Journal articles on the topic 'Efficient market theory Econometric models'
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1
Gilbert, Richard J. "The Role of Potential Competition in Industrial Organization." Journal of Economic Perspectives 3, no. 3 (August 1, 1989): 107–27. http://dx.doi.org/10.1257/jep.3.3.107.
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Potential competition is important as a mechanism to control market power. I assess the strengths and limitations of alternative theories of potential competition by examining the available theoretical, empirical and institutional knowledge. I consider four major schools of thought: the traditional model of limit pricing, dynamic limit pricing, the theory of contestable markets, and the market efficiency model. Traditional limit pricing models rest on the assumption that firms respond to entry but are able to earn persistent profits when the structural characteristics of markets make entry difficult. Dynamic limit pricing is similar, but emphasizes that markets can only be temporarily protected from entry. Contestability theory, in its pure form, asserts that potential competition is as effective as actual competition in controlling market performance. The efficient markets hypothesis, broadly interpreted, states that markets are workably competitive and that the market structure reflects differential efficiency, not strategic behavior.
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Landais, Camille, Pascal Michaillat, and Emmanuel Saez. "A Macroeconomic Approach to Optimal Unemployment Insurance: Theory." American Economic Journal: Economic Policy 10, no. 2 (May 1, 2018): 152–81. http://dx.doi.org/10.1257/pol.20150088.
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This paper develops a theory of optimal unemployment insurance (UI) in matching models. The optimal UI replacement rate is the conventional Baily-Chetty replacement rate, which solves the tradeoff between insurance and job-search incentives, plus a correction term, which is positive when an increase in UI pushes the labor market tightness toward its efficient level. In matching models, most wage mechanisms do not ensure efficiency, so tightness is generally inefficient. The effect of UI on tightness depends on the model: increasing UI may raise tightness by alleviating the rat race for jobs or lower tightness by increasing wages through bargaining. (JEL E24, J22, J23, J31, J41, J64, J65)
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Murrell, Peter. "Can Neoclassical Economics Underpin the Reform of Centrally Planned Economies?" Journal of Economic Perspectives 5, no. 4 (November 1, 1991): 59–76. http://dx.doi.org/10.1257/jep.5.4.59.
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This paper addresses whether neoclassical economics can provide the intellectual underpinning for a theory of reform. I examine whether the neoclassical model satisfies an essential condition to qualify for this role: does it give us a satisfactory explanation for the vast differences in performance between capitalist and socialist economic systems? First, I focus on the theoretical arguments that have traditionally been used to examine the comparative properties of central planning and markets. I show that developments within theory over the last 20 years have substantially changed the tone of these arguments, making their message more equivocal. Next I discuss empirical evidence, but of a particular sort. Much research shows that centrally planned economies perform less well than market economies; but few studies test whether the superiority of market economies appears within empirical models derived using the framework of basic neoclassical economics. Those studies are the relevant ones for the present exercise. The central conclusion is that economists must look outside the standard models of competition, the focus on Pareto-efficient resource allocation, and the welfare theorems to build a theory of reform.
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Hasanov, Niyazi, Tokhtaposha Akbulaeva, Kamal Ahmadov, and Akram Hasanzadeh. "Application of Management Based on Mathematical Models to Solve Investment Strategy Problems." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 19 (May 6, 2022): 1130–39. http://dx.doi.org/10.37394/23207.2022.19.99.
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This article analyzes the emergence of large investment opportunities for the development of different areas of the economy in the context of political and economic changes in a competitive environment of the market economy and its relevance shows itself in the underdevelopment of risk analysis and its experimental methodology with the need to improve quality of investment activity, as well as project decision making, the contradictions between the possibility and impossibility of achieving the planned outcome and application of management based on mathematical models to solve investment strategy problems of firms and companies in this field. Application of management based on mathematical models to solve investment strategy problems, development and intensification of risk analysis theory and specification of strategy for purpose, the introduction of practice to the process of making investment decisions and efficient recommendations were developed and ways to reach the goals were designated for all the activities and measures taken in this direction. The action process is established based on the solution of made decisions and proved its compatibility with the pre-defined trajectory based on strategic opinions and occurrence time of the existing and principally indefinite, mentioned relevant events, the efficiency of application of management based on mathematical models to solve investment strategy problems. Analysis methods have been establishetod to apply management based on mathematical models to solve relevant problems in the market economy and suggestions and recommendations for its practical usage in investment-project activity have proved that economic-mathematical models are efficient tools.
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Svoboda, Milan, and Pavla Říhová. "STOCK PRICE PREDICTION USING MARKOV CHAINS ANALYSIS WITH VARYING STATE SPACE ON DATA FROM THE CZECH REPUBLIC." E+M Ekonomie a Management 24, no. 4 (December 2021): 142–55. http://dx.doi.org/10.15240/tul/001/2021-4-009.
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The article describes empirical research that deals with short-term stock price prediction. The aim of this study is to use this prediction to create successful business models. A business model that outperforms the stock market, represented by the Buy and Hold strategy, is considered to be successful. A stochastic model based on Markov chains analysis with varying state space is used for short-term stock price prediction. The varying state spate is defined based on multiples of the moving standard deviation. A total of 80 state space models were calculated for the moving standard deviation with 5-step lengths from 10 to 30 in combination with the standard deviation multiples from 0.5 to 2.0 with the step of 0.1. The efficiency of the business models was verified for 3 long-term, liquid stocks of the Czech stock market, namely the stocks of KB, CEZ, and O2 within a 14-year period – from the beginning of 2006 to the end of 2019. Business models perform best when they use a state space defined on the length of a moving standard deviation between 15 and 30 in combination with multiples of the standard deviation between 1.1 and 1.2. Business models based on these parameters outperform the passive Buy and Hold strategy. In fact, they outperform the Buy and Hold strategy for both the entire period under review and the yielded five-year periods (including transaction fees). The only exception is the five-year periods covering 2015 for O2 stocks. After the end of the uncertainty period caused by unclear intentions of the new majority stockholder, the stock price rose sharply. These results are in conflict with the efficient markets theory and suggest that in the period under review, the Czech stock market was not effective in any form.
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Ilie, Livia, and Diana Vasiu. "Capital Structure and Profitability. The Case of Companies Listed in Romania." Studies in Business and Economics 17, no. 3 (December 1, 2022): 100–112. http://dx.doi.org/10.2478/sbe-2022-0049.
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Abstract Alongside with the acquisition and the efficient use of assets (investment decision and asset management), financial managers are concerned with their financing. The capital structure of a company is of interest not only for practitioners but also for theorists so that in the last six decades important theories were developed from the capital structure irrelevance theory of Modigliani and Miller to theories that include market imperfections and incentives into the models (the static trade-off theory, the pecking order theory). In practice, financial managers take into account not only quantitative determinants, but also qualitative ones, so that the decision becomes complex and the outcome differs across industries and companies. Many empirical studies were performed in the last decades in an effort to identify the relationship between the chosen capital structure and the performance of a company. We aim to add specific results to empirical studies already performed. Our study investigates the relationship between the financial mix and the profitability of companies listed in Romania, covering the interval 2017-2021.
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Peng Chow, Yee. "Sectoral Analysis of the Determinants of Corporate Capital Structure in Malaysia." Organizations and Markets in Emerging Economies 10, no. 2 (December 31, 2019): 278–93. http://dx.doi.org/10.15388/omee.2019.10.14.
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This study investigates the determinants of corporate capital structure of various sectors in the Bursa Malaysia Main Market with the aim to establish whether the determinants of capital structure can be explained by either the trade-off or the pecking order theory. This study also examines whether there are any differences between the regressions for any two sectors or not. This study applies both the ordinary least squares (OLS) and the seemingly unrelated regression (SUR) estimators to estimate the leverage models, and subsequently determines the efficiency of each estimator. The results indicate that profitability, asset tangibility, growth opportunities, and firm size are important determinants of corporate capital structure. However, the signs of the regression coefficients suggest that the trade-o and pecking order theories are complementary. Moreover, the importance of some of these determinants differs across sectors. In most cases of the regression analyses between two sectors, the SUR estimator is found to be more efficient in explaining the determinants of capital structure among the various sectors. Hence, this study concludes that the SUR method could serve as a useful alternative methodology for capital structure research.
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Volontyr, L., and L. Mykhalchyshyna. "Organizational and economic mechanism of grain sales: information component." Scientific Messenger of LNU of Veterinary Medicine and Biotechnologies 21, no. 92 (May 11, 2019): 81–89. http://dx.doi.org/10.32718/nvlvet-e9213.
