Efficient Pricing Research Articles

Legal systems and stock market efficiency: an empirical analysis of stock indices around the world

AbstractWe examine whether the differences in the legal origins of countries (Common Law versus Civil Law) can explain the variations in the price efficiencies of the stock markets of different countries. Based on multifractal detrended fluctuation analysis of the daily stock indices of 34 countries over 21 years, we find that the stock price indices in Common Law origin countries show greater price efficiency than the stock price indices in Civil Law countries. These results provide additional evidence that the legal origins of countries affect their economic activities and outcomes.

Innovative technology for ammonia abatement from livestock buildings using advanced oxidation processes

The feasibility of using advanced oxidation processes (AOPs) for abatement of ammonia from livestock buildings was examined in a series of pilot plant experiments. In this study, all the experiments were conducted in a two-step unit containing a dry photolytic reactor (UV185/UV254/O3) and a photochemical scrubber (UV254/H2O2). The unit efficiency was tested for two initial ammonia concentrations (20 and 35 ppmv) and three different air flows (150, 300 and 450 m3·h−1). While the first step removes mainly organic pollutants that are often present together with ammonia in the air and ammonia only partially, the second step removes around 90% of ammonia emissions even at the highest flow rate of 450 m3·h−1. Absorbed ammonia in the aqueous phase can be effectively removed without adjusting the pH (i.e. without the addition of other additives) using UV and ozone. Complete removal of ammonia was achieved after 15 h of irradiation. In order to assess the price efficiency of the suggested technology and to be able to compare it with other methods the figures-of-merit were determined. The price needed for lowering ammonia emission by one order of magnitude is 0.002 € per cubic meter of treated air at the highest flow rate of 450 m3·h−1 and for initial ammonia concentrations of 20 ppmv. These findings demonstrate that AOPs are a promising method for ammonia abatement from livestock buildings which are rarely using any waste air treatment method.

Institutional investor inattention bias in auctioned IPOs

We investigate a unique dataset that includes detailed bidding information of 783 Chinese IPOs. First, we find that institutional investors who participate in multiple IPOs on a single day suffer from limited attention and submit less precise bids. Second, we form several proxies for investor attention capacity and show that investors with larger attention capacities are less affected by the inattention bias. Furthermore, we show that investors are more affected by the inattention bias in IPOs that are more difficult to price. Moreover, we find that the allocation rule change from pro-rata to lottery leads to a reduction in investors’ multiple participations, and improves their bidding precision. Third, we show that investors are more likely to submit lower bids when participating in multiple IPOs. Consequently, the investors affected by the inattention bias are allocated fewer shares and earn less profit. Finally, we find that aggregate investor inattention at the IPO level significantly reduces the IPO's pricing efficiency.

System value and utilization performance analysis of grid-integrated energy storage technologies in Japan

Deploying utility-scale storage systems is expected to play a critical role in improving energy flexibility and economic performance considering rising variable renewable energy penetration. However, existing studies take the impacts of storage duration times and changes in the real-world electricity market into account less. This study develops a framework to evaluate and compare the opportunity value of different storage technologies as a price taker aiming at maximizing the arbitrage profit. Firstly, long-term operational data of real-world grids were collected, and results indicate that rising penetration of renewable energy generation increases the inter-annual volatility and decreases the average value of spot prices. Comparative results verified that the storage roundtrip efficiency, duration time and variation of spot prices impacted the storage arbitrage profits and utilization rates significantly. The rising volatility of spot prices is largely driven by the rapid expansion of renewable energy generation, adds more opportunity value to the storage system dispatch process, and amplifies the influence of storage duration. The results present the potentiality of deploying power to hydrogen as long-duration storage to deliver economic benefits by exploring the variations of the spot prices. Overall, a full understanding of how the role of storage systems changes provides insight into options for storage planning of renewable-dominated electricity systems.

Correction: Cross-listing and price efficiency: An institutional explanation

Correction: Cross-listing and price efficiency: An institutional explanation

Heterostructured mixed metal oxide electrocatalyst for the hydrogen evolution reaction.

