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Journal articles on the topic 'Stocks - Prices - Econometric models'

Author: Grafiati

Published: 4 June 2021

Last updated: 30 January 2023

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1

Akbulaev, Nurkhodzha, Basti Aliyeva, and Shehla Rzayeva. "Analysis of the Influence of the Price of Raw Oil and Natural Gas on the Prices of Indices and Shares of the Turkish Stock Exchange." Pénzügyi Szemle = Public Finance Quarterly 66, no. 1 (2021): 151–66. http://dx.doi.org/10.35551/pfq_2021_1_8.

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This article is a review on the impact of prices and their dependence on the cost of oil and natural gas on the world stock markets. The main studies and results achieved in the field of the impact of prices on both the stock index and industrial stocks and the dependence on the level of oil prices are presented. The paper presents an econometric study on the choice of offers on the securities market that allows us to identify the main specifics of changes in prices for the stock index and industrial shares in the daily period from 13. 05. 2012 to 01. 12. 2019. The article uses methods for est

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Zhu, Rong, Zuo Quan Zhang, Xiao Yue Li, Xuan Wu, and Su Zhang. "The Study on the Plasticity Theoretical Models of the Volatility of Stock Prices." Advanced Materials Research 518-523 (May 2012): 5963–67. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.5963.

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This paper analyzes the characteristics of the stock price fluctuation compared with elastic-plastic theory in mechanics and introduces the concept of stock equilibrium price, plasticity of stock price analogically. A basic model of the stock plasticity under the relationship between stock price fluctuation and trading volume changes is also built. Tested by 20 kinds of stocks from Shanghai and Shenzhen stock markets in China by using the econometric analysis software Eviews3.0 afterwards, the basic model is improved, and three developed models are built from it. Finally, this paper obtains mo

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3

Nautiyal, Neeraj, and P. C. Kavidayal. "Analysis of Institutional Factors Affecting Share Prices: The Case of National Stock Exchange." Global Business Review 19, no. 3 (March 14, 2018): 707–21. http://dx.doi.org/10.1177/0972150917713865.

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This study offers empirical findings on the impact of institutional variables on firm’s stock market price performance. In order to identify the influence of companies financial on NIFTY 50 Index, our sample consists of balanced panel of 30 actively traded companies (that becomes the study’s index representative) over a massive transition period, 1995–2014. Attempts have been made with a wide range of econometric models and estimators, from the relatively straightforward to (static) more complex (dynamic panel analyses) to deal with the relevant econometric issues. Results indicate that increa

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Shi, Chao, and Xiaosheng Zhuang. "A Study Concerning Soft Computing Approaches for Stock Price Forecasting." Axioms 8, no. 4 (October 18, 2019): 116. http://dx.doi.org/10.3390/axioms8040116.

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Financial time-series are well known for their non-linearity and non-stationarity nature. The application of conventional econometric models in prediction can incur significant errors. The fast advancement of soft computing techniques provides an alternative approach for estimating and forecasting volatile stock prices. Soft computing approaches exploit tolerance for imprecision, uncertainty, and partial truth to progressively and adaptively solve practical problems. In this study, a comprehensive review of latest soft computing tools is given. Then, examples incorporating a series of machine

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Olena Nikolaieva, Anzhela Petrova, and Rostyslav Lutsenko. "FORECASTING OF THE STOCK RATE OF LEADING WORLD COMPANIES USING ECONOMETRIC METHODS AND DCF ANALYSIS." International Journal of Innovative Technologies in Economy, no. 2(29) (May 31, 2020): 33–41. http://dx.doi.org/10.31435/rsglobal_ijite/31052020/7067.

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In this article, we will cover various models for forecasting the stock price of global companies, namely the DCF model, with well-reasoned financial analysis and the ARIMA model, an integrated model of autoregression − moving average, as an econometric mechanism for point and interval forecasting. The main goal is to compare the obtained forecasting results and evaluate their real accuracy. The article is based on forecasting stock prices of two companies: Coca-Cola HBC AG (CCHGY) and Nestle S.A. (NSRGF). At the moment, it is not determined which approach is better for predicting the stock pr

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Peñalvo, Francisco José García, Tamanna Maan, Sunil K. Singh, Sudhakar Kumar, Varsha Arya, Kwok Tai Chui, and Gaurav Pratap Singh. "Sustainable Stock Market Prediction Framework Using Machine Learning Models." International Journal of Software Science and Computational Intelligence 14, no. 1 (January 1, 2022): 1–15. http://dx.doi.org/10.4018/ijssci.313593.