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A significant part of the output of the agro-industrial complex of Ukraine is exported. Therefore, it is desirable to determine the optimal volume of products to be implemented each month. Prices for grain are formed depending on demand and supply, costs for production and sale, market fees, etc. The analysis of the price situation on the Ukrainian cities shows a large variation. The average price of 1 kg of grain crops does not give a full opportunity to characterize the price situation of the Ukrainian grain market. There is seasonal price cyclicality: their growth with the decrease of stocks and the reduction after harvesting, when mass sales of grain are carried out by producers who are not able to store the grown crops, and consumers make grain crops. In the article the solution of the economic-mathematical model of optimization of the calendar plan for the sale of agricultural products is developed and found. The model is considered from the standpoint of deterministic product prices and under the probabilistic nature of future market prices. The system of restrictions consists of two constraints: to determine the optimal size of grain crop harvesting of each type and the capacity of the warehouse. If future market prices are considered not deterministic, then the commodity producer always has the risk of receiving in the future revenue from the sale of products smaller than expected. A risk-averse person will be guided by two criteria when deciding to: maximize the expected total net income and minimize the dispersion of total net income. In this case, the model will be two-criterial and nonlinear. The method of supporting the process of determining the predominance of multi-criteria optimization is that the owner first of all has received information about the limits of the variation of the expected total net income and the standard deviation of income on the set of effective options for the calendar plan. The peculiarities of the individual attitude to risk are calculated by drawing information on the permissible levels of the indicated criterion. Further among all effective variants of the calendar plan of realization is calculated precisely the one that best reflects the individual predominance of the owner of the product. The following information is needed to construct a numerical model for grain sales: sales prices and the cost of storing 1 ton of grain crops to a certain month. The predicted values are based on a simple linear econometric model based on statistical sampling. The reliability of the econometric model is determined by the determination coefficient or on the basis of Fisher's F-criterion according to the theory of statistical hypotheses. Econometric models have weak extropolitic properties, so the forecast can be formed only short-term. The solution of the model showed: all kinds of grain crops, except for barley, are economically unprofitable to be implemented in such months as January, May, June, July and August. Wheat grades 3 and 6, corn is also unprofitable to be sold in September. Unlike other crops, barley is beneficial throughout the year. In February, the maximum sales of wheat is 2, 3 and 6 classes, in March the maximum sale of barley, and the minimum is in May. Maize has the maximum sales in May, and the minimum in September. The minimum sale of wheat depends on its class – September, April and December respectively 2, 3 and 6 classes. With such incomplete loading of warehouses, the profit from storage of grain crops will be 743 thousand. UAH. Thus, PJSC “Gnivan Grain Reciprocal Enterprise” is more likely to load its warehouses to improve its financial position. One of the ways of solving the problem of seasonal grain sales is to create a network of modern certified grain elevators, taking into account the logistically rational location, which will allow to keep enough grain in addition and of the proper quality. This will allow an increase in the efficiency of grain producers through the sale of grain at favorable market conditions in a wider range of time. Independent operators should also be encouraged to ensure that the quality of the grain is objectively measured. At present, the analysis of the work of the grain storage system shows that the high cost of services of active elevators is also a problem.
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Kononenko, Rodion, Larisa Solovyeva, Roza Tedeeva, and Elena Tokar. "Updating the Assessment of Company Performance Through the Use of Economic and Mathematical Methods." Regionalnaya ekonomika. Yug Rossii, no. 2 (July 2022): 152–65. http://dx.doi.org/10.15688/re.volsu.2022.2.15.
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The digital transformation of the economy allows an enterprise to respond to constant changes in the market situation and to be competitive. Such a comprehensive fundamental change requires a complete revision of the tool of economic analysis of enterprise performance. Assessment of the economic performance of an enterprise is a prerequisite for competitiveness. In the conditions of digital transformation of the economy the purpose of efficiency growth of the enterprise becomes the search for internal reserves of growth of activity results. The analysis of business performance includes: study of changes in each indicator for the period under analysis; study of the structure of indicators and their changes; study of financial performance in dynamics; identification of causes of changes in indicators. Until recently, economic analysis mainly used mathematical models describing the phenomenon under analysis using equations, inequalities, functions and other mathematical tools. Today, economic and mathematical methods are becoming an important tool for economic analysis, which helps in making optimal management decisions and contributes to the solution of various problems of a complex nature. Economic and mathematical methods are a synthesis of economic, mathematical and statistical approaches to the analysis. Economics and mathematical methods include: methods of elementary mathematics, classical methods of mathematical analysis, econometric methods, methods of operations research, heuristic methods, methods of mathematical statistics, methods of mathematical programming, methods of economic cybernetics, and mathematical theory of optimum processes. Application of economic and mathematical methods can significantly improve the analysis effectiveness of an enterprise, ensures high accuracy of the result when optimizing time costs, allows you to expand the range of tasks. Wide application of mathematical methods is one of the important directions in the field of improvement of economic analysis of enterprise activity. Economic and mathematical modeling can be widely used for planning and forecasting of enterprise activities.
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Shcherbak, Olena V. "JUSTIFICATION OF ORGANIZATIONAL CHANGES INCLUDING SPECIFICS OF HIERARCHICAL RELATIONS IN DEVELOPING ORGANIZATIONS." Management 26, no. 2 (April 24, 2018): 110–24. http://dx.doi.org/10.30857/2415-3206.2017.2.9.
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Introduction and study objective: the requirement to create an effective system of enterprise’s innovation development brings forward issues of theory and methodology, including specifics of necessary organizational changes and cooperation within the company including management –employees’ interaction. Thus, scientific ground for solution to these problems will facilitate the creation of organizational structures for efficiently functioning enterprises.Hypothesis of scientific research. It is often assumed that the choice of effective and required methods of the enterprise’s adjustment to the market environment would allow to systematize the organizational changes enabling performance increase of its economic activity.The purpose of this study is theoretical and methodological justification of concept approaches and methods in organization change management of enterprise structures and functions during its adjustment to the conditions of economic environment.Research methodology: application of the system analysis justifies 5 sets of hypothetical relations linking perceived power with perceived behavior of reward and penalty.Furthermore, two-dimensional correlation, stepwise multiple regression and hierarchical multiple regression analysis help to construct a model of relevant organizational changes.Results achieved: diagnostic methods were developed that determine external and internal conditions of the enterprise in order to choose the right change strategy; the methodology of evolution analysis of change efficiency was proposed. Additionally, high-quality econometric models were created for assessment of the impact of changes based on the enterprise’s performance.Conclusions: the proposed approach to justification of organizational changes enables the implication of methods designed to analyze the need for restructuring of organization culture, management style, employees’ relations and takes into account specifics of hierarchical structure in a developing organization. Furthermore, new methods were developed to assess the effectiveness of management system at an industrial enterprise, including introduction of changes and their dynamics’ assessment.
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Shiller, Robert J. "From Efficient Markets Theory to Behavioral Finance." Journal of Economic Perspectives 17, no. 1 (February 1, 2003): 83–104. http://dx.doi.org/10.1257/089533003321164967.
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The efficient markets theory reached the height of its dominance in academic circles around the 1970s. Faith in this theory was eroded by a succession of discoveries of anomalies, many in the 1980s, and of evidence of excess volatility of returns. Finance literature in this decade and after suggests a more nuanced view of the value of the efficient markets theory, and, starting in the 1990s, a blossoming of research on behavioral finance. Some important developments since 1990 include feedback theories, models of the interaction of smart money with ordinary investors, and evidence on obstacles to smart money.
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Brown, Jeff E., Don E. Ethridge, Darren Hudson, and Carlos Engels. "An Automated Econometric Approach for Estimating and Reporting Daily Cotton Market Prices." Journal of Agricultural and Applied Economics 27, no. 2 (December 1995): 409–22. http://dx.doi.org/10.1017/s1074070800028467.
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AbstractAn automated price reporting system developed through computer technology and hedonic price theory is used to estimate daily cotton market prices, premiums, and discounts. This objective approach for reporting cotton market prices was developed to complement the objective measures of high volume instrument grading of cotton. The computerized, econometric system is limited to the Texas and Oklahoma marketing regions where sales are readily available from electronic markets. The econometric based system has shown all the characteristics of an efficient price reporting system; it is accurate, reliable, consistent, and repeatable in its working process and price estimates.
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Shen, Ze, Qing Wan, and David J. Leatham. "Bitcoin Return Volatility Forecasting: A Comparative Study between GARCH and RNN." Journal of Risk and Financial Management 14, no. 7 (July 20, 2021): 337. http://dx.doi.org/10.3390/jrfm14070337.
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One of the notable features of bitcoin is its extreme volatility. The modeling and forecasting of bitcoin volatility are crucial for bitcoin investors’ decision-making analysis and risk management. However, most previous studies of bitcoin volatility were founded on econometric models. Research on bitcoin volatility forecasting using machine learning algorithms is still sparse. In this study, both conventional econometric models and a machine learning model are used to forecast the bitcoin’s return volatility and Value at Risk. The objective of this study is to compare their out-of-sample performance in forecasting accuracy and risk management efficiency. The results demonstrate that the RNN outperforms GARCH and EWMA in average forecasting performance. However, it is less efficient in capturing the bitcoin market’s extreme events. Moreover, the RNN shows poor performance in Value at Risk forecasting, indicating that it could not work well as the econometric models in explaining extreme volatility. This study proposes an alternative method of bitcoin volatility analysis and provides more motivation for economic researchers to apply machine learning methods to the less volatile financial market conditions. Meanwhile, it also shows that the machine learning approaches are not always more advanced than econometric models, contrary to common belief.
