Efficient Pricing Research Articles

Social Media Networks and Stock Price Synchronicity: Evidence from a Chinese Stock Forum

The widespread communication and interaction between small investors on social media in the capital market has resulted in the formation of a social media network specific to listed companies. Using a unique dataset from an active online stock forum in China, we construct a social media network of listed companies by assigning listed companies as nodes and common commenters who post in each of the subforums for two listed companies in a year as edges. Then, we investigate the relationship between the network centrality of the listed companies and stock price synchronicity. The results show that there is a significantly negative relationship between the social network centrality of listed companies and stock price synchronicity, indicating that social media networks can improve the price efficiency of capital markets. The mechanism analysis shows that social media networks can produce more corporate‐specific information and improve the efficiency of information dissemination, thus reducing stock price synchronicity.

Price Spread, Marketing Efficiency and Postharvest Losses in Marketing of Selected kharif Vegetables in Palghar District of Maharashtra State, India

Vegetables play an important role both in the regional and national economy of the agricultural sector. These crops are generally of short duration. The post-harvest losses in kharif vegetables due to insufficient storage, packaging, transportation, and handling technologies for perishable crops, such as vegetables, lead to significant wastage. The present study was undertaken to estimate these losses at various stages and price spread of selected vegetables in study area. The study was conducted in Palghar district of Maharashtra, involving 90 farmers, 6 commission agents, 9 wholesalers and 30 retailers, that the study involves multiple groups of stakeholders (farmers, commission agents, wholesalers, and retailers), with specific numbers from each group. The sampling technique used in this case likely purposive sampling. The important kharif vegetables were identified for the detailed analysis. In of case brinjal the total postharvest losses were 12.62 kg/q. out of which maximum postharvest losses of brinjal vegetables was observed to be highest (4.62 kg/q), at retailer level followed by (3.2 kg/q) at wholesaler level and (1.65 kg/q) at commission agent level. Similarly in case of okra, postharvest losses in kharif season was estimated to 13.52 kg /q, out of which the retailers level postharvest losses was highest at (5.12 kg/q), followed by (3.78 kg /q) at wholesaler level, (2.87 kg /q) at farmer level and (1.75 kg/q) at commission agent level .Whereas for cowpea total postharvest losses was workout to 12.73 kg/q out of which 4.12 kg /q postharvest losses was observed at retailer level, 3.65 kg /q losses at wholesaler level, 3.08 kg /q at farmer level and 1.88 kg /q postharvest losses at commission agent level. In study were identified channel-I (Producer-Commission agent-wholesaler-Retailer-Consumer), channel-II (Producer-Wholesaler-Retailer-Consumer) and channel-III(Producer-Consumer). For brinjal, the price spread was Rs. 2962.91 in Channel-I and Rs. 2634.72 in Channel II, with marketing efficiency of 1.01, 1.24, and 33.76 in Channels-I, II, and III, respectively. Channel-III exhibited the highest marketing efficiency, while Channel II had the lowest price spread. For okra, the price spread was Rs. 1939.70 in Channel-I and Rs. 1733.20 in Channel II, with marketing efficiency of 1.51, 1.85, and 28.84 in Channels-I, II, and III, respectively. Channel II demonstrated the highest marketing efficiency and lowest price spread. In the case of cowpea, the price spread was Rs. 4000 in Channel-I and Rs. 3260 in Channel-II, with marketing efficiency of 0.91, 1.76, and 29.76 in Channels -I, II, and III, respectively. Again, Channel III provided the highest efficiency, while Channel II had the lowest price spread. Channel-III emerged as the most efficient channel for all crops due to the direct sale to consumers, resulting in the highest marketing efficiency. Channel-II also showed better efficiency, especially in okra, while Channel-I consistently had the lowest efficiency across all crops.

Small-Sample Data Pricing Based on Data Augmentation and Meta-Learning

Data trading platforms play a crucial role in facilitating data circulation and promoting the sustainable allocation of data resources. Establishing a transparent, fair, and efficient pricing mechanism is key to ensuring the long-term stability and development of such platforms. However, these platforms face challenges in pricing due to the small sample problem, as traditional machine learning methods typically rely on large amounts of data. To address this issue, this paper proposes a data resource pricing model that combines WGAN-GP data augmentation and the Reptile algorithm. Data augmentation generates related datasets to increase sample size, enhancing the renewability of data resources, while meta-learning transfers knowledge across tasks, improving the model’s ability to quickly adapt to new tasks and efficiently utilize resources. Validation using actual trading data from the data trading platform shows that the proposed model accurately predicts data resource prices under small-sample conditions, outperforming other models. This study addresses the limitations of existing pricing methods in small-sample scenarios, providing a sustainable pricing solution for small-sample data resources and improving the accuracy and long-term stability of data pricing in the market.

