A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This paper uses graph neural networks to predict SME default risk using transaction and ownership networks.
The paper shows how cross-ownership increases equity correlations during financial crises.
Multinational corporations use highly complex structures of parents and subsidiaries to organize their operations and ownership. Offshore Financial Centers (OFCs) facilitate these structures through low taxation and lenient regulation, but are increasingly under scrutiny, for instance for enabling tax avoidance. Theref…
Firms with different ownership structures could be argued to have different levels of efficiency.Highly concentrated firms are expected to be more efficient as this type of ownership structure may alleviate the conflict of interest between managers and shareholders.In Malaysia, public-listed firms have been found to ha…
We introduce a model for the adaptive evolution of a network of company ownerships. In a recent work it has been shown that the empirical global network of corporate control is marked by a central, tightly connected "core" made of a small number of large companies which control a significant part of the global economy.…
This article presents results from the first statistically significant study of causes of cost escalation in transport infrastructure projects. The study is based on a sample of 258 rail, bridge, tunnel and road projects worth US$90 billion. The focus is on the dependence of cost escalation on (1) length of project imp…
Study shows foreign institutional investment increases liquidity commonality in large Australian stocks.
Paper introduces a new edge exchangeable block model for complex networks.
Based on the work of Suzuki (2002), we consider a generalization of Merton's asset valuation approach (Merton, 1974) in which two firms are linked by cross-ownership of equity and liabilities. Suzuki's results then provide no arbitrage prices of firm values, which are derivatives of exogenous asset values. In contrast …
Ownership cost calculation plays an important role in optimal operation of distributed energy resources (DERs) and microgrids (MGs) in the future power system, known as smart grid. In this paper, a general framework for ownership cost calculation is proposed using uncertainty and risk analyses. Four ownership cost calc…
The commercialization of deep learning creates a compelling need for intellectual property (IP) protection. Deep neural network (DNN) watermarking has been proposed as a promising tool to help model owners prove ownership and fight piracy. A popular approach of watermarking is to train a DNN to recognize images with ce…
We generalize Merton's asset valuation approach to systems of multiple financial firms where cross-ownership of equities and liabilities is present. The liabilities, which may include debts and derivatives, can be of differing seniority. We derive equations for the prices of equities and recovery claims under no-arbitr…
Study simulates liquidity in fractional ownership markets using ABM.
NTL protects AI models by restricting their generalization ability to specific domains.
Data taggants verify dataset ownership without harming models or requiring model internals.
The price of a given stock is exactly known only at the time of sale when the stock is between the traders. If we know the price (owner) then we have no information on the owner (price). A more general description including cases when we have partial information on both price and ownership is obtained by using the quan…
A simple quantitative example of a reflexive feedback process and the resulting price dynamics after an exogenous price shock to a financial network is presented. Furthermore, an outline of a theory that connects financial reflexivity, which stems from cross-ownership and delayed or incomplete information, and no-arbit…
NFTs revolutionize art sales by providing proof of ownership.
We propose a methodological framework to study the dynamics of inter-regional investment flow in Europe from a Complex Networks perspective, an approach with recent proven success in many fields including economics. In this work we study the network of investment stocks in Europe at two different levels: first, we comp…
We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the indu…
Model analyzes Proof-of-Stake network dynamics and speculative capital effects on token prices.
In this paper, we consider a dynamic asset pricing model in an approximate fractional economy to address empirical regularities related to both investor protection and past information. Our newly developed model features not only in terms with a controlling shareholder who diverts a fraction of the output, but also goo…
The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international …
Paper introduces proof-of-learning to verify ML model training.
This paper investigates the effect of cross-shareholding on stock price synchronicity, as a measure of price informativeness, of the listed firms in the Chinese stock market. We gauge firms' levels of cross-shareholdings in terms of centrality in the cross-shareholding network. It is confirmed that it is through a nois…
Unified theory of ownership concentration, overlap, and dependence.
We study the possibility of completing data bases of a sample of governance, diversification and value creation variables by providing a well adapted method to reconstruct the missing parts in order to obtain a complete sample to be applied for testing the ownership-structure/diversification relationship. It consists o…
Study finds corporate boards with women appoint more women, leading to better profitability.
Decentralized machine learning is a promising emerging paradigm in view of global challenges of data ownership and privacy. We consider learning of linear classification and regression models, in the setting where the training data is decentralized over many user devices, and the learning algorithm must run on-device, …
Investors trade based on shifting prices, leading to market inefficiencies.
For the convenience of readers of the article {\em No-arbitrage pricing under systemic risk: accounting for cross-ownership} (Fischer, 2012, arXiv:1005.0768), a full proof of Lemma A.5 and a shorter proof of Lemma A.6 of that paper are provided.
As companies continue to invest heavily in larger, more accurate and more robust deep learning models, they are exploring approaches to monetize their models while protecting their intellectual property. Model licensing is promising, but requires a robust tool for owners to claim ownership of models, i.e. a watermark. …
A blockchain replaces central counterparties with time-consuming consensus protocols to record the transfer of ownership. This settlement latency slows cross-exchange trading, exposing arbitrageurs to price risk. Off-chain settlement, instead, exposes arbitrageurs to costly default risk. We show with Bitcoin network an…
Study reveals similarities in knowledge flows between pharmaceutical and AI industries.
How are economic activities linked to geographic locations? To answer this question, we use a data-driven approach that builds on the information about location, ownership and economic activities of the world's 3,000 largest firms and their almost one million subsidiaries. From this information we generate a bipartite …
The sustainability conditions for the market participants with a different ownership model were also determined. It was revealed, that the nonlinear form of the equations describing the market behavior with the prevailing private capital, predetermines the development of such a market according to the subharmonic casca…
We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us…
Study shows how business cycle affects dividend payout based on managerial stock incentives.
Bangladesh's banking sector improved through financial reforms, but challenges remain.
Cryptocurrencies evolve through survival of the fittest, modeled with evolutionary finance.
New method preserves privacy while detecting communities in distributed networks.
Passenger Name Records (PNRs) are at the heart of the travel industry. Created when an itinerary is booked, they contain travel and passenger information. It is usual for airlines and other actors in the industry to inter-exchange and access each other's PNR, creating the challenge of using them without infringing data…
Entangled watermarks improve model defense against extraction attacks.
Financial networks analyzed using statistical physics methods.
A new algorithm improves Bayesian federated learning by reducing communication overhead.
Data ownership and data protection are increasingly important topics with ethical and legal implications, e.g., with the right to erasure established in the European General Data Protection Regulation (GDPR). In this light, we investigate network embeddings, i.e., the representation of network nodes as low-dimensional …
Despite the overwhelming success of the existing Social Networking Services (SNS), their centralized ownership and control have led to serious concerns in user privacy, censorship vulnerability and operational robustness of these services. To overcome these limitations, Distributed Social Networks (DSN) have recently b…
Perpetual futures offer leverage without maturity, with prices influenced by funding rates.