Search results
1 – 10 of over 1000To conceptualize a new approach to economic development that fully embraces its fractal complexity, providing a basis for sustained socioeconomic welfare within cultures that…
Abstract
Purpose
To conceptualize a new approach to economic development that fully embraces its fractal complexity, providing a basis for sustained socioeconomic welfare within cultures that encourage collaborative democracy and social learning.
Design/methodology/approach
Following the premise that healthy development must follow the natural laws of growth that apply to all ecosystems, the paper examines fractal intricacy as the basis of economic systems that are able to sustain sufficient flows of energy and information to all sub‐systems. Two methodological approaches that emerge for planning are called hierarchical (fractal) coherence and fractal connectivity. The first refers to sufficient density and variety of nodes (firms, economic processes, customers, etc.) at all scales in the hierarchy of an economic system; and the second denotes multiple paths of connection between the nodes, to handle the necessary flows.
Findings
This approach highlights the fundamental importance of locally‐based entrepreneurship and democratic control, and also suggests new methods for measuring system interconnectedness at all scales, supplementing economic growth measures such as GDP.
Research limitations/implications
The paper indicates the need for empirical research to calibrate and further refine the approach in real‐world settings.
Practical implications
The paper outlines a fresh planning strategy for dealing with the geometrically worsening dimensions of uneven economic development and poverty, at all levels of scale from the local to the global.
Originality/value
The paper articulates a viable cybernetic alternative to prevailing economic development approaches that are based on the neo‐classical, neo‐liberal, and neo‐conservative models embodied in our present system of economic globalization.
Details
Keywords
Faheem Aslam, Paulo Ferreira and Wahbeeah Mohti
The investigation of the fractal nature of financial data has been growing in the literature. The purpose is to investigate the multifractal behavior of frontier markets using…
Abstract
Purpose
The investigation of the fractal nature of financial data has been growing in the literature. The purpose is to investigate the multifractal behavior of frontier markets using multifractal detrended fluctuation analysis (MFDFA).
Design/methodology/approach
This study used daily closing prices of nine frontier stock markets up to 31-Aug-2020. A preliminary analysis reveals that these markets exhibit fat tails and clustering patterns. For a more robust analysis, a combination of Seasonal and Trend Decomposition using Loess (STL) and MFDFA has been employed. The former method is used to decompose daily stock returns, where later detected the long rang dependence in the series.
Findings
The results confirm varying degree of multifractality in frontier stock markets, implying that they exhibit long-range dependence. Based on these multifractality levels, Serbian and Romanian stock markets are the ones exhibiting least long-range dependence, while Slovenian and Mauritius stock markets indicating highest dependence in their series. Furthermore, the markets of Kenya, Morocco, Romania and Serbia exhibit mean reversion (anti-persistent) behavior while the remaining frontier markets show persistent behaviors.
Practical implications
The information given by the detection of the fractal measure of data can support for investment and policymaking decisions.
Originality/value
Frontier markets are of great potential from the perspective of international diversification. However, most of the research focused on other emerging and developed markets, especially in the context of multifractal analysis. This study combines the STL method and a physics-based robust technique, MFDFA to detect the multifractal behavior of frontier stock markets.
Details
Keywords
Maria Mora Rodríguez, Francisco Flores Muñoz and Diego Valentinetti
The purpose of this paper is to explore the impact of recent developments in corporate reporting, specifically from the carbon disclosure project (CDP) environment, in the…
Abstract
Purpose
The purpose of this paper is to explore the impact of recent developments in corporate reporting, specifically from the carbon disclosure project (CDP) environment, in the evolution of European post-crisis financial markets.
Design/methodology/approach
Theoretical and instrumental advancements from nonlinear dynamics have been applied to the analysis of market behaviour and the online presence or reputation of major European listed banks.
Findings
The application of a nonlinear statistical methodology (i.e. the autoregressive fractionally integrated moving average [ARFIMA] estimation model) demonstrates the presence of a long history of collected data, thus indicating a certain degree of predictability in the time series. Also, this study confirms the existence of structural breakpoints, specifically the impact of the CDP reporting in both stock prices and online search trends of the sampled companies for certain periods.
Research limitations/implications
This study introduces new methodological perspectives in corporate reporting studies, as the application of nonlinear techniques can be more effective in capturing corporate transparency issues. A limitation to overcome is to explore whether the impact of reporting is different due to the specific reporting behaviour each company adopts.
Practical implications
The “breakpoint” concept should enlighten the importance to firms of providing more information in specific moments, which can impact on both traditional (i.e. stock prices) and modern (i.e. online popularity) performance metrics. Additionally, it should be taken into account by stakeholders, when analysing the accountability of firms to improve their decision-making processes and policymakers, for monitoring and contrasting speculative and insider trading activities.
Social implications
Online search trends represent a new public attitude to how society “measures” the effectiveness of firms’ disclosure behaviours.
