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Journal articles on the topic 'Model of the financial market'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Evstigneeva, L., and R. Evstigneev. "Metamorphoses of Financial Capital." Voprosy Ekonomiki, no. 8 (August 20, 2013): 106–22. http://dx.doi.org/10.32609/0042-8736-2013-8-106-122.

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Financial capital is considered as a precondition of forming an integral market system. Based on financial capital a vertical market model is taking shape. It includes the following leading markets: strategic markets of financial capital, finance and money markets, markets of physical (cluster) capital, markets of social (consumers) capital. Markets of financial capital build the world reproduction model of synergetic character. Sustainability of the world market is maintained within the framework of the following types of big financial capital systems: cooperation of industrial and banking ca

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2

Sheng, Haoran. "Prediction of Gold ROI Based on LSTM model." BCP Business & Management 38 (March 2, 2023): 2925–29. http://dx.doi.org/10.54691/bcpbm.v38i.4212.

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The developed financial market system must develop the gold market and play an important role in the financial market. Like other financial markets, the gold market also faces the risk of price fluctuation. Although gold has the monetary attribute, its own value is stable, and it has the hedging function, the price of any commodity always fluctuates around its own value, and the market risk caused by gold price fluctuation is inevitable. At the same time, the gold market trading products are almost homogeneous, which determines that the price of gold in the domestic market and the domestic and

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Al-Ali, Ali Hameed Hindi, Ali Abdulameer Flaifel, and Hayder M. Kareem Al_Duhaidahawi. "A Financial Behavior Measurement Model to Evaluate the Financial Markets." International Journal of Professional Business Review 8, no. 5 (2023): e01417. http://dx.doi.org/10.26668/businessreview/2023.v8i5.1417.

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Purpose: This study examines the relationship between the financial behavior measurement models and evaluate the financial markets all sectors listed on Iraq Stock Exchange. The current study also to develop a quantitative model for measuring the financial behavior of investors in the financial markets, and thus knowing their behavior, therefore, determining the efficiency of the investment sectors that are being traded. Theoretical framework: Quantitatively measuring the financial behavior of investors is one of the important issues that have occupied specialists in the financial field due to

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Ilinski, Kirill N., and Alexander S. Stepanenko. "Electrodynamical Model of Quasi-Efficient Financial Markets." Advances in Complex Systems 01, no. 02n03 (1998): 143–48. http://dx.doi.org/10.1142/s0219525998000107.

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The modelling of financial markets presents a problem which is both theoretically challenging and practically important. The theoretical aspects concern the issue of market efficiency which may even have political implications (Cuthbertson, 1996), whilst the practical side of the problem has clear relevance to portfolio management (Elton and Gruber, 1995) and derivative pricing (Hull, 1997). Up till now all market models contain "smart money" traders and "noise" traders whose joint activity constitutes the market (De Long et al., 1990; Bak et al., 1997). On a short time scale this traditional

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Wang, Xue. "The time-varying co-movements between energy market and global financial market." Journal of Computing and Electronic Information Management 10, no. 1 (2023): 88–95. http://dx.doi.org/10.54097/jceim.v10i1.5763.

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Since the global financial crisis in 2008, international energy markets have become more closely linked to financial markets and energy prices have exhibited more financial characteristics. Therefore, it is of great theoretical and practical significance to study the time-varying synergy between the energy market and the global financial market. This paper sets up a model for realizing the time-varying co-movements between energy markets and global financial markets: It uses the Diebold &Yilmaz spillover index method and its dynamic expansion model to test the spillover mechanism of market

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Kochorba, Valeriia Yu. "Model of Interaction of Structural Elements of the Financial Market of Ukraine." PROBLEMS OF ECONOMY 2, no. 60 (2024): 254–63. http://dx.doi.org/10.32983/2222-0712-2024-2-254-263.

