Improve Market Efficiency Research Articles

МЕТОДИКА ОЦЕНКИ КАЧЕСТВА ОКАЗАНИЯ ГОСУДАРСТВЕННЫХ УСЛУГ СЛУЖБОЙ ЗАНЯТОСТИ НАСЕЛЕНИЯ (НА ПРИМЕРЕ ОМСКОЙ ОБЛАСТИ)

The relevance of the study is caused by the necessity to reorganize the activity of regional employment centers within the implementation of measures of the federal project “The employment support and labor market efficiency improvement to ensure better performance”. The authors study the up-to-date sectors of work of Government Employment Services. The paper presents a model of the quality management system of government authorities developed based on the process approach and the PDCA cycle. This model offers customer satisfaction monitoring to assess the degree of meeting the specified requirements. The authors analyzed the key regulatory documents governing the process of rendering services, developed the technique to evaluate the quality of public service in promoting self-employment to unemployed citizens. The methodology includes the expert analysis of administrative procedures of rendering services to demander; the service quality assessment using a mystery shopper; service receiver survey; identifying the integral index of service conformance with the consumer expectations to assess the consumer perception. The authors analyzed the administrative procedure of public service in promoting self-employment to unemployed citizens. The study identified the reasons for service consumer demotivation, including the difficulty of perception of the procedure text, the plenty of bureaucratic terms, the lack of information on the additional services, and possibilities that can be received by an unemployed citizen. To evaluate the conformance of service quality with consumer expectations, the authors applied the well-known SERVQUAL methodology used in marketing research. The paper shows an example of a calculation of the integral index of service rendering conformance. The practical significance of the quality assessment methodology is in the possibility to carry out a complex evaluation of the work of regional employment centers, consumer satisfaction, and, finally, in the creation of the consumer-attractive services.

Market in Financial Instruments Directive (MiFID), stock price informativeness and liquidity

Abstract The paper examines the impact of MiFID on stock price informativeness and liquidity in 28 EU countries. We find that post-MiFID the stock prices reflect greater firm specific information and the market becomes more liquid. Consistent with the ‘Catch-up Hypothesis’ our evidence shows that the impact of MiFID in terms of price informativeness is greater for countries that have weaker quality of regulation. We find that regulation with enforcement improves market efficiency. Our results are robust with respect to the choice of price informativeness and liquidity proxies as well as the control sample.

Government Intervention in Malaysian Housing Market

Housing is a basic need for society to improve their quality of life and as important assets for the country’s economic. Malaysian Housing Policy has focused and concentrated to provide adequate housing supply for the targeted group, especially for the bottom 40% income earner. The urbanisation process creates the socio-economic changes has led to the increases in demand for housing. The previous study stated that there was a discrepancy between demand and supply in housing market resulted from rising trend in house price compared to the household income, thus leading to market imperfection. Thus, this paper attempted to explore the government intervention in the housing market. In a nutshell, government intervention is necessary to correct the market imperfection through policies and project implementations. There is a need to improve market efficiency and review the delivery of both supply and demand in the housing market.

Dynamic Information Aggregation and Welfare

In a market with a safe rate and a risky asset that pays a continuous dividend stream depending on a latent state of the economy, several agents make consumption and investment decisions based on public information — prices and dividends — and private signals. We obtain the equilibrium in closed form, assuming that each investor has constant absolute risk aversion. Equilibrium prices do not reveal all the private signals, but lead to the same estimate of the state of the economy that one would hypothetically obtain from the knowledge of all private signals. Accurate information leads to low volatility, ostensibly improving market efficiency. But it also reduces each agent's consumption through a decrease in the price of risk. Overall, the equilibrium reaches perfect informational efficiency at the expense of agents' welfare.

Does a ‘financial transaction tax’ drive out information mirages? An experimental analysis

Motivated by the debate over the economic implications of financial transaction taxes, the present study involved a thorough investigation of the impact of such taxes on a financial market of the type described by Camerer and Weigelt (J Bus 64:463–493, 1991), whereby noise traders are unaware of whether privileged information is fluctuating in the market. Two treatment conditions were opposed to a baseline condition in which no tax was levied. The two treatment conditions imposed a transaction tax equal to 0.5% and 1% of each transaction’s market value, respectively. The findings show that: (1) the introduction of a tax did not affect the occurrence of a mirage, (2) the introduction of a tax did not improve market efficiency and (3) the introduction of a tax did not reduce the number of transactions.