The hydrogen evolution reaction (HER) has attracted considerable attention lately because of the high energy density and environmental friendliness of hydrogen energy. However, lack of efficient electrocatalysts and high price hinder its wide application. Compared to a single-phase metal oxide catalyst, mixed metal oxide (MMO) electrocatalysts emerge as a potential HER catalyst, especially providing heterostructured interfaces that can efficiently overcome the activation barrier for the hydrogen evolution reaction. In this mini-review, several design strategies for the synergistic effect of the MMO catalyst on the HER are summarized. In particular, metal oxide/metal oxide and metal/metal oxide interfaces are explained with fundamental mechanistic insights. Finally, existing challenges and future perspectives for the HER are discussed.

Decomposing Economic Efficiency into Technical and Allocative Components: An Essential Property

We introduce two desirable properties concerning the allocative efficiency term in the decomposition of economic efficiency. Since Farrell, economic efficiency, defined in terms of the cost, revenue, profitability, or profit functions, is decomposed into a technical efficiency measure and allocative efficiency. Resorting to duality theory, allocative efficiency is calculated as a residual. In this framework, we show that this residual is numerically inconsistent for several economic efficiency decompositions: those based on the Russell Efficiency Measures, the Slack-Based Measure and the Weighted Additive Measures. It should be expected that a technical inefficient firm, if projected to the optimal economic benchmark, e.g., that maximizing profit, should be allocative efficient, yet we show that the above decompositions may signal that it is allocative inefficient. Our first property, called ‘essential,’ demands that economic efficiency decompositions satisfy the above criterion. We also extend this property by requiring that the allocative efficiency of a technically inefficient firm, evaluated at the projected benchmark on the production frontier, coincides with the allocative efficiency of the benchmark itself. Regarding this extension of the property, we show that, besides the measures mentioned above, the Directional Distance Function and the Hölder Distance Function fail in general to comply with it. However, we also prove that, thanks to the flexibility of these two approaches in choosing a common directional vector for all the assessed firms or a specific Hölder norm, these measures may satisfy the extended essential property. We conclude that unless both properties are fulfilled, the (residual) allocative component of many previously published decompositions cannot be correctly interpreted as price inefficiency.

Myopic fiscal objectives and long-Run monetary efficiency

Is the pursuit of myopic fiscal objectives, such as short-run redistribution or public spending, a threat to long-run monetary efficiency? We answer this question in the context of a textbook overlapping generations model where we introduce a sequence of one-period fiscal authorities that can tax endowments and trade money. Each authority is myopic in that it cares only about current agents’ utility and its own consumption, without any concern about the future. Nonetheless, we show that the sequence of fiscally-backed money purchases that maximize the current authority’s objective also selects a unique equilibrium – one in which money is traded at the efficient intertemporal price – as a by-product. In fact, myopic redistribution policies ensure equality in marginal utilities making up for incomplete markets, without interfering with the efficiency of private intertemporal choices. Multiplicity and sub-optimality emerge as fiscal capacity is bounded, inducing authorities to use money trades to generate resources for public consumption.

Measuring price efficiency in petroleum markets: New insights using various long-range dependence techniques

This paper empirically measures pricing efficiency in the petroleum markets using a battery of long-range dependence techniques. We analyse the volatility (absolute returns) of fourteen petroleum products using daily prices from January 1990 to April 2020. We use bootstrapping techniques to estimate the confidence intervals of the long-range dependence parameters. Overall results obtained using CMA-MAF, CMA-MSF, GPH and periodogram techniques suggest that there is no evidence of long-range dependence in absolute returns of petroleum markets prices indices at least at the 10% level of significance. For robustness purposes, findings from the rolling windows estimates reveal that the results are not affected by the normality assumption under different rolling window sizes. Furthermore, we find that Gas oil, Biofuel and Heating oil are the most correctly priced while Crude Oil Dubai emerging is the least efficient. Comparing the efficiency index of the all six crude oil returns in our sample, WTI oil was seen to be less efficient than Brent crude oil. In all, our work uncovers crucial implications for investors and policymakers.

