Готові списки джерел за темами / Economial model- Stock market

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Автор: Grafiati
Опубліковано: 6 вересня 2023

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Статті в журналах з теми "Economial model- Stock market"

1

Zevallos, Mauricio, and Carlos del Carpio. "Metal Returns, Stock Returns and Stock Market Volatility." Economia 38, no. 75 (August 1, 2015): 101–22. http://dx.doi.org/10.18800/economia.201501.003.

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Given the extensive participation of mining stocks in the Peruvian stock market, the Lima Stock Exchange (BVL) provides an ideal setting for exploring both the impact of metal returns on mining stock returns and stock market volatility, and the comovements between mining stock returns and metal returns. This research is a first attempt to explore these issues using international metal prices and the prices of the most important mining stocks on the BVL and the IGBVL index. To achieve this, we use univariate GARCH models to model individual volatilities, and the Exponentially Weighted Moving Average (EWMA) method and multivariate GARCH models with time-varying correlations to model comovements in returns. We found that Peruvian mining stock volatilities mimic the behavior of metal volatilities and that there are important correlation levels between metals and mining stock returns. In addition, we found time-varying correlations with distinctive behavior in different periods, with rises potentially related to international and local historical events.
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2

Shkolnyk, Inna, Serhiy Frolov, Volodymyr Orlov, Viktoriia Dziuba, and Yevgen Balatskyi. "Influence of world stock markets on the development of the stock market in Ukraine." Investment Management and Financial Innovations 18, no. 4 (November 24, 2021): 223–40. http://dx.doi.org/10.21511/imfi.18(4).2021.20.

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Viewing the development of the stock market in Ukraine, the economy, which world financial organizations characterize as small and open, is largely determined by the trends formed by the global stock markets and leading stock exchanges. Therefore, the study aims to analyze Ukraine’s stock market, the world stock market, stock markets in the regions, and to assess their mutual influence. The study uses the data of the World Federation of Exchanges and National Securities and Stock Market Commission (Ukraine) from 2015 to 2020. Stock market performance forecasts are built using triple exponential smoothing. Based on pairwise correlation coefficients, the existence of a significant dependence in the development of the world stock market on the development of the American stock market was determined. Regarding the Ukrainian stock exchanges, only SE “PFTS” demonstrated its dependence on the US stock market. The results of the regression model based on an exponentially smoothed series of trading volumes in all markets showed that variations in the volume of trading on the world stock market are due to the situation on the US stock markets. Trading volume dynamics on Ukrainian stock exchanges such as SE “PFTS” and SE “Perspektiva” is almost 50% determined by the development of stock markets in the American region. Although Ukraine is geographically located in Europe, the results show a lack of significant links and the impacts of stock markets in this region on the major Ukrainian stock exchanges and the stock market as a whole.
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3

Chi, Wei, Robert Brooks, Emawtee Bissoondoyal-Bheenick, and Xueli Tang. "Classifying Chinese bull and bear markets: indices and individual stocks." Studies in Economics and Finance 33, no. 4 (October 3, 2016): 509–31. http://dx.doi.org/10.1108/sef-01-2015-0036.

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Purpose This paper aims to investigate Chinese bull and bear markets. The Chinese stock market has experienced a long period of bear cycle from early 2000 until 2006, and then it fluctuated greatly until 2010. However, the cyclical behaviour of stock markets during this period is less well established. This paper aims to answer the question why the Chinese stock market experienced a long duration of bear market and what factors would have impacted this cyclical behaviour. Design/methodology/approach By comparing the intervals of bull and bear markets between stocks and indices based on a Markov switching model, this paper examines whether different industries or A- and B-share markets could lead to different stock market cyclical behaviour and whether firm size can determine the relationship between the firm stock cycles on the market cycles. Findings This paper finds a high degree of overlapping of bear cycles between stocks and indices and a high level of overlapping between the bear market and a fraction of stock with increasing stock prices. This leads to the conclusion that the stock performance and trading behaviour are widely diversified. Furthermore, the paper finds that the same industry may have different overlapping intervals of bull or bear cycles in the Shanghai and Shenzhen stock markets. Firms with different sizes could have different overlapping intervals with bull or bear cycles. Originality/value This paper fills the literature gap by establishing the cyclical behaviour of stock markets.
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4

Fu, Maggie Mei-Zhi, Kokkiang Tan, Ahmad Nadzri Rose, and Banafsheh Samadi. "Spillover Effect of Chinese Export on New ASEAN-5 Stock Markets using Markov Regime Switching Model." International Journal of Advanced Business Studies 2, no. 1 (March 1, 2023): 53–64. http://dx.doi.org/10.59857/raod1747.

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China as the second largest economy supposes to produce spillover effect on the emerging market economies especially the ASEAN nations. The main objective of this paper is to study the spillover effect of the Chinese export on the new ASEAN-5 stock markets (Indonesia, Malaysia, Philippines, Thailand, and Vietnam). In this paper, multivariate Markov-Switching Intercept Autoregressive Heteroscedasticity (MSIAH) model is employed to analyze the linkage between Chinese export and the new ASEAN-5 stock markets over the sample period of August 2000 to December 2018. The monthly data have been analysed using EViews. Their relationship is also strong and positive. The findings report that the spillover effects of China export on new ASEAN-5 stock markets is significant. There is positive relationship between China export and the stock markets for both regimes. The conclusion can be made is China exports should be one of the important factors in determining the stock prices in new ASEAN-5 stock markets. Investors should alert China export information when investing in new ASEAN-5 stock market. New ASEAN-5 are important emerging economies in Asia Pacific region and China is a rising economic power, but there is very least literature to study the Spillover effect of China export on stock market in new ASEAN-5.
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5

Karolyi, G. Andrew, and Ying Wu. "A New Partial-Segmentation Approach to Modeling International Stock Returns." Journal of Financial and Quantitative Analysis 53, no. 2 (March 19, 2018): 507–46. http://dx.doi.org/10.1017/s0022109017001016.