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Watanapalachaikul, Sethapong, and Sardar M. N. Islam. "Rational Speculative Bubbles in the Thai Stock Market: Econometric Tests and Implications." Review of Pacific Basin Financial Markets and Policies 10, no. 01 (March 2007): 1–13. http://dx.doi.org/10.1142/s0219091507000921.
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Understanding of factors like economic fundamentals or bubbles that normally determine the returns of stock in any emerging market such as the Thai stock market is essential for academic, investment planning and public policy reasons. An empirical study of the existence of rational speculative bubbles in the Thai stock market is undertaken by using the Weibull Hazard model. The conventional Weibull Hazard model is used as a benchmark model for other speculative bubble models. Empirical results suggest the presence of rational speculative bubbles in the Thai stock market, especially during the pre-crisis period. While rational speculative bubbles were not present immediately after the post-crisis period, some were observed a few years after the crisis. A possible explanation for such a result concerning rational speculative behaviour and bubbles in the emerging stock markets could be attributed to the presence of market imperfections in emerging stock markets, requiring institutional and policy developments to ensure efficient operation of the stock market.
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Cerović, Julija, Milena Lipovina-Božović, and Saša Vujošević. "A Comparative Analysis of Value at Risk Measurement on Emerging Stock Markets: Case of Montenegro." Business Systems Research Journal 6, no. 1 (March 1, 2015): 36–55. http://dx.doi.org/10.1515/bsrj-2015-0003.
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Abstract Background: The concept of value at risk gives estimation of the maximum loss of financial position at a given time for a given probability. The motivation for this analysis lies in the desire to devote necessary attention to risks in Montenegro, and to approach to quantifying and managing risk more thoroughly. Objectives: This paper considers adequacy of the most recent approaches for quantifying market risk, especially of methods that are in the basis of extreme value theory, in Montenegrin emerging market before and during the global financial crisis. In particular, the purpose of the paper is to investigate whether extreme value theory outperforms econometric and quantile evaluation of VaR in emerging stock markets such as Montenegrin market. Methods/Approach: Daily return of Montenegrin stock market index MONEX20 is analyzed for the period January, 2004 - February, 2014. Value at Risk results based on GARCH models, quantile estimation and extreme value theory are compared. Results: Results of the empirical analysis show that the assessments of Value at Risk based on extreme value theory outperform econometric and quantile evaluations. Conclusions: It is obvious that econometric evaluations (ARMA(2,0)- GARCH(1,1) and RiskMetrics) proved to be on the lower bound of possible Value at Risk movements. Risk estimation on emerging markets can be focused on methodology using extreme value theory that is more sophisticated as it has been proven to be the most cautious model when dealing with turbulent times and financial turmoil.
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Michaletz, Vladimir, and Andrey I. Artemenkov. "The transactional asset pricing approach." Journal of Property Investment & Finance 37, no. 3 (April 10, 2019): 255–88. http://dx.doi.org/10.1108/jpif-10-2018-0078.
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Purpose The purpose of this paper is to present a methodology based on the transactional asset pricing approach (TAPA) and to illustrate the application of TAPA within the context of professional property valuation. Design/methodology/approach The TAPA is a novel analytical valuation methodology recasting the traditional derivations of the income approach techniques, including DCF, from a transactional perspective based on the principle of inter-temporal transactional equity, instead of the conventional investor-specific view originating from I. Fisher (1907, 1930). Findings The authors present DCF analysis as a specific case of a more general TAPA approach to valuation under the income method. This also leads to novel analytical derivations of the Direct income capitalization, Gordon, Inwood, Hoskold and Ring models. Based on the TAPA framework, the authors also research the value-enhancing effects of benchmark market volatility on the subject property value and conclude that such effects can be statistically significant depending on the DCF analysis period. Research limitations/implications The research has a direct bearing on time-variable discount rate forecasting capabilities, as it uses a time-variant structure for the discount rates. Practical implications Using the US Case-Shiller and BLS rental indices as a valuation benchmark, the paper contains an example of applying the general TAPA framework to value a notional property under a TAPA’s DCF version. Such property valuations can be easily replicated in practice – especially in the context of equitable/fair value determination under the International Valuation Standards Council valuation standards. Social implications TAPA is a deductive principles-based theory of asset valuation especially fit for the transactional and illiquid asset valuation contexts – thus enabling a more efficient pricing for such assets in a sense of reflecting the transactional interests of the parties more closely than achievable under the conventional valuation methods. Originality/value TAPA is an original filiation of research with roots going as far back as Aristotelian Catallactics. It contains analytical formalizations of certain transactional equity principles.
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Biørn, Erik. "VAR INTERPRETATIONS OF HAAVELMO’S MARKET MODEL OF CAPITAL AND INVESTMENT." Econometric Theory 31, no. 2 (June 27, 2014): 195–212. http://dx.doi.org/10.1017/s0266466614000267.
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In the paper attempts are made to integrate two parts of Trygve Haavelmo’s work: investment theory and dynamic econometric models of interrelated markets. Specifically, the duality in the representation of the capital service price and the capital quantity in relation to the investment price and quantity are brought to the forefront and confronted with elements from simultaneous equation modeling of vector autoregressive systems containing exogenous variables (VARX), using linear four-equation models. The role of the interest rate and the modeling of the expectation element in the capital service price and the capital’s retirement pattern, and their joint effect on the model’s investment quantity and price dynamics are discussed. Stability conditions are illustrated by examples. Extensions relaxing geometric decay and ways of accounting for forward-looking behavior, including rational expectations, are outlined. Some remarks on the theory-data confrontation of this kind of model are given.
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Fan, Qintao. "Earnings Management and Ownership Retention for Initial Public Offering Firms: Theory and Evidence." Accounting Review 82, no. 1 (January 1, 2007): 27–64. http://dx.doi.org/10.2308/accr.2007.82.1.27.
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This paper investigates, both theoretically and empirically, how earnings management and ownership retention interact, and how these two jointly affect the equilibrium market valuation of IPO firms in the presence of information asymmetry. Analytically, this paper extends the univariate signaling framework of Leland and Pyle (1977) and derives an efficient signaling equilibrium in which both reported earnings and ownership retention are endogenously chosen to convey the IPO issuer's private information. It is shown that even though either ownership retention or reported earnings communicates the issuer's type to the market unambiguously, the issuer will strategically employ both signals to achieve separation from potential lower quality imitators at minimal cost. Comparative statics analysis shows that the trade-off between the two signals depends critically on the uncertainty over future earnings. The theoretical analysis generates several empirical implications regarding market efficiency, IPO pricing, and the strategic choice of earnings management. Through systematic econometric analysis, I confirm the major predictions of the model.
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Callado, Antônio André Cunha, and Carla Renata Silva Leitão. "Dynamics of Stock Prices and Market Efficiency." International Business Research 11, no. 6 (May 9, 2018): 29. http://dx.doi.org/10.5539/ibr.v11n6p29.
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Over the last few decades, academic research on market efficiency has taken a leading position in the field of financial theories. The objective of this paper is to present contradictions within the evidence about market efficiency and discuss efficiency measurement as an emerging approach. The paper presents the evolution of research and also the lack of convergence between evidence provided by the literature and the lack of consistent arguments for explaining them. The paper also presents a framework that illustrates intermediate levels of efficiency and the first approach designed to measuring market efficiency. Finally the paper points out that divergences amongst the empirical evidence found in the literature should be considered as a key issue and further efforts should focus on specific conceptual elements inherent to its operationalization. Therefore, econometric models should not be given the exclusive responsibility of explaining market efficiency, nor possibility of incorporating alternative epistemological perspectives into the efficient / inefficient duality should be kept outside.
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Sun, Chao, and Yoonmin Kim. "Efficient Market Testing of the Chinese Stock Market During the COVID-19 Recession." East Asian Trade Association 4, no. 1 (June 30, 2022): 35–46. http://dx.doi.org/10.47510/jeat.2022.4.1.35.
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Purpose – The purpose of this paper is exploring whether Chinese stock market (SSEC) is effective during the COVID-19 recession. Recent asset market bubbles and bursts have generated interest in the efficiency of stock market behavior. Efficient market hypothesis (EMH) has been challenged by the COVID-19 recession.
Design/Methodology/Approach – Based on Efficient market hypothesis, this research will present results of nonparametric tests employed in an econometric investigation of stock market efficiency in China during COVID-19 recession. To test this hypothesis, the Augmented Dickey-Fuller (ADF) test, Autocorrelation Function (ACF) test, Runs test, and Variance Ratio Test were used to assess the behavior of the SSEC.
Findings – This paper studies the Chinese stock market’s (SSEC) behavior passed weak form efficient market tests for random walk. According to Variance Ratio Test, a certain group of SSEC investors could experience abnormal returns since there is a possibility that they could know something about a shock that is not already reflected in the stock's price.