Electric Vehicle Fleets: Scalable Route and Recharge Scheduling Through Column Generation

The rise of battery-powered vehicles has led to many new technical and methodological hurdles. Among these, the efficient planning of an electric fleet to fulfill passenger transportation requests still represents a major challenge. This is because of the specific constraints of electric vehicles, bound by their battery autonomy and necessity of recharge planning, and the large scale of the operations, which challenges existing optimization algorithms. The purpose of this paper is to introduce a scalable column generation approach for routing and scheduling in this context. Our algorithm relies on four main ingredients: (i) a multigraph reformulation of the problem based on a characterization of nondominated charging arcs, (ii) an efficient bidirectional pricing algorithm using tight backward bounds, (iii) sparsification approaches permitting to decrease the size of the subjacent graphs dramatically, and (iv) a diving heuristic, which locates near-optimal solutions in a fraction of the time needed for a complete branch-and-price. Through extensive computational experiments, we demonstrate that our approach significantly outperforms previous algorithms for this setting, leading to accurate solutions for problems counting several hundreds of requests. Funding: This work was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico [Grants 08528/2018-2 and 315361/2020-4], Coordenação de Aperfeiçoamento de Pessoal de Nível Superior [Finance Code 001], and Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro [Grants E-26/010.002232/2019 and E-26/202.790/2019]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.1199 .

The Impact of COVID-19 on the Performance of Islamic Banks in the MENA Region

Purpose — This research explores the impact of COVID-19 on the financial return of Islamic banks (IBs) in nine countries located in the Middle East and North Africa (MENA) region. It also examines the determinants of IBs’ profitability during stable and uncertain periods, namely before and during the development of coronavirus. Design/Methodology/Approach — The financial data of this paper were collected from annual reports of IBs and the Orbis Bank Focus database over four years: 2018, 2019, 2020 and 2021. Descriptive statistics were used to examine the progress of IBs’ performance from 2018 to 2021. The t-test was employed in this research paper to compare the financial proxies of IBs, and the multiple regression model was used to assess the determinants of IBs’ performance before and during the development of coronavirus in MENA countries. Findings — The empirical findings show that IBs in MENA countries were dramatically influenced by the development of COVID-19. All financial proxies of IBs like financial return and liquidity experienced a sharp drop during the lockdown period. The empirical findings also indicate that the financial situation of IBs in 2021 became close to the pre-pandemic situation but was nonetheless below the banks’ performance prior to the pandemic period (2018-2019). Finally, the results show that the determinants of IBs’ return were not the same during stable and uncertain periods. During the COVID-19 period, credit risk, managerial efficiency and oil price were the significant determinants of IBs’ profitability. Before the development of COVID-19, besides the elements of credit risk, managerial efficiency and oil price, liquidity risk and bank size were also found to have an influence on IBs’ profitability. Originality/Value — The research offers new insights to top managers in IBs to increase the institutions’ financial return and mitigate the negative shock of crises by managing several factors such as credit risk and managerial efficiency. ErratumArticle classification: Erratum from: ISRA International Journal of Islamic Finance Vol. 15 No. 1 (2023)Publisher: ISRA Research Management Centre, INCEIF University El-Chaarani, H. (2023), ‘The Impact of COVID-19 on the Performance of Islamic Banks in the MENA Region’, ISRA International Journal of Islamic Finance, Vol. 15 No. 1, pp. 109–129. https://doi.org/10.55188/ijif.v15i1.488. It has been brought to our attention by the author that minor mistakes have been left out in the author’s details which appear on pages 109 and 129 of the article. The author would like to make the following corrections within his affiliation: The author’s affiliation on page 109 should instead read: ‘Beirut Arab University, Tripoli, Lebanon’. Under ABOUT THE AUTHOR on page 129, the author’s details should instead read: He is the Director of the Faculty of Business Administrationat Beirut Arab University, Tripoli, Lebanon. These have been corrected in the online version of the paper.Citation:(2023), ‘Erratum’, ISRA International Journal of Islamic Finance, Vol. 15 No. 1, https://doi.org/10.55188/ijif.v15i1.488

Economic policy uncertainty, investor attention and post-earnings announcement drift