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The aim of the article is to improve the methodology of studying the financial market of Ukraine, analyzing the interaction between the components of the financial market, studying the reaction of the components of the financial market to sudden changes and forecasting the behavior of the structural elements of the financial market. The financial market plays a decisive role in the modern market economy of Ukraine, providing a mechanism for the redistribution of capital between creditors and investors through intermediaries based on the principles of supply and demand. The development of the f

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Pastushkov, A. "An Evolutionary Model of Financial Market Efficiency with Costly Information." Higher School of Economics Economic Journal 28, no. 2 (2024): 276–301. http://dx.doi.org/10.17323/1813-8691-2024-28-2-276-301.

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8

Choustova, Olga Al. "Quantum Bohmian model for financial market." Physica A: Statistical Mechanics and its Applications 374, no. 1 (2007): 304–14. http://dx.doi.org/10.1016/j.physa.2006.07.029.

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9

Betz, Frederick. "Models of Financial Markets." Asian Business Research 1, no. 2 (2016): 30. http://dx.doi.org/10.20849/abr.v1i2.88.

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Computer-based algorithms &amp; models have become important in trading in financial markets. We illustrate the significance of model analysis of financial systems by a case study of BlackRock’s analytical platform called ‘Aladdin’. The nature of the model used in a computer algorithm is central to its real performance. Unreal models in financial algorithms will yield inaccurate performances. We review five fundamental models of economic dynamics: (1) traditional price-equilibrium of a commodity market, (2) Keynes-Minsky financial transactions over time, (3) price-disequilibrium of a finan

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Guan, Zerui. "Simulation of Financial Market Performance and Algorithmic Economic Model based on Complex Network." BCP Business & Management 18 (April 13, 2022): 1–5. http://dx.doi.org/10.54691/bcpbm.v18i.527.

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At present, traditional macro-financial models such as random walk model and log-periodic power law model in academia cannot explain the stylized characteristics of financial markets. So, we propose a microscopic model that produces stylized characteristics of real financial markets. The model integrates the herding effect, the non-linear relationship of investors and the non-linear structure of the system very well. The research results show that the financial market model established in this paper can simulate most of the characteristics of the real financial market price time series relativ

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Zhou, Rongtian, Xiong Xiong, Bàrbara Llacay, and Gilbert Peffer. "Market Impact Analysis of Financial Literacy among A-Share Market Investors: An Agent-Based Model." Entropy 25, no. 12 (2023): 1602. http://dx.doi.org/10.3390/e25121602.

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Financial literacy has become increasingly crucial in today’s complex financial markets. This paper explores the impact of financial literacy on the stock market by establishing an artificial financial market that aligns with the characteristics of the Chinese A-share market using agent-based modeling. The study incorporates financial literacy into investors’ mixed beliefs and simulates their behavior in the market. The results show that improving individual investors’ financial literacy can improve market quality and investor performance, as well as reduce the unequal distribution of wealth t

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12

Li, Yanting. "A Test of Fama-French Five-Factor Model in Quantitative Easing." Highlights in Business, Economics and Management 40 (September 1, 2024): 789–93. http://dx.doi.org/10.54097/6722e485.

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In the evolving context of financial markets, the global financial crisis and subsequent quantitative easing policies have reignited scrutiny of the effectiveness of asset pricing models. This study employs the Fama-French methodology to conduct a detailed analysis of data from July 1963 to January 2024, a period encompassing significant economic shifts, to evaluate the robustness of the Fama-French three-factor and five-factor models under different market conditions. By examining five key factors—market excess returns, size premium, value premium, profitability, and investment style—across v

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Enow, Samuel Tabot. "Investigating mean reversion in financial markets using Hurst Model." International Journal of Research in Business and Social Science (2147- 4478) 12, no. 6 (2023): 197–201. http://dx.doi.org/10.20525/ijrbs.v12i6.2664.