Research Implications – In the management of this paper, this study will provide help for stock market investors when investing or provide reference significance for the state to manage the stock market.
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Boshoff, Douw Gert Brand. "Empirical analysis of space and capital markets in South Africa: A review of the REEFM- and FDW models." South African Journal of Economic and Management Sciences 16, no. 4 (November 29, 2013): 383–94. http://dx.doi.org/10.4102/sajems.v16i4.359.
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This paper assesses the different models, in conjunction with the different theories surrounding the distinction and interdependencies between space- and capital markets. First, the theory of space- and capital markets is discussed with reference to two models, the FDW and the REEFM models. The FDW model provides a diagrammatic explanation of the behaviour of the property market, while the REEFM is an econometric model based on statistical principles that are able to forecast property-market behaviour by interpreting specific given variables. The REEFM model as the perceived more sophisticated model, un-tested in South Africa, was then analysed to test its applicability in the South African context. The findings confirmed the applicability of the model, although one part is not confirmed and is suggested for further research.
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Koubaa, Yosra. "Tunisian Labor Market and Regional Heterogeneity: Application of PSTR Model." International Journal of Regional Development 4, no. 1 (January 15, 2017): 51. http://dx.doi.org/10.5296/ijrd.v4i1.10299.
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This paper is devoted to investigating the matching process for Tunisia using desaggregated data by assuming that the rising of the unemployment rate result from regional disparities which yield variation of matching efficiencies across regions. Since most econometric aspects of spatial heterogeneity can be handled by means of the standard panel data methods, we focus our discussion on the new technique: Panel Smooth Transition Regression models (PSTR). The distinction is that we can compute regional specific sensibilities for 23 regions over the period 1984-2004. Given this objective, we consider three structural factors that allow explaining the regional imbalances. Contrary to the previous econometric techniques of the matching theory, estimates of the coefficients depend, of three transition variables. The results show that women insertion, the qualification share and population density significantly contribute to explain the asymmetry of the matching process across regions. Our main conclusion is that the hiring in Tunisia is driven essentially by the stock of vacancies about is the region. The willingness of job seekers, obviously, remains low, although it is different between regions and seems relatively important in urban zones.
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Wright, Randall, Philipp Kircher, Benoît Julien, and Veronica Guerrieri. "Directed Search and Competitive Search Equilibrium: A Guided Tour." Journal of Economic Literature 59, no. 1 (March 1, 2021): 90–148. http://dx.doi.org/10.1257/jel.20191505.
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This essay surveys the literature on directed search and competitive search equilibrium, covering theory and a variety of applications. These models share features with traditional search theory, but also differ in important ways. They share features with general equilibrium theory, but with explicit frictions. Equilibria are often efficient, mainly because markets price goods plus the time required to get them. The approach is tractable and arguably realistic. Results are presented for finite and continuum economies. Private information and sorting with heterogeneity are analyzed. While emphasizing issues and applications, we also provide several hard-to-find technical results. (JEL D50, D83)
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Barboza Martignone, Gustavo, Karl Behrendt, and Dimitrios Paparas. "Price Transmission Analysis of the International Soybean Market in a Trade War Context." Economies 10, no. 8 (August 19, 2022): 203. http://dx.doi.org/10.3390/economies10080203.
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This study analysed the dynamics of the international soybean market using econometric techniques and economic models to study the impacts of the US–China trade war. It considered the analysis of “spatial” (horizontal) price transmission during an approximately ten-year period from September 2009 to May 2019 using monthly time-series data. The research focused on the leaders in the international soybean market, namely, China, the USA, the EU, Brazil and Argentina. Several econometric techniques were employed. The stationarity of the price time series was determined using the augmented Dickey–Fuller (ADF) unit root test. Structural breaks were inferred using the ADF test with a breaks test and a Bai–Perron multiple break test. The long-term relation/cointegration amongst the series was determined using the Johansen cointegration test (1988), with the previous breaks input as dummy variables. The direction of the causality was inferred using the Granger causality test (1969). The long-term and short-term causal relations were determined using the vector autoregression model (VAR) and the vector error correction model (VECM). The results showed a highly efficient and cointegrated market. The incidents of the trade war, as represented by tariffs and subsidies, had minor effects on the market efficacy, cointegration and price transmission. The arbitrage process of the studied market managed to get around the tariffs. In other words, there was no empirical evidence to support the claim that the law of one price (LOOP) did not hold.
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Zaimi, Wiam. "An Empirical Analysis of a Stock Market Index of a Developing Country: Case of the Main Index of the Casablanca Stock Exchange MASI." GLOBAL BUSINESS FINANCE REVIEW 27, no. 4 (August 31, 2022): 1–16. http://dx.doi.org/10.17549/gbfr.2022.27.4.1.
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Purpose: Managing stock market risk and making an optimal investment decision in a stock market requires study- ing the dynamics of this market and analyzing the fluctuations of its benchmark index in order to avoid heavy damage in the event of crises. This paper aims to study and analyze the fluctuations of the main index of the Casablanca Stock Exchange "MASI" to explore its efficiency and stability in the normal financial context (especially before the recent pandemic crisis).
Design/methodology/approach: To carry out this study, two methods are proposed, the first one, how evolves this index over time depending on some random data generation processes widely used for stock prices: A Random Walk with a drift RW(α) and an autoregressive process of order 1 AR(1). Based on the actual MASI returns series used (2007-2018), we estimate each equation parameter according to the process chosen to generate the artificial MASI returns series to know the most relevant data generation process in the case of The Moroccan financial market. The second method focuses on the technique of "simple moving average" as a method of stock prices fluctuation analysis to make its investment decision, choosing the proper order on the same series.
Findings: The results and findings of our econometric study show, in the first method, that either the RW(α) or the AR(1) process cannot adequately model MASI fluctuation. However, the results of the second method affirm the utility of the simple moving average to identify trends, their strength and buy / sell signals, using some techniques known in this field, in order to make decisions and draw interpretations in investment terms and risk management, which can prove that the market is less efficient and stable.
Research limitations/implications: An important implication of this study is the need to explore the efficient models to describe the MASI return series.
Originality/value: This study offers empirical evidence in relation to the estimation of the econometric model to describe MASI and how to make adequate investment decisions in the Moroccan stock market. Moreover, contributes to future research to find other more appropriate models.
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Sikalo, Mirza, Almira Arnaut-Berilo, and Azra Zaimovic. "Efficient Asset Allocation: Application of Game Theory-Based Model for Superior Performance." International Journal of Financial Studies 10, no. 1 (March 9, 2022): 20. http://dx.doi.org/10.3390/ijfs10010020.
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In this paper, we compared the models for selecting the optimal portfolio based on different risk measures to identify the periods in which some of the risk measures dominated over others. For decades, the best known return-risk model has been Markowitz’s mean-variance model. Based on the criticism of the classical Markowitz model, a whole series of risk measures and models for selecting the optimal portfolio have been developed, which are divided into two groups: symmetrical and downside risk measures. Based on the tools provided by game theory, we presented a minimax model for selecting the optimal portfolio based on the maximum loss as a measure of risk. Recent research has shown the adequacy of the application of this risk measure and its dominance concerning variance in certain circumstances. Theoretically, the model based on maximum loss as a measure of risk relies on a much smaller number of assumptions that must be satisfied. In the empirical part of the paper, we analyzed the real return performance, structure, correlation, stability, and predictive efficiency of the model based on maximum loss return as a measure of risk and compared it with the other famous models to determine whether the maximum loss-based risk measure model is more suitable for use in certain circumstances than conventional return-risk models. We compared portfolios created based on different models over the period of 2000–2020 from a selected sample of stocks that are components of the STOXX Europe 600 index, which covers 90% of the free market capitalization in the European capital market. The observed period included 3 bear market periods, including the period of market decline during the COVID-19 crisis. Our analysis showed that there was no significant difference in portfolio returns depending on the selected model using the “buy-and-hold” strategy, but there were crisis periods. The results showed a significantly higher stability of portfolios selected on the criterion of minimizing the maximum loss than others. In periods of market decline, this portfolio achieved the best performance and had a shorter recovery period than others. This allowed superior use of the minimax model at least for investors with a pronounced risk aversion.
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Koulis, Alexandros, George Kaimakamis, and Christina Beneki. "Hedging effectiveness for international index futures markets." Economics and Business 32, no. 1 (July 31, 2018): 149–59. http://dx.doi.org/10.2478/eb-2018-0012.
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Abstract This paper investigates the hedging effectiveness of the International Index Futures Markets using daily settlement prices for the period 4 January 2010 to 31 December 2015. Standard OLS regressions, Error Correction Model (ECM), as well as Autoregressive Distributed Lag (ARDL) cointegration model are employed to estimate corresponding hedge ratios that can be employed in risk management. The analyzed sample consists of daily closing market rates of the stock market indexes of the USA and the European futures contracts. The findings indicate that the time varying hedge ratios, if estimated through the ARDL model, are more efficient than the fixed hedge ratios in terms of minimizing the risk. Additionally, there is evidence that the comparative advantage of advanced econometric approaches compared to conventional models is enhanced further for capital markets within peripheral EU countries
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ZIMMERMANN, GEORG, RALPH NEUNEIER, and RALPH GROTHMANN. "MULTI-AGENT MARKET MODELING OF FOREIGN EXCHANGE RATES." Advances in Complex Systems 04, no. 01 (March 2001): 29–43. http://dx.doi.org/10.1142/s021952590100005x.
