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Financial Innovation 2021年第1期7卷 233-254页

作者： Veli Yilanci Onder Ozgur Muhammed Sehid Gorus Sakarya University SerdivanSakaryaTurkey Ankara Yildirim Beyazit Universitesi ÇubukAnkaraTurkey

This study investigates the stock price–economic activity nexus in 12 member countries of the Organization for Economic Cooperation and Development(OECD)by employing monthly data over the period 1981:1–2018:*** this purpose,the study uses Granger causality in the frequency domain in the panel setting by decomposing the symmetric and asymmetric *** methodology determines whether the predictive power of interested variables is concentrated on quickly,moderately,or slowly fluctuating *** findings show that the stock prices have predictive power for future long-term economic activity in the panel ***,economic activity has more reliable information for stock prices for negative ***,empirical findings for asymmetric shocks are not fully consistent with those of symmetric ***,the country-specific results provide different causal linkages across members and *** findings may provide valuable information for policymakers to design proper and effective policies in OECD countries regarding the stock market and economic activity nexus.

关键词： Asymmetric causality Economic activity Frequency domain OECD countries Panel data stock prices

Bankruptcy Probability and stock prices： The Effect of Altman Z-Score Information on stock prices Through Panel Data

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Journal of Modern Accounting and Auditing 2011年第7期7卷 689-696页

作者： Nicholas Apergis John Sorros Panagiotis Artikis Vasilios Zisis University of Piraeus Greece

There is an extensive branch of literature that examines the success of Altman＇s Z-score in predicting bankruptcy or financial distress. The goal of this research paper is to investigate the stock price performance of firms that exhibit a large probability of bankruptcy according to the model of Airman. Regardless of the validity of Airman＇s Z-score, we utilize a new empirical design that relates stock price movements to Altman＇s Z-score. We focus and examine, through the methodology of panel data, whether stocks that have a high probability of bankruptcy underperform stocks with a low probability of bankruptcy or if there are differences in the way the markets react to the financial health of the sample firms.

关键词： Airman's Z-score stock prices panel data

A Panel Data Analysis of Corporate Attributes and stock prices for Indian Manufacturing Sector

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Journal of Modern Accounting and Auditing 2013年第11期9卷 1519-1525页

作者： Mehul Raithatha Varadraj Bapat Institute for Financial Management and Research Chennai India Indian Institute of Technology Bombay Mumbai India

stock prices have always been considered as unpredictable phenomena due to their dynamic patterns. Identifying the forces that contribute to variations of stock prices is probably one of the most researched areas in finance. This study relates stock prices to the stock volatility （measured by beta） and to corporate attributes, i.e., size, liquidity, profits, leverage, and returns. The study is based on manufacturing sector in India, and it is based on a sample of 3,027 manufacturing companies during the periods from 1991-1992 to 2006-2007 collected from the Centre for Monitoring Indian Economy （CMIE） database. The regressions were performed with the dummies for time effect and firm effect separately and then for both effects together. Panel data models have been used to estimate the stock prices equation. The model finds out fixed and random effects between independent and explanatory variables and analyzes them through Hausman test. The paper also studies multicollineairity that may exist amongst the selected variables. The study shows that volatility （represented by Beta）, profit （represented by earnings per share （EPS））, and size （represented by market capitalization （MCAP）） significantly influence the stock prices （at the level of 5%）. Panel data analysis using Hausman test supports the fixed effect model.

关键词： panel data stock prices correlation Hausman test

stock market and macroeconomic variables:new evidence from India

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Financial Innovation 2019年第1期5卷 503-519页

作者： R.Gopinathan S.Raja Sethu Durai School of economics shri mata vaishno devi universitykatrajammu&kashmir 182320india school of economics university of hyderabadhyderabadtelangana 500046india

Understanding the relationship between macroeconomic variables and the stock market is important because macroeconomic variables have a systematic effect on stock market *** study uses monthly data from India for the period from April 1994 to July 2018 to examine the long-run relationship between the stock market and macroeconomic *** empirical findings suggest that standard cointegration tests fail to identify any relationship among these ***,a transformation that extracts the actual functional relationship between these variables using the alternating conditional expectations algorithm of(J Am Stat Assoc 80:580–598,1985)identifies strong evidence of cointegration and indicates nonlinearity in the long-run ***,the continuous partial wavelet coherency model identifies strong coherency at a lower frequency for the transformed variables,establishing the fact that the long-run relationship between stock prices and macroeconomic variables in India is nonlinear and *** evidence has far-reaching implications for understanding the dynamic relationships between the stock market and macroeconomic variables.