How the market incorporates information into stock price is a core issue in finance. This study focuses on the impact of economic policy uncertainty (EPU) on the stock prices information efficiency of China's A-share market and underlying role of investors' attention allocation mechanism. This study analyzes the information efficiency of stock prices using the sensitivity of stock cumulative abnormal return to earnings information across different windows following earnings announcement. Based on the earnings announcement events of listed companies in China's A-share market, this study presents an empirical study of the aforementioned issues using event study and regression analysis methods. The following results are seen: (1) EPU aggravates the underreaction of stock price earnings information and the post-earnings announcement drift in the A-share market. (2) Under highly uncertain economic policies, investors show a limited attention allocation pattern of devoting increasing attention to macroeconomic policies and decreasing attention to earnings information, which leads to a decrease in the information efficiency of stock price. This study also analyzes the heterogeneity of the influence of EPU on stock price information efficiency using the institutional shareholding ratio. The results show that increasing institutional shareholding does not reduce the adverse effects of EPU on the information efficiency of stock prices. This study not only provides empirical evidence for Brunnermeier, Sockin, and Xiong (2022) and rational inattention theory, but also reveals that institutional investors show similar behavioral characteristics to retail investors in China's stock market. The results of this study have policy significance for improving the information efficiency of stock market.

Forecasting Daily Stock Volatility: A Comparison between GARCH and Recurrent Neuro-networks

Forecasting the volatility of financial derivatives and securities returns has always been the core of financial research. Accurate volatility forecast is integral to financial risk management, which is vital for investors and supervision authorities. Traditional time series models (e.g., ARCH and GARCH models) have been famous tools for volatility forecasting. However, those models cannot capture non-linear correlations, and prediction capability is unsatisfactory. In this paper, we use multifactorial deep learning algorithms RNN, LTSM, and GRU with sentiment data to predict the future volatility of Apple (AAPL), then compare the accuracy of prediction with the GARCH model. According to the analysis, the prediction accuracy of LSTM and GRU significantly improved compared with the GARCH model. These results shed light on guiding further exploration of stock volatility prediction using deep learning algorithms. Besides, it advises investors to choose efficient stock price volatility forecasting and risk management tools.

Evaluation of the Impact of Groundwater Management Policies Under Climate and Economic Changes in Tunisia

This study develops a hydro-economic model for the coastal aquifer Mahdia Ksour Essef in Tunisia in order to analyze how external shocks (climate change, energy price increase) and management policies can affect groundwater sustainability during the coming decades. Twenty-one scenarios covering three management policies (free market, partial cooperation, and full cooperation policy) under various potential climate and economic changes are evaluated. The results of scenario simulations show the potential impact of energy soaring prices and climate change on the aquifer’s water table level, groundwater extractions, cropland areas, and farmers’ benefits under each policy option in the future. They also show that the best scenario to address the effects of climate change would need to take into account environmental externalities and efficient energy prices. The findings of this study are very important in the context of climate change and uncertain global energy markets and provide feasible alternatives to preserve the regional economy and aquifer sustainability.

Price efficiency of the foreign exchange rates of BRICS countries: A comparative analysis

In this paper, we analyze BRICS countries’ long-term exchange rate market efficiency. Our analysis, using multifractal detrended fluctuation analysis (MFDFA) for the 2009–2021 period, shows considerable differences in the exchange rate efficiency of BRICS countries, with South Africa the most efficient and China the least efficient. Based on daily exchange rates, our analysis shows that after a country shifts to a flexible exchange rate regime, the price efficiency of its currency improves, but not immediately. All the BRICS countries show improvements in market efficiency over the 13-year period of our study. The adaptive market hypothesis supports our finding of efficiency improvements over time more than the efficient market hypothesis does.

AHP 기법을 활용한 새벽 배송 서비스 운영의 성과 요인 분석

This study analyzes the performance factors from the consumer's point of view to strengthen the competitiveness of early-morning delivery companies. Through literature review and case analyses, the performance factors of early morning delivery services are derived in terms of product and service. The performance factors in the product aspect are product excellence, price efficiency, and product diversity, and the service aspect performance factors are after-sales service, product packaging, the company's eco-friendly image, and the company's social contribution image. Based on the consumer survey, we conducted an AHP analysis to analyze the importance, weight, and priorities of early morning delivery service performance factors. The analysis found that maintaining and improving the basic production factors is more important than improving the service factors. Through gender analysis, we reveal that women, the main consumers, consider affordable prices more important than high-quality products. In addition, customers under the age of thirty, who will be major future customers, consider improving after-sales service as the most crucial factor in choosing an early-morning delivery company. Therefore, it is necessary to have a fast and convenient after-sales service process.