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A market mechanism is basically driven by a superposition of decisions of many agents optimizing their profit. The macroeconomic price dynamic is a consequence of the cumulated excess demand/supply created on this micro level. The behavior analysis of a small number of agents is well understood through the game theory. In case of a large number of agents one may use the limiting case that an individual agent does not have an influence on the market, which allows the aggregation of agents by statistic methods. In contrast to this restriction, we can omit the assumption of an atomic market structure, if we model the market through a multi-agent approach. The contribution of the mathematical theory of neural networks to the market price formation is mostly seen on the econometric side: neural networks allow the fitting of high dimensional nonlinear dynamic models. Furthermore, in our opinion, there is a close relationship between economics and the modeling ability of neural networks because a neuron can be interpreted as a simple model of decision making. With this in mind, a neural network models the interaction of many decisions and, hence, can be interpreted as the price formation mechanism of a market.
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Endri, Endri, Widya Aipama, A. Razak, Laynita Sari, and Renil Septiano. "Stock price volatility during the COVID-19 pandemic: The GARCH model." Investment Management and Financial Innovations 18, no. 4 (October 4, 2021): 12–20. http://dx.doi.org/10.21511/imfi.18(4).2021.02.
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This study examined the response of stock prices on the Indonesia Stock Exchange (IDX) to COVID-19 using an event study approach and the GARCH model. The research sample is the closing price of the Composite Stock Price Index (JCI) and companies that are members of LQ-45 in the 40-day period before the COVID-19 incident, 1 day during the COVID-19 incident (March 2, 2020) and 10 days after, January 6, 2020 – March 16, 2020. Empirical findings prove that abnormal returns react negatively to COVID-19, JCI volatility fluctuates widely during the COVID-19 event, and the GARCH(1,2) model can be used to assess volatility and predict stock abnormal returns in IDX in market conditions infected with COVID-19. The practical implication of the study’s findings for investors is that the COVID-19 event caused stock price volatility, which affects abnormal returns. Therefore, to face the conditions of uncertainty and increased volatility in the future, several lines of risk management are needed in managing a stock portfolio. In addition, it also opens up opportunities for speculators to profit in an inefficient market environment. This study is based on the empirical literature currently being developed to investigate the phenomenon of stock price volatility behavior during COVID-19 on the IDX. The GARCH model used proves that during the COVID-19 pandemic, stock price volatility increases and leads to a decrease in abnormal returns. The empirical findings also validate the efficient market hypothesis theory related to the study of events and the theory of financial behavior related to uncertainty.
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Spulbar, Cristi, Ramona Birau, Jatin Trivedi, Iqbal Thonse Hawaldar, and Elena Loredana Minea. "Testing volatility spillovers using GARCH models in the Japanese stock market during COVID-19." Investment Management and Financial Innovations 19, no. 1 (March 22, 2022): 262–73. http://dx.doi.org/10.21511/imfi.19(1).2022.20.
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This paper investigates volatility spillovers in the stock market in Japan during the COVID-19 pandemic by using GARCH family models. The empirical analysis is focused on the dynamics of the NIKKEI 225 stock market index during the sample period from July 30, 1998, to January 24, 2022. In other words, the sample period covers both the period of the global financial crisis (GFC) and the COVID-19 pandemic. The econometrics includes GARCH (1,1), GJR (1,1), and EGARCH (1,1) models. By applying GARCH family models, this empirical study also examines the long-term behavior of the Japanese stock market.The Japanese stock market is much more stable and efficient than emerging or frontier markets characterized by higher volatility and lower liquidity. The paper establishes that NIKKEI 225 index dynamics is different in intensity in the case of the two most recent extreme events analyzed, namely the global financial crisis (GFC)of 2007–2008 and the COVID-19 pandemic. The findings confirmed the presence of the leverage effect during the sample period. Moreover, the empirical results identified the presence of high volatility in the sample returns of the selected stock market. Nevertheless, the econometric framework showed that the negative implications of the GFC were much more severe and caused more significant contractions compared to the COVID-19 pandemic for the Japanese stock market. This study contributes to the existing literature by providing additional empirical evidence on the long-term behavior of the stock market in Japan, especially in the context of extreme events.
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VOLONTYR, Ludmila, Nadiya POTAPOVA, and Oksana ZELINSKA. "ECONOMETRIC MODELING IN FORMATION OF OPTIMAL PRICE FOR IMPLEMENTATION OF AGRICULTURAL PRODUCTS." "EСONOMY. FINANСES. MANAGEMENT: Topical issues of science and practical activity", no. 5 (45) (May 2019): 83–93. http://dx.doi.org/10.37128/2411-4413-2019-5-9.
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Ukraine is a predominantly agricultural country, and this branch has been recently demonstrating relatively high efficiency. Vegetable growing is a specific branch of crop production, which includes a large set of vegetables grown according to different technologies, with different shelf life of vegetable products, their different cost and production efficiency. The analysis of the situation on the vegetable market of Ukraine showed that there is a certain correlation between production volumes, sales and products sales prices. The price market environment on the vegetable market in recent years is largely determined by the ratio of supply and demand on the market. Thus, sales volumes increase when the supply on the market is the highest and the price level on the market is the lowest. The absence of permanent wholesale distribution channels also leads to an increase in the hidden market for vegetable products. According to experts of the Ukrainian Agrarian Confederation, the hidden market for fruit and vegetables is about $ 14 billion, or about 60% of the total turnover of vegetable products in Ukraine. Due to the moratorium on the sale of agricultural land, businesses are not able to buy land on their own and develop their business in the long-term prospects. Today, government support in the vegetable sector is limited to preferential lending and to individual funding programs, most often in collaboration with international donors. Much of the support for agro-industrial farms goes to grain and pulse plant producers, which significantly limits the opportunity for developing crop producers with higher marginality. The conditions in which the agrarian sector operates have a high degree of changeable uncertainty, and this circumstance requires agricultural producers to find ways to obtain reliable information about the state of the agricultural market, organizational and functional links between the subjects of the agricultural market, prices for agricultural products. etc. The purpose of this study is to: analyze the price of vegetable sales in Ukraine; substantiation of the use of the AGMEMOD partial equilibrium model for forecasting vegetable production in Ukraine; establish dependence of demand and supply of vegetable production on their sales price; determine the point of equilibrium of supply and demand and calculate of the optimal selling price of vegetables in Ukraine; justify the optimal costs for vegetable production; analyze of the price of selling vegetables in Ukraine and determine the optimal price according to supply and demand, as well as the optimal cost of vegetable production. Now, there are 12 key vegetable crops in Ukraine. These are potatoes, cucumbers, tomatoes, cabbage, beets, carrots, onions, garlic, peppers, zucchini, eggplants and pumpkin. Of these 12 cultures, 9 showed an increase in the period 2010-2016, even without taking into account the uncontrolled Crimea and Donbass. This increase has been driven by two crucial factors: - yield increase. This was made possible due to improving the quality of the seed and natural technological progress in the processing and the use of crop protecting agents. - increase in export demand for products. The demand, for example, for Ukrainian carrots and onions has increased, and therefore the opportunities for their cultivation have become greater. Price is a complex economic category, practically the only element of marketing that enables an enterprise to earn real income. Without proper economic justification of the price level, the normal functioning of economic entities and entire sectors of the economy is impossible, which in turn has a significant impact on the material well-being of the population. The level of market price depends on the value of other marketing elements, as well as on the level of competition on the market and the general state of the economy. As a rule, other marketing elements also change (for example, with increasing product differentiation in order to maximize price or at least the difference between price and cost). The price formation strategy allows determining the price level and marginal prices for individual product groups. The price formation should always be carried out taking into account the nomenclature and quality of products, their usefulness, importance and purchasing power of consumers and prices of the competitors. The strategy of price formation management is a set of measures to maintain conditional prices while actually regulating them in accordance with the variety and characteristics of demand, competition in the market. The AGMEMOD model is an example of the partial equilibrium (PE) models used in agriculture. The main advantages of partial equilibrium models are: the simplicity of the implemented algorithms, the operation of which is quite easily traced; relative availability of necessary data; the calculations are amenable to adequate economic interpretation, making it possible to quickly analyze the consequences of making a decision in the agricultural sector. However, partial equilibrium models are not without their disadvantages. In particular, they do not permit to assess macroeconomic effects such as changes in national income or employment levels, the effects that may be obtained from the redistribution of resources (labor, capital, etc.) into more efficient sectors. For national researchers, it is advisable to use these models, because they have a module of Ukraine, but it is necessary to supplement the program with statistics on vegetables. The demand is a function of price changes in the current period, and the supply is a function of price changes in previous periods. Econometric models of supply and demand dependence of vegetable production on the price of their sale are constructed. The equilibrium of the system is observed at the price of 6558 UAH. for 1 ton of vegetables under the given conditions of consumption, the demand is equal to supply and is 9321 thousand tons. Econometric models of price dependence on material costs, labor costs and depreciation have been constructed. By the first model, it can be determined that the content of unaccounted factors is estimated at 99.82 UAH. per hectare; with an increase in material costs by 1 hectare by 1 UAH, selling price increases by 0.9 UAH. per ton. Based on the Fisher's ratio test, the model is adequate, the relationship between the indicators is tight. The relationship between the indicators of the second model is weak, the calculated correlation coefficient can be trusted, but in general, the adequacy of the model conclusion cannot be made. The model shows that with an increase in labor costs by 1 UAH per hectare, the price increases by 10.03 UAH per ton. The third model based on the Fisher's ratio test is adequate, the relationship between the indicators is average. With the increase in depreciation costs per hectare by 1 UAH, the selling price will increase by 12.42 UAH per ton. The value of the linear correlation coefficient other than zero is statistically significant. Based on the calculated models, we will determine the optimal cost per hectare: material – 7144.2 UAH, labor costs – 689.4 UAH, depreciation costs – 543.4 UAH.