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In the dynamic world of financial markets, the prices of assets can exhibit dramatic fluctuations, sometimes soaring to dizzying heights or plummeting to alarming lows. However, amidst the chaos, a fascinating phenomenon emerges: a tendency for prices to revert back to their long-term average or mean level. This concept known as mean reversion has intrigued traders, investors, and researchers for decades. Understanding mean reversion provides valuable insights into market dynamics, investor behavior, and the potential for profitable trading strategies. The aim of this study was to empirically

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Wu, Yifan, and Jun’an Dong. "Construction of the China financial pressure index measurement model based under the AHP-EWM-TOPSIS model." SHS Web of Conferences 169 (2023): 01018. http://dx.doi.org/10.1051/shsconf/202316901018.

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With the complexity of the internal structure of the financial market, systemic financial risks occur frequently. The cross cycle of the real economy and the financial system makes the bad problems in the economic development enter into the financial system with the transmission mechanism, thus leading to the reduction of the macroeconomic stability. Therefore, the foundation for preventing systemic financial risks and economic crises in the financial market is the accurate detection of pertinent potential threats. Based on relevant literature, combined with the characteristics of China’s fina

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Chen, Fan. "Deep Neural Network Model Forecasting for Financial and Economic Market." Journal of Mathematics 2022 (March 24, 2022): 1–10. http://dx.doi.org/10.1155/2022/8146555.

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Recently, the Internet financial market has developed rapidly both at home and abroad. Simultaneously, its study has also become the focus of academic circles. The financial markets have higher liquidity and volatility as compared to traditional financial markets. In view of the Internet financial market dynamic (volume and daily trading), it is proposed based on a deep neural network for fusion level time series prediction model. First, the proposed model processes the input of characteristic variables of multiple series (market macrodynamic series and multiseed series) and uses an attention

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Musin, Artur R. "Economic-mathematical model for predicting financial market dynamics." Statistics and Economics 15, no. 4 (2018): 61–69. http://dx.doi.org/10.21686/2500-3925-2018-4-61-69.

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Study purpose.Existing approaches to forecasting dynamics of financial markets, as a rule, reduce to econometric calculations or technical analysis techniques, which in turn is a consequence of preferences among specialists, engaged in theoretical research and professional market participants, respectively. The main study purpose is developing a predictive economic-mathematical model that allows combining both approaches. In other words, this model should be estimated using traditional methods of econometrics and, at the same time, take into account the impact on the pricing process of the eff

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GECZY, CHRISTOPHER C. "Financial market assumptions and pension plan models: a comment on PIMS model asset markets assumptions." Journal of Pension Economics and Finance 14, no. 2 (2015): 127–43. http://dx.doi.org/10.1017/s1474747214000432.

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AbstractThe financial market assumptions of the Pension Benefit Guaranty Corporation (PBGC)'s Pension Insurance Modeling System model are critical inputs to simulations for most apparent uses of the system. They currently appear to be based on a reduced form, ‘classical’ approach to assessing and forecasting the distribution of returns on various classes of input assets, allowing for a fairly sophisticated and useful approach to understanding simulated distributions of potential pension insurance outcomes as well as the net financial status of the PBGC. This technical note discusses some of th

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18

Kemetmüller, Thomas. "The Theory and Empirics of Financial Development in the East Asian Bond Markets." Vienna Journal of East Asian Studies 5, no. 1 (2014): 45–76. http://dx.doi.org/10.2478/vjeas-2014-0003.

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Abstract The Asian financial crisis marked a turning point in financial development in East Asia that brought the development of bond markets within the focus of policy-makers. This paper tracks the benefits of an advanced bond market, the current state of the East Asian corporate and government bond markets and their rapid evolution since the Asian crisis. Subsequently, a multivariate model is used to determine the endogenous economic and institutional factors that drove growth in the region’s bond markets. The following findings may be noted: (1) growth in the government bond market was driv

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19

Yeh, Wei-Chang, Yu-Hsin Hsieh, Kai-Yi Hsu, and Chia-Ling Huang. "ANN and SSO Algorithms for a Newly Developed Flexible Grid Trading Model." Electronics 11, no. 19 (2022): 3259. http://dx.doi.org/10.3390/electronics11193259.