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Prediction of stock prices is a challenging task owing to its volatile and constantly fluctuating nature. Stock price prediction has sparked the interest of various investors, data analysists, and researchers because of high returns on their investments. A sustainable framework for stock price prediction is proposed to quantify the factors affecting the stock price and impact of technology on the ever-changing business world. The proposed framework also helps to understand how technology can be used to predict the future price of stocks by using some historical dataset to produce desirable res

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MISSAOUI, Sahbi, and Nizar RAISSI. "Underpricing Process of IPOs in Tunis Stock Exchange: An Agent-Based Modelling Approach." Accounting and Finance Research 10, no. 2 (April 7, 2021): 1. http://dx.doi.org/10.5430/afr.v10n2p1.

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The fundamental problematic treated in our study was an attempt to explain an anomaly in the issuance of new stocks in IPOs process. The objective of this research is to analyze the effect of certain variables on the level of undervaluation by presenting certain econometric models issued from Agent-based modelling approach. Certain variables can be predictive of the phenomenon of undervaluation such as: the Stock equity distributed to institutional investors, liquidity in the secondary market measured by the price range and the type of investor who can be insiders or outsiders, in addition to

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Majewski, Sebastian, Waldemar Tarczynski, and Malgorzata Tarczynska-Luniewska. "Measuring investors’ emotions using econometric models of trading volume of stock exchange indexes." Investment Management and Financial Innovations 17, no. 3 (September 30, 2020): 281–91. http://dx.doi.org/10.21511/imfi.17(3).2020.21.

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Traditional finance explains all human activity on the ground of rationality and suggests all decisions are rational because all current information is reflected in the prices of goods. Unfortunately, the development of information technology and a growth of demand for new, attractive possibilities of investment caused the process of searching new, unique signals supporting investment decisions. Such a situation is similar to risk-taking, so it must elicit the emotional reactions of individual traders.The paper aims to verify the question that the market risk may be the determinant of traders’

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9

EKSTRÖM, ERIK, and JOHAN TYSK. "OPTIONS WRITTEN ON STOCKS WITH KNOWN DIVIDENDS." International Journal of Theoretical and Applied Finance 07, no. 07 (November 2004): 901–7. http://dx.doi.org/10.1142/s0219024904002694.

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There are two common methods for pricing European call options on a stock with known dividends. The market practice is to use the Black–Scholes formula with the stock price reduced by the present value of the dividends. An alternative approach is to increase the strike price with the dividends compounded to expiry at the risk-free rate. These methods correspond to different stock price models and thus in general give different option prices. In the present paper we generalize these methods to time- and level-dependent volatilities and to arbitrary contract functions. We show, for convex contra

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10

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.

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Hamad, Dr Abed Ali, and Dr Ahmad Hussein Battal. "Use GARCH Models to Build a Econometric Model to Predict Average Daily Closing Prices of the Iraqi Stock Exchange for the Period 2013-2016." Webology 18, Special Issue 04 (September 30, 2021): 385–400. http://dx.doi.org/10.14704/web/v18si04/web18136.

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This research aims to build a standard model for the analysis and prediction of the average daily closing price fluctuations for companies registered in the Iraq Stock Exchange for the period 07/01/2013 to 30/06/2016, using the conditional generalized Heteroscedasticity Generalized Autoregressive (GARCH) models. As these models deal with the fluctuations that occur in the financial time series. The results of the analysis showed that the best model for predicting the volatility of average closing prices in the Iraq Stock Exchange is the EGARCH model (3,1), depending on the statistical criteria

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Fang, Hao, Yen-Hsien Lee, and William Chang. "Nonlinear short-run adjustments between house and stock prices in emerging Asian regions." Panoeconomicus 65, no. 1 (2018): 37–63. http://dx.doi.org/10.2298/pan140125018f.