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We propose a new multi-factor model for international stock returns that includes size, value, and momentum factor portfolios and that builds them in a partial-segmentation capital market framework. Accounting for externalities driven by the incomplete accessibility to stocks and stock markets, our model not only captures strong common variation in international stock returns but also achieves low pricing errors and rejection rates relative to pure segmentation and pure integration models. This partial-segmentation approach is evaluated using monthly returns for over 37,000 stocks from 46 developed and emerging market countries over 2 decades and for a wide variety of test assets.
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6

Han, Shi-Zhuan, Li Zhang, Guang-Yu Han, and Lei Wang. "The Three-factor Model and China’s Multiple Stock Markets." Journal of International Commerce, Economics and Policy 10, no. 03 (October 2019): 1950016. http://dx.doi.org/10.1142/s1793993319500169.

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This paper aims at discussing the applicability of the three-factor model in China’s multiple security markets. The monthly returns of Shenzhen Main Board Market, Shanghai Stock Market, GEM Securities Market and Small and Medium Board Securities Market from January 2012 to December 2016 are selected as samples. The following conclusions are drawn: the three-factor model is applicable in Shenzhen Main Board Market, that is, the change of stock return is proportional to market factor, book-to-market ratio factor, and inversely proportional to scale factor. Moreover, in terms of the explanatory power of the change of stock return, the market factor is the highest, the scale factor is the second, and the book-to-market ratio factor is the lowest. But in the other three markets, the two-factors model that excludes the ratio of book market value can explain the change of stock return better. In addition, the explanatory power of market factor is better than scale factor.
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7

Olotu, Samuel Ibukun. "A multivariate LSTM-based deep learning model for stock market prediction." Applied and Computational Engineering 2, no. 1 (March 22, 2023): 965–73. http://dx.doi.org/10.54254/2755-2721/2/20220602.

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Stocks represent ownership in a company and a proportionate claim on its assets and earn-ings. Investors trade stocks via an exchange by buying at a price and selling at a higher price. Due to market volatility forecast it is a necessity for trading to determine the direc-tion of the stock price in order to maximize profit and minimize loss. Traditional methods of stock price predictions include technical and fundamental analysis. The technical deals with historical price movement while fundamental analysis uses the relationship between financial information about the company. However, these predictions methods sometimes fail to yield desired result sometimes due to the influence of factors such as national poli-cies, global and regional economics, psychological, human among many. This work propos-es a prediction model for stock market using LSTM algorithm. Multivariate time series stock price data is obtained from Nigerian Stock Exchange Index to implement the model. The experimental result of the technique is measured using MAPE, MAE, MSE and rRMSE performance metrics. The accuracy of the result shows that the proposed system outper-forms existing traditional and deep learning methods.
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8

Baumöhl, Eduard, Mária Farkašovská, and Tomáš Výrost. "Stock Market Integration: DCC MV-GARCH Model." Politická ekonomie 58, no. 4 (August 1, 2010): 488–503. http://dx.doi.org/10.18267/j.polek.743.

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9

Moolman, E., and C. Du Toit. "An econometric model of the South African stock market." South African Journal of Economic and Management Sciences 8, no. 1 (January 13, 2015): 77–91. http://dx.doi.org/10.4102/sajems.v8i1.1285.

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A wealth of literature exists concerning the modelling of stock markets, as well as the examination of the relationshiop between share price and various economic factors, both theoretically and empirically. However, most studies use data for developed countries in their analyses, while the literature moselling emerging stock markets in general, and the south African stock market in particular, is quite sparse. This study develops a structural theoretically founded model of the South African stock market that is estimated using co-integration and error-correction techniques. These techniques respectively estimate the long-term equilibrium or intrinsic value of the stock market, and the short-term fluctuations around the quilibrium level. According to the results, share prices are co-integrated with the variables dictated by the expected present value model of asset price determination. The short-term fluctuations are determined by various factors such as interest rates, a risk premium, the exchange rate, foreign stock market adn other variables.
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10

Fatima, Nudrat, Muhammad Waqas, Rameez Hassan, Ahmad Fraz, and Muhammad Arif. "Cash to Price Ratio & Stock Returns: Evidence from Emerging Markets." International Journal of Economics and Finance 9, no. 11 (October 23, 2017): 153. http://dx.doi.org/10.5539/ijef.v9n11p153.

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This study examines the impact of size premium and value premium on average return in emerging economies i.e. Pakistan, India and China equity markets for the period from June 2000 to June 2015 by using three factors model. This study predicts the significance and positive relationship between value premium(C/P Ratio) and stock return for all non-financial companies listed on Karachi stock exchange, Bombay stock exchange and Shanghai stock exchange on the basis of market Capitalization. The regression results of the study illustrate that size premium predict returns more for small firms than big firms while market premium found significantly positive with stock returns in Pakistan, India, and China. Value premium is found positive for all created portfolios. Therefore, it can be concluded that value effect is present in three emerging markets. High C/P ratio outperforms the low C/P ratio stocks. In this study C/P ratio (value premium) integrated with size and market premium to check whether it can predict stock returns of small and large firms for high or low C/P ratio. The finding is similar that the positive relationship of value premium and stock return and the negative relationship of size premium and stock return. The explanatory power of Fama and French three-factor model is greater than CAPM for all three equity markets, so, the asset pricing model can facilitate investors in efficient portfolio diversification for getting enhanced returns.
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Дисертації з теми "Economial model- Stock market"

1

Sharma, Amita. "Optimal portfolio selection contemplating risk propensity of investors in stock markets." Thesis, IIT Delhi, 2016. http://localhost:8080/xmlui/handle/12345678/7098.

