Energy storage shifts energy from off-peak periods to on-peak periods. Unlike conventional generation, storage is duration-limited: the stored energy capacity constrains the duration over which it can supply power. To understand how these constraints affect optimal pricing and investment decisions, we extend the classic two-period peak-load pricing model to include duration-limited storage. By adopting assumptions typical of solar-dominated systems, we link on- and off-peak prices to storage investment costs, round-trip efficiency, and the duration of the peak period. The bulk of the scarcity premium from on-peak prices is associated with the fixed costs of storage as opposed to variable costs stemming from round-trip efficiency losses. Unlike conventional generators, the binding duration constraints lead storage to recover energy capacity costs on a per-peak-event basis instead of amortizing these costs over total peak hours. A numerical example illustrates the implications for equilibrium prices and capacity investment.
In finance, Large Language Models (LLMs) face frequent knowledge conflicts arising from discrepancies between their pre-trained parametric knowledge and real-time market data. These conflicts are especially problematic in real-world investment services, where a model's inherent biases can misalign with institutional objectives, leading to unreliable recommendations. Despite this risk, the intrinsic investment biases of LLMs remain underexplored. We propose an experimental framework to investigate emergent behaviors in such conflict scenarios, offering a quantitative analysis of bias in LLM-based investment analysis. Using hypothetical scenarios with balanced and imbalanced arguments, we extract the latent biases of models and measure their persistence. Our analysis, centered on sector, size, and momentum, reveals distinct, model-specific biases. Across most models, a tendency to prefer technology stocks, large-cap stocks, and contrarian strategies is observed. These foundational biases often escalate into confirmation bias, causing models to cling to initial judgments even when faced with increasing counter-evidence. A public leaderboard benchmarking bias across a broader set of models is available at https://linqalpha.com/leaderboard
Type of article: Research Article
AbstractThe mobilization of banking sector capital is increasingly viewed as a pivotal component of the global transition to renewable energy sources (RES), given the sector’s capacity to finance capital-intensive projects. However, banks typically favor investments and lending opportunities that offer predictable cash flows and low default risk, characteristics often lacking in RES projects without policy support. This study investigates whether the development of the banking sector facilitates the uptake of RES and how feed-in tariffs (FiTs), which provide guaranteed purchase periods and stable prices, modify this relationship. Using a panel dataset of 66 countries (selected based on data availability, allowing robust results that may be cautiously applied to countries with comparable financial and institutional contexts) from 2000 to 2020, fixed effects regression models with time dummies and robust standard errors are employed. The analysis finds that banking sector development alone does not lead to increased consumption from RES (coefficient = 0.0011, p = 0.950), suggesting that banks are reluctant to invest in renewables due to the lack of mechanisms to guarantee returns. The standalone introduction of FiTs is associated with a temporary decrease in RES uptake (coefficient = −5.07; p < 0.001), likely reflecting initial market distortions. However, when FiTs are implemented in countries with a more significant economic role of banks, the interaction yields a significant positive effect (coefficient = 0.0412; p < 0.001), indicating that FiTs reduce investment risk and unlock bank financing for RES. The model explains 20.8% (R2=0.208) of within-country variation, and fixed effects vary substantially, underscoring structural differences across countries.
Duane G. Schulthess, Gwen O’Loughlin, Madeline Askeland
et al.
Abstract Background The Congressional Budget Office has stated there is no evidence of a systematic decrease in the percentage of venture capital flowing to pharmaceutical companies since IRA’s passage. This was echoed in Prof. Rita Conti’s September 17, 2024, Senate Finance Committee testimony. Methods To test the IRA’s impacts on early-stage investments targeting therapeutics for the Medicare-aged population, a longitudinal dataset of commercially sponsored clinical trials by companies with a market valuation < $2 billion was obtained from the BioMedTracker database from January 1, 2018, to May 6, 2024. These trials were filtered to match early-stage investments to lead assets undergoing clinical development. Results From 161 lead assets with 897 investments, we find the aggregated total into large molecules in 2024 was 10 times larger than that for small molecules, which underwent a 70% decline after passage of the IRA. Individual investments made into small molecules decline by minus one-half as exposure to the Medicare-aged population increases after the passage of the IRA (p < 0.0018). Testing large molecule investments by their exposure to Medicare post IRA’s passage is statistically inconclusive. Research Conclusions This study presents evidence of a decline in the development of new therapies targeting the Medicare-aged population since the passage of the IRA. If these impacts were due to the economic downturn post-pandemic, we would observe statistically similar results in both large and small molecules. However, the results by molecule type diverge. Investors perceive large molecules to be of a lower investment risk relative to small molecules after IRA’s passage.