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This study uses the powerful nonparametric cointegration test to examine whether nonlinear cointegration exists between prices of used houses and corresponding stock markets in China and the four Asian Tigers. Then, it uses the smooth transition vector error-correction model (STVECM) to explore the adjustment efficiencies of the short-run house and corresponding stockreturn dynamics when there is disequilibrium between house and stock prices. The empirical results indicate that there is a nonlinear cointegration between the house prices and corresponding stock prices in China, South Korea, Sin

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13

Hong, Harrison, and Jeremy C. Stein. "Disagreement and the Stock Market." Journal of Economic Perspectives 21, no. 2 (April 1, 2007): 109–28. http://dx.doi.org/10.1257/jep.21.2.109.

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A large catalog of variables with no apparent connection to risk has been shown to forecast stock returns, both in the time series and the cross-section. For instance, we see medium-term momentum and post-earnings drift in returns—the tendency for stocks that have had unusually high past returns or good earnings news to continue to deliver relatively strong returns over the subsequent six to twelve months (and vice-versa for stocks with low past returns or bad earnings news); we also see longer-run fundamental reversion—the tendency for “glamour” stocks with high ratios of market value to earn

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14

DeJong, David N., and Charles H. Whiteman. "Modeling Stock Prices without Knowing How to Induce Stationarity." Econometric Theory 10, no. 3-4 (August 1994): 701–19. http://dx.doi.org/10.1017/s0266466600008732.

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Bayesian procedures for evaluating linear restrictions imposed by economic theory on dynamic econometric models are applied to a simple class of presentvalue models of stock prices. The procedures generate inferences that are not conditional on ancillary assumptions regarding the nature of the nonstationarity that characterizes the data. Inferences are influenced by prior views concerning nonstationarity, but these views are formally incorporated into the analysis, and alternative views are easily adopted. Viewed in light of relatively tight prior distributions that have proved useful in forec

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15

Ghosh, Papiya, and Brishti Guha. "THE STUDY OF RELATIONSHIP BETWEEN TOBIN’S Q AND US STOCK PERFORMANCE OF SELECTED FIRMS." International Journal of Advanced Economics 1, no. 2 (June 22, 2020): 85–94. http://dx.doi.org/10.51594/ijae.v1i2.56.

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The objective of study was to test the dynamic effects of changes in Tobin’Q on stock prices of selected 249 US public companies of different industry categories. Panel unit roots tests and cointegration tests are implemented. Next, DOLS and GMM models are estimated. Annual data for the 2004-2012 period are used for the above selected US companies. Panel unit root tests provide somewhat mixed evidence of non-stationarity of both variables. There is clear evidence of cointegration between the above variables. The negative coefficient of the error-correction term shows convergence toward long-ru

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16

Rahman, Matiur, and Muhammad Mustafa. "Dynamics of Tobin’s Q and US Stock Performance." International Review of Business and Economics 2, no. 2 (2018): 52–68. http://dx.doi.org/10.56902/irbe.2018.2.2.3.

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To study the dynamic effects of changes in Tobin’s Q on stock prices of selected 249 US public companies of different industry categories. Panel unit roots tests and cointegration tests are implemented. Next, DOLS and GMM models are estimated. Annual data for the 2004-2012 period are used for the above selected US companies. Panel unit root tests provide somewhat mixed evidence of non-stationarity of both variables. There is clear evidence of cointegration between the above variables. The negative coefficient of the error-correction term shows convergence toward long-run equilibrium, though at

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17

Bundala, Ntogwa N. "Homo-Hetero Pairing Regression Model: An Econometric Predictive Model of Homo Paired Data." International Journal of Finance Research 3, no. 2 (July 31, 2022): 147–86. http://dx.doi.org/10.47747/ijfr.v3i2.792.

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The study aimed to examine the technical and fundamental hypotheses in NYSE, NASDAQ and S&P 500 stock exchange markets. The main determinants (variables) that were examined were stock trading volumes, closing stock prices and stock information available in the stock exchange market. The 240 days, 197 days and 253 days data of closing stock prices and trading volumes at NYSE, S&P500 and NASDAQ stock exchange markets were systematically collected from June 2021 to June 2022. The data was analysed by using the Homo-Hetero Pairing (HHP) Regression Model. This model was developed to detect

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18

FRAME, SAMUEL J., and CYRUS A. RAMEZANI. "BAYESIAN ESTIMATION OF ASYMMETRIC JUMP-DIFFUSION PROCESSES." Annals of Financial Economics 09, no. 03 (December 2014): 1450008. http://dx.doi.org/10.1142/s2010495214500080.