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2

Wan, Hakman Alberick. "On the agent market model of stock markets." Thesis, University of Sunderland, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288016.

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3

Alshogeathri, Mofleh Ali Mofleh. "Macroeconomic determinants of the stock market movements: empirical evidence from the Saudi stock market." Diss., Kansas State University, 2011. http://hdl.handle.net/2097/11989.

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Doctor of Philosophy
Department of Economics
Lance J. Bachmeier
This dissertation investigates the long run and short run relationships between Saudi stock market returns and eight macroeconomic variables. We investigate the ability of these variables to predict the level and volatility of Saudi stock market returns. A wide range of Vector autoregression (VAR) and generalized autoregressive conditional heteroskedasticity (GARCH) models estimated and interpreted. A Johansen-Juselius cointegration test indicates a positive long run relationship between the Saudi stock price index and the M2 money supply, bank credit, and the price of oil, and a negative long run relationship with the M1 money supply, the short term interest rate, inflation, and the U.S. stock market. An estimated vector error correction model (VECM) suggests significant unidirectional short run causal relationships between Saudi stock market returns and the money supply and inflation. The VECM also finds a significant long run causal relationship among the macroeconomic variables in the system. The estimated speed of adjustment indicates that the Saudi stock market converges to the equilibrium within half a year. Granger causality tests show no causal relationship between Saudi stock market returns and the exchange rate. Impulse response function analysis shows no significant relationship between Saudi stock market returns and the macroeconomic variables. Forecast error variance decompositions suggest that 89% of the variation in Saudi stock market returns is attributable to its own shock, which implies that Saudi stock market returns are largely independent of the macroeconomic variables in the system. Finally, a GARCH-X model indicates a significant relationship between volatility of Saudi stock returns and short run movements of macroeconomic variables. Implications of this study include the following. (i) Prediction of stock market returns becomes more difficult as the volatility of the macroeconomic variables increases in the short run. (ii) Investors should look at the systematic risks revealed by these macroeconomic variables when structuring their portfolios and diversification strategies. (iii) Policymakers should seek to minimize macroeconomic fluctuations considering the effect of macroeconomic variables changes on the stock market when formulating economic policy.
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4

Cândido, Maria Teresa. "Financial market liquidity, asset pricing, and financial crises /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1998. http://wwwlib.umi.com/cr/ucsd/fullcit?p9914068.

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5

Sundelius, Gustaf. "The Stock Market and Unemployment : The Cross-Section Volatility Model on Swedish data." Thesis, Uppsala University, Department of Economics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6407.

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Ever since the evolvement of modern macroeconomics, theories without foundation in the

Keynesian view, such as Real Business Cycle (RBC) theories, have aimed for recognition.

The purpose of this paper is to examine whether the Cross-Section Volatility model (CSV), a

RBC-model developed by Laclair Brainard and David Cutler (1993) based on US data, holds

and demonstrates similar results applied on Swedish data. The CSV is constructed by

weighting volatility for a number of industry-indices in the stock market. Brainard and Cutler

(1993) find evidence that the CSV is an explanatory variable on US data for sectoral as well

as aggregate unemployment. The results of this paper cannot disclaim the findings of Brainard

and Cutler (1993) but rather suggest that the CSV-measure to a limited degree is an

explanatory variable to unemployment on Swedish data as well.

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6

Truedsson, Christian. "Stock Markets and Real Economic Activity : Zooming out to show a broader picture using 12 EU Membership Countries." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44007.

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This thesis analyzes the long run relationship between stock markets and macroeconomic variables, such as the real industrial production index, consumer price index, money supply, and long-term government bonds. By the use of recent developments in cointegration methodologies a larger set of countries is analyzed due to mitigation of the issue where variables are integrated of different orders. Based on a present value model, this thesis applies an ARDL model and conducts the bounds testing procedure for analysis of cointegrating relationships among the variables. Complemented by the popular Johansen cointegration methodology, it is found that the variables are cointegrated for all of the twelve countries. Hence, the present value model provides a theoretical explanation of the long run connection between stock markets and macroeconomic variables. Finally, the long run relationship is estimated using both FMOLS and DOLS. Results show that real economic activity, proxied by the real industrial production index, enters a positive relationship with the stock market indices, and so does money supply. In contrast, the consumer price index and long-term government bonds enter a negative relationship with the stock market indices. Hence, this thesis adds to the literature by applying new methodologies to the topic, through which a larger set of countries can be analyzed, and by further analyzing the long run relationship between stock markets and real economic activity.
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7

Perez, Tomas Rene. "Oil Price and the Stock Market: A Structural VAR Model Identified with an External Instrument." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595877677072786.

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8

Yang, Juan. "Three essays on monetary policy, the financial market, and economic growth in the U.S. and China." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1030.

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9

Jonasson, Jesper, and Tobias Rosén. "The influence of real estate price fluctuations on real estate stocks : An analysis of Swedish asset classes." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44330.