Originality/value
Combining ARFIMA with structural break techniques can be regarded as a relevant and complementary addition to classic “market reaction” or “value relevance” techniques.
Details
Keywords
Asset pricing dynamics in a multi-asset framework when investors’ trading exhibits the disposition effect is studied. The purpose of this paper is to explore asset pricing…
Abstract
Purpose
Asset pricing dynamics in a multi-asset framework when investors’ trading exhibits the disposition effect is studied. The purpose of this paper is to explore asset pricing dynamics and the switching behavior among multiple assets.
Design/methodology/approach
The dynamics of complex financial markets can be best explored by following agent-based modeling approach. The artificial financial market is populated with traders following two heterogeneous trading strategies: the technical and the fundamental trading rules. By simulation, the switching behavior among multiple assets is investigated.
Findings
The proposed framework can explain important stylized facts in financial time series, such as random walk price dynamics, bubbles and crashes, fat-tailed return distributions, absence of autocorrelation in raw returns, persistent long memory of volatility, excess volatility, volatility clustering and power-law tails. In addition, asset returns possess fractal structure and self-similarity features; though the switching behavior is only allowed among the asset markets.
Practical implications
The model demonstrates stylized facts of most real financial markets. Thereafter, the proposed model can serve as a testbed for policy makers, scholars and investors.
Originality/value
To the best of knowledge, no research has been conducted to introduce the disposition effect to a multi-asset agent-based model.
Details
Keywords
Yaoqi Guo, Jianbo Huang and Hui Cheng
Recently, many scholars have been paying more attention to studying the existence and application of multifractality. However, most researches concentrate on studying multifractal…
Abstract
Purpose
Recently, many scholars have been paying more attention to studying the existence and application of multifractality. However, most researches concentrate on studying multifractal features of returns or volume separately, and ignore the correlation between them. The purpose of this paper, therefore, is to give an empirical test on multifractal features of price‐volume correlation in China metal futures market and then to conduct a comparative analysis from time and space dimensions, in order to better understand metals futures market behavior.
Design/methodology/approach
This paper gives an empirical test by means of multifractal detrended cross‐correlation analysis (MF‐DCCA) approach, which is a technique employed in statistical physics to detect multifractal features of two cross‐correlated nonstationary time series.
Findings
Empirical results show that the price‐volume correlation in China metal futures market is multifractal and that long range correlation and non‐Gaussian probability distribution are the main reasons for the existence of multifractality. Also, a comparative analysis is conducted and it is found that although China metal futures market is becoming more and more effective, the effectiveness is lower than that in mature LME metal futures markets. The futures market still needs further development.
Originality/value
The paper's conclusions would help to understand the nonlinear dependency relationship and potential dynamics mechanism in price‐volume correlation.
Details
Keywords
Miriam Sosa, Edgar Ortiz and Alejandra Cabello-Rosales
The purpose of this research is to analyze the Bitcoin (BTC) and Ether (ETH) long memory and conditional volatility.
Abstract
Purpose
The purpose of this research is to analyze the Bitcoin (BTC) and Ether (ETH) long memory and conditional volatility.
Design/methodology/approach
The empirical approach includes ARFIMA-HYGARCH and ARFIMA-FIGARCH, both models under Student‘s t-distribution, during the period (ETH: November 9, 2017 to November 25, 2021 and BTC: September 17, 2014 to November 25, 2021).
Findings
Findings suggest that ARFIMA-HYGARCH is the best model to analyze BTC volatility, and ARFIMA-FIGARCH is the best approach to model ETH volatility. Empirical evidence also confirms the existence of long memory on returns and on BTC volatility parameters. Results evidence that the models proposed are not as suitable for modeling ETH volatility as they are for the BTC.
Originality/value
Findings allow to confirm the fractal market hypothesis in BTC market. The data confirm that, despite the impact of the Covid-19 crisis, the dynamics of BTC returns, and volatility maintained their patterns, i.e. the way in which they evolve, in relation to the prepandemic era, did not change, but it is rather reaffirmed. Yet, ETH conditional volatility was more affected, as it is apparently higher during Covid-19. The originality of the research lies in the focus of the analysis, the proposed methodology and the variables and periods of study.
Details
Keywords
Burak Erkut, Tugberk Kaya, Marco Lehmann-Waffenschmidt, Mandeep Mahendru, Gagan Deep Sharma, Achal Kumar Srivastava and Mrinalini Srivastava
The purpose of this paper is to propose an integrative framework bringing together results from neuroplasticity and decision-making from a neuroscience perspective with those from…
Abstract
Purpose
The purpose of this paper is to propose an integrative framework bringing together results from neuroplasticity and decision-making from a neuroscience perspective with those from market plasticity, i.e. with which practices market actors shape markets.
Design/methodology/approach
Provided that developments in neuroscience indicate that training the brain for orientation toward efficient decision-making processes under uncertainty is possible, an in-depth analysis can be conducted by using the integrative framework, which was set up by the authors for advancing research efforts in neuroeconomics and neurofinance on these lines.