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The hypothesis that asset returns are normally distributed has been widely rejected. The literature has shown that empirical asset returns are highly skewed and leptokurtic. The affine jump-diffusion (AJD) model improves upon the normal specification by adding a jump component to the price process. Two important extensions proposed by Ramezani and Zeng (1998) and Kou (2002) further improve the AJD specification by having two jump components in the price process, resulting in the asymmetric affine jump-diffusion (AAJD) specification. The AAJD specification allows the probability distribution of

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Madhavan, Vinodh, and Partha Ray. "Price and Volatility Linkages Between Indian Stocks and Their European GDRs." Journal of Emerging Market Finance 18, no. 2_suppl (June 21, 2019): S213—S237. http://dx.doi.org/10.1177/0972652719846353.

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This article tests for price and volatility linkages between Indian global depositary receipts (GDRs) traded in Luxembourg/London and their underlying shares traded in Mumbai. The relationship is studied between the GDR price and the domestic share price along with the appropriate exchange rates, the foreign stock index and the domestic stock index using the vector autoregression (VAR) and dynamic conditional correlation (DCC) specification of multivariate generalised autoregressive conditional heteroscedasticity (GARCH) models. VAR results indicate a similarity between the two prices of scrip

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Srivastava, H., P. Solomon, and S. P. Singh. "Do Exogenous Shocks in Macroeconomic Variables Respond to Changes in Stock Prices?" Finance: Theory and Practice 26, no. 6 (December 30, 2022): 104–14. http://dx.doi.org/10.26794/2587-5671-2022-26-6-104-114.

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The research aims to examine the unexpected changes in stock prices due to external shocks given to the macroeconomic variables to forecast future stock market returns. The study applies two econometric models such as «Variance Decomposition» (VDC) and «Impulse Response Function» (IRF) for examining the exogenous shocks in macroeconomic variables respond to changes in stock prices. Monthly time series data of five significant macroeconomic variables Real Exchange Rate, Interest Rate, Consumer Price Index (CPI), Crude Oil Prices, and Trade Openness, taken as independent variables and BSE SENSEX

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21

Zhang, Junhao, and Yifei Lei. "Deep Reinforcement Learning for Stock Prediction." Scientific Programming 2022 (April 30, 2022): 1–9. http://dx.doi.org/10.1155/2022/5812546.

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Investors are frequently concerned with the potential return from changes in a company’s stock price. However, stock price fluctuations are frequently highly nonlinear and nonstationary, rendering them to be uncontrollable and the primary reason why the majority of investors earn low long-term returns. Historically, people have always simulated and predicted using classic econometric models and simple machine learning models. In recent years, an increasing amount of research has been conducted using more complex machine learning and deep learning methods to forecast stock prices, and their res

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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 measur

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Baranovskyi, O., M. Kuzheliev, D. Zherlitsyn, and K. Serdyukov. "CRYPTOCURRENCY MARKET TRENDS AND FUNDAMENTAL ECONOMIC INDICATORS: CORRELATION AND REGRESSION ANALYSIS." Financial and credit activity: problems of theory and practice 3, no. 38 (June 30, 2021): 249–61. http://dx.doi.org/10.18371/fcaptp.v3i38.237454.

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Abstract. The first cryptocurrency was born in 2008. Already today, virtual financial assets and tokens are a significant part of trading in global financial markets. The cryptocurrency market capitalization currently exceeds 600 billion U.S. dollars. However, there is a lot of discussion about cryptocurrency functions and the correlation between Bitcoin prices and the basic economic indices. Therefore, the purpose of the paper is to define the statistical substantiation of the influence of fundamental economic indicators on the market of virtual financial assets and the possibility of u

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Ji, Xuan, Jiachen Wang, and Zhijun Yan. "A stock price prediction method based on deep learning technology." International Journal of Crowd Science 5, no. 1 (March 5, 2021): 55–72. http://dx.doi.org/10.1108/ijcs-05-2020-0012.