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With background to recent price growth in Swedish real estate and consequently real estate stocks, our aim is to examine the relationship between real estate price development and real estate stock price development. To test our hypothesis, that real estate price development have had an impact on the return of real estate stocks, we built a capital asset pricing model. We divide the return of real estate stocks into two parts, the return in relation to the Swedish market premium and the excess return that is given for the exposure of the real estate market. We found that real estate exposure would treat the investor with an additional return beyond the return given from stock market exposure; hence, real estate price development has contributed to real estate stock returns.
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10

Ahmadin, Muhammad S. "ESSAYS ON THE VALUE OF A FIRM’S ECO-FRIENDLINESS IN THE FINANCIAL ASSET MARKET." UKnowledge, 2014. http://uknowledge.uky.edu/agecon_etds/31.

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This dissertation presents three different closely related topics on the value of eco-friendliness in the financial market. The first essay attempts to estimate hedonic stock price model to find a contemporaneous relationship between stock return and firms’ environmental performance and recover the value of investor’s willingness to pay of eco-friendliness. This study follows stock and environmental performances of the 500 largest US firms from 2009 to 2012. The firms’ environmental data come from the Newsweek Green Ranking, both aggregate measures: green ranking (GR) and green score (GS), and disaggregate measures: environmental impact score (EIS), green policy and performance score (GPS), reputation survey score (RSS), and environmental disclosure score (EDS). The results show a non-linear relationship between environmental variables and stock return, i.e. upside down bowl shape or increasing in decreasing rate. That means for low green ranking firms the marginal effect is positive while for high green ranking firms the marginal effect is negative. The investor’s willingness to pay (WTP) for a greener stock for firms in the lowest 25 green ranking, on average, is 0.0096% higher stock price. The second essays attempt to determine if a firm’s environmental performance affects future systematic risk. Systematic risk measures an individual stock’s volatility relative to the market price. This study also uses the Newsweek Green Ranking’s environmental variables. The results show significant evidence of a non-linear relationship between green variables and systematic (market) risk, but the shape is not unanimous for all environmental variables. The shape of the relationship for green ranking (GR), for example, is U-shape. This means that for the firms in the bottom rank, improving rank will lower systematic (market) risk, and for the firms in the top rank improving rank will increase systematic (market) risk. On average the marginal effect for the firms in the bottom and top 25 firms are -0.2% and 0.09% respectively. The third essay is the effect of a firm’s environmental performances on a firm’s idiosyncratic risk. Idiosyncratic risk measures an individual stock’s volatility independent from the market price. This study also uses the Newsweek Green Ranking’s environmental variables. The results show significant non-linear relationships between environmental variables and idiosyncratic risk, even though there is no unanimous shape among the environmental variables. In the case of green ranking, for example, it has U-shape; for the firms in the bottom rank, improving green ranking will lower idiosyncratic risk and for firm in the top green ranking, improving green ranking will increase idiosyncratic risk. On average the marginal effect for firm in bottom and top 25 firms are -0.4% and 0.2% respectively.
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Книги з теми "Economial model- Stock market"

1

Santa Fe Institute (Santa Fe, N.M.), ed. Agent-based modeling: The Santa Fe Institute artificial stock market model revisited. Berlin: Springer, 2008.

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2

Francois-Serge, Lhabitant, and Gregoriou Greg N. 1956-, eds. Stock market liquidity: Implications for market microstructure and asset pricing. Hoboken, NJ: J. Wiley & Sons, 2007.

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3

Arbuthnott, Andrew. Risk, return and seasonality: Evidence from the Irish stock market. Dublin: University College Dublin, 1993.

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4

Campbell, John Y. By force of habit: A consumption-based explanation of aggregate stock market behavior. Cambridge, MA: National Bureau of Economic Research, 1994.

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5

Campbell, John Y. By force of habit: A consumption-based explanation of aggregate stock market behavior. Philadelphia: Federal Reserve Bank of Philadelphia, Economic Research Division, 1994.

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6

Levine, Ross. Stock markets, growth, and policy. [Washington, DC]: Country Economics Dept., World Bank, 1990.

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7

Campbell, John Y. Consumption and the stock market: Interpreting international experience. Cambridge, MA: National Bureau of Economic Research, 1996.

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8

Pension systems, demographic change, and the stock market. Berlin: Springer, 2008.

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9

Vigna, Stefano Della. Attention, demographics, and the stock market. Cambridge, Mass: National Bureau of Economic Research, 2005.

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Vigna, Stefano Della. Attention, demographics, and the stock market. Cambridge, MA: National Bureau of Economic Research, 2005.

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Частини книг з теми "Economial model- Stock market"

1

Li, Jiayin, and Ruiting Yi. "Investigation of Asset Pricing Model on Stock Market." In Proceedings of the 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022), 1045–51. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-052-7_117.

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2

Ballestero, Enrique. "Using Compromise Programming in a Stock Market Pricing Model." In Lecture Notes in Economics and Mathematical Systems, 388–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57311-8_33.

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3

Zhu, Yuxuan. "Comparison of SVM and ARIMA Model in Stock Market." In Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022), 928–34. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-036-7_137.

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4

Tinyakova, Viktoria I., Alexandr N. Maloletko, Olga V. Kaurova, Marina V. Vinogradova, and Anna A. Larionova. "Model of Evaluation of Influence of Globalization on the National Stock Market." In Contributions to Economics, 261–72. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55257-6_35.

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Arekar, Kirti, Rinku Jain, and Surender Kumar. "Bayesian Estimation of Irregular Stochastic Volatility Model for Developed and Emerging Stock Market." In Finance & Economics Readings, 37–47. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8147-7_3.