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In the modern era, the trading methods and strategies used in the financial market have gradually changed from traditional on-site trading to electronic remote trading, and even online automatic trading performed by pre-programmed computer programs. This is due to the conduct of trading automatically and self-adjustment in financial markets becoming a competitive development trend in the entire financial market, with the continuous development of network and computer computing technology. Quantitative trading aims to automatically form a fixed and quantifiable operational logic from people’s i

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20

BIANCHI, SERGIO, ALEXANDRE PANTANELLA, and AUGUSTO PIANESE. "EFFICIENT MARKETS AND BEHAVIORAL FINANCE: A COMPREHENSIVE MULTIFRACTIONAL MODEL." Advances in Complex Systems 18, no. 01n02 (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 financia

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21

Ruan, Lei. "Research on Sustainable Development of the Stock Market Based on VIX Index." Sustainability 10, no. 11 (2018): 4113. http://dx.doi.org/10.3390/su10114113.

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The frequent occurrence of financial crises has made the dynamic linkage between international financial markets an important research topic. In the past, scholars mostly studied the correlation between financial markets directly, however ignored the impact of exogenous financial variables on financial markets. The stock market is an important part of the financial market and plays an important role in the overall economy. Information asymmetry is common and has a certain degree of impact on investors’ returns. However, many scholars believe that the problem of information asymmetry in China h

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Ji, Xiuping, Sujuan Wang, Honggen Xiao, Naipeng Bu, and Xiaonan Lin. "Contagion Effect of Financial Markets in Crisis: An Analysis Based on the DCC–MGARCH Model." Mathematics 10, no. 11 (2022): 1819. http://dx.doi.org/10.3390/math10111819.

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Global crises have created unprecedented challenges for communities and economies across the world, triggering turmoil in global finance and economy. This study adopts the dynamic conditional correlation multiple generalized autoregressive conditional heteroskedasticity (DCC–MGARCH) model to explore contagion effects across financial markets in crisis. The main findings are as follows: (1) the financial crisis and COVID-19 pandemic intensified the connection between the Chinese and US stock markets in the short term; (2) the dynamic conditional correlations (DCCs) during the COVID-19 pandemic

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23

Linh, Phan Thi. "Forecasting the Crisis of Vietnam's Financial Market by Markov Switching VAR Model." Journal of Hunan University Natural Sciences 49, no. 2 (2022): 259–68. http://dx.doi.org/10.55463/issn.1674-2974.49.2.26.

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The global economy and financial markets have experienced "The most adverse shock in a century" due to the impact of the Covid-19 epidemic but are also transforming enormously in the digital era. Besides, Vietnam's financial system has been making vital development steps, increasing its resilience. Still, its development prospects depend mainly on the recovery of the global economy and financial markets, the Stability of the economy, and the Stability of the economic stability and sustainability of investor confidence in the market. The Markov Switching Var (MSVAR) model will measure the crisi

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Rim, Hong, and Robert Setaputra. "The Impacts Of The U.S. Financial Crisis On Financial Markets In Asia And Europe." International Business & Economics Research Journal (IBER) 11, no. 1 (2011): 45. http://dx.doi.org/10.19030/iber.v11i1.6670.

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This study is to examine the impacts of the U.S. financial crisis (2008) on a few financial markets in Asia and Europe in the framework of vector auto-regressive model. This study uses daily returns of the stock market indexes during January 2005-February 2010. Some important findings are: 1) the U.S. market became more integrated with Asian markets during the crisis but less integrated with European markets; 2) the U.S. influence remained strong in both Asia and Europe during the U.S. crisis; 3) the speed of adjustments increased in some markets but decreased in other markets; and 4) there we

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Mai, Ziting. "A Literature Study of the Stock Market Volatility." BCP Business & Management 44 (April 27, 2023): 150–55. http://dx.doi.org/10.54691/bcpbm.v44i.4806.