Multi-market trading and overnight price discovery: Evidence from American Depository Receipts

This article compares the overnight price discovery of American Depository Receipts (ADRs) and common stocks traded in the US stock market. It examines how trading activities of ADRs’ underlying shares in home markets affect price discovery. We find that the efficiency of the opening price and the price discovery during the close-to-open period is significantly higher than that of US common stocks. Further analyses show that the price discovery of ADRs shifts from the trading day to the overnight, and the opening prices of ADRs are more efficient if there are more trading activities of underlying shares in home markets. The results suggest that trading similar assets in multiple markets over non-overlapping hours improves price efficiency. JEL Classification: G12, G14, G15

New control variates for pricing basket options

Abstract Accepted by: Giorgio Consigli Accurate pricing of basket options, which are financial derivatives on multiple underlying assets, is a challenging and practically important task for financial institutions. We propose several new control variates for accurate, fast and efficient pricing of basket options. The first approach to deriving new control variates is the use of Hermite polynomial approximation of appropriate function of the underlying asset prices, which leads to a Black–Scholes-like analytic solution. This approach is new in the option pricing context and opens up new possibilities in derivative pricing. Further control variates are analytically derived using Jensen’s inequality in one case, and distributional properties of multivariate Wiener processes in other cases. All the newly proposed control variates are shown to lead to excellent variance reduction in numerical experiments based on realistic data. The proposed methods are novel, computationally simple and have a strong potential to replace more conventional methods, such as the geometric lower bound in simulation-based pricing of basket options and similar products used in financial risk management.

High Price Impact Trade Identification and Its Implication for Volatility and Price Efficiency

High Price Impact Trade Identification and Its Implication for Volatility and Price Efficiency

A branch-and-price approach for the nurse rostering problem with multiple units

In this paper, we study the nurse rostering problem that considers multiple units and many soft time-related constraints. An efficient branch and price solution approach that relies on a fast algorithm to solve the pricing subproblem of the column generation process is presented. For the nurse rostering problem, its pricing subproblem can be formulated as a shortest path problem with resource constraints, which has been the backbone of several solutions for several classical problems like vehicle routing problems. However, approaches that perform well on these problems cannot be used since most constraints in the nurse rostering problem are soft. Based on ideas borrowed from global constraints in constraint programming to model rostering problems, an efficient dynamic programming algorithm with novel label definitions and dominating rules specific to soft time-related constraints is proposed. In addition, several acceleration strategies are employed to improve the branch and price algorithm. Computational results on two sets of instances ranging from 2 to 4 units over a horizon of 2 or 4 weeks demonstrate the effectiveness of the proposed algorithms. The accelerated dynamic programming algorithm is able to solve pricing subproblems to optimality with the fewest extended labels. When contrasted with Cplex, the branch and price approach yields solutions that are either equivalent or superior across all instances.

Cryptocurrency hacking and trader behavior in bitcoin futures

We investigate the effect of cryptocurrency hacking on trader positions in CME bitcoin futures. Our results indicate that the occurrence of hacking and fraudulent incidents lead to more net-short positions and fewer participation ratio for leveraged funds in bitcoin futures. Additionally, U.S. dollar index, futures basis, and price efficiency also play significant roles in the trading of leveraged funds. Lastly, we find that the number of hacking incidents negatively affects dealers’ net-long positions. This study provides new insights into trader behaviors in bitcoin futures and offers practical implications for bitcoin investors and regulators.