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Cai, Ningrong, Danqing Song, Yiqing Zhang, and Zhuoqun Zhang. "Fama French Three Factor Model in Chinese Stock Market during Covid-19." In Proceedings of the 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022), 581–92. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-052-7_68.

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Lee, Hao. "Does Stock Market Contribute to the Growth of Company? An Agent-Based Simulation of Industrial Model in Which Stock Markets and Product Markets Exist." In Agent-Based Approaches in Economic and Social Complex Systems VIII, 143–60. Tokyo: Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55236-9_11.

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Lin, Jiahao, Yunyang Lu, and Lulu Zhang. "Research on the Application of Minimum Variance Model and Utility Maximization Model in Stock Market Portfolio." In Proceedings of the 2022 2nd International Conference on Financial Management and Economic Transition (FMET 2022), 306–15. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-054-1_35.

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Wei, Yue. "Reviewing on China Development on Stock Market Volatility Model for The Last 20 Years." In Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022), 535–42. Dordrecht: Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-098-5_60.

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Consoli, Sergio, Matteo Negri, Amirhossein Tebbifakhr, Elisa Tosetti, and Marco Turchi. "Forecasting the IBEX-35 Stock Index Using Deep Learning and News Emotions." In Machine Learning, Optimization, and Data Science, 308–23. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95467-3_23.

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AbstractMeasuring the informational content of text in economic and financial news is useful for market participants to adjust their perception and expectations on the dynamics of financial markets. In this work, we adopt a neural machine translation and deep learning approach to extract the emotional content of economic and financial news from Spanish journals. To this end, we exploit a dataset of over 14 million articles published in Spanish newspapers over the period from 1st of July 1996 until 31st of December 2019. We then examine the role of these news-based emotions indicators in forecasting the Spanish IBEX-35 stock market index by using DeepAR, an advanced neural forecasting method based on auto-regressive Recurrent Neural Networks operating in a probabilistic setting. The aim is to evaluate if the combination of a richer information set including the emotional content of economic and financial news with state-of-the-art machine learning can help in such a challenging prediction task. The DeepAR model is trained by adopting a rolling-window approach and employed to produce point and density forecasts. Results look promising, showing an improvement in the IBEX-35 index fitting when the emotional variables are included in the model.
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Тези доповідей конференцій з теми "Economial model- Stock market"

1

Liu, Zhiqiang, and Qing Huang. "Market Competition and Stock Collapse Risk." In 2019 International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2019. http://dx.doi.org/10.1109/icemme49371.2019.00016.

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2

Tasevska, Ivona. "EMPIRICAL RESEARCH ON THE INFORMATION EFFICIENCY OF THE MACEDONIAN STOCK EXCHANGE." In Economic and Business Trends Shaping the Future. Ss Cyril and Methodius University, Faculty of Economics-Skopje, 2022. http://dx.doi.org/10.47063/ebtsf.2022.0027.

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One of the basic hypotheses in modern finance that defines financial markets is the Efficient Market Hypothesis. The existence of information efficient markets, where all information is incorporated in the price of financial instruments is the basis of rational economic theory. There may be an upward or downward trend in the financial markets, but after the inclusion of new information in the financial instruments, they would stabilize until the next new information. In addition to the definition of efficient markets, the hypothesis of random walk has a significant application, which explains that the market cannot be beaten and that prices and returns move in a random upward or downward direction. The paper includes two methodologies to confirm the efficiency of the financial markets. The first research was conducted in order to confirm the hypothesis of a random walk implementing a coefficient of variance test. The test was conducted using a large series of data of the returns’ movement of stock exchange indices on the Macedonian, Belgrade, Zagreb, Sofia and Ljubljana Stock Exchange, as well as the American S&P500 index. The second research which is including the model of market multipliers was conducted for the most liquid stocks on the Macedonian Stock Exchange and selected stocks from the US Stock Exchange Markets, in order to show the underestimation or overestimation in relation to the market value of stocks, thus to show the sentiment that investors have when trading a certain type of stock. The results of the research show that the regional financial markets, as well as the domestic ones, do not follow the random walk, giving an opportunity to the possibility of using alternative behavioral approaches to explain the reasons for the deviation. For the second survey, where significant differences in the fundamental and market value of the stocks appear, the reason for the deviation is the expectations of investors.
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Zheng, Zhongbin, Jinwu Fang, and Tao Fu. "Stock Market Risk Measurement Based on QGARCH and Machine Learning Algorithm." In 2019 International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2019. http://dx.doi.org/10.1109/icemme49371.2019.00098.

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Marine, FJ, JC Bribiesca, and A. Arrona-Palacios. "BEHAVIORAL APPROACH ON THE MEXICAN STOCK MARKET MODELED THROUGH PLSSEM." In The 7th International Conference on Education 2021. The International Institute of Knowledge Management, 2021. http://dx.doi.org/10.17501/24246700.2021.7121.