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Purpose Stock price prediction is a hot topic and traditional prediction methods are usually based on statistical and econometric models. However, these models are difficult to deal with nonstationary time series data. With the rapid development of the internet and the increasing popularity of social media, online news and comments often reflect investors’ emotions and attitudes toward stocks, which contains a lot of important information for predicting stock price. This paper aims to develop a stock price prediction method by taking full advantage of social media data. Design/methodology/appr

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Tufail, Saira, and Sadia Batool. "An Analysis of the Relationship between Inflation and Gold Prices: Evidence from Pakistan." LAHORE JOURNAL OF ECONOMICS 18, no. 2 (July 1, 2013): 1–35. http://dx.doi.org/10.35536/lje.2013.v18.i2.a1.

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In this study, we formulate a new inflation equation to capture the potential effects of gold and stock prices on inflation in Pakistan. We aim to assess the inflation-hedging properties of gold compared to other assets such as real estate, stock exchange securities, and foreign currency holdings. Applying time-series econometric techniques (cointegration and vector error correction models) to data for 1960–2010, we find that gold is a potential determinant of inflation in Pakistan. On the other hand, it also provides a complete hedge against unexpected inflation. Real estate assets are more t

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Gregoriou, Andros, and Mark Rhodes. "The accuracy of spread decomposition models in capturing informed trades." Review of Behavioral Finance 9, no. 1 (April 10, 2017): 2–13. http://dx.doi.org/10.1108/rbf-02-2017-0016.

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Purpose The purpose of this paper is to examine the empirical relationship between trades undertaken by informed agents (managers) and the proxies for informed trades computed by bid-ask spread decomposition models. Design/methodology/approach An econometric application of spread decomposition models to data from the London Stock Exchange, with an examination of whether the model predictions are co-integrated with actual outcomes. Findings The authors find overwhelming evidence of non-stationary behaviour between the actual and predicted informed trade prices. The findings suggest that there i

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Tarczyński, Waldemar, Urszula Mentel, Grzegorz Mentel, and Umer Shahzad. "The Influence of Investors’ Mood on the Stock Prices: Evidence from Energy Firms in Warsaw Stock Exchange, Poland." Energies 14, no. 21 (November 5, 2021): 7396. http://dx.doi.org/10.3390/en14217396.

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The subject of this publication is an analysis of the sentiment of stock exchange investors in terms of making investment decisions in the energy sector of the Polish stock exchange. The investment mood is considered in the context of the possible impact of weather factors on investment decisions. Possible effects are verified in relation to the rates of return and the volume of trading of energy sector entities. The analysis is carried out both in terms of co-integration analyses as well as in econometric terms, in the cross-section of classic OLS models or causality analysis using VAR vector

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28

Abbahaddou, Kaoutar, Mohammed Salah Chiadmi, and Rajae Aboulaich. "An Enhanced Adaptative System based on Machine Learning for Predicting the Evolution of Islamic Stock Prices." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 19 (October 11, 2022): 1661–68. http://dx.doi.org/10.37394/23207.2022.19.150.

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This paper suggests an enhanced machine-learning-based system to guide future stock price decisions. In reality, most existing machine learning systems, such as SEA (Stream Ensemble Algorithm), VFDT (Very Fast Decision Tree ), and online bagging and boosting, keep models updated with only new data and reduce training timeframes to allow working rapidly with the most recent model. However, limited learning times and the exclusion of essential information from previous data may result in a bad performance. When it comes to learning models, our system takes a different approach. It builds several

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29

Hannum, Christopher, Kerem Yavuz Arslanli, and Ali Furkan Kalay. "Spatial analysis of Twitter sentiment and district-level housing prices." Journal of European Real Estate Research 12, no. 2 (August 8, 2019): 173–89. http://dx.doi.org/10.1108/jerer-08-2018-0036.

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Purpose Studies have shown a correlation and predictive impact of sentiment on asset prices, including Twitter sentiment on markets and individual stocks. This paper aims to determine whether there exists such a correlation between Twitter sentiment and property prices. Design/methodology/approach The authors construct district-level sentiment indices for every district of Istanbul using a dictionary-based polarity scoring method applied to a data set of 1.7 million original tweets that mention one or more of those districts. The authors apply a spatial lag model to estimate the relationship b

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Jiang, Xiaoquan, and Qiang Kang. "Cross-Sectional PEG Ratios, Market Equity Premium, and Macroeconomic Activity." Journal of Accounting, Auditing & Finance 35, no. 3 (January 8, 2018): 471–500. http://dx.doi.org/10.1177/0148558x17748277.