Spatio-temporal differentiation characteristics of coal mine safety levels in China based on spatial spillover effects

In order to solve the problem of "potpourri" of safety risk prevention and control measures, which is caused by the unclear mechanism of the spatial effect of coal mine safety level heterogeneity and its influencing factors. This paper discriminates the dominant factors of spatio-temporal heterogeneity of coal mine safety production level in China and their spatial effect types by means of GeoDetector and the Spatial Dubin Model (SDM), specifies the categories and degrees of acts on local and surrounding areas by changes in indicators, and provides further visualization of the detection outcomes with the assistance of the Neo4j graph database, and the findings indicate that:(1) All 15 indicators selected in the study have a certain influence on the generation of spatial heterogeneity in China's coal mine safety production level, and all of them show an enhancement relationship after the interaction of indicators. Especially, the combination of excavated environment and other indicators basically has a non-linear enhancement relationship. (2) In terms of spatial effects, the influence of the 5 effects on the spatio-temporal heterogeneity of coal mine safety level is, in descending order, industrial development effect > capital allocation effect > production environment effect > government supervision effect > enterprise management effect, which indicates that macroeconomic and market conditions have a much stronger influence on the generation of spatio-temporal heterogeneity in coal mine production safety status. (3) From the single indicator perspective, the average annual temperature, average annual wind speed, coal consumption and monitoring efficiency primarily affect the dependent variable through direct effects; GDP per capita, average labor compensation as well as railroad operating mileage have positive spatial spillover on the changes of coal mine safety production level in surrounding areas; the evaluation of the spatial effect for average labor compensation exhibits a positive indirect effect with low influence; for the two indicators of production efficiency and ex-factory price, not only do they have negative effects on the local coal mine safety level, but also have significant spillover effects on surrounding areas.

Do Investors’ Site Visits Improve Bond Market Pricing Efficiency? —An Empirical Study from the Secondary Bond Market

ABSTRACT Taking bonds issued by A-share companies listed on the Shenzhen Stock Exchange from 2014 to 2020 as a sample, this paper explores the effect of corporate site visits on bond trading spreads. The study finds that the more investors visit a given firm, the lower the trading spreads of bonds issued by that firm, and this phenomenon is more pronounced in companies with greater information asymmetry or agency conflicts. Further research shows that investors evaluate the financial status of the company more accurately through site visits and reduce irrational decisions caused by information uncertainty. Consequently, site visits reduce the financing gap caused by macroeconomic factors. The results show that personal communication between investors and listed companies could provide effective information for bond investors and reduce their information risk. This paper expands the existing research on issues related to secondary bond market pricing and investors’ site visits and provides important empirical evidence for regulators to use to further optimize the bond market disclosure system to reduce information asymmetry.

Electricity Industry Strategies in Ecuador and Peru: Their Impacts on Energy Efficiency and Prices

Through an empirical analysis of the impact of determinants on energy efficiency and electricity prices using monthly data, we compare the outcomes of energy strategies in Ecuador and Peru from 2014 to 2023. OLS regression models with Newey-West matrices are applied in two contexts: Energy efficiency and energy prices. Energy efficiency is explained through variables such as the proportion of renewable energies, national income, and the international oil price. The results indicate that in Ecuador, the proportion of renewable energies is positively related to energy efficiency, whereas in Peru, energy efficiency mainly depends on the trend component capturing changes in productivity and the decline in fuel prices. Furthermore, electricity prices are sensitive to fluctuations in oil prices, especially in Peru, due to its dependence on thermoelectric generation. The energy strategies of both countries, including the integration of renewables and the management of fossil fuel costs, play crucial roles in determining energy efficiency and prices. This study provides a comprehensive view of how various economic and structural factors influence the performance of the energy sector in both nations, highlighting the differences in their approaches and outcomes.

Adaptability, diversification, and energy shocks: A firm level productivity analysis

Energy economists have long argued that energy systems need to be adaptable in the face of shocks. In the early twentieth century, Denmark embodied the opposite, with its industry almost entirely dependent on imports of coal from the UK. Towards the end of the First World War, however, and well into the 1920s, coal imports became expensive and more difficult to obtain. Local diversification was possible, however, through peat. We exploit detailed microlevel data from butter factories, covering the period 1900–28. Employing an event study approach, we find significant productivity advantages for firms closer to available peat fields in the wake of the coal shortage, and that these gains persisted even when peat was no longer used. Our results thus suggest that public policy might aim to support adaptability for firms less able to transition to more sustainable energy if that is the price of longer-term efficiency and survival.

Social media, investor‒firm interactions and informational efficiency of stock prices: Evidence from China

Using a sample of Chinese listed companies from 2010 to 2022, we examine how investor‒firm online interactions influence informational efficiency of stock prices. The empirical results indicate that investor–firm online interactions significantly enhance informational efficiency. After conducting a series of robustness checks, the conclusions remain valid. Mechanistic analysis demonstrates that investor–firm online interactions enhance informational efficiency primarily by reducing information asymmetry and correcting stock mispricing. We emphasize the critical importance of retail investor–firm online interactions within social media platforms in promoting informational efficiency of stock prices.