This study employs expected certainty equivalents to explore the reinsurance and investment issue pertaining to an insurer that aims to maximize the expected utility while being subject to random risk aversion. The insurer's surplus process is modeled approximately by a drifted Brownian motion, and the financial market is comprised of a risk-free asset and a risky asset with its price depicted by Heston's stochastic volatility (SV) model. Within a game theory framework, a strict verification theorem is formulated to delineate the equilibrium reinsurance and investment strategies as well as the corresponding value function. Furthermore, through solving the pseudo Hamilton-Jacobi-Bellman (HJB) system, semi-analytical formulations for the equilibrium reinsurance and investment strategies and the associated value function are obtained under the exponential utility. Additionally, several numerical experiments are carried out to demonstrate the characteristics of the equilibrium reinsurance and investment strategies.
This paper explores the optimal investment problem of a renewal risk model with generalized Erlang distributed interarrival times. The phases of the Erlang interarrival time is assumed to be observable. The price of the risky asset is driven by the constant elasticity of variance model (CEV) and the insurer aims to maximize the exponential utility of the terminal wealth by asset allocation. By solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation, we establish the concavity of the value function and derive an explicit expression for the optimal investment policy when the interest rate is zero. When the interest rate is nonzero, we obtain an explicit form of the optimal investment strategy, along with a semi-explicit expression of the value function, whose concavity is also rigorously proven.
One of the main demands of investors (depositors and shareholders) of banks is transparency. However, in addition to the requirements for meeting this demand, measuring how to meet it has become challenging. So far, researchers have proposed different qualitative criteria for transparency. In this study, while introducing the correlation coefficient between book and market value at risk (VaRs) as a criterion of transparency, we seek to examine the stability of this criterion in different economic conditions. For this purpose, first, by using the e-garch model, the value at risk was estimated based on the balance sheet (book) information and also the market information of the banks' shares, then by calculating the correlation coefficients between book and market VaR’s under normal conditions, we predict book and market VaR’s using vector auto-regressive (VAR) models, along with defining three stress scenarios (Mild - Severe - hyper stress). We examined the significance of the difference between the calculated correlation coefficients in the three stress test modes. We thus tested the stability of the correlation coefficient of the defined scenarios. The findings showed that except for the correlation caused by the unemployment rate factor in mild and hyper-stress scenarios, in other cases, no evidence of H0 rejection was found, indicating the stability of the correlation coefficient between book and market VaRs as a measure of transparency.
Bharti Meetali, Baswaraju Swathi, Nijhawan Ginni
et al.
In the current time the climate change risk has continued to intensify such that sustainability of the world is difficult, hence urgent emission mitigation actions. An in-depth analysis of GHG emission reduction policies is provided in this paper, with a focus on strategies involving technology, policy, society, and the economy. Regulations play a significant role in reducing the amount of carbon in the atmosphere, which gives a framework for the development of incentives for all sectors. The social cost of carbon is internalized by carbon pricing strategies like carbon taxes and cap-and-trade programs, which promote businesses to invest in greener practices and technological advances. Based on market structures, standards for energy efficiency and mandates for emissions targets may act as catalysts for changes in the market that push towards such low-carbon options. If a significant reduction in greenhouse gas emissions from major economic sectors like agriculture, industry, transportation, or energy is to be achieved, technological advancement will continue to be crucial. Consequently, renewables including solar power wind turbine systems and hydroelectricity plus others replaced fossil fuelled-based sources thereby reducing emission in generation of electrical power. Further, this is to be achieved through efforts in grid modernization, smart infrastructural development and energy storage facilitating the penultimate connection of vast amount of renewable power to electricity grids especially during peak times. Again, industrial sector seems promising as far as decarbonizing production processes and reducing emissions are concerned by adopting clean technologies such as carbon capture and storage (CCS), electrification and sustainable manufacturing processes. Additionally, changes that result into modification in the transport sector like electric vehicles expansion of public transportation systems, promotion of active transport modes amongst others also reduces emission levels whilst enhancing air quality. Transitioning to a low-carbon economy through financing will therefore require significant mobilization of investments towards clean energy infrastructure, sustainable land use practices and climate-resilient development. To direct capital towards low-carbon investment green bonds, carbon markets and public-private partnerships provide innovative financing mechanisms.