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Doszyń, Mariusz. "Algorithm of real estate mass appraisal with inequality restricted least squares (IRLS) estimation." Journal of European Real Estate Research 13, no. 2 (May 22, 2020): 161–79. http://dx.doi.org/10.1108/jerer-11-2019-0040.
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Purpose The purpose of this paper is to present an algorithm of real estate mass appraisal in which the impact of attributes (real estate features) is estimated by inequality restricted least squares (IRLS) model. Design/methodology/approach This paper presents the algorithm of real estate mass appraisal, which was also presented in the form of an econometric model. Vital problem related to econometric models of mass appraisal is multicollinearity. In this paper, a priori knowledge about parameters is used by imposing restrictions in the form of inequalities. IRLS model is therefore used to limit negative consequences of multicollinearity. In ordinary least squares (OLS) models, estimator variances might be inflated by multicollinearity, which could lead to wrong signs of estimates. In IRLS models, estimators efficiency is higher (estimator variances are lower), which could result in better appraisals. Findings The final effect of the analysis is a vector of the impact of real estate attributes on their value in the mass appraisal algorithm. After making expert corrections, the algorithm was used to evaluate 318 properties from the test set. Valuation errors were also discussed. Originality/value Restrictions in the form of inequalities were imposed on the parameters of the econometric model, ensuring the non-negativity and monotonicity of real estate attribute impact. In case of real estate, variables are usually correlated. OLS estimators are then inflated and inefficient. Imposing restrictions in form of inequalities could improve results because IRLS estimators are more efficient. In the case of results inconsistent with theoretical assumptions, the real estate mass appraisal algorithm enables having the obtained results adjusted by an expert. This can be important for low quality databases, which is often the case in underdeveloped real estate markets. Another reason for expert correction may be the low efficiency of a given real estate market.
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Silva, Marcos Soares da, and José Angelo Divino. "Estabilidade Financeira e Estrutura de Mercado: Evidências Internacionais." Brazilian Review of Finance 10, no. 1 (April 21, 2012): 7. http://dx.doi.org/10.12660/rbfin.v10n1.2012.3264.
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Although the economic theory recognizes the ambiguous relationship between market structure and stability of the bank sector, some models, such as the one of competition-fragility by Allen and Gale (2004), suggest that increasing competition leads financial institutions to take more risks. As a result, financial markets that are more concentrated also present higher financial stability. To assess this hypothesis, we estimate a dynamic panel data model for 41 countries in the period from 1987 to 2007. The econometric model included covariates for level of income, characteristics of the financial market, economic environment, and macro prudential regulation. We used the following databases: “A new database on financial development and structure” and “Bank regulation and supervision”, from the World Bank, and “Systemic banking crises: a new database”, from the International Monetary Fund. The results indicate that the greater the market concentration the higher the stability of the banking system.
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GULKO, LES. "THE ENTROPY THEORY OF BOND OPTION PRICING." International Journal of Theoretical and Applied Finance 05, no. 04 (June 2002): 355–83. http://dx.doi.org/10.1142/s021902490200147x.
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An informationally efficient price keeps investors as a group in the state of maximum uncertainty about the next price change. The Entropy Pricing Theory (EPT) captures this intuition and suggests that, in informationally efficient markets, perfectly uncertain market beliefs must prevail. When the entropy functional is used to index collective market uncertainty, then the entropy-maximizing consensus beliefs must prevail. The EPT resolves the ambiguity of arbitrage-free valuation in incomplete markets. The EPT produces a new bond option model that is similar to Black–Scholes' with the lognormal distribution replaced by a beta distribution. Unlike alternative models, the beta model is valid for arbitrary term structure dynamics and for arbitrary credit risk of the underlying bonds. Option replication and hedging under the beta model accounts for random changes in the underlying bond price, price volatility and short-term interest rates.
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Ploegmakers, Huub, and Friso de Vor. "Determinants of industrial land prices in The Netherlands: a behavioural approach." Journal of European Real Estate Research 8, no. 3 (November 2, 2015): 305–26. http://dx.doi.org/10.1108/jerer-04-2015-0016.
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Purpose – The purpose of this paper is to demonstrate how the specification of hedonic pricing models can be improved by using insights generated from qualitative research. In doing so, it seeks to address one of the main problems in the specification of hedonic models, namely that theory yields little guidance in the selection of the characteristics that should be included on the right-hand side. Design/methodology/approach – Building on the behavioural tradition in real estate research, this paper introduces a research approach that integrates insights from qualitative analysis in an econometric model of land values. The empirical segment explores the way in which asking prices of building plots for industrial purposes are determined in The Netherlands. It draws from interviews with municipal land developers, who dominate supply in this market. The information secured during these interviews relates to the characteristics considered important and the kind of information used in the valuation process. Based on these qualitative data, an econometric model is developed and estimated. Findings – The estimation results confirm qualitative evidence that the typical developer considers only a limited number of features of the land in the valuation process and that the primary source of information in setting asking prices relates to the prices charged in neighbouring municipalities. Originality/value – This paper represents a novel attempt to examine the determination of land and property values by merging qualitative and quantitative, econometric analyses.
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Alemayehu, Yidnekachew, and Mebratu Alemu. "The determinants of smallholder coffee producers’ market outlet choice decision in Debub ari district of South Omo Zone, SNNPR, Ethiopia." International Journal of Agricultural Research, Innovation and Technology 12, no. 1 (August 23, 2022): 166–73. http://dx.doi.org/10.3329/ijarit.v12i1.61048.
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This study mainly aimed at analyzing coffee market chain and the determinants of coffee market outlet choice decision of smallholder coffee producers in the Debub Ari District. The descriptive statistics and econometric models were used to analyze the data. Multivariate probit model was used to identify factors affecting market outlet choices of the smallholder coffee producers. Both primary and secondary data were collected from the study area. The multi-stage sampling techniques have been employed for this study. A total of 194 coffee producer household heads have been randomly selected and interviewed with the help of pre-tested structured questionnaire. The focus group discussion and key informants interviews were conducted to supplement the formal data. The probability of choosing collector, wholesalers, retailer, processor, consumer’s outlets is 67.1%, 66.4%, 36.9%, 71.6% and 15.3%, respectively. The joint probabilities of households to jointly choose the four market outlets was 0.031% which is greater than the likely of not choosing all market outlets which is 0.003%. Access to credit negatively influenced retailer, processor and consumer market outlet choice, distance to the nearest market negatively influenced processor market outlet choices, market information, off-farm participation positively influenced retailer and consumer market outlets choices. Therefore, the intervention is needed to improve coffee marketing chain through promoting cooperatives, infrastructural development and timely market information for efficient marketing system in the study area. Int. J. Agril. Res. Innov. Tech. 12(1): 166-173, June 2022
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Berghorn, Wilhelm, and Sascha Otto. "Mandelbrot Market-Model and Momentum." International Journal of Financial Research 8, no. 3 (June 12, 2017): 1. http://dx.doi.org/10.5430/ijfr.v8n3p1.
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Mandelbrot was one of the first who criticized the oversimplifications in finance modeling. In his view, markets have long-term memory, were fractal and thus much wilder than classical theory suggests. Recently, we were able to show that the scaling behaviour of trends, as defined by a specific trend decomposition using wavelets, are causing the momentum effect. In this work, we will show that this effect can be modeled by fractal trends. The so-called Mandelbrot Market-Model shows that markets are wilder compared with classical models. In conclusion, we derive what Mandelbrot always knew: There are no efficient markets.
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Liao, Zhipeng, and Peter C. B. Phillips. "AUTOMATED ESTIMATION OF VECTOR ERROR CORRECTION MODELS." Econometric Theory 31, no. 3 (March 13, 2015): 581–646. http://dx.doi.org/10.1017/s026646661500002x.