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This article explores the information content of PEG ratios (price/earnings to growth ratios) for future aggregate returns and economic fundamentals. We first establish an analytic link between PEG ratios and time-varying expected returns of stocks. We then combine the link with empirical asset pricing models to extract market-wide information from cross-sectional PEG ratios. The resultant cross-section estimates of the risk premiums on stock betas serve as proxies for market-wide information. The proxies contain salient information about future market equity premiums and macroeconomic activit

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31

Milon, J. Walter. "Travel Cost Methods for Estimating the Recreational Use Benefits of Artificial Marine Habitat." Journal of Agricultural and Applied Economics 20, no. 1 (July 1988): 87–101. http://dx.doi.org/10.1017/s0081305200025681.

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AbstractThe growing popularity of marine recreational fishing has created considerable interest in artificial marine habitat development to maintain and enhance coastal fishery stocks. This paper provides a comparative evaluation of travel cost methods to estimate recreational use benefits for new habitat site planning. Theoretical concerns about price and quality effects of substitute sites, corner solutions in site choice, and econometric estimation are considered. Results from a case study indicate that benefit estimates are influenced by the way these concerns are addressed, but relatively

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Hami, Mustapha El, and Ahmed Hefnaoui. "Analysis of Herding Behavior in Moroccan Stock Market." Journal of Economics and Behavioral Studies 11, no. 1(J) (March 10, 2019): 181–90. http://dx.doi.org/10.22610/jebs.v11i1(j).2758.

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Frontier markets, particularly the Moroccan financial market, are characterized by a narrowness of market, inability to absorb erratic price fluctuations and the low liquidity of securities that encourage investors to herd and imitate those who have all the information about the market. A quantitative research approach was used to analyze the existence of herding n Moroccan stock market. The daily data used in this study concerns the period from 04/01/2010 to 29/12/2017 and contains the daily returns of the MASI and a total of 43 traded stocks. Statistical and econometric methods such as multi

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Rudzkis, Rimantas, Roma Valkavičienė, and Virmantas Kvedaras. "Prediction of Baltic Sectorial Share Price Indices." Lietuvos statistikos darbai 53, no. 1 (December 20, 2014): 53–59. http://dx.doi.org/10.15388/ljs.2014.13894.

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Extending the research started in [31], the paper uses econometric methods for the short-term forecasting of quarterly values of sector indexes of stock prices from the OMX Baltic stock exchange. The ARMA models and modelling methodology that was used to build the statistical models in the previous paper are now augmented with the algorithms of time series aggregation and identification of special features of the series. Here, the search for informative factors relies on the study of related literature. The specification of models is further tailored using the traditional significance (p-value

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Manikandan, Narayanan, and Srinivasan Subha. "Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks." Scientific World Journal 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/6709352.

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Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artifi

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Bayram, Mehmet, and Muzaffer Akat. "Market-neutral trading with fuzzy inference, a new method for the pairs trading strategy." Engineering Economics 30, no. 4 (October 30, 2019): 411–21. http://dx.doi.org/10.5755/j01.ee.30.4.14350.

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Financial pricing and prediction of stock markets is a specific and relatively narrow field, which have been mainly explored by mathematicians, economists and financial engineers. Prediction with the purpose of making profits in a martingale domain is a hard task. Pairs trading, a market neutral arbitrage strategy, attempts to resolve the drawback of unpredictability and yield market independent returns using relative pricing idea. If two securities have similar characteristics, so should their prices. Deviation from the acceptable similarity range in prices is considered an anomaly, and whene

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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 th

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Neves, Maria Elisabete, Mário Abreu Pinto, Carla Manuela de Assunção Fernandes, and Elisabete Fátima Simões Vieira. "Value and growth stock returns: international evidence (JES)." International Journal of Accounting & Information Management 29, no. 5 (October 7, 2021): 698–733. http://dx.doi.org/10.1108/ijaim-05-2021-0097.