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This paper analyzes the Mexican Stock Market indicators and their relationships to study the ten most representative stocks in The Mexican Stock Market Index between 2011 to 2020, reflecting behavioral effects using the Mexican Volatility Index. A longitudinal research design of 119 observations sample size is modeled monthly; this sample was transformed into categorical variables to reflect emotional stages. The main objective was to analyze the stock market emotions applying a novel approach to create latent behavioral variables using current Mexican behavioral indicators as reflexive constructs. There is a lack of knowledge in using different techniques to model financial behavior in financial and economic modeling. The typical techniques employed to model market time series have been simple and multiple regression, broadly used in this science. Since behavioral science appliances, there is a need for evolution to modeling the complex nature of behavior. Partial Least Squares and Structural Equation Models (PLS-SEM) can manage different scales, complex relations, reflexive or formative models, non-normal data, and small samples. Possible because of the lack of knowledge al flexibility of PLSSEM models, there is an evident lack in the use of this methodology in modern research and financial teaching, so a new methodology for modeling financial data is exposed that can resolve problems in financial researching and teaching. It is relevant to show a way of modeling emotional financial markets; it is recommended the use of this modeling in different kind of data, different countries, characteristics, sectors, industries, or variables, or any possible application in different sciences with the same problems of assumptions like in economics sciences. Keywords: Investor behavior, risk, market efficiency, Structural Equations, and Partial Least Squares methods
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Gercekovich, David. "Us Stock Market Sliding Verification Of Profit-Risk Model." In Trends and Innovations in Economic Studies, Science on Baikal Session. European Publisher, 2020. http://dx.doi.org/10.15405/epsbs.2020.12.34.

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6

Su, Weiwei. "Research on the Linkage Between the Foreign Exchange Market of RMB and Chinese and American Stock Markets." In 2019 International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2019. http://dx.doi.org/10.1109/icemme49371.2019.00031.

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Jablanovic, Vesna. "THE DOW JONES INDUSTRIAL AVERAGE (DJIA) STOCK MARKET INDEX AND THE CHAOTIC GROWTH MODEL." In Fourth International Scientific Conference ITEMA Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/itema.2020.113.

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The Dow Jones Industrial Average (DJIA) index includes the stocks of 30 of the largest companies in the United States. It represents about a quarter of the value of the entire U.S. stock market. The changes in the DJIA index are often considered to be representative of the entire stock market. The basic aims of this paper are: firstly, to create the simple chaotic the DJIA stock market index growth model that is capable of generating stable equilibria, cycles, or chaos; secondly, to analyze the local stability of the DJIA index movements in the period 1982-2009; and thirdly, to discover the equilibrium level of the DJIA index in the observed period. This paper confirms the existence of the stable convergent fluctuations of the DJIA index in the observed period. Also, the golden ratio can be used to define the equilibrium level of the DJIA index in the presented chaotic model.
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Bonelli, Marco I. "What Type of Asset is Bitcoin? An Answer from the Stock Market." In 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2020. http://dx.doi.org/10.1109/icemme51517.2020.00211.

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Tekin, Bilgehan, and Seda Nur Bastak. "The Relationship of Stock Prices and Stock Market Performance Ratios in Companies Trading on Borsa Istanbul: An Application in Companies with the Highest Trading Volume." In International Conference on Eurasian Economies. Eurasian Economists Association, 2021. http://dx.doi.org/10.36880/c13.02599.

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In this study, the effect of certain ratios that investors pay attention to on stock prices in Borsa Istanbul is examined. For this purpose, 30 of the stocks with which the investors traded the most were taken as a sample. In the study, 30 companies with the highest average trading volume in the analysis period were selected according to their transactions in Borsa Istanbul. The study covers the period between 2010: 1Q-2019: 4Q. Variables included in the study are stock market price, P/E ratio, trading volume, market to book ratio, beta, free float percentage. In this study, it has been tried to understand at what level the stock market prices of companies' publicly traded stocks are affected by the indicators that emerge as a result of the transactions realized in the stock exchange, rather than the ratios discussed within the scope of financial analysis and ratio analysis, examples of which are very common in the literature. Panel regression analysis was performed in the study. Before proceeding to the panel regression analysis, preliminary tests were carried out and the model was tried to be given its most suitable form. For this purpose, multicollinearity tests, cross section dependency test, second generation unit root tests, varying variance test, panel regression model selection were made. The model created in the last stage was estimated. As a result of the study, it was seen that the Price/Earnings, Transaction Volume, Market Value/Book Value and Beta variables were significantly effective on the stock market prices of the companies' stocks. Among these variables, BETA affects negatively, while other variables affect positively. The variable with the highest effect on the share price is the negative BETA coefficient and the positive direction is the trading volume.
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Zhu, Haidan. "Study on the Influence of Stock Index Futures on the Volatility of Spot Market." In 2019 International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2019. http://dx.doi.org/10.1109/icemme49371.2019.00084.

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Звіти організацій з теми "Economial model- Stock market"

1

López-Piñeros, Martha Rosalba, Norberto Rodríguez-Niño, and Miguel Sarmiento. Política monetaria y flujos de portafolio en una economía de mercado emergente. Banco de la República de Colombia, May 2022. http://dx.doi.org/10.32468/be.1200.

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Portfolio flows are an important source of funding for both private and public agents in emerging market economies. In this paper, we study the influence of changes in domestic and US monetary policy rates on portfolio inflows in an emerging market economy and discriminate among fixed income instruments (government securities and other corporate bonds) and variable income instruments (shares). We employ monthly data on portfolio inflows of non-residents in Colombia during the period 2011-2020 and identify the monetary policy shocks using a SVAR model with long-run restrictions. We find a positive and statistically significant response of portfolio inflows in government securities and corporate bonds to changes in both domestic and US monetary policy rates. Portfolio inflows in the stock market react more to changes in the inflation rate and do not react to changes in monetary policy rates. Our findings are consistent with the predictions of the interest rate channel and reestablish the predominant role of inflation rate in driving portfolio inflows. The results suggest that domestic and US monetary policy actions have an important effect on the behavior of portfolio inflows in emerging economies.
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Turner, Christopher, Richard Startz, and Charles Nelson. A Markov Model of Heteroskedasticity, Risk, and Learning in the Stock Market. Cambridge, MA: National Bureau of Economic Research, January 1989. http://dx.doi.org/10.3386/w2818.