关键词： stock prices Nonlinear cointegration Alternating conditional expectations Continuous wavelet transformation

Exploring the growth value equity valuation model with data visualization

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Financial Innovation 2023年第1期9卷 19-55页

作者： I‑Cheng Yeh Yi‑Cheng Liu Department of Civil Engineering Tamkang University151 Yingzhuan Rd.Tamsui Dist.New Taipei City 25137Taiwan Department of International Business Tamkang University151 Yingzhuan Rd.Tamsui Dist.New Taipei City 25137Taiwan

The Growth Value Model(GVM)proposed theoretical closed form formulas consist-ing of Return on Equity(ROE)and the Price-to-Book value ratio(P/B)for fair stock prices and expected rates of *** regression analysis can be employed to verify these theoretical closed form formulas,they cannot be explored by classical quintile or decile sorting approaches with intuition due to the essence of multi-factors and dynamical *** article uses visualization techniques to help intuitively explore *** discerning findings and contributions of this paper is that we put forward the concept of the smart frontier,which can be regarded as the reasonable lower limit of P/B at a specific ROE by exploring fair P/B with ROE-P/B 2D dynamical process *** coefficients in the formula can be determined by the quantile regression analysis with market *** moving paths of the ROE and P/B in the cur-rent quarter and the subsequent quarters show that the portfolios at the lower right of the curve approaches this curve and stagnates here after the portfolios are ***,exploring expected rates of return with ROE-P/B-Return 3D dynamical process visualization,the results show that the data outside of the lower right edge of the“smart frontier”has positive quarterly return rates not only in the t+1 quarter but also in the t+2 *** farther away the data in the t quarter is from the“smart frontier”,the larger the return rates in the t+1 and t+2 quarter.

关键词： Data visualization stock prices Rates of return Return on equity Price-tobook value ratio

The Effects of Exchange Rate Fluctuations on the stock Price of Anglo-American PLC

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The Effects of Exchange Rate Fluctuations on the Stock Price...

作者： Baone V.Moshebashebi 上海师范大学

学位级别：硕士

Several variables influence the market prices of mining companies,such as inflation,exchange rates,interest rates,geopolitics,basic metal prices,*** purpose of this analysis is to examine the effect of such factors influencing the stock price of the Anglo-American mining company in South Africa and the United Kingdom,specifically,exchange,inflation,and interest rates with inflation and interest rates being controlled *** data from the Anglo-American Plc reports,the Johannesburg and London stock exchanges and the two countries’ central reserves are used as the statistics collection *** study uses a special case of panel data which is,time-series data and it adopts a longitudinal study or panel *** findings are evaluated using the application of R Statistical software through a linear data regression analysis *** data is tested for unit *** technical analysis used shows that exchange rates and stock prices significantly follow a random-walk *** variables are non-stationary at their level and they become stationary in their first *** tests and further statistical inferences are *** findings realized will shed some additional light on the risks involved in exchange rates and commodity prices for policymakers of countries dependent primarily on commodity *** findings show that there is a rather low statistically significant linear relationship between the USD/GBP exchange rate and the AAL: LO stock price in the short *** findings are reached for the USD/ZAR exchange rate and the ANG: JO stock *** means that there is no instantaneous effect of exchange rates on the stock price.

关键词： Exchange Rate stock prices Cointegration ANOVA

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基于LSTM预测方法研究

基于LSTM预测方法研究

作者： Ahoussou Kouassi Rodrigue 安徽农业大学

学位级别：硕士

Forecasting stock market prices have always been challenging task for many business analyst and *** fact,stock market price prediction is an interesting area of research for *** successful investment,many investors are interested in knowing about the future situation of the *** prediction systems indirectly help traders by providing supportive information such as the future market *** mining techniques are effective for forecasting future by applying various algorithms to *** researchers have contributed in this area of chaotic forecast in their *** many year different method have been used for resolving many problem in this *** this project,we study the problem of stock market forecasting using Recurrent Neural Network(RNN)with Long Short-Term Memory(LSTM).The purpose of this project is to examine the feasibility and performance of LSTM in stock market *** test the performance of the LSTM with other types of *** Neural Network is trained on the stock quotes using the Back propagation Algorithm which is used to predict share market closing *** our work we use different inputs to build our recurrent neural network to see what the impact on the different predictions *** Accuracy of the performance of the neural network is compared with other accuracy of different *** also prove that some algorithm are good for prediction in a short period but not as a long *** our work of prediction prices,we got the data on the site of *** our work we use three different type of *** different types of technique are:the first technique used to calculate the loss error is named The technique of standard Average and the linear regression news.;the second we use is called the technique of Exponential Moving Average,and finally we use the last technique we use is called the long Short Term memory Network or also called(LSTM).After using these different methods we p

关键词： Long Short-Term Memory(LSTM) root mean square error(RMSE) prediction stock prices

The Voice of Physics in Finance:A Glance on the Theoretical Application of Heat Equation to stock Price Diffusions

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Journal of Economic Science Research 2021年第1期4卷 1-4页

作者： Leonard Mushunje Midlands State University Department of Applied Mathematics and StatisticsZimbabwe

stock price volatility is considered the main matter of concern within the investment ***,the diffusivity of these prices should as well be *** such,proper modelling should be done for investors to stay *** paper suggest to model stock price diffusions using the heat equation from *** hypothetically state that,our model captures and model the diffusion bubbles of stock prices with a better precision of *** compared our model with the standard geometric Brownian motion model which is the wide commonly used stochastic differential equation in asset ***,the models proved to agree as evidenced by a bijective relation between the volatility coefficients of the Brownian motion model and the diffusion coefficients of our heat diffusion model as well as the corresponding drift ***,a short proof for the martingale of our model is done which happen to hold.

关键词： stock prices Volatility Diffusion Heat equation Brownian motion model Physics