Study uses TV news to measure climate risks affecting clean energy firms.
problem Understanding how climate risks impact clean energy firms' financial stability.
method Developed climate risk measures from TV news coverage and analyzed their effects on clean energy firms' risks.
result Increased TV news coverage of climate risks correlates with higher systematic risk and lower idiosyncratic risk for clean energy firms.
Study optimal incentives for cleaner energy production.
problem Accelerate transition to cleaner technologies in energy market.
method Stochastic control models for three scenarios: single firm, two firms, and two firms without incentives.
result Optimal strategies for investment and production emerge, highlighting firm interactions and incentive effects.
SREC markets are a relatively novel market-based system to incentivize the production of energy from solar means. A regulator imposes a floor on the amount of energy each regulated firm must generate from solar power in a given period and provides them with certificates for each generated MWh. Firms offset these certif…
Fossil power firms have recently profited more than renewables, but this may be a temporary phenomenon.
problem The profitability gap between renewable and fossil power firms in Europe.
method Machine-learning clustering and Bayesian model averaging.
result Renewable power firms are becoming more profitable, while fossil power firms are becoming less so.
Quantum computing offers energy savings over classical computing.
problem Energy efficiency in computing services.
method Cournot competition model constrained by energy usage.
result Quantum computing firms can outperform classical counterparts in energy efficiency.
The study finds that firm membership in flagship indices and TCFD endorsement are strong predictors of a wider Disclosure-Performance Gap.
problem The Aggregate Confusion hypothesis and the measurement of greenwashing in environmental disclosures.
method The study uses a Disclosure-Performance Gap (DPG) model to measure the divergence between voluntary environmental disclosures and realised emissions performance for 200 large European firms. The model selection process involved multiple stages and robust standard errors.
result Firm membership in flagship indices and TCFD endorsement are strong predictors of a wider gap, while renewable energy use and environmental capital expenditure significantly narrow the gap.
Study optimizes SREC generation and trading in solar energy markets.
problem Optimizing solar energy generation and trading in SREC markets.
method Mean-field game approach to solve stochastic game with heterogeneous agents.
result Characterized firms' optimal controls and equilibrium SREC price.
R package tsrobprep cleans and prepares time series data robustly.
problem Inefficient methods for handling missing values and outliers in time series data.
method Model-based methods for imputation and outlier detection considering time series properties.
result Robust and tunable methods for data preprocessing in time series analysis.
Modeling intraday dispatch for wind-battery assets to meet grid targets.
problem Meeting grid targets for wind-battery assets in an intraday context.
method Developed a mathematical model with closed-form solutions and a novel algorithm for stochastic control.
result Calibrated model to 140+ wind-battery assets in Texas, demonstrating economic benefits.
The study visualizes Spanish fish and meat processing companies using financial, environmental, and social ratios.
problem Mapping financial, environmental, and social performance of Spanish processing companies.
method Used compositional data and principal-component analysis biplot for statistical analysis.
result Identified clusters of companies with similar financial, environmental, and social performance.
New method improves sampling from noisy energy models.
problem Training and sampling challenges in Energy-Based Models.
method Pseudo-Gibbs sampling with moment matching.
result Effective sampling from clean model using noisy DSM-trained model.
New image restoration method using localized patches and external databases.
problem Image restoration challenges.
method Localized structured prediction and non-linear multi-task learning for optimizing a penalized energy function.
result Strong statistical guarantees and practical effectiveness demonstrated on various image restoration problems.
TS-Fault benchmarks TSF models against structural faults.
problem Evaluating the robustness of time series forecasting models against structured events.
method TS-Fault uses parameterized fault scenarios with controllable difficulty.
result Three findings contradict common leaderboard intuition.
Robinhood users react strongly to overnight price changes and big losers, trading quickly after extreme losses.
problem Understanding trading behavior of Robinhood users, especially in high-frequency trading scenarios.
method Analyzed intraday and overnight price changes, focusing on big losers and gainers.
result Robinhood users react more to overnight price changes and big losers, trading quickly after extreme losses.
Study analyzes climate-tech investments across 14 sectors.
problem Accelerating climate-tech innovation in nascent value chains.
method Analysis of 4,172 firms and 12,929 investments over 15 years.
result Only 15% of firms develop end products, 59% support them, and 26% develop services.
