Element and Everything Tokens: Two-Tier Architecture for Mobilizing Alternative Assets
- URL: http://arxiv.org/abs/2508.11266v1
- Date: Fri, 15 Aug 2025 07:02:57 GMT
- Title: Element and Everything Tokens: Two-Tier Architecture for Mobilizing Alternative Assets
- Abstract summary: Alternative assets such as mines, power plants, or infrastructure projects are often large, heterogeneous bundles of resources, rights, and outputs.<n>This paper proposes a novel two-tier tokenization architecture to enhance the liquidity and transparency of such complex assets.
- Score: 2.8195433571821162
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: Alternative assets such as mines, power plants, or infrastructure projects are often large, heterogeneous bundles of resources, rights, and outputs whose value is difficult to trade or fractionalize under traditional frameworks. This paper proposes a novel two-tier tokenization architecture to enhance the liquidity and transparency of such complex assets. We introduce the concepts of Element Tokens and Everything Tokens: elemental tokens represent standardized, fully collateralized components of an asset (e.g., outputs, rights, or credits), while an everything token represents the entire asset as a fixed combination of those elements. The architecture enables both fine-grained partial ownership and integrated whole-asset ownership through a system of two-way convertibility. We detail the design and mechanics of this system, including an arbitrage mechanism that keeps the price of the composite token aligned with the net asset value of its constituents. Through illustrative examples in the energy and industrial sectors, we demonstrate that our approach allows previously illiquid, high-value projects to be fractionalized and traded akin to stocks or exchange-traded funds (ETFs). We discuss the benefits for investors and asset owners, such as lower entry barriers, improved price discovery, and flexible financing, as well as the considerations for implementation and regulation.
Related papers
- A Taxonomy of Real-World Asset Tokenization for Blockchain-Based Financial Infrastructure [0.0]
Real-world asset (RWA) tokenization has emerged as a prominent application of blockchain technology.<n>This paper develops a systems-level taxonomy of RWA tokenization to classify how off-chain assets are legally, economically, and technically represented on-chain.
arXiv Detail & Related papers (2026-06-07T09:30:11Z) - Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers [50.98108117044413]
We show that the choice of a graph-to-token map is a fundamental component of transformer expressivity.<n>We examine three tokenizations that serve as building blocks for many existing graph tokenizations: spectral, random-walk, and adjacency tokenizations.
arXiv Detail & Related papers (2026-05-21T13:32:20Z) - EpochX: Building the Infrastructure for an Emergent Agent Civilization [46.36919485684112]
We introduce EpochX, a credits-native marketplace infrastructure for human-agent production networks.<n> EpochX treats humans and agents as peer participants who can post tasks or claim them.<n>Credits lock task bounties, budget delegation, settle rewards upon acceptance, and compensate creators when verified assets are reused.
arXiv Detail & Related papers (2026-03-28T15:20:48Z) - Crypto-asset Taxonomy for Investors and Regulators [4.460049392395535]
This paper develops a multidimensional taxonomy for crypto-assets.<n>It connects technical design to market structure and regulation.<n>We map top 100 assets within the structure and provide case studies.
arXiv Detail & Related papers (2026-02-04T22:29:13Z) - Let It Flow: Agentic Crafting on Rock and Roll, Building the ROME Model within an Open Agentic Learning Ecosystem [90.17610617854247]
We introduce the Agentic Learning Ecosystem (ALE), a foundational infrastructure that optimize the production pipeline for agentic model.<n>ALE consists of three components: ROLL, a post-training framework for weight optimization; ROCK, a sandbox environment manager for trajectory generation; and iFlow CLI, an agent framework for efficient context engineering.<n>We release ROME, an open-source agent grounded by ALE and trained on over one million trajectories.
arXiv Detail & Related papers (2025-12-31T14:03:39Z) - THEME: Enhancing Thematic Investing with Semantic Stock Representations and Temporal Dynamics [30.94860968271092]
Thematic investing aims to construct portfolios aligned with structural trends.<n>We introduce THEME, a framework that fine-tunes embeddings using hierarchical contrastive learning.<n>By jointly modeling thematic relationships from text and market dynamics from returns, THEME generates stock embeddings specifically tailored for a wide range of practical investment applications.
arXiv Detail & Related papers (2025-08-23T08:05:37Z) - Tokenize Everything, But Can You Sell It? RWA Liquidity Challenges and the Road Ahead [0.10878040851637999]
The tokenization of real-world assets (RWAs) promises to transform financial markets by enabling fractional ownership, global accessibility, and programmable settlement of traditionally illiquid assets such as real estate, private credit, and government bonds.<n>This paper investigates the gap between tokenization and tradability, drawing on recent academic research and market data from platforms such as RWA.xyz.