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This review explains and explores the performance of stock volatility in financial markets and historical research to understand the operation of financial markets. From finding the meaning of the existence of the financial market to understanding what the stock volatility is, gradually understanding the measurement methods of various stock volatility, and finally comparing the actual application of stock volatility in financial markets with different development levels. Through specific enumeration of GARCH family analysis methods and combined with application case analysis, such as ARCH mode

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Wray, Christopher M., and Steven R. Bishop. "A Financial Market Model Incorporating Herd Behaviour." PLOS ONE 11, no. 3 (2016): e0151790. http://dx.doi.org/10.1371/journal.pone.0151790.

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GRORUD, AXEL, and MONIQUE PONTIER. "FINANCIAL MARKET MODEL WITH INFLUENTIAL INFORMED INVESTORS." International Journal of Theoretical and Applied Finance 08, no. 06 (2005): 693–716. http://dx.doi.org/10.1142/s0219024905003219.

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We develop a financial model with an "influential informed" investor who has an additional information and influences asset prices by means of his strategy. The prices dynamics are supposed to be driven by a Brownian motion, the informed investor's strategies affect the risky asset trends and the interest rate. Our paper could be seen as an extension of Cuoco and Cvitanic's work [4] since, as these authors, we solve the informed influential investor's optimization problem. But our main result is the construction of statistical tests to detect if, observing asset prices and agent's strategies,

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Palatella, Luigi. "A reflexive toy-model for financial market." Physica A: Statistical Mechanics and its Applications 389, no. 2 (2010): 315–22. http://dx.doi.org/10.1016/j.physa.2009.09.037.

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Cafferata, Alessia, and Fabio Tramontana. "A financial market model with confirmation bias." Structural Change and Economic Dynamics 51 (December 2019): 252–59. http://dx.doi.org/10.1016/j.strueco.2019.08.004.

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Denys, M., T. Gubiec, and R. Kutner. "Reinterpretation of Sieczka-Hołyst Financial Market Model." Acta Physica Polonica A 123, no. 3 (2013): 513–17. http://dx.doi.org/10.12693/aphyspola.123.513.

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Vashishtha, Ashutosh, and Anil K. Sharma. "Indian financial market regulation: A dialectic model." Journal of Economics and Business 64, no. 1 (2012): 77–89. http://dx.doi.org/10.1016/j.jeconbus.2011.05.002.

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Popescu, Andrei-Dragos, and Cristi Spulbar. "FINANCIAL DIGITAL ASSETS AND THEIR INTERACTIONS WITH THE TRADITIONAL FINANCIAL MARKETS: A DSGE ANALYSIS." Social Sciences and Education Research Review 10, no. 1 (2023): 284–313. https://doi.org/10.5281/zenodo.8241416.

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We start from the premise that all markets, regardless of the shocks they experience, tend toward equilibrium. This is a characteristic that has been identified for any type of market, as the balance is required to be achieved in order for them to evolve. We are evolving a Dynamic General Stochastic Equilibrium model (DSGE) in order to assess and analysis the capital flows of shocks identified within different digital and traditional markets. The model is based on the fundamental theory of general equilibrium which attempts to describe the fluctuations based on supply, demand, and prices in a

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Joseph, Angelo D. "Emerging Market Default Risk Charge Model." Journal of Risk and Financial Management 16, no. 3 (2023): 194. http://dx.doi.org/10.3390/jrfm16030194.