Modeling wind dynamics in Saudi Arabia using deep learning and stochastic PDEs.
problem Accurately modeling spatio-temporal wind patterns in a large, diverse, and understudied region.
method Energy distance-based spatial reduction, sparse stochastic Echo State Network, non-stationary stochastic PDE reconstruction.
result Produces more accurate wind speed and energy forecasts, saving $1 million annually.
Graph neural networks over-smooth when layers increase, reducing discriminative power.
problem Over-smoothing in graph neural networks reduces model performance as the number of layers increases.
method Analyzed over-smoothing in general graph neural network architecture using Dirichlet energy.
result The Dirichlet energy of embeddings converges to zero, leading to loss of discriminative power.
Bayesian optimization helps learn optimal controls for nuclear fusion reactions.
problem Learning optimal controls for nuclear fusion reactions to prolong plasma stability.
method Theoretical Bayesian optimization algorithm to recommend state-action pairs.
result More efficient use of simulator for learning optimal controls.
Optimal penalties for RECs balance environmental and revenue impacts.
problem Optimizing penalties for RECs to balance environmental and revenue impacts.
method Mean field games and extended McKean-Vlasov control problems.
result Optimal penalty function is linear in agents' state.
Two methods for pricing swing contracts using neural networks or explicit functions.
problem Evaluating optimal energy purchases in swing contracts with firm constraints.
method Two approaches: explicit parametric function and neural network approximation.
result Neural network approach provides better prices in shorter computation time.
Study reveals supply chain correlations in firm growth rates.
problem Understanding correlations in firm growth rates and their supply chain relationships.
method Investigated correlation structure of firm growth rates and used Gaussian Markov Models to reconstruct supply chain networks.
result Supply chain-linked firms exhibit stronger correlation in growth rates than non-linked firms.
A new algorithm reduces imbalanced data classification errors in multi-class settings.
problem Imbalanced data classification, especially with noise and overlapping classes.
method MC-CCR algorithm combining cleaning and resampling.
result High robustness to noise and superior performance compared to state-of-the-art methods.
Analyzed US firm data 1970-2019, identifying scale effects and distributional forms.
problem Understanding differences between small and large firms over time.
method Examined all public US firms, used stylized facts and DLN distribution analysis.
result Small firms are systematically different from large firms, with scale-dependent heteroskedasticity.
Studies report that firms do not invest in cost-effective green technologies. While economic barriers can explain parts of the gap, behavioural aspects cause further under-valuation. This could be partly due to systematic deviations of decision-making agents' perceptions from normative benchmarks, and partly due to the…
Revisits granular models explaining firm growth rates and sizes.
problem Understanding the relationship between firm size and growth rate statistics.
method Developed new theoretical insights linking firm size and growth rate statistics within granular models.
result Growth volatility distribution is size-independent but fat-tailed, challenging granular models.
We develop a probabilistic consumer choice framework based on information asymmetry between consumers and firms. This framework makes it possible to study market competition of several firms by both quality and price of their products. We find Nash market equilibria and other optimal strategies in various situations ra…
Study examines financial structure's impact on non-financial firms' growth in Kenya.
problem Declining financial performance and growth of non-financial firms listed at Nairobi Securities Exchange.
method Analyzes the effect of financial structure on financial growth.
result Established the impact of financial structure on non-financial firms' growth.
Study on-chain peak shaving to reduce Ethereum transaction costs.
problem Reducing transaction costs in blockchain networks, especially during congested periods.
method Analyzing transaction-level data from multiple firms across various industries to understand scheduling responses and cost management strategies.
result Firms' scheduling responses to congestion vary, leading to different fee savings and residual costs.
The understanding of complex social or economic systems is an important scientific challenge. Here we present a comprehensive study of the Spanish Stock Exchange showing that most financial firms trading in that market are characterized by a resulting strategy and can be classified in groups of firms with different spe…
Deep networks learn clean structure before memorizing corrupted labels, leaving a spectral signature in gradient centered scatter.
problem Deep networks' transition from learning clean structure to memorizing corrupted labels under label noise.
method Analysis of the centered scatter of per-example last-layer gradients to identify Fisher Rank Inflation.
result Fisher Rank Inflation is a spectral signature of memorization under label noise, with effective rank expanding during memorization.