We consider the classical multi-asset Merton investment problem under drift uncertainty, i.e. the asset price dynamics are given by geometric Brownian motions with constant but unknown drift coefficients. The investor assumes a prior drift distribution and is able to learn by observing the asset prize realizations during the investment horizon. While the solution of an expected utility maximizing investor with constant relative risk aversion (CRRA) is well known, we consider the optimization problem under risk and ambiguity preferences by means of the KMM (Klibanoff et al. (2005)) approach. Here, the investor maximizes a double certainty equivalent. The inner certainty equivalent is for given drift coefficient, the outer is based on a drift distribution. Assuming also a CRRA type ambiguity function, it turns out that the optimal strategy can be stated in terms of the solution without ambiguity preferences but an adjusted drift distribution. To the best of our knowledge an explicit solution method in this setting is new. We rely on some duality theorems to prove our statements. Based on our theoretical results, we are able to shed light on the impact of the prior drift distribution as well as the consequences of ambiguity preferences via the transfer to an adjusted drift distribution, i.e. we are able to explain the interaction of risk and ambiguity preferences. We compare our results with the ones in a pre-commitment setup where the investor is restricted to deterministic strategies. It turns out that (under risk and ambiguity aversion) an infinite investment horizon implies in both cases a maximin decision rule, i.e. the investor follows the worst (best) Merton fraction (over all realizations of it) if she is more (less) risk averse than a log-investor. We illustrate our findings with an extensive numerical study.
This paper examines how risk and budget limits on investment mandates affect the bidding strategy in a uniform-price auction for issuing corporate bonds. I prove the existence of symmetric Bayesian Nash equilibrium and explore how the risk limits imposed on the mandate may mitigate severe underpricing, as the symmetric equilibrium's yield positively relates to the risk limit. Investment mandates with low-risk acceptance inversely affect the equilibrium bid. The equilibrium bid provides insights into the optimal mechanism for pricing corporate bonds conveying information about the bond's valuation, market power, and the number of bidders. These findings contribute to auction theory and have implications for empirical research in the corporate bond market.
This study delves into the origins of excess capacity by examining the reactions of capital, labor, and capital intensity. To achieve this, we have employed a novel three-layered production function model, estimating the elasticity of substitution between capital and labor as a nested layer, alongside capital intensity, for all industry groups. We have then selectively analyzed a few industry groups for comparative purposes, taking into account the current government policies and manufacturing plant realities. Ultimately, we recommend that policymakers address the issue of excess capacity by stimulating the expansion of manufacturing plants with cutting-edge machinery. Our findings and recommendations are intended to appeal to academics and policymakers alike.
Adrian Arnaiz-Rodriguez, Georgina Curto, Nuria Oliver
Social networks contribute to the distribution of social capital, defined as the relationships, norms of trust and reciprocity within a community or society that facilitate cooperation and collective action. Therefore, better positioned members in a social network benefit from faster access to diverse information and higher influence on information dissemination. A variety of methods have been proposed in the literature to measure social capital at an individual level. However, there is a lack of methods to quantify social capital at a group level, which is particularly important when the groups are defined on the grounds of protected attributes. To fill this gap, we propose to measure the social capital of a group of nodes by means of the effective resistance and emphasize the importance of considering the entire network topology. Grounded in spectral graph theory, we introduce three effective resistance-based measures of group social capital, namely group isolation, group diameter and group control, where the groups are defined according to the value of a protected attribute. We denote the social capital disparity among different groups in a network as structural group unfairness, and propose to mitigate it by means of a budgeted edge augmentation heuristic that systematically increases the social capital of the most disadvantaged group. In experiments on real-world networks, we uncover significant levels of structural group unfairness when using gender as the protected attribute, with females being the most disadvantaged group in comparison to males. We also illustrate how our proposed edge augmentation approach is able to not only effectively mitigate the structural group unfairness but also increase the social capital of all groups in the network.
