natural isomorphism to singular homology of the loop space. The construction is also new in finite dimensions. The main idea is to build a Morse filtration usi…
Improved security of smart contracts by classifying them into four categories.
Study on contracting maps and their rigidity under curvature constraints.
We study locally compact contractive local groups, that is, locally compact local groups with a contractive pseudo-automorphism. We prove that if such an object is locally connected, then it is locally isomorphic to a Lie group. We also prove a related structure theorem for locally compact contractive local groups whic…
Study shows some contractible complexes can't have certain immersions.
This paper presents some partial answers to the following question. QUESTION. If a normal space X is the union of an increasing sequence of open sets U(1), U(2), U(3) ... such that each U(n) contracts to a point in X, must X be contractible? The main results of the paper are: THEOREM 1. If a normal space X is the union…
The simplicial volume of non-R^3 contractible 3-manifolds is infinite.
Machine learning algorithms learn from data and use data from databases that are mutable; therefore, the data and the results of machine learning cannot be fully trusted. Also, the machine learning process is often difficult to automate. A unified analytical framework for trustable machine learning has been presented i…
Study efficient derivative computation for nondifferentiable maps in machine learning.
Study on reinsurance decisions using mean-variance criterion with irreversible contracts.
Optimal contracts help principals delegate data collection in decentralized ML.
Optimal contracts are found for agents with quadratic effort costs.