Near-Optimal Scheduling in Day-Ahead Markets: Pricing Models and Payment Redistribution Bounds

Near-optimal unit commitment (UC) scheduling is a practical reality in wholesale electricity markets. This paper revisits previous work that has found that minor differences in cost among near-optimal schedules can result in a large redistribution of market payments (i.e., changes in generator profits and consumer surplus). It has been believed that this instability is unavoidable, but previous studies have only calculated prices using what we call the Restricted pricing model. This paper compares previous results to three additional models that are based on integer relaxation, and which we call the Partial, Tight, and Loose Dispatchable pricing models. Results are presented for a suite of test cases, including four ISO-scale cases. Similar to previous findings, the Restricted and Partial Dispatchable models both result in large payment redistributions among alternative solutions. In contrast, theoretical and experimental results for the Tight and Loose Dispatchable models show that pricing models with unconditional integer relaxation will have bounded payment redistributions, and, further, this bound can become quite small by tightening the UC problem's convex relaxation. In the presence of market power, stable financial outcomes may improve market efficiency by reducing incentives to bid strategically.

Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study

This letter investigates the dynamic relationship between market efficiency, liquidity, and multifractality of Bitcoin. We find that before 2013 liquidity is low and the Hurst exponent is less than 0.5, indicating that the Bitcoin time series is anti-persistent. After 2013, as liquidity increased, the Hurst exponent rose to approximately 0.5, improving market efficiency. For several periods, however, the Hurst exponent was found to be significantly less than 0.5, making the time series anti-persistent during those periods. We also investigate the multifractal degree of the Bitcoin time series using the generalized Hurst exponent and find that the multifractal degree is related to market efficiency in a non-linear manner.

When Anomalies Are Publicized Broadly, Do Institutions Trade Accordingly?

This paper studies whether institutional investors trade on 14 well documented stock market anomalies. We show that there is an increase in anomaly-based trading when information about the anomalies is readily available through academic publications and the release of necessary accounting data. This finding is more pronounced among hedge funds and institutions with high turnover, that is, the subset of investors who likely have the abilities and incentives to act on the anomalies. We directly relate the increase in trading to the observed decay in post-publication anomaly returns. Our results support the role of institutional investors in the arbitrage process and in improving market efficiency.This paper was accepted by Renée Adams, finance.

A Unified Approach to Pricing Under Nonconvexity

Nonconvexity in electricity markets creates difficulties in the pricing of electricity today. Equilibrium prices often do not exist, and some forms of side payments are required to provide revenue adequacy for cleared offers and bids in markets. To improve market efficiency and transparency, academia and industry have proposed different pricing schemes, each of that emphasizes only a certain aspect of the desired price. In this paper, we summarize the existing pricing objectives and propose a unified model for pricing under nonconvexity. The tradeoff among competing objectives can be modeled. A specific example of the unified nonconvexity pricing model is presented, which can be regarded as a general representation of the convex hull pricing method and the commonly adopted locational marginal pricing scheme. The primal formulation of this model is derived. The economic insight of the convex hull pricing method is illustrated based on this model. An extreme-point-based solution method is presented. The proposed pricing model establishes a framework for analyzing the tradeoff among different objectives for pricing under nonconvexity and provides an opportunity to construct more economically justifiable prices through a modification of the objective function and constraints of the proposed pricing model.

The influence of social network structure on stock price disclosure

We propose a new heterogeneous agent model of a dynamic continuous double auction stock market embedding multiple social network to investigate the influence of different network structures on stock price disclosure. According to the four network formation algorithms (preferential connection, random connection, weighted random connection and random reconnection), we construct scale-free random network, weighted random network and small-world network respectively. We find that the small-world characteristic of social network speed up the diffusion of private information in market, and then improve market efficiency and promote price discovery. Furthermore, to some extent, simulation results indicate that the network structure can explain the occurrence of anomalies like underreaction and overreaction in the financial market.