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3

Naddafi, Rahmat, Göran Sundblad, Alfred Sandström, Lachlan Fetterplace, Jerker Vinterstare, Martin Ogonowski, and Nataliia Kulatska. Developing management goals and associated assessment methods for Sweden’s nationally managed fish stocks : a project synthesis. Department of Aquatic Resources, Swedish University of Agricultural Sciences, 2023. http://dx.doi.org/10.54612/a.31cfjep2i0.

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This report summarizes and synthesizes results from the Swedish Agency of Marine and Water Management (SwAM, or HaV) funded project “Förvaltningsmål för nationella arter (Management goals for nationally managed species)”. The objectives of the project have been to promote the development of management goals and associated status assessment methods and indicators, as well as reference points, for some nationally managed fish stocks both in coastal as well as freshwater areas. The report focusses largely on species and stocks that can be defined as data-poor. Such stocks are characterised by marked limitations in data availability and/or resources allocated to detailed analytical stock projections. Data-poor stocks also often lack carefully formulated management goals and associated methods and indicators for assessing stock status. In this report, we provide an overview of potential assessment methods and indicators and try to synthesise how they work and what the strengths and weaknesses are by applying them to selected data poor stocks such as pikeperch, pike, whitefish, and vendace. We also discuss how they relate to different potential management goals and provide recommendations for their application. We grouped the indicators and assessment methods by the three categories that are now used in the yearly status assessment framework provided by SLU Aqua (Resursöversikten/Fiskbarometern) – i) mortality, ii) abundance/biomass and iii) size/age structure. The results are also described for these three main categories of assessment indicators. Included is also a status report from a size- and age-based population dynamics model (Stock Synthesis 3) that is being developed for pikeperch in Lake Hjälmaren. An important experience from the project is that to improve the assessment methods for Swedish national fish stocks, it is important that managers develop both general as well as more detailed quantitative goals for the individual stocks. This should ideally be conducted in various forms of collaboration with the main stakeholders and scientists involved with assessment as participatory processes foster legitimacy. Carefully articulated management goals, which are possible to translate into quantitative targets, will facilitate the development of various approaches and methods to monitor stock statuses. Given the strong and complex interactions of fish and their environments it is also important to consider other pressures than fisheries when developing indicators and assessment methods. Our synthesis highlights a number of areas where the assessment of data-poor stocks can be improved: 1. Apply precautionary principles for data-limited stocks, particularly ones that are known to be vulnerable to exploitation. 2. Tailor approaches to how fisheries are managed in Sweden. Swedish nationally managed fish stocks are not managed by quotas (with one exception, vendace in the Bothnian Bay) and do not aim for maximum sustainable yield. Instead, the coastal and inland fisheries are managed by regulating the effort in the small-scale commercial fisheries (number of fishers/licenses and amount of gear). Regulation of recreational and subsistence fisheries effort, in terms of licenses or number of fishers) is not applied, nor possible since the fisheries is lacking obligatory notification and reporting systems. All national fisheries, however, are regulated by various technical measures (closed areas, size-limits, bag-limits, gear restrictions etc). Thus, goals and assessment methods that result in harvest limits or quota recommendations expressed in e.g. biomass/numbers are difficult to use as basis for management. Instead, there is a need for alternative management goals and associated assessment methods. 3. Use best practice methods and indicators and adapt as scientific knowledge is developed. Data-limited methods are developing rapidly, and new methods/approaches are proposed in the scientific literature every year. It is thus important to be updated on the most recent developments. 4. Clearly describe limitations/assumptions of methods used. It is important to be aware of and critically evaluate the assumptions underlying the analyses, and to carefully communicate uncertainty together with the stock status assessment. 5. Be particularly careful with low sample numbers. Many indicators and methods can be applied also on small sample sizes, however, the accuracy and precision of the estimates risk being low in such cases. 6. Accept that there is no "gold standard" for fisheries assessment. Each case study is unique and needs to be balanced against data availability, local needs and other important factors. This also means that analysts need to be careful when using generic reference levels or “borrowing” data from other stocks. 7. If possible, use several different methods/indicators. Although several indicators aim to measure similar aspects of the stock, small methodological differences can support the overall interpretation of individual indicator values. It is particularly important to incorporate many aspects and indicators (size/age/abundance/mortality) in order to produce a balanced assessment. 8. Develop means of communication. Indicators and goals should be easy to understand. However, interpretation of results from multi-indicator frameworks can be challenging. There is thus a need for finding ways of communication that can convey complicated results in a simple-to-understand manner. 9. For details on additional improvements, we refer the reader to the sub-header “recommendations for the future” found under each chapter. The implementation of Stock Synthesis for pikeperch in Lake Hjälmaren showed that it is possible to develop a more ambitious and detailed stock assessment model for a relatively data-poor stock. The model results partly support earlier interpretations of the development of the stock and the importance of the changes in regulations in 2001 (increased minimum size, increased mesh size and reduced mortality of undersized pikeperch). Before the model can be implemented and used for practical management, a number of actions for improvement are needed, which are highlighted in the relevant chapter. The most important next step is establishing management goals and reference levels for this stock. We recommend that such a dialogue is initiated by managers. The fisheries management goals should consider both biomass, fisheries mortality and size-based targets. To conclude, we stress the importance of improving all ongoing aspects related to the assessments of data-poor Swedish stocks. Strong local stocks and sustainable fisheries are vital for a variety of fisheries-related businesses and practices, particularly in rural areas, providing economical and societal value. Fishes also have important roles in aquatic food-webs and it is important that ecological values are managed wisely in order to reach targets for water quality, ecosystem structure and diversity. Given the strong and complex interactions of fish and their environments it is also important to consider other pressures than fisheries when developing indicators and assessment methods.
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Соловйов, В. М., та В. В. Соловйова. Моделювання мультиплексних мереж. Видавець Ткачук О.В., 2016. http://dx.doi.org/10.31812/0564/1253.