Donald R. Walkinshaw, Meghan E. E. Wright, Marni Williams
et al.
Abstract Investment in Strep A vaccine R&D is disproportionately low relative to the large burden of Strep A diseases globally. This study presents a novel Strep A vaccine global demand and financial forecast model with estimates of potential global demand and associated revenue and profits for a hypothetical Strep A vaccine as well as a net present value (NPV) analysis of return on capital investments required to develop the vaccine. A positive NPV was calculated for a variety of developer scenarios and target populations, including the global rollout of the vaccine in private and public markets by a multinational pharmaceutical corporation and a staged rollout by a developing country vaccine manufacturer for both infant and child populations. The results suggest there is a viable commercial market for a Strep A vaccine. It is hoped that this study will help to inform industry decision-making and drive increased prioritization of, and investment in, Strep A vaccine research and development.
Immunologic diseases. Allergy, Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Nadiia Davydenko, Svitlana Boiko, Olena Cherniavska
et al.
This paper aims to provide a retrospective assessment of Ukraine’s state policy concerning state-owned banks and evaluate their impact on the sustainability of Ukraine’s public finances. The research methodology employs an empirical study of the cash flow of public funds to state-owned banks and the reverse cash flow to determine the impact of the activity and stability of public finances. The cash flow to state-owned banks includes the expenditure of public funds for the creation of authorised capital during the establishment of state-owned banks, the acquisition of shares in operating commercial banks, additional capitalisation of state-owned banks, etc. The reverse cash flow comprises dividends paid based on the performance of state-owned banks, as well as revenue generated for public funds through the sale of shares (privatisation) of state-owned banks. This study highlights the costs associated with recapitalising state-owned banks. These costs disrupt the stability of public finances, create additional debt dependency for Ukraine, impose an additional burden on public finances, and lead to structural changes that reduce funding for social spending. As a result, Ukrainian taxpayers are financing the inefficient activities of state-owned banks while experiencing reduced investments in education, healthcare, social protection, environmental protection, and other essential areas.
Strelnik Evgeniya, Usanova Diana, Khairullin Ildar
et al.
This article is devoted to the description of the results of the research of the impact of the introduction of ERP-systems on the economic and financial performance of the company. To conduct an empirical study, 50 Russian companies of petrochemical production were selected. The purpose of the research was to quantify the results of the ERP systems implementation. Performance evaluation is of the interest to company executives and the board of directors, since the process of implementing an ERP system requires impressive financial investments and labor costs. However, at present, there are difficulties with scientifically based methods for evaluating the results of the ERP systems implementation. Software vendors announce attractive numbers about the effectiveness of the ERP systems implementation, but can they be trusted, since they are interested in sales. Therefore, we proposed the Monte Carlo method to assess the impact of the introduction of ERP systems on the efficiency of the company. The company's costs and savings characterize variables, increase in net profit and NPV were selected as result variables. As a result of the study, obtained data show both the probability distribution in relation to the indicated variables, and the average values of the implementation effects in such areas as stocks and production, working capital, efficiency, labor costs and reporting. According to the results of the analysis of the selected population, the greatest effects from the introduction of ERP-systems were obtained in the formation of management reporting and logistics, which is due to the greatest attention of managers and IT companies to these issues.
Objective
Recent research confirms the view that companies need foreign capital to finance their labor payments and financing frictions can affect labor investment. Real earnings smoothing can affect labor investment efficiency through its effect on market frictions caused by information asymmetry between managers and suppliers of external capital sources. The purpose of the current research is to investigate the effect of real earnings smoothing and its components on labor investment efficiency.
