Paper proposes a framework for calculating ownership costs of DERs using uncertainty and risk analyses.
problem Optimal operation of distributed energy resources (DERs) and microgrids (MGs) in smart grids.
method A general framework for ownership cost calculation using uncertainty and risk analyses, with four approaches compared.
result Best ownership cost calculation approach chosen based on simulation results for a typical diesel generator (DiG).
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…
The study finds variations in ownership structure and efficiency across sectors in Malaysia.
problem Investigate variations in ownership structure and firm efficiency across sectors in Malaysia.
method Frequency distributions of ownership structure, DEA under CRS and VRS, stratified random sampling.
result There are variations in firm ownership structure and efficiency across sectors in Malaysia.
Study shows foreign institutional investment increases liquidity commonality in large Australian stocks.
problem Impact of foreign institutional investment on liquidity commonality in Australian stocks.
method Cross-sectional and time-series analysis of Australian equity market data.
result Foreign institutional investment contributes to increased exposure of large stocks to unexpected liquidity events.
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 …
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.
problem Understanding liquidity dynamics in illiquid markets.
method Agent-based modeling (ABM) with empirical data.
result Simulation reveals insights into market structures and trading behaviors.
NTL protects AI models by restricting their generalization ability to specific domains.
problem Protecting AI models as intellectual property in a secure and robust manner.
method Non-Transferable Learning (NTL) captures exclusive data representation and restricts model generalization ability.
result NTL provides robust resistance to watermark removal and data-centric protection for usage authorization.
Data taggants verify dataset ownership without harming models or requiring model internals.
problem Verifying dataset ownership without harming models or requiring model internals.
method Using pairs of out-of-distribution samples and random labels as secret keys, subtly altering a dataset to detect models trained on it.
result Data taggants reliably detect models trained on the protected dataset with high confidence, without compromising validation accuracy.
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…
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…
The study examines how investor protection and past information affect stock returns and interest rates.
problem Empirical regularities related to investor protection and past information in asset pricing models.
method Developed a dynamic asset pricing model with a controlling shareholder and good/bad memory in budget dynamics.
result Good/bad memory of investors on historical market information affects stock returns and interest rates, strengthening investor protection in high ownership concentration.
The paper shows how cross-ownership increases equity correlations during financial crises.
problem Understanding and explaining rising correlations in financial markets during crises.
method Examined interlinkages among firms through a financial network, mathematically relating equity correlations to asset correlations and network sensitivity.
result Equity correlations are higher than asset correlations, and this relationship is independent of the equities level.
This paper uses graph neural networks to predict SME default risk using transaction and ownership networks.
problem Predicting credit risk for SMEs facing limited financial histories and collateral constraints.
method Graph Neural Networks applied to multilayer network data of SME transactions and ownership.
result Combining network data with traditional data improves credit scoring and models contagion risk.
NFTs revolutionize art sales by providing proof of ownership.
problem Lack of provenance and authenticity in digital art.
method Analysis of major art NFT marketplaces.
result NFTs reduce the need for intermediaries in the art trade.
Entangled watermarks improve model defense against extraction attacks.
problem Model extraction attacks risk leaking valuable intellectual property.
method Entangled Watermarking Embeddings (EWE) leverages model capacity to overfit to outlier input-output pairs.
result The approach successfully claims model ownership with high confidence and minimal performance loss.
New system assigns vehicles to routes for cost and energy efficiency.
problem Optimizing vehicle route assignment for cost and energy efficiency.
method Machine learning-based neural network algorithm to estimate energy consumption and provide real-time recommendations.
result Demonstrated efficient vehicle assignment for medium and heavy duty trucks.
Perpetual futures offer leverage without maturity, with prices influenced by funding rates.
problem Understanding and pricing perpetual futures with funding rates.
method Derive no-arbitrage prices and bounds in markets with trading costs. Empirically analyze deviations and Sharpe ratios of implied arbitrage strategies.
result Implied arbitrage strategies in crypto markets yield high Sharpe ratios, indicating significant pricing inefficiencies.
The paper challenges the assumption that majority voting rights equate to 'effective control' in foreign ownership regulations.
problem The assumption that majority voting rights determine 'effective control' in foreign ownership regulations is flawed.
method The paper proposes and demonstrates a method for calculating 'effective control' based on voting thresholds and weights.
result The 'effective control' of a foreign minority stockholder can be higher than their shareholding size, challenging the assumption that majority voting rights equate to 'effective control'.
Paper introduces proof-of-learning to verify ML model training.
problem No mechanism to prove ML model training parameters were obtained through optimization.
method Inspired by proof-of-work and verified computations, introduces proof-of-learning mechanism.
result Proves model training parameters were obtained through optimization with minimal adversary work.
Blockchain trading faces limits due to time-consuming settlement, exposing arbitrageurs to price risk.
problem Time-consuming settlement in blockchain trading limits arbitrage opportunities.
method Analysis of Bitcoin network and order book data.
result Cross-exchange price differences coincide with high settlement latency and low default risk.
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.…
Unified theory of ownership concentration, overlap, and dependence.
problem Understanding the complex layers of ownership concentration, overlap, and dependence in financial markets.
method Develops a unified quadratic framework for analyzing these layers and their interactions.
result Unified framework shows that the same residual operator measures static overlap and governs linearized market transmission.