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In a default event, several obligors simultaneously experience financial difficulty in servicing their debt to the point where the entire market can experience a sudden yet significant jump to a credit default. To help protect lenders against a jump-to-default event, regulators require banks to hold capital equivalent to the default risk charge as a buffer against the losses they may incur. The Basel regulatory committee has articulated and set default risk modelling guidelines to improve comparability amongst banks and enable a consistent bank-wide default risk charge estimation. Emerging mar

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Ciobanu, Ghenadie, Mihai Dinu, Oana Camelia Iacob (Pârgaru), and Victor George Constantinescu. "Digital Labour Market Model and Financial Opportunities in the Context of Sustainable Development in the EU Countries." European Journal of Sustainable Development 11, no. 3 (2022): 15. http://dx.doi.org/10.14207/ejsd.2022.v11n3p15.

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Technological opportunities have a transformative impact on labour markets. In this article, we aim to study the ways in which digital technologies contribute to the development of the digital model of the labour market and digital platforms. We aim to highlight digital opportunities to support efforts to ensure the development of strategies, policies and labour market transformations. We intend to build the digital model of the labour market within the model of the systemic digital economy, in close connection with other digitalization models (business, financial markets, public finance, comm

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IRSHAD, Shoaib, Muzammil KHURSHİD, Waqar BADSHAH, and Mehmet BULUT. "Volatility Spillovers from US to Emerging Seven Stock Markets: Pre & Post Analysis of GFC." International Journal of Contemporary Economics and Administrative Sciences 11, no. 1 (2021): 046–59. https://doi.org/10.5281/zenodo.5136385.

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<strong>Abstract</strong> This study is conducted to check volatility spillovers from the US to Emerging seven stock markets before and after the Global Financial Crisis through the VAR-GARCH model. The pre The Global Financial Crisis (GFC) sub-sample data ranges from January 8, 2002 to June 29, 2007 and Post GFC data starts from July 4, 2009 to December 28, 2014. The outcomes of the VAR-GARCH model show that there are significant volatility spillovers from US stock market to emerging seven stock markets in most cases. The correlations reveal that the US stock market is strongly correlated wit

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Machek, Ondřej, Luboš Smrčka, Jiří Hnilica, Markéta Arltová, and Dimitrios P. Tsomocos. "General Equilibrium Analysis of the Czech Financial Market and a Financial Fragility Model." Politická ekonomie 62, no. 4 (2014): 437–58. http://dx.doi.org/10.18267/j.polek.963.

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Paskaleva, Mariya, and Ani Stoykova. "GLOBALIZATION EFFECTS ON CONTAGION RISKS IN FINANCIAL MARKETS." Ekonomicko-manazerske spektrum 15, no. 1 (2020): 38–54. http://dx.doi.org/10.26552/ems.2021.1.38-54.

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Financial globalization has opened international capital markets to investors and companies worldwide. However, the global financial crisis also caused massive stock price volatility due in part to global availability of market information. We explore ten EU member states (France, Germany, the United Kingdom, Belgium, Bulgaria, Romania, Greece, Portugal, Ireland, and Spain), and the USA. The explored period is March 3, 2003 to June 30, 2016, and includes the effects of the global financial crisis of 2008. The purpose of the article is to determine whether there is a contagion effect between th

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Espinosa-Vega, Marco A., and Chong K. Yip. "Government financing in an endogenous growth model with financial market restrictions." Economic Theory 20, no. 2 (2002): 237–57. http://dx.doi.org/10.1007/s001990100225.

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Mabeba, Mahlatse. "The Effect of Financial Market Depth on Economic Growth in Developing Countries with Large Financial Sectors." Social Science Studies 4, no. 2 (2024): 66–81. http://dx.doi.org/10.47153/sss42.8022024.