Indirect Customer-to-Customer Energy Trading With Reinforcement Learning

In this paper, we explore the role of emerging energy brokers (middlemen) in a localized event-driven market (LEM) at the distribution level for facilitating indirect customer-to-customer energy trading. This proposed LEM does not aim to replace any existing energy service or become the best market model; but instead to diversify the energy ecosystem at the edge of distribution networks. In light of this philosophy, the market mechanism will provide additional options for customers and prosumers who have the willingness to directly participate in the retail electricity market occasionally, on top of using existing utility services. It also helps in improving market efficiency and encouraging local-level power balance, while taking into account the characteristics of customers’ behavior. The energy trading process will be built as a Markov decision process with some reinforcement learning and data-driven methods applied. Some economic concepts, like search friction , related to this kind of typical search cost involved market model are also discussed.

Visible and Invisible Forces. What Drives the Intensity of Trading in the European Carbon Market?

This study models the trading intensity in European Allowances (EUA) futures contracts, in the European Climate Exchange (ECX) using various specifications and investigates the forecasting ability of observable versus unobservable factors. This set up tests empirically the impact of the evolving market structure through regulatory updates and the contribution of the different market participants to the intensity of trading in the European Carbon market. The findings suggest that observable market characteristics capture better the dynamics of trading intensity than their latent counterparts, which implies that regulatory changes that enhance transparency would also improve market efficiency.

The social-political roles of NGOs: a study on a triadic business network

PurposeThis study examines the institutional setting and decision-making structures among key industry actors in the Malaysian housing industry, using the IMP network approach and institutional theory as theoretical lenses. The purpose of this study is to uncover the role of NGOs, housing developers and the government at a collective level within a highly regulated housing market. This study uses “relationships” as the unit of analysis, focusing on triadic interactions of NGOs, housing developers and the government.Design/methodology/approachThis study applies the qualitative case-study-research approach, using 20 in-depth interviews from the purposefully selected industry actors within the housing market, online observations and documents.FindingsThe findings suggest that NGOs play an influential role in housing-industry interactions and outcomes. In particular, the Real Estate and Housing Developers Association can influence the members’ decisions through supportive and disruptive actions.Originality/valueThis study contributes to our understanding of how NGOs interact with their regulator and housing developers and how these three parties co-evolve and respond to institutional demands in a housing market that is bound by a highly restricted housing policy. By understanding how actors interact within a network and how it affects each other’s decision, it may assist policymakers in formulating policies that can improve market efficiency. It also aids businesses in formulating their collective strategies.

Risk-averse market clearing for coupled electricity, natural gas and district heating system

Multiple energy carriers can be coupled as an Integrated Energy System (IES) through interconnection technologies. Unexpected risks will be transferred with the growing coupling of energy systems, mainly stemming from the uncertainties in different energy sectors. It is imperative to coordinate the operation of different energy systems to improve energy efficiency and ensure energy security. With the close integration of different energy systems, it is necessary to couple these different energy markets to achieve the holistic energy supply economy. On the other hand, uncertainties in the energy systems will bring the financial risk for the operator of IES. A risk-averse stochastic market clearing model for the IES is proposed to study the operating strategy aiming at minimizing the operation cost. While the financial risk imposed by the wind power uncertainties is restricted to a predefined level. Simulations results are provided to verify that the proposed model can improve market efficiency and handle the trade-off between cost and risk.

Consumer Savings, Price, and Emissions Impacts of Increasing Demand Response in the Midcontinent Electricity Market

This paper estimates consumer savings, CO2 emissions reductions, and price effects from increasing demand response (DR) dispatch in the Midcontinent Independent System Operator (MISO) electricity market. To quantify market effects, we develop a dynamic supply and demand model to explore a range of DR deployment scenarios. The study is motivated by the existence of regulatory and market rule barriers to market-based deployment of DR resources in the MISO region. We show annual consumer savings from increased market-based DR can vary from $1.3 million to $17.6 million under typical peak operating conditions, depending on the amount of DR resources available for market dispatch and the frequency of deployment. Consumer savings and other market effects increase exponentially during atypical periods with tight supply and high prices. Additionally, we find that DR deployment often reduces CO2 emissions, but the magnitude of emissions reductions varies depending on the emissions content of marginal generation at the time and location of deployment. The results of this study suggest regulators and other stakeholders should focus policy efforts to reducing regulatory barriers to DR deployment in wholesale markets, particularly in locations that experience high price spikes, to improve market efficiency and achieve cost savings for consumers.

Mobile Phones and Mozambique Traders: What is the Size of Reduced Search Costs and Who Benefits?