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Purpose This study aims to analyze the returns obtained from companies with strong growth potential (growth stocks) and the returns from companies with quite low stock prices, but with high value (value stocks). Design/methodology/approach The sample comprises monthly data, from January 2002 to December 2016, from seven countries, Germany, France, Switzerland, the UK, Portugal, the USA and Japan. The authors have used linear regression models for three different periods, the pre-crisis, subprime crisis and post-crisis period. Findings The results point out that the performance of value and gro

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Akbulaev, N. N., F. S. Ahmadov, and M. R. Mammadova. "Analysis of the Impact of the COVID-19 Pandemic on Stock Exchange Indices in Italy." Economy of Region 18, no. 4 (2022): 1276–86. http://dx.doi.org/10.17059/ekon.reg.2022-4-22.

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The present paper investigates the impact of the COVID-19 pandemic on the prices of the Italian stock exchange indices. During the pandemic, the global economy as well as financial markets suffered due to isolation and social distancing. Paired models of the dependence of the key indices of the Italian stock exchange on the number of patients, recovered and died were analysed using the least squares method. Further, various tests were performed to verify the feasibility of the Gauss-Markov conditions by applying Gretl tools: White Test for heteroskedasticity of residues, Durbin-Watson test for

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Czinkan, Norbert, and Áron Horváth. "Determinants of housing prices from an urban economic point of view: evidence from Hungary." Journal of European Real Estate Research 12, no. 1 (May 7, 2019): 2–31. http://dx.doi.org/10.1108/jerer-10-2017-0041.

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Purpose The purpose of the paper is to investigate a cross section of Hungarian settlement-level unit housing prices with a special emphasis on measuring the effect of population and its growth, along with accessibility to the centre of an aggregated spatial unit such as a micro-region, county or region, for the period of 2001-2011. Design/methodology/approach The analysis uses cross-sectional ordinary least squares techniques with Moulton-corrected standard errors. The estimation is guided by the implications of a simplified monocentric urbanized area framework following the model of DiPasqua

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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 stock

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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 esti

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S, Monish, Mridul Mohta, and Shanta Rangaswamy. "ETHEREUM PRICE PREDICTION USING MACHINE LEARNING TECHNIQUES – A COMPARATIVE STUDY." International Journal of Engineering Applied Sciences and Technology 7, no. 2 (June 1, 2022): 137–42. http://dx.doi.org/10.33564/ijeast.2022.v07i02.018.

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In recent years, popularity and use of cryptocurrencies has been rising along with their prices and Ethereum is the second most famous cryptocurrency after Bitcoin. Cryptocurrencies are based on blockchain, which is a distributed and empowered technology that has the power to transform any banking systems. It has become an attractive investment for traders as well as individuals looking to invest. The price of Ethereum varies and is controlled by different factors, such as the crypto market in which it is sold, supply and demand. Ethereum is so valuable because it could be used as cash, we cou

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Rege, Sameer, and Samuel Gil Martín. "PORTUGUESE STOCK MARKET: A LONG-MEMORY PROCESS?" Business: Theory and Practice 12, no. 1 (March 10, 2011): 75–84. http://dx.doi.org/10.3846/btp.2011.08.

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This paper gives a basic overview of the various attempts at modelling stochastic processes for stock markets with a specific application to the Portuguese stock market data. Long-memory dependence in the stock prices would completely alter the data generation process and econometric models not considering the long-range dependence would exhibit poor forecasting abilities. The Hurst exponent is used to identify the presence of long-memory or fractal behaviour of the data generation process for the daily returns to ascertain if the process follows a fractional brownian motion. Detrended fluctua

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Coen-Pirani, Daniele. "Markups, Aggregation, and Inventory Adjustment." American Economic Review 94, no. 5 (November 1, 2004): 1328–53. http://dx.doi.org/10.1257/0002828043052376.

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In this paper I suggest a unified explanation for two puzzles in the inventory literature: first, estimates of inventory speeds of adjustment in aggregate data are very small relative to the apparent rapid reaction of stocks to unanticipated variations in sales. Second, estimates of inventory speeds of adjustment in firm-level data are significantly higher than in aggregate data. The paper develops a multi-sector model where inventories are held to avoid stockouts, and price markups vary along the business cycle. The omission of countercyclical markup variations from inventory targets introduc

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Yan, Runze. "Option pricing and risk hedging for Visa." BCP Business & Management 32 (November 22, 2022): 203–10. http://dx.doi.org/10.54691/bcpbm.v32i.2889.