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The financial market depth has emerged as a phenomenon shaping developing economies with large financial sectors. This paper presents the effect of financial market depth on economic growth in developing countries with large financial sectors from 1996 to 2022. While developing countries are typically characterized by lower levels of economic development and industrialization, some of them may have relatively large financial sectors. These countries include Brazil, India, Indonesia, Malaysia, Mexico, and South Africa. We utilize the random effects model, a panel data econometrics model, to est

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Wulandari, Vera Pipin, and Kusdhianto Setiawan. "ANALYSIS OF MARKET TIMING TOWARD LEVERAGE OF NON-FINANCIAL COMPANIES IN INDONESIA." Journal of Indonesian Economy and Business 30, no. 1 (2015): 42. http://dx.doi.org/10.22146/jieb.7333.

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ABSTRACTThis study aimed to examine the effect of market timing on leverage on non-financial compa-nies in Indonesia. Market timing was tested on the hot and cold market conditions. Hot and cold markets are determined by the monthly market to book ratio. A hot (cold) market occurs when the average market to book ratio of a particular month is above (below) the value of the moving average of the monthly market to book ratio. This study also aimed to test whether non-financial companies in Indonesia persistently applied leverage policies. This study used two research models. The first model was

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Moskvyak, Yaroslava, Anatolii Kucher, Sviatoslav Kniaz, Nelli Heorhiadi, and Oleksii Fedorchak. "Construction of a model for forecasting the rationality of financial decisions under the conditions of financial markets digitalization." Eastern-European Journal of Enterprise Technologies 2, no. 13 (134) (2025): 38–50. https://doi.org/10.15587/1729-4061.2025.325518.

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The object of this study is to predict the rationality of financial decisions in the context of digitalization of financial markets. In the context of digitalization of financial markets, about ¼ of financial decisions turn out to be irrational for financial market participants. Under these conditions, the problem is the inability of financial market participants to predict the rationality of financial decisions. The devised multi-vector model for predicting the rationality of financial decisions in the context of digitalization of financial markets makes it possible to evaluate key indicators

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Cont, Rama, and Jean-Philipe Bouchaud. "HERD BEHAVIOR AND AGGREGATE FLUCTUATIONS IN FINANCIAL MARKETS." Macroeconomic Dynamics 4, no. 2 (2000): 170–96. http://dx.doi.org/10.1017/s1365100500015029.

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We present a simple model of a stock market where a random communication structure between agents generically gives rise to heavy tails in the distribution of stock price variations in the form of an exponentially truncated power law, similar to distributions observed in recent empirical studies of high-frequency market data. Our model provides a link between two well-known market phenomena: the heavy tails observed in the distribution of stock market returns on one hand and herding behavior in financial markets on the other hand. In particular, our study suggests a relation between the excess

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Liu, Yirou. "Positive Affect of Financial Derivatives onThe Stock Market." Advances in Economics, Management and Political Sciences 7, no. 1 (2023): 163–70. http://dx.doi.org/10.54254/2754-1169/7/20230229.

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The derivatives market is widely recognized in financial markets, and it has developed rapidly, but there is little evidence that it contributed to the development of financial and economic markets. This article investigates the dynamic relationship between the Indian derivatives market and the stock market to determine how it affects market pricing. This paper use the DCC-garCH model to examine the dynamics of India from the third quarter of 2018 to 2022, I find that the financial derivatives market is more financially contagious than the equity market. Therefore, I can analyse that the devel

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Han, Zhenyu. "Forecast Research on the Fluctuation Risk of Green Financial Market in China based on the GARCH-LSTM Mixed Model." Highlights in Business, Economics and Management 9 (June 13, 2023): 549–69. http://dx.doi.org/10.54097/hbem.v9i.9233.

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With the rapid development of China’s green financial market, there is also the problem of uncertain risk of fluctuation in the transaction price of green financial products. Therefore, it is imperative to give play to the role of price fluctuations in early warning of risks in green financial markets. Based on the closing price data of green stock market and green bond market from April 19, 2018 to April 18, 2023, this paper combines the traditional time series model and deep learning model to fit and forecast the yield volatility of green financial market, and quantifies the risk value of gr

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Paskaleva, Mariya, and Ani Stoykova. "Globalization Effects on Contagion Risks in Financial Markets." SHS Web of Conferences 92 (2021): 03021. http://dx.doi.org/10.1051/shsconf/20219203021.