Methods
Since the results of the research can be used in the decision-making process, the present study falls within the domain of applied research, and since the data were collected based on the real information of the past, it qualifies as an ex-post facto. Furthermore, this research adopts a descriptive-correlational approach, aiming to explore and analyze the relationships between variables under study. The Labor Investment Efficiency is measured according to the framework proposed by Pinnock and Lillis (2007), while the variable of earnings smoothing through real activities and its components is assessed based on the methodologies outlined in the research of Tucker and Zarowin (2006). Additionally, the approach employed by Dou, Hope, and Thomas (2013) to isolate the components of earnings smoothing has been utilized in this study. Given the conditions and constraints applied to the statistical population of the study, a sample comprising 106 companies listed on the Tehran Stock Exchange was selected. This sample was then subjected to analysis using multivariate regression models.
Results
The findings indicate that as the degree of real earnings smoothing rises, there is a corresponding increase in labor investment efficiency. This relationship holds for the informational component of real earnings smoothing as well, demonstrating a positive and significant association with labor investment efficiency. However, the influence of the garbling component on labor investment efficiency was not found to be significant.
Conclusion
According to the obtained results, it appears that managers employ real earnings smoothing as a means to communicate concealed information regarding the company's prospects. By smoothing earnings across consecutive periods, they aim to provide investors and creditors with a coherent and optimistic outlook on the company's future trajectory. Managers reduce information asymmetry by using signaling tools, which causes them to have the necessary financial resources for their investments in labor and make efficient decisions about that. In general, based on the private information signaling perspective, it can be concluded that real earnings smoothing serves as a mechanism for managers to convey their private insights into the company's future earnings. This practice helps mitigate information asymmetry between companies and foreign capital suppliers, consequently enhancing labor investment efficiency. Regarding the garbling component of real earnings smoothing and considering the rejection of the hypothesis of its effect on the efficiency of labor investment, it can be concluded that several potential factors could potentially neutralize this effect. These may include the ignorance or misdirection of certain market participants, the prevalence of irrational behaviors, a steadfast belief in stability, and an excessive emphasis on the informational component. Finally, in addition to highlighting the positive role of real earnings smoothing in increasing the efficiency of labor investment, considering the importance of this issue and also the lack of recognition of the management's intention of real earnings smoothing, this study suggests the need for further exploration in this field.
During the restart of the investment cycle in the new economic reality, the Government of the Russian Federation has adopted and is preparing to implement a number of measures designed to simplify the implementation of investment projects and thereby create prerequisites for maintaining interest in investing in the real sector of the economy. Thanks to the current model of financial support for investment projects in Russia, a diverse and necessary toolkit is available to the investor when choosing ways to make investments in order to make management decisions on the implementation of projects aimed at ensuring the sustainability of companies of various types. Naturally, within the framework of preparing management decisions for the implementation of investment projects, the question arises of rationally determining the parameters of financial support for an investment project, taking into account all aspects of its implementation, from the choice of sources of financing to the procedure for returning capital raised, as well as structuring projects when assessing their compliance with ESG (Environmental, Social, Governance) criteria. The purpose of this work is to study the importance of structuring an investment project in ensuring the sustainability of companies, to study all aspects of project implementation as part of the management decision-making process, which directly affects the possibility of its implementation. The methodological and theoretical basis of the article is general scientific and particular scientific approaches devoted to the issues of structuring projects in the framework of preparing investment decisions. In addition, CyberLeninka, eLibrary.Ru, Scopus, Web of Science, and Google Scholar were used as academic databases. To ensure the accuracy of the literature review process, all publications were independently reviewed by the authors. An analysis of the procedure for preparing and making investment decisions, structuring projects was made. The authors’ logic of interpreting the goal of structuring in making managerial decisions on project financing is proposed.
Nikolay Dmitriev, Andrey Zaytsev, Oleg Kichigin
et al.
This paper aims to develop a multifactor model of the impact of attracting investment in the fixed capital of a region. To this end, the authors conducted a factor analysis of regional investment attractiveness. Correlation and regression analysis served as the methodological basis for determining the qualitative dependencies of regional fixed capital investments. Testing of the examined model allowed the authors to identify dependencies between controlled variables (factors that can be influenced at the regional level) and the resulting indicator (investment in the fixed capital of a region) for the Russian federal subjects. The significance of the model lies in the possibility of developing practical measures (focused on specific conditions of territorial functioning) to improve regional investment policies.