Forecasting Stock Prices on the Basis of Technical Analysis in the Industrial Sectors of the UK Stock Market

This study aims to evaluate, critically and rigorously the weak-form market efficiency and forecasting power of technical analysis in different industries in the London Stock Exchange. Weekly data were collected from the FTSE-all share index, FTSE-350 general industrial index and twenty companies of four different industries, for the period between 1997 and 2017. Bai-Perron’s multiple breaks test was applied to diagnose plain data period for the purpose of forecasting. The statistical inference was made from the application of the runs test, variance ratio tests, Ljung-Box’s test and ADF-unit root test that the market is not weak-form efficient and stock prices are predictable. This study extends the current literature by considering the existence of weak-form inefficiency in different industrial sectors. The findings do not support for weak-form efficiency over the periods tested from the application of the ARIMA and GARCH (1, 1) models and double and triple exponential smoothing techniques

Designing an Insurance Pricing Model using a Mathematical Approach

Purpose: Every time drivers take to the road, and with each mile that they drive, exposes themselves and others to the risk of an accident. Insurance premiums are only weakly linked to mileage, however, and have lump-sum characteristics largely. The result is too much driving, and too many accidents. The purpose of carrying out this research was to determine a model for calculating the premiums for Pay-As-You-Drive in automobile insurances. Methodology: To price Pay-As-You-Drvie auto insurance, we define a discounted collective risk model while the total number of claim has non-homogeneous Poisson distribution. By applying non-homogeneous Poisson distribution we can enter the mileage to the discounted collective risk model to the premiums for Pay-As-You-Drive in Automobile insurances. We apply the double Double Stochastic Poisson Process for modeling the DCRM. The Double Stochastic Poisson Process provides flexibility by letting the intensity not only depend on time but also by allowing it to be a stochastic process. Findings: By applying the doubly stochastic Poisson process to review the driver’s mileage in the model, the study found the distribution of discounted collective risk model and present the expected value of total loss for calculating the premiums. Recommendation: The current auto insurance pricing systems are inequitable because low-mileage drivers subsidize insurance costs for high-mileage drivers, and low-income people drive fewer miles on average. The study recommends a more efficient pricing systems model to find a good model for calculating the fair auto insurance premium. Keywords: Cox process, martingales, aggregate risk models, PAYD, actuarial mathematics.

National team intervention and price efficiency differentiation under the impact of COVID-19

ABSTRACT This paper examines how the ‘national team’, a direct government investment policy, influences the price efficiency of listed companies in the Shanghai Stock Index (SSE). We find that stocks directly invested in by the national team show greater price efficiency than stocks without direct bailout. We also analyse the impact of the COVID-19 pandemic on this price efficiency differentiation. The data period is divided into two sub-periods, and the results show that the price efficiency of stocks decreased after COVID-19. The reduction in price efficiency is more notable for stocks with direct government investment; the difference observed under national team investment in price efficiency is clearly reduced. Increased pessimistic investor expectations due to the pandemic could explain these changes. Our study provides novel evidence for the policy evaluation of national team intervention and a more detailed explanation about the decrease in financial market efficiency in the post-COVID-19 era.

The impact of the El Niño phenomenon on electricity prices in hydrologic‐based production systems: A switching regime semi‐nonparametric approach

AbstractElectricity production in highly hydrological‐dependent systems is determined by different weather phenomena, which strongly impact spot prices. To account for such stylized facts, we propose a stochastic process with a mean reversion and switching regime component to represent the dynamics of the spot price. The short‐term movements are represented by semi‐nonparametric (SNP) distributions, in contrast to previous studies that traditionally assume Gaussian processes. We consider the Colombian electricity market as a study case, in which 68% of its electrical generation comes from water resources, and the El Niño phenomenon represents a critical source of risk for maintaining long‐term supply, sustainability of investments, and efficiency of prices. We show that under scarcity seasons, the spot price mean, variance, and some superior‐order moments of electricity price distribution increase, as does the risk level of the system. In particular, the switching regime model with SNP distributions for the random components outperforms traditional models, leading to accurate estimates and simulations, thus being a helpful tool for resource planning, risk management, and policy‐makers for electricity markets with high climatic dependency.