An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents is described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm dire…
This study assesses how share capital affects financial growth of non-financial firms listed at NSE.
problem Non-financial firms listed at NSE struggle with financial growth due to declining performance and lack of investor interest.
method Descriptive and panel data analysis of 45 non-financial firms over 10 years.
result Share capital positively and significantly influences financial growth, explaining 32.73% and 11.62% of variations in earnings per share and market capitalization growth, respectively.
Neural networks learn clean data patterns first, then noisy data, leading to improved performance initially but deteriorating later.
problem Improvement in prediction error on clean data during early training of neural networks with noisy labels.
method Theoretical analysis and experiments to explore the dynamics of gradient descent and the impact of clean and noisy data.
result Neural networks prioritize learning clean data patterns first, leading to improved performance initially but deteriorating later due to diminishing gradient dominance of clean samples over noisy ones.
The distribution of firms' growth and firms' sizes is a topic under intense scrutiny. In this paper we show that a thermodynamic model based on the Maximum Entropy Principle, with dynamical prior information, can be constructed that adequately describes the dynamics and distribution of firms' growth. Our theoretical fr…
I study the behavior and the performance of the long-term forecasts issued by financial analysts with respect to the Extrapolation Hypothesis. That hypothesis states that investors, extrapolating from the firms' recent performances, are too optimistic about growth and large firms and too pessimistic about value and sma…
We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor-the debt-to-asset ratio R-in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market …
Study shows long-term debt impacts financial growth of non-financial firms listed at Nairobi Securities Exchange.
problem Declining financial performance and reluctance to lend to non-financial firms listed at Nairobi Securities Exchange.
method Descriptive and panel data analysis of 45 non-financial firms over 10 years.
result Long-term debt positively and significantly influences financial growth measured by earnings per share and market capitalization.
Study assesses short-term debt's impact on non-financial firms' financial growth.
problem Declining financial performance and reluctance to lend to non-financial firms listed at Nairobi Securities Exchange.
method Explanatory research design, descriptive statistics, and panel data analysis.
result Short-term debt positively and significantly influences financial growth.
Study finds financial constraints explain zero-leverage firms.
problem Why some firms have zero leverage despite various explanations.
method Examined three measures of financial constraints; analyzed firms' behavior before and after levering.
result Firms are financially constrained, not due to managerial entrenchment or market valuation.
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.
We consider the scaling behaviors for fluctuations of the number of Korean firms bankrupted in the period from August 1 2002 to October 28 2003. We observe a power law for the distribution of the number of the bankrupted firms. The Pareto exponent is close to unity. We also consider the daily increments of the number o…
Both theoretical and applied economics have a great deal to say about many aspects of the firm, but the literature on the extinctions, or demises, of firms is very sparse. We use a publicly available data base covering some 6 million firms in the US and show that the underlying statistical distribution which characteri…
The new business paradigms originate a strong necessity to re-think the theory of the firm with the aim to get a better understanding on the organizational and functional principles of the firm, operating in the investment economies in the prosperous societies. In this connection, we make the innovative research to adv…
We analyze a database comprising quarterly sales of 55624 pharmaceutical products commercialized by 3939 pharmaceutical firms in the period 1992--2001. We study the probability density function (PDF) of growth in firms and product sales and find that the width of the PDF of growth decays with the sales as a power law w…
New method for estimating firm linkages using CVLs and QCML.
problem Estimating firm linkages for profitable trading strategies.
method Characteristic Vector Linkages (CVLs) and Quantum Cognition Machine Learning (QCML).
result QCML similarity outperforms Euclidean similarity in constructing profitable trading strategies.
We investigate the structure of global inter-firm linkages using a dataset that contains information on business partners for about 400,000 firms worldwide, including all the firms listed on the major stock exchanges. Among the firms, we examine three networks, which are based on customer-supplier, licensee-licensor, a…
Study examines cash conversion cycle in manufacturing firms, finding negative relationships with profitability and size.
problem Understanding cash conversion cycle in manufacturing firms and its impact on profitability and size.
method Empirical study of 30 manufacturing firms in Dhaka Stock Exchanges, categorizing them into six industries, analyzing industry averages and relationships with size and profitability.
result Negative relationship between cash conversion cycle and profitability, especially ROE; negative relationship with firm size in terms of net sales.
A model is presented of the market dynamics to emphasis the effects of increasing returns to scale, including the description of the born and death of the adaptive producers. The evolution of market structure and its behavior with the technological shocks are discussed. Its dynamics is in good agreement with some empir…