arXiv Detail & Related papers (2025-08-03T10:30:15Z) - Transaction Profiling and Address Role Inference in Tokenized U.S. Treasuries [5.00898007095729]
Tokenized U.S. Treasuries have emerged as a prominent subclass of real-world assets (RWAs)<n>This paper conducts a quantitative, function-level dissection of U.S. Treasury-backed RWA tokens across multi-chain networks.
arXiv Detail & Related papers (2025-07-20T03:54:06Z) - Learning Item Representations Directly from Multimodal Features for Effective Recommendation [51.49251689107541]
multimodal recommender systems predominantly leverage Bayesian Personalized Ranking (BPR) optimization to learn item representations.<n>We propose a novel model (i.e., LIRDRec) that learns item representations directly from multimodal features to augment recommendation performance.
arXiv Detail & Related papers (2025-05-08T05:42:22Z) - Universal Item Tokenization for Transferable Generative Recommendation [89.42584009980676]
We propose UTGRec, a universal item tokenization approach for transferable Generative Recommendation.<n>By devising tree-structured codebooks, we discretize content representations into corresponding codes for item tokenization.<n>For raw content reconstruction, we employ dual lightweight decoders to reconstruct item text and images from discrete representations.<n>For collaborative knowledge integration, we assume that co-occurring items are similar and integrate collaborative signals through co-occurrence alignment and reconstruction.
arXiv Detail & Related papers (2025-04-06T08:07:49Z) - STORM: A Spatio-Temporal Factor Model Based on Dual Vector Quantized Variational Autoencoders for Financial Trading [55.02735046724146]
In financial trading, factor models are widely used to price assets and capture excess returns from mispricing.<n>We propose a Spatio-Temporal factOR Model based on dual vector quantized variational autoencoders, named STORM.<n>Storm extracts features of stocks from temporal and spatial perspectives, then fuses and aligns these features at the fine-grained and semantic level, and represents the factors as multi-dimensional embeddings.
arXiv Detail & Related papers (2024-12-12T17:15:49Z) - Clustering Digital Assets Using Path Signatures: Application to Portfolio Construction [0.0]
We propose a new way of building portfolios of cryptocurrencies that provide good diversification properties to investors.
First, we seek to filter these digital assets by creating some clusters based on their path signature.
The goal is to identify similar patterns in the behavior of these highly volatile assets.
arXiv Detail & Related papers (2024-10-15T17:17:02Z) - Towards Proxy Staking Accounts Based on NFTs in Ethereum [0.0]
This paper describes an innovative approach to blockchain networks based on a non-fungible token that behaves as an account (NFTAA)
The key novelty of this article is using NFTAA to leverage the unique properties of NFTs to manage your ownership better and effectively isolate them to improve the security, transparency, and even interoperability possibilities.
arXiv Detail & Related papers (2024-04-22T10:35:26Z) - E2EAI: End-to-End Deep Learning Framework for Active Investing [123.52358449455231]
We propose an E2E that covers almost the entire process of factor investing through factor selection, factor combination, stock selection, and portfolio construction.
Experiments on real stock market data demonstrate the effectiveness of our end-to-end deep leaning framework in active investing.
arXiv Detail & Related papers (2023-05-25T10:27:07Z) - Object Discovery from Motion-Guided Tokens [50.988525184497334]
We augment the auto-encoder representation learning framework with motion-guidance and mid-level feature tokenization.
Our approach enables the emergence of interpretable object-specific mid-level features.
arXiv Detail & Related papers (2023-03-27T19:14:00Z) - CircleChain: Tokenizing Products with a Role-based Scheme for a Circular
Economy [0.5138012450471438]
In a circular economy, tracking the flow of second-life components for quality control is critical.
We propose a role-based token management scheme, which can achieve authentication, synthesis, circulation, and reuse of these second-life components.
The proposed scheme achieves fine-grained and scalable second-life component management, but also enables on-chain trading, subsidies, and green-bond issuance.
arXiv Detail & Related papers (2022-05-23T11:43:31Z) - Factors in the Portability of Tokenized Assets on Distributed Ledgers [1.6582968942719265]
Tokenization of assets deployed to distributed ledger technology is increasingly cited to revolutionize financial services.
To realize these benefits it is important the token is transferrable, that is, portable from one distributed ledger to another.
arXiv Detail & Related papers (2020-05-15T10:35:08Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.