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As the core of the option transaction, the option price changing with the supply and demand in the market is a variable which affects the profit and loss of both trading sides directly. In the 20th century, multitudinous econometric pricing models proposed lacked universal recognition until the Black Scholes Merton model came out. This paper focuses on the stocks and options from Visa Inc. to do the article consisting of calibration, option pricing and hedging using fundamental Black Scholes Merton model and the extensive jump model mainly under the seldom used method. The article demonstrates

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TRIVEDI, JATIN, MOHD AFJAL, CRISTI SPULBAR, RAMONA BIRAU, KRISHNA MURTHY INUMULA, and NARCIS EDUARD MITU. "Investigating the impact of COVID-19 pandemic on volatility patterns and its global implication for textile industry: An empirical case study for Shanghai Stock Exchange of China." Industria Textila 73, no. 04 (August 31, 2022): 365–76. http://dx.doi.org/10.35530/it.073.04.202148.

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This research paper aims to examine the impact of the COVID-19 pandemic on volatility patterns and its global implication for the textile industry in China. The COVID-19 pandemic has generated a global health crisis with profound economic, social and financial implications, but also has triggered a ruthless global recession. The global economic recovery as a result of the COVID-19 pandemic can also generate significant investment opportunities for the textile industry in China. In this paper, the application of empirical methods could explain historical prices, the movement dynamics of financi

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Phuong, Lai Cao Mai. "Investor Sentiment by Money Flow Index and Stock Return." International Journal of Financial Research 12, no. 4 (March 18, 2021): 33. http://dx.doi.org/10.5430/ijfr.v12n4p33.

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Factors affecting stock prices have been studied by many scholars on different stock markets. However, the number of empirical studies applying technical analysis indicators to measure investor sentiment is quite limited. To explore this interesting topic, this study uses the Money Flow Index (MFI) indicator to measure an investor's sentiment by various thresholds and to test its effect on the excess return on Vietnam stock market. Data series including market, interest rate, finance and transaction data of 138 companies listed on the Ho Chi Minh City Stock Exchange from 2015 to June 2020 are

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Karmakar, Madhusudan. "Modeling Conditional Volatility of the Indian Stock Markets." Vikalpa: The Journal for Decision Makers 30, no. 3 (July 2005): 21–38. http://dx.doi.org/10.1177/0256090920050303.

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Traditional econometric models assume a constant one period forecast variance. However, many financial time series display volatility clustering, that is, autoregressive conditional heteroskedasticity (ARCH). The aim of this paper is to estimate conditional volatility models in an effort to capture the salient features of stock market volatility in India and evaluate the models in terms of out-ofsample forecast accuracy. The paper also investigates whether there is any leverage effect in Indian companies. The estimation of volatility is made at the macro level on two major market indices, name

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Fationa Halili. ""The Impact of Macroeconomic Factors on the Change of Residential Prices" The case study of Albania." International Journal of Applied Research in Management and Economics 5, no. 4 (January 7, 2023): 29–44. http://dx.doi.org/10.33422/ijarme.v5i4.946.

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The housing market is a very important sector worldwide and occupies a significant part of their capital stock. Given that the economy is experiencing a difficult situation, because of the Covid-19 pandemic crisis, also based on the financial crisis of 2007-2008, their impact has been immediate in the change in house prices. Moreover, this paper will contain the investigation of some of the macroeconomic variables that affect housing prices in Albania. The study is built on econometric models, using bound test to understand what correlation relationship exists between GDP, inflation and mortga

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Dell’Anna, Federico. "What Advantages Do Adaptive Industrial Heritage Reuse Processes Provide? An Econometric Model for Estimating the Impact on the Surrounding Residential Housing Market." Heritage 5, no. 3 (July 6, 2022): 1572–92. http://dx.doi.org/10.3390/heritage5030082.

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When industrial relics, such as obsolete buildings, sites, and infrastructures, enter into a process of adaptive reuse, they become transformation engines capable of shaping the urban fabric. They provide tangible and intangible links to our past and have the potential to play a significant role in today’s cities’ futures. One unresolved issue is the quantification of the externalities of these transformation processes. If undertaken correctly, adaptive reuse can contribute to the development of social and cultural capital, environmental sustainability, urban regeneration, and, most importantl

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