Strategies to Inelasticize the Halal Food Industry in Indonesia

This research has three main objectives. First, to analyze the potential and prospects of the halal food industry in Indonesia. Second, analyze the elasticity of the halal food industry in Indonesia. Finally, formulate a strategy to inelasticize the halal food industry in Indonesia. The research approach used in this study is mixed methods, which combines quantitative and qualitative research. There are several important findings in this study. First, the potential and projection of the halal food industry in Indonesia, which is based on estimates for 2021, continues to grow. Second, the factors that influence the demand for halal food in Indonesia are income, price, advertising, and halal labeling, and the highest -lowest short-term elasticity values are price elasticity, halal labeling, advertising, and income. Finally, the strategy to inelasticize the halal food industry in Indonesia is divided into two, namely priority strategies and supporting strategies. Priority strategies include: Maintain the stability of people's income; Increase production efficiency (technical efficiency and price efficiency); Improve the quality of Human Resources (HR) and technology improvement; Application of tax incentives; Improving the quality and quantity of advertising; Socialization of halal labeling; Halal certification management; Development of halal supply; Development of halal logistics. Supporting strategies consisting of Need for innovation in the development of halal food industry products; Guarantee of legal certainty and quality of halal food products; Increased ease of location and access; Service innovation; Improved facilities.

From code to coin: Unravelling the practical business impact of algorithmic pricing

This paper examines the impact of algorithmic pricing on company value and presents the results of 31 expert interviews in various industries. The focus is on nine hypotheses, including the efficiency of automation, segmentation and value-based pricing, efficient resource allocation, perception of fairness, price transparency and uncertainty, the use of personal data and price competition. The surveys show that algorithmic pricing has considerable potential for efficiency gains through automation, particularly in terms of revenue growth. The potential for cost savings, however, varies from sector to sector. Segmentation and value-based pricing are proving to be feasible, but their implementation requires clear justification and economic rationale. Efficient resource allocation through dynamic pricing shows potential, especially in industry-specific scenarios. The perception of unfairness can have a negative impact, however, and personalised pricing risks alienating customers and reducing business value. Price transparency and uncertainty have a mixed effect, as customers often place more value on the transparency of alternative offers than on the company’s pricing process. The use of personal data poses a low risk to company value if it is transparent and mutually beneficial. The potential intensification of competition through algorithmic pricing depends on the market structure and the company’s objectives; however, algorithmic pricing can be used as an instrument to reduce price competition and increase company value. Overall, the results make it clear that the integration of algorithmic pricing strategies must be carefully and ethically designed in order to sustainably increase company value.

Analysis of Short-selling Effects Using KOSPI200 and KOSDAQ150 Indexing

Financial regulators often react to crises by restricting short-selling to stabilize the stock market. In response to the COVID-19 pandemic, the Korean government banned short-selling in 2020. Since 2021, it has allowed partial resumption only for stocks indexed in KOSPI200 and KOSDAQ150. This unique short-selling regime in Korea makes newly indexed or excluded stocks experience exogenous variations in their short-selling availability when the constituents of the two indices are updated. Using this quasi-natural experimental setting, we examine the impact of short-selling permission and ban. The results show that short-selling permission enhances stocks’ price efficiencies while short-selling permission and ban do not strongly influence stock return or volatility. Overall, this paper provides empirical evidence supporting the positive role of short-selling, further casting doubts on the reasons behind banning short-selling.

Efficient option pricing in the rough Heston model using weak simulation schemes

We provide an efficient and accurate simulation scheme for the rough Heston model in the standard (H>0) as well as the hyper-rough regime ( -1/2 $ ]]> H > − 1 / 2 ). The scheme is based on low-dimensional Markovian approximations of the rough Heston process derived in [Bayer and Breneis, arXiv:2309.07023], and provides a weak approximation to the rough Heston process. Numerical experiments show that the new scheme exhibits second-order weak convergence, while the computational cost increases linearly with respect to the number of time steps. In comparison, existing schemes based on discretization of the underlying stochastic Volterra integrals such as Gatheral's HQE scheme show a quadratic dependence of the computational cost. Extensive numerical tests for standard and path-dependent European options and Bermudan options show the method's accuracy and efficiency.