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Model selection and associated issues of post-model selection inference present well known challenges in empirical econometric research. These modeling issues are manifest in all applied work but they are particularly acute in multivariate time series settings such as cointegrated systems where multiple interconnected decisions can materially affect the form of the model and its interpretation. In cointegrated system modeling, empirical estimation typically proceeds in a stepwise manner that involves the determination of cointegrating rank and autoregressive lag order in a reduced rank vector autoregression followed by estimation and inference. This paper proposes an automated approach to cointegrated system modeling that uses adaptive shrinkage techniques to estimate vector error correction models with unknown cointegrating rank structure and unknown transient lag dynamic order. These methods enable simultaneous order estimation of the cointegrating rank and autoregressive order in conjunction with oracle-like efficient estimation of the cointegrating matrix and transient dynamics. As such they offer considerable advantages to the practitioner as an automated approach to the estimation of cointegrated systems. The paper develops the new methods, derives their limit theory, discusses implementation, reports simulations, and presents an empirical illustration with macroeconomic aggregates.
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Ginther, Donna K. "AN INTERVIEW WITH JAMES J. HECKMAN." Macroeconomic Dynamics 14, no. 4 (September 2010): 548–84. http://dx.doi.org/10.1017/s1365100510000611.
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James Heckman is one of the most important and influential scholars to have graced the economics profession. His work is deeply rooted at the intersection of economic theory and empirical microeconomics, and he has made significant contributions to the study of labor economics, microeconometrics, and the use of micro data in macroeconomic analysis. Heckman's work is motivated by the scientific method, in which theory is held up to the scrutiny of the data and empirical analysis is informed by economic theory. During the course of his work, he has made lasting contributions to the study of sample selection bias, duration analysis, heterogeneity, and treatment effects in microeconometrics. In labor economics, he has applied these econometric methods to the study of labor supply and life-cycle dynamic models of unemployment, wage growth, and skill formation. In addition, he is the leading scholar on the evaluation of active labor market programs. As an applied microeconomist, one cannot do research on labor supply, sample selection, duration models, or life-cycle dynamics without encountering Jim Heckman's work.
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Singh, Amanjot, and Manjit Singh. "A revisit to how linkages fuel dependent economic policy initiatives." International Journal of Law and Management 59, no. 6 (November 13, 2017): 1068–108. http://dx.doi.org/10.1108/ijlma-08-2016-0074.
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Purpose The authors aim to report empirical linkages between the US and Brazil, Russia, India and China (BRIC) financial stress indices catalyzing catalyzing dependent economic policy initiatives (an extended version of Singh and Singh, 2017a). Design/methodology/approach Initially, the study develops financial stress indices for the respective BRIC financial markets. Later, it captures linkages among the said US-BRIC indices by using Johansen cointegration, vector autoregression/vector error correction models (VECM), generalized impulse response functions, Toda–Yamamoto Granger causality, variance decomposition analyses and bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model under constant conditional correlation framework, in general. Markov regime switching and efficient causality tests proposed by Hill (2007) are also used. Findings Overall, there are both short-run and long-run dynamic interactions observed between the US and Indian financial stress indices. For rest of the markets, only short-run interactions are found to be in existence. The time-varying co-movement coefficients report financial contagion impact of the US financial crisis on Russian and Indian financial systems only. Contrary to this, Brazilian and Chinese financial systems are largely exhibiting interdependence with the US financial system. Efficient causality tests report indirect impact of the Russian financial system on Brazilian via auxiliary Indian financial system. Originality/value The present study is the first of its kind capturing linkages among the US-BRIC financial stress indices by using diverse econometric models. The results support different market participants and policymakers in understanding effectiveness and implementation of economic policies while considering their cross-market interactions as well.
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Miller, Jason W., Jessica L. Darby, and Alex Scott. "The Moderating Effect of COVID-19 on the Relationship between Spot Market Prices and Capital Investment in the Motor-Carrier Sector." Transportation Journal 61, no. 2 (2022): 151–94. http://dx.doi.org/10.5325/transportationj.61.2.0151.
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Abstract Capital investment by motor carriers in new trucks and trailers is essential for the effective and efficient operation of supply chains. Strong evidence exists that motor carriers’ capital investment is positively correlated with truckload spot prices. This article explores whether the onset of the COVID-19 pandemic moderated the relationship between spot prices and capital investment by motor carriers. We theorize that the onset of the COVID-19 pandemic muted the relationship between spot prices and investment in trucks to a greater degree than it muted the relationship between spot prices and investment in trailers. We attribute this to the COVID-19 pandemic creating tremendous uncertainty about the availability of truck drivers, which made investing in trucks less attractive than investing in trailers that do not require additional labor. To test our theory, we assemble a time series dataset that combines proprietary and public data from several sources. Econometric estimates corroborate our predictions and are robust to instrumental variable estimation to assuage concerns about endogeneity of spot prices. We explain the implications of our findings for theory and practice.
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Vartanov, Sergey. "A Strategic Approach to Russian Media System Analysis: Defining Mission, Values and Priorities." Strategizing: Theory and Practice 2021, no. 2 (November 30, 2021): 173–89. http://dx.doi.org/10.21603/2782-2435-2021-1-2-173-189.
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Modern media has transformed into a full-fledged industry, embedded in the national economy and inextricably linked with other industries. The strong dependence between the main economic indicators of the media industry and macroeconomic indicators determines the importance of a long-term media strategy. A successful strategy of media system development may improve the national economy and ensure social prosperity in the sense of Aristotelian eudaimonia. The research objective was to develop a new methodology for media strategizing with its mission, values, objectives, and strategic priorities. The study was based on strategy theory, media theory, mathematical economics, econometric methods of strategic media monitoring, and a new method of game-theoretic models of the three-sided market. The object of strategizing was a complex multi-level environment formed by media institutions in their interaction with each other and society, media market, infrastructure, manufacturers, developers, and distributors. The Russian media system was subjected to a primary OTSW analysis, which revealed five priorities. The author developed a quantitative assessment methodology for each priority. The research is a foundation for a separate interdisciplinary discipline “Theory of Media Strategy”.
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Zavera, Ioana Coralia. "Application of Markowitz Model on Romanian Stock Market." HOLISTICA – Journal of Business and Public Administration 8, no. 1 (April 1, 2017): 97–103. http://dx.doi.org/10.1515/hjbpa-2017-0008.
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Abstract Performance evaluation of financial instruments has become a concern for more and more economists, while security trading activities have developed over time. “Modern portfolio theory” comprises statistical and mathematical models which describe various ways in order to evaluate and especially analyse profitability and risk of these portfolios. This article offers an application of this type of model on Romanian stock market, the Markowitz model, by focusing on portfolios comprising three securities, and determining the efficient frontier and the minimum variance portfolio.
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Park, Dojoon, Young Ho Eom, and Jaehoon Hahn. "Estimating the Risk-Return Relation in the Korean Stock Market." Journal of Derivatives and Quantitative Studies 25, no. 1 (February 28, 2017): 1–39. http://dx.doi.org/10.1108/jdqs-01-2017-b0001.
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Finance theory such as Merton’s ICAPM suggests that there should be a positive relationship between the expected return and risk. Empirical evidence on this relationship, however, is far from conclusive. Building on the recent econometric research on this topic such as Lundblad (2007) and Hedegaard and Hodrick (2016), we estimate the risk-return relation implied in the ICAPM using a long sample (1962~2016) of daily, weekly, and monthly excess stock returns in Korea. More specifically, we estimate various volatility models including GARCH-M using the overlapping data inference (ODIN) method suggested by Hedegaard and Hodrick (2016), as well as the traditional maximum likelihood estimation methodology. For the full sample period, we fail to find a positive risk-return relationship that is significant and robust. For the subsample period from 1998 to 2016, however, we find a significantly positive risk-return relation for GARCH-M model regardless of return intervals and estimation methods. This result is also robust to using other specifications such as EGARCH-M which includes the leverage effect of the variance process and EGARCH-M-GED whose conditional distribution has fatter tails. Our findings suggest that there is indeed a positive relationship between the expected return and risk in the Korean stock market, at least for the period after 1998.
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Kokot, Sebastian, and Sebastian Gnat. "Simulative Verification of the Possibility of using Multiple Regression Models for Real Estate Appraisal." Real Estate Management and Valuation 27, no. 3 (September 1, 2019): 109–23. http://dx.doi.org/10.2478/remav-2019-0029.