Findings
Markets have a plastic character; they can change shape and form and remain in that way thereafter. The marketers have always been causing this change to succeed in their marketing strategies and efforts. Plasticity, hitherto considered by marketing, market sociology and evolutionary economics, has a potential in financial decision-making processes, especially regarding its role in training the brain for stable financial decisions.
Research limitations/implications
The theoretical approach can be incorporated for delivering an alternative representation of the knowledge processes associated with financial decisions.
Practical implications
The practical approach can be used for improving the practical aspects of financial decision-making processes.
Originality/value
The contribution is the first of its kind which integrates neuroscience approaches of plasticity and decision-making with the concept of market plasticity from the literature on economics and management, showing their similarities and opening a new front of discussion on how these two approaches can learn from each other to increase the explanatory power of financial decision-making processes and to gain new insights for financial decision makers on how to make more efficient financial decisions in the times of uncertainty.
Details
Keywords
Kingstone Nyakurukwa and Yudhvir Seetharam
The authors’ goal is to provide an overview and historical context for the various alternatives to the efficient market hypothesis (EMH) that have emerged over time. The authors…
Abstract
Purpose
The authors’ goal is to provide an overview and historical context for the various alternatives to the efficient market hypothesis (EMH) that have emerged over time. The authors found eight current alternatives that have emerged to address the EMH's flaws. Each of the proposed alternatives improves some of the assumptions made by the EMH, such as investor homogeneity, the immediate incorporation of information into asset values and the inadequacy of rationality to explain asset prices.
Design/methodology/approach
To come up with the list of studies relevant to this review article, the authors used three databases, namely Scopus, Web of Science and Google Scholar. The first two were mostly used to get peer-reviewed articles while Google Scholar was used to extract articles that are still work in progress. The following words were used as the search queries; “efficient market hypothesis” and “alternatives to the efficient market hypothesis”.
Findings
The alternatives to the EMH presented in this article demonstrate that market efficiency is a dynamic concept that can be best understood with a multidisciplinary approach. To better comprehend how financial markets work, it is crucial to draw on concepts, theories and ideas from a variety of disciplines, including physics, economics, anthropology, sociology and others.
Originality/value
The authors comprehensively summarise the current state of the behavioural finance literature on alternatives to the EMH.
Details
Keywords
Christian Acuña-Opazo and Alejandro Álvarez-Marín
La presente investigación examina la existencia de memoria de largo plazo por medio del cálculo del coeficiente de Hurst y Hurst ajustado, y del análisis de características de…
Abstract
Propósito
La presente investigación examina la existencia de memoria de largo plazo por medio del cálculo del coeficiente de Hurst y Hurst ajustado, y del análisis de características de estructuras caóticas en la serie del mercado bursátil de Chile, específicamente a través del Índice de Precios Selectivo de Acciones.
Diseño/metodología/enfoque
Se desarrolló un breve análisis del mercado, según la metodología de Box y Jenkings. La validez de los resultados se realizó por medio de la prueba propuesta por Brock, Dechert y Scheinkman. En segundo lugar, se procedió a analizar la dinámica y patrones del índice y de su rendimiento, para observar si existía evidencia de memoria de largo plazo.
Hallazgos
Los resultados demuestran la presencia de esta memoria en el mercado bursátil chileno, determinado a través del índice accionario en dos escalas, diaria y trimestral, lo que además corrobora resultados obtenidos por otros autores, confirmando el uso de la metodología de Rango Re-escaldo para la identificación y determinación de memoria de largo plazo en una serie temporal.
Originalidad/valor
Este estudio permitirá a futuros investigadores realizar análisis similares en otros mercados, aportando un nuevo enfoque al analizar la memoria de la largo plazo y los factores que inciden en ella.
Palabras clave
Exponente de Hurst, Índice bursátil, Mercados eficientes, Mercados fractales
Tipo de artículo
Artículo de investigación
Purpose
This research examined the existence of long-term memory by calculating the coefficient of Hurst and Hurst set, and the analysis of characteristics of chaotic structures in the series of stock market of Chile, specifically through the Selective Price Index Shares.
Design/methodology/approach
A brief analysis of the market was developed, according to Box and Jenkins methodology. The validity of the results was performed by means of the test proposed by Brock, Dechert and Scheinkman. Secondly, we proceeded to analyze the dynamics and patterns of the index and its performance, to see if there was evidence of long-term memory.
Findings
The results demonstrate the presence of long-term memory in the Chilean stock market, determined by stock index in two scales, daily and quarterly, which also corroborates results obtained by other authors, confirming the use of the methodology Range Re-scalded for the identification and determination of long-term memory in a time series.
Originality/value
This study will allow future researchers to perform similar analyzes in other markets, providing a new approach when analyzing the long-term memory and the factors that affect it.
Details
Keywords