We investigate to what extent the roll-out of the mobile phone network in Mozambique reduced transport costs and search costs, and thereby decreased spatial price dispersion and improved market efficiency. Estimations are based on data of transport costs of maize grain and maize market prices. The mobile phone rollout explains a 10%-13% reduction in maize price dispersion. Around half of this reduction is associated with search costs related to transport, the other half with other search costs, for example for the collection of maize in source markets. Search costs are substantial and also a substantial component of total transport costs. Benefits of increased market efficiency are biased towards consumer markets. Results are robust for non-random rollout of the mobile phone network and several other threats.

The Impact of Adverse Selection on Stock Exchange Specialists’ Price Quotation Strategy

This paper focuses on the activity of the specialists – one of the key participants in stock exchange trading. We attempt to model the price quotations of specialists in a modelling framework where some of the parties involved in the transactions may be informed, while others are uninformed “liquidity traders”. It is in this adverse selection modelling framework that, relying on the technique of Monte Carlo simulation, we seek an answer to the following research questions: how does adverse selection impact the price quotation of specialists; to what extent are prices and logreturns influenced by uncertainty; to what degree of accuracy can specialists determine the proportion of informed traders and liquidity traders from trading volumes? Our model confirmed that as soon as uncertainty subsided in the simulated market, the number of transactions, wealth and the stock portfolio started to grow, while price fluctuations began to decline and the standard deviation and the distribution of logreturns edged closer and closer to a normal distribution, which points to improving market efficiency.

How Elastic Demand Affects Bidding Strategy in Electricity Market: An Auction Approach

The deepening of electricity reform results in increasingly frequent auctions and the surge of generators, making it difficult to analyze generators’ behaviors. With the difficulties to find analytical market equilibriums, approximate equilibriums were obtained instead in previous studies by market simulations, where in some cases the results are strictly bound to the initial estimations and the results are chaotic. In this paper, a multi-unit power bidding model is proposed to reveal the bidding mechanism under clearing pricing rules by employing an auction approach, for which initial estimations are non-essential. Normalized bidding price is introduced to construct generators’ price-related bidding strategy. Nash equilibriums are derived depending on the marginal cost and the winning probability which are computed from bidding quantity, transmission cost and demand distribution. Furthermore, we propose a comparative analysis to explore the impact of uncertain elastic demand on the performance of the electricity market. The result indicates that, there exists market power among generators, which lead to social welfare decreases even under competitive conditions but elastic demand is an effective way to restrain generators’ market power. The feasibility of the models is verified by a case study. Our work provides decision support for generators and a direction for improving market efficiency.

How does product market competition affect corporate takeover in an emerging economy?

This study investigates the effect of product market competition as an external control mechanism on the operation and efficiency of corporate takeovers in an emerging economy. Empirically, we find that firms in more competitive product markets are more likely to experience a change in control than those in less competitive markets after controlling for other firm and industry characteristics. Further, the positive effect of a change in control on shareholder wealth is observed in more competitive product markets but disappears in less competitive markets. The results imply that product market competition improves market efficiency for corporate control in an emerging economy with less developed capital markets and weak investor protection, supporting the complementary Hypothesis between product market competition and corporate takeover.

Investigating the impacts of price‐taking and price‐making energy storage in electricity markets through an equilibrium programming model

The envisaged decarbonisation of electricity systems has attracted significant interest around the role and value of energy storage systems (ESSs). In the deregulated electricity market, there is a need to investigate the complex impacts of ESSs, considering the potential exercise of market power by strategic players. This study aims at comprehensively analysing the impacts of both price-taking and price-making storage behaviours on energy market efficiency, corresponding to potential settings with small and large storage players, respectively. In order to achieve this and in contrast to previous papers, this work develops a multi-period equilibrium programming market model to determine market equilibrium stemming from the interactions of independent strategic producers and ESSs, while capturing the time-coupling operational constraints of ESSs as well as network constraints. The results of case studies on a test market capturing the general conditions of the GB electricity system demonstrate that the introduction of ESSs mitigates market power exercise and improves market efficiency, with this beneficial impact being higher when ESSs act as price takers. When the electricity network is congested, the location of ESSs also affects the market outcome, with their beneficial impact on market efficiency being higher when they are located in higher-priced areas.