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Abstract The possibility of using multiple regression models in real estate valuation is the subject of disputes, both in theory and in practice. Econometric modelling is a difficult process, since a number of issues of substantive and numerical nature occur during that process. Modern technologies enable quick and easy model estimation with the use of virtually any quality of data. Naturally, it provokes property appraisers to use such models in the practice of real property valuation, particularly in mass appraisal, frequently without taking those issues into account. Consequently, the models obtained and applied in practice turn out to be of poor quality and, objectively speaking, should not serve as the basis for determining real estate value. The specificity of the real estate market and of the real properties themselves as objects traded in that market additionally exert a negative impact on the quality of the obtained models. In this article, the authors present the results of research which involved a simulation of various types of disturbances of a model artificially developed database of real estate prices and attributes as well as their impact on the quality of estimated models. The research will make it possible to answer the question of the degree and type of disturbances that are permissible in the functioning of a real estate market if the estimated models are to still satisfy the qualitative requirements defined for them, and thereby produce accurate valuation results. A model database will be disturbed by the deviation of prices from model prices and by reducing its size. Radom generators were used to obtain database disturbances.
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BIANCHI, SERGIO, ALEXANDRE PANTANELLA, and AUGUSTO PIANESE. "EFFICIENT MARKETS AND BEHAVIORAL FINANCE: A COMPREHENSIVE MULTIFRACTIONAL MODEL." Advances in Complex Systems 18, no. 01n02 (February 2015): 1550001. http://dx.doi.org/10.1142/s0219525915500010.
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Real-world financial dynamics daily do challenge the credibility of the Efficient Market Hypothesis, the pillar of the whole martingale-based modern financial theory stating that at any time asset prices discount all past information. As a matter of fact, the empirical evidence accumulated so far indicates that current models cannot explain the complexity of financial market movements, to the extent that a strand of skeptical thought, the Behavioral Finance, has been booming. The question whether a model exists which is able to make consistent the two paradigms is a living matter that financial markets demand to address. The paper deals with a parsimonious stochastic model able to include as special cases both market efficiency and "psychological" phenomena such as the underreaction and the overreaction, peculiar features of the behavioral finance. The great readability of the model, its capability to agree the controversial results provided by literature on efficient markets and the simplicity of the financial intuition it offers are discussed.
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Ovcharov, A. O., and A. M. Terekhov. "Econometric analysis of the use of biological assets in agricultural organizations." Statistics and Economics 17, no. 1 (March 10, 2020): 79–87. http://dx.doi.org/10.21686/2500-3925-2020-1-79-87.
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The purpose of the study. The purpose is to analysis the use of biological assets through econometric models and quantifies the relationship between economic indicators of agricultural activity. The article is devoted to the possibilities of econometric analysis in the context of limited empirical data on Russia regarding the use of biological assets.Materials and methods. The article analyzed the Russian and foreign bibliography on the problems of biological assets research. In the context of the study of biological assets, the possibilities of using econometric analysis methods based on spatial, temporal or panel data are shown. A multi-regression model based on three groups of indicators (livestock and crop indicators, as well as indicators reflecting agricultural development in general) and implemented in two phases has been built. This model allowed making estimates of the impact of biological assets on the value of agricultural products in Russia. The methods of correlation analysis investigated the closeness of the relationship between the variables in the model. The initial data for this study were the annual data for the period 2000–2018. An array of more than 150 observations was used. For the purpose of comparability, this array has been converted into relative values, i.e. econometric analysis was carried out on growth rates.Results. This article highlights the main areas of research on biological assets presented in the works of Russian and foreign scientists-economists. It is concluded that there are a wide range of issues of assessment and accounting of biological assets in Russian publications and in the context of the transition to international reporting standards. These problems are not relevant for foreign researchers – in foreign publications presented mainly the search for effective mechanisms for assessing the market value of biological assets using complex econometric models. The article substantiates the importance of using econometric analysis methods in Russian conditions, highlights a number of areas of such analysis and presents a multifactorial regression model. The implementation of the model allowed quantifying the hypothesis of the strong impact of biological asset productivity on the value of agricultural organizations. Based on the construction of the trend line and the choice of the optimal value of the value of the value of the approximation, a short-term forecast of the value of agricultural products produced by livestock and crop production was made. In addition, the correlation matrix assesses the closeness of the relationship between economic indicators.Conclusion. Economic analysis of biological assets should include a variety of areas – valuation, accounting and auditing, insurance and leasing, efficient use and management. The debate between proponents and opponents of the valuation of biological assets at fair value as an alternative to historical value accounting is of particular relevance today. Many issues relating to the valuation and use of biological assets can be addressed by econometric analysis techniques. In Russian practice, this approach is not yet widespread. However, it is it that it quantifies the complex links between economic variables (including biological assets) that characterize agricultural activities.
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Antoine, Bertille, Kevin Proulx, and Eric Renault. "Pseudo-True SDFs in Conditional Asset Pricing Models*." Journal of Financial Econometrics 18, no. 4 (September 18, 2018): 656–714. http://dx.doi.org/10.1093/jjfinec/nby017.
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Abstract This article is motivated by the need to bridge some gap between modern asset pricing theory and recent developments in econometric methodology. While asset pricing theory enhances the use of conditional pricing models, econometric inference of conditional models can be challenging due to misspecification or weak identification. To tackle the case of misspecification, we utilize the conditional Hansen and Jagannathan (1997) (HJ) distance as studied by Gagliardini and Ronchetti (2016), but we set the focus on interpretation and estimation of the pseudo-true value defined as the argument of the minimum of this distance. While efficient Generalized Method of Moments (GMM) has no meaning for estimation of a pseudo-true value, the HJ-distance not only delivers a meaningful loss function, but also features an additional advantage for the interpretation and estimation of managed portfolios whose exact pricing characterizes the pseudo-true pricing kernel (stochastic discount factor (SDF)). For conditionally affine pricing kernels, we can display some managed portfolios which are well-defined independently of the pseudo-true value of the parameters, although their exact pricing is achieved by the pseudo-true SDF. For the general case of nonlinear SDFs, we propose a smooth minimum distance (SMD) estimator (Lavergne and Patilea, 2013) that avoids a focus on specific directions as in the case of managed portfolios. Albeit based on kernel smoothing, the SMD approach avoids instabilities and the resulting need of trimming strategies displayed by classical local GMM estimators when the density function of the conditioning variables may take arbitrarily small values. In addition, the fact that SMD may allow fixed bandwidth asymptotics is helpful regarding the curse of dimensionality. In contrast with the true unknown value for a well-specified model, the estimated pseudo-true value, albeit defined in a time-invariant (unconditional) way, may actually depend on the choice of the state variables that define fundamental factors and their scaling weights. Therefore, we may not want to be overly parsimonious about the set of explanatory variables. Finally, following Antoine and Lavergne (2014), we show how SMD can be further robustified to deal with weaker identification contexts. Since SMD can be seen as a local extension of the method of jackknife GMM (Newey and Windmeijer, 2009), we characterize the Gaussian asymptotic distribution of the estimator of the pseudo-true value using classical U-statistic theorems.
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Palić, Irena, Sabina Hodžić, and Ksenija Dumičić. "Personal Income Taxation Determinants in Federation of Bosnia and Herzegovina." Business Systems Research Journal 10, no. 1 (April 1, 2019): 153–63. http://dx.doi.org/10.2478/bsrj-2019-0011.
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Abstract Background: In recent years’ income inequality has been an economic issue. The primary instrument for redistributing income is personal income tax. However, based on economic theory income inequality concerns indicators such as wages, transfer payments, taxes, social security contributions, and geographical mobility. Objectives: The objective of this paper is to examine the impact of certain labor market indicators on personal income taxation in Federation of Bosnia and Herzegovina (FB&H). Methods/Approach: Since personal income taxation consists of a very broad definition and for the purpose of this research only, income from dependent (employment) activity is observed. The econometric analysis is conducted using error correction modeling, as well as forecast errors variance decomposition. Results: The error correction model is estimated, and the cointegrating equation indicates that monthly wage and number of employees statistically significantly positively affect personal income taxes in FB&H in the long-run. After two years, the selected labor market indicators explain a considerable part of forecasting error variance of personal income tax revenues. Conclusions: The implementation of reforms in the labor market and tax policies of the FB&H is suggested. In order to achieve necessary reforms, efficient governance and general stable political environment are required.
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Khoa, Bui Thanh, and Tran Trong Huynh. "Forecasting stock price movement direction by machine learning algorithm." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (December 1, 2022): 6625. http://dx.doi.org/10.11591/ijece.v12i6.pp6625-6634.
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<p><span lang="EN-US">Forecasting stock price movement direction (SPMD) is an essential issue for short-term investors and a hot topic for researchers. It is a real challenge concerning the efficient market hypothesis that historical data would not be helpful in forecasting because it is already reflected in prices. Some commonly-used classical methods are based on statistics and econometric models. However, forecasting becomes more complicated when the variables in the model are all nonstationary, and the relationships between the variables are sometimes very weak or simultaneous. The continuous development of powerful algorithms features in machine learning and artificial intelligence has opened a promising new direction. This study compares the predictive ability of three forecasting models, including <a name="_Hlk106797328"></a>support vector machine (SVM), artificial neural networks (ANN), and logistic regression. The data used is those of the stocks in the VN30 basket with a holding period of one day. With the rolling window method, this study got a highly predictive SVM with an average accuracy of 92.48%.</span></p>