New mortgage contracts reduce underwater default by adjusting loan balances, but must balance prepayment incentives.
problem Underwater default incentives in mortgages.
method Analyzes automatic balance adjustment and prepayment penalties in mortgage contracts.
result Automatic balance adjustments are preferable to traditional contracts at certain spreads, reducing underwater default.
Evolutionary algorithm improves DNN watermarking with fewer false positives.
problem Protecting deep learning models from piracy and proving ownership.
method Evolutionary algorithm for generating and optimizing trigger patterns.
result Reduces false positive rates in DNN watermarking.
Using the formalism of Lyapunov potential function it is shown that the stability principles for biomass in the ecosystem and for employment in economics are mathematically similar. The ecosystem is found to have a stable and an unstable stationary state with high (forest) and low (grasslands) biomass, respectively. In…
Investors trade based on shifting prices, leading to market inefficiencies.
problem Market inefficiencies due to trading behavior and financial dynamics.
method Analyzes trading strategies and market dynamics.
result Arbitrage opportunities arise from concentrated ownership and low collateral requirements.
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.
Paper introduces a new edge exchangeable block model for complex networks.
problem Limitations of the stochastic block model in analyzing complex networks.
method Develops a Bayesian nonparametric edge exchangeable block model.
result The new model outperforms state-of-the-art SBMs for link prediction.
Bandana stores deep learning models using NVM with DRAM caching.
problem Reducing memory footprint of deep learning models stored on DRAM.
method Uses NVM as primary storage, DRAM as cache, hypergraph partitioning, and cache simulation.
result Significantly reduces the cost of ownership for storing deep learning models.
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…
This paper explores how decentralized finance mitigates traditional finance's shortcomings.
problem Lack of transparency and moral hazard in centralized finance.
method Analysis of smart contracts and decentralized governance in DeFi.
result DeFi mitigates traditional finance's shortcomings through decentralized governance and smart contracts.
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…
Study shows how business cycle affects dividend payout based on managerial stock incentives.
problem Impact of managerial stock incentives on dividend payout policy during business cycles.
method Using S&P 1500 companies data from 2000-2018, analyzing full sample and recession periods.
result Negative relationship between managerial stock options and dividend payouts, significant for medium-sized companies.
Bangladesh's banking sector improved through financial reforms, but challenges remain.
problem Weak asset quality, inadequate provisioning, and negative capitalization of state-owned banks.
method Two phases of reforms: private ownership promotion and gradual deregulation.
result Significant improvements in asset quality and capitalization, but challenges persist.
Proposes a federated learning approach for RUL prediction from nonparametric degradation and failure signals.
problem Cost-effective RUL prediction from limited, non-shared CM signals with unknown parametric forms.
method Joint modeling of nonlinear degradation signals and failure events using federated learning.
result Superior RUL prediction compared to alternatives, validated through simulations and real data.
Cryptocurrencies evolve through survival of the fittest, modeled with evolutionary finance.
problem Understanding the dynamics of cryptocurrency markets.
method Evolutionary finance concepts applied to toy models of cryptocurrency data.
result Survival of the fittest in cryptofinance is explained through scaling laws.
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…
Graph-based method predicts business conduct risk from incomplete data.
problem Sparse and biased data limits risk assessment.
method Visibility-aware GCNII framework on corporate graph.
result Graph-based approach outperforms non-graph methods in predicting future incidents.
New method preserves privacy while detecting communities in distributed networks.
problem Privacy-preserving community detection in locally distributed multi-layer networks.
method Privacy-preserving Distributed Spectral Clustering (ppDSC) using randomized response mechanism.
result Developed a novel algorithm that maintains community structure while protecting privacy.
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…
Study finds corporate boards with women appoint more women, leading to better profitability.
problem Influence of female board members on corporate profitability.
method Analysis of Japanese corporate boards and their interlocks.
result Corporate boards with women appoint more women, leading to higher profitability.
Model analyzes Proof-of-Stake network dynamics and speculative capital effects on token prices.
problem Understanding and managing price dynamics in Proof-of-Stake networks.
method Developed an open-economy macroeconomic model to analyze Proof-of-Stake dynamics and speculative capital effects.
result Speculative capital can shift staked-token ownership, potentially improving consensus decentralization.
New piracy-resistant watermarks for deep neural networks prevent false claims.
problem Protecting deep learning models from false claims by embedding pirate watermarks.
method Null embedding, a new approach to build watermarks that resist removal and addition.
result Null embedding achieves piracy resistance and other watermark properties over various tasks and models.
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 …
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…
COLA trains linear models on decentralized data without a central coordinator.
problem Learning linear models on decentralized, privacy-sensitive data.
method COLA, a decentralized training algorithm with strong theoretical and practical guarantees.
result Achieves superior communication efficiency, scalability, elasticity, and resilience.
Cross-shareholding improves stock price synchronicity in China.
problem Measuring price informativeness in Chinese stock market firms.
method Analyzing cross-shareholding networks and centrality measures.
result Cross-shareholding reduces price delay and enhances price synchronicity.