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From the standpoint of interdisciplinary self-organization theories and synergetics analyzes current approaches to modeling socio-economic systems. It is shown that the complex network paradigm is the foundation on which to build predictive models of complex systems. We consider two algorithms to transform time series or a set of time series to the network: recurrent and graph visibility. For the received network designed dynamic spectral, topological and multiplex measures of complexity. For example, the daily values the stock indices show that most of the complexity measures behaving in a characteristic way in time periods that characterize the different phases of the behavior and state of the stock market. This fact encouraged to use monitoring and prediction of critical and crisis states in socio-economic systems.
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Baratta, James N. Network-Centric Warfare and Information Technology: The Stock Market as a Historical Model. Fort Belvoir, VA: Defense Technical Information Center, February 2000. http://dx.doi.org/10.21236/ada378505.

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Bajari, Patrick, and John Krainer. An Empirical Model of Stock Analysts' Recommendations: Market Fundamentals, Conflicts of Interest, and Peer Effects. Cambridge, MA: National Bureau of Economic Research, August 2004. http://dx.doi.org/10.3386/w10665.

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7

Hambrey, John, Paul Medley, Sue Evans, Crick Carlton, Carole Beaumont, and Tristan Southall. Evidence gathering in support of sustainable Scottish inshore fisheries: work package (6) final report: integrating stock management considerations with market opportunities in the Scottish inshore fisheries sector – a pilot study. Marine Alliance for Science and Technology for Scotland (MASTS), 2015. http://dx.doi.org/10.15664/10023.24677.

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In June 2014, Hambrey Consulting successfully responded to a call for tenders for research to undertake a pilot assessment of the potential economic and associated benefits of establishing minimum market landing size (MMLS) in excess of minimum legal landing size (MLS) for shellfish; and to evaluate if such an intervention could be undertaken at a regional level. The project was originally conceived as including 3 case studies, but the scope of the research led us to focus mainly on the trawl and creel fishery for Nephrops prosecuted by the fleet based in Skye and SW Ross. The basic framework for the assessment approach was to: Develop an economic profile of the case study area and its fishing fleet; Review and synthesise existing data on size profile of the catch, the factors that affect size, including costs associated with individual (vessel) actions or strategies to increase the size profile of the catch; Analyse market and market trends, and the prices for different sizes of product; Develop economic models of representative fishing enterprises, taking account of the relationships between costs and returns and the size profile of the catch; Use plausible scenarios to explore likely short term economic consequences of any changes in MMLS; Use yield and utility per recruit analysis to explore possible yield benefits associated with increased MMLS.
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Yasuhara, Tsuyoshi. Working Paper PUEAA No. 11. Profit Seeking Model and the Monetary Policy in Japan: cross-border asset holdings via Offshore Financial Centers. Universidad Nacional Autónoma de México, Programa Universitario de Estudios sobre Asia y África, 2022. http://dx.doi.org/10.22201/pueaa.009r.2022.

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Recently, the Junichiro Koizumi and Shinzo Abe administration has adopted labor reforms, and monetary authorities have updated unconventional monetary policies: quantitative easing of money supply and negative interest rate control. It can be identified that quantitative easing policy and negative interest rate policy have introduced and stimulated new styles of profit-seeking through stock market transactions, which only increases corporate and bank profits under a stagnant labor productivity growth rate. Under such a context, this paper analyzes the changing phase of the profit-seeking patterns of the financial and non-financial sector in Japan. The hypothesis is that the large-scale corporate sector has created a new profit-seeking paradigm and that this has been supported by the monetary control of the so-called "Abenomics".
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Gálvez, Julio, and Gonzalo Paz-Pardo. Richer earnings dynamics, consumption and portfolio choice over the life cycle. Madrid: Banco de España, November 2022. http://dx.doi.org/10.53479/23686.

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Households face earnings risk which is non-normal and varies by age and over the income distribution. We show that allowing for these rich features of earnings dynamics, in the context of a structurally estimated life-cycle portfolio choice model, helps to better understand the limited participation of households in the stock market and their low holdings of risky assets. Because households are subject to more background risk than previously considered, the estimated model implies a substantially lower coeffcient of risk aversion and a lower optimal risky share for older workers with low wealth and high earnings.
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Gálvez, Julio, and Gonzalo Paz-Pardo. Richer earnings dynamics, consumption and portfolio choice over the life cycle. Madrid: Banco de España, November 2022. http://dx.doi.org/10.53479/23706.

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Households face earnings risk which is non-normal and varies by age and over the income distribution. We show that, in the context of a structurally estimated life-cycle portfolio choice model, allowing for these rich features of earnings dynamics helps to better understand the limited participation of households in the stock market and their low holdings of risky assets. Because households are subject to more background risk than previously considered, the estimated model implies a substantially lower coefficient of risk aversion and a lower optimal risky asset share for older workers with low wealth and high earnings.
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