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Research background: Financial globalization has opened international capital markets to investors and companies worldwide. However, the global financial crisis has created big volatility in the stock prices that induces a restriction in the reflection of full information. We explore ten EU Member States (France, Germany, The United Kingdom, Belgium, Bulgaria, Romania, Greece, Portugal, Ireland, Spain), and the USA. The explored period is 03.03.2003 - 30.06.2016, as it includes the effects of the global financial crisis of 2008. Purpose of the article: To determine if there is a contagion effe

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Olkhov, Victor. "Financial Variables, Market Transactions, and Expectations as Functions of Risk." International Journal of Financial Studies 7, no. 4 (2019): 66. http://dx.doi.org/10.3390/ijfs7040066.

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This paper develops methods and a framework of financial market theory. We model financial markets as a system of agents which perform market transactions with other agents under the action of numerous expectations. Agents’ expectations are formed of economic and financial variables, market transactions, the expectations of other agents, and other factors that impact financial markets. We use the risk ratings of agents as their coordinates and approximate a description of financial variables, market transactions, and expectations of numerous separate agents by density functions of aggregated a

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Chandrasekara, Vasana, Chandima Tilakaratne, and Musa Mammadov. "An Improved Probabilistic Neural Network Model for Directional Prediction of a Stock Market Index." Applied Sciences 9, no. 24 (2019): 5334. http://dx.doi.org/10.3390/app9245334.

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Financial market prediction attracts immense interest among researchers nowadays due to rapid increase in the investments of financial markets in the last few decades. The stock market is one of the leading financial markets due to importance and interest of many stakeholders. With the development of machine learning techniques, the financial industry thrived with the enhancement of the forecasting ability. Probabilistic neural network (PNN) is a promising machine learning technique which can be used to forecast financial markets with a higher accuracy. A major limitation of PNN is the assumpt

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Wang, Z. G., Y. Q. Sun, and Y. Zheng. "Study of the Dynamical Model for Manufacturing and Materials Market." Key Engineering Materials 693 (May 2016): 1954–59. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1954.

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Econophysics is a new interdiscipline where physics concept and methods are applied to financial analysis. For example, the application of theoretical physics in the modeling of financial markets has aroused wide concern. In the process of random fluctuation of prices in financial markets, many nonlinear dynamical problems are hidden in set coefficients and assumptions, resulting in the invisibility of market price fluctuations and unavailability of hidden benefits in fluctuations. Based on the analysis of price fluctuation mechanism in financial markets, this paper analyzes the characteristic

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Abdelhedi, Mouna, and Mouna Boujelbène-Abbes. "Transmission of shocks between Chinese financial market and oil market." International Journal of Emerging Markets 15, no. 2 (2019): 262–86. http://dx.doi.org/10.1108/ijoem-07-2017-0244.

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Purpose The purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period. Design/methodology/approach This study used the daily and monthly China market price index, oil-price index and composite index of Chinese investor’s sentiment. The authors first use the DCC GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to capture both time- and frequency-varying features of co-

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Popov, Evgeny, Anna Veretennikova, and Sergey Fedoreev. "The Model of OTC Securities Market Transformation in the Context of Asset Tokenization." Mathematics 10, no. 19 (2022): 3441. http://dx.doi.org/10.3390/math10193441.

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The relevance of this study stems from the fact that the development of a market for financial instruments can significantly expand lending opportunities for small- and medium-sized businesses. While research on the impact of tokenization on financial markets is extensive, literature provides virtually no description of mathematical models that can be used in the design and development of information systems issuing tokenized financial instruments. Thus, the study aims to develop mathematical models representing the transformation of the over-the-counter (OTC) securities market induced by the

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