Information acquisition, market professional and discretionary liquidity trading

We analyze an insider trading strategy and market professionals’ information acquisition strategies, and explore their impact on market liquidity and price efficiency in endogenous noise trading. Our findings highlight the negative precision effect on market professionals’ information acquisition. With an increase in market professionals, two opposing effects emerge on market liquidity and price efficiency: the strategic complementarity effect and the precision effect. However, the negative precision effect predominates, which impairs market liquidity and price efficiency. Furthermore, enhancing the ex-ante precision of the risky asset or adjusting liquidity compensation reduces market professionals’ involvement in information acquisition, leading to diminished price efficiency.

Optimizing vertical farm cultivation of Cichorium spinosum L.: White Light's influence and nutrition management

The objective of this study was to examine the integration of a wild leafy vegetable, Cichorium spinosum L., in vertical farms. This research comprises two experiments focusing on different “white” light products and nutrient solutions. During both experiments, the temperature varied between 25 and 28 °C, relative humidity ranged from 50 to 70 %, carbon dioxide was at 450 ppm, and light intensity was set at 300 μmol m−2 s−1 respectively. In the lighting experiment, the three spectra used had the commercial names Neutral, Full and a SunLike™, and their spectral composition (blue:green:red:far-red) were 14:32:43:10, 16:36:40:8, and 21:34:36:7 respectively. The photoperiod was set to 12 h and the plant density was 50 plants m−2. Results showed no significant impact on agronomical parameters and leaf anatomy. The stomatal length and width decreased as the red:blue ratio of the light sources decreased, being greater in the Neutral treatment (red:blue ratio of 3.1) compared to the Full and SunLike™ (red:blue ratios of 2.5 and 1.7 respectively). Based on these results the preferable “white light” product was the one with the highest efficiency and lowest market price at the time of the experiment. In the nutrient solution experiment, the agronomical and nutritional attributes of stamnagathi plants supplied with a control nutrient solution, “N10-Fe15” were compared to plants cultivated under limited nitrogen, “N4-Fe15” and elevated iron, “N10-Fe48”, EC was 1.5 ds m−1, and pH was 5.6–6.5. The experiment simulated commercial practices by increasing the photoperiod to 15 h and plant density to 100 plants per square meter. The results did not demonstrate significant effect of the nutrient solution differences on the agronomical characteristics except from a decrease in total Kjeldahl nitrogen under limited nitrogen conditions. Notably, leaf tissue phosphorus content increased under elevated iron conditions. The nitrate content remained within safe for consumption thresholds for all treatments. Based on these results, stamnagathi can be integrated in vertical farms under limited nitrogen conditions. Stamnagathi's resilience to elevated iron in the nutrient solution demonstrated its potential for future biofortification experiments.

External costs of high-voltage overhead transmission lines: Evidence from a causal approach in rural France

In light of climatic change and global warming, electricity transmission networks need to be developed for the integration of renewable sources. In North America and Europe, to achieve renewable electricity goals, massive investments in electricity transport infrastructure are planned to connect solar and wind generation sites to the grid network. However, local opposition to new installations of high-voltage overhead transmission lines (HVOTLs) is causing delays and cost overruns. Visual nuisance is an important basis of local stakeholders' opposition to a new project. Estimations of the local economic impact of HVOTLs can help in identifying the external costs of the electricity supply industry to improve both efficiency in electricity pricing and fairness in defining provision for host community compensation. Prior research has provided evidence that existing HVOTLs have negative but not substantial effects on their immediate neighbourhoods. However, these studies have applied a correlational approach. This paper revisits the external effects of HVTOLs, exploring the case of a 225 kV line connecting two medium-size cities (Saint-Privat-d'Allier to Saint-Etienne) in France. We take advantage of the public disclosure in 2009 of undergrounding 8 km out of a total of 87 km lines as a result of a network upgrade project, to develop a difference-in-difference specification of a hedonic regression model, by comparing house sale prices at different distances from existing pylons, before and after the announcement of the decision to upgrade the line. We show that undergrounding was accompanied by an increase of about 38% in the price of treated houses located within 200 m of old pylons. The implied environmental costs of proximity to high-voltage pylons are substantial and their reduction is internalized into house prices as soon as the decision to go underground is announced.