Currency exposures of the oil and natural gas stock prices in the Hushen-300 stock market： A nonlinear model approach

The paper embarks to investigate the relationship between currency risk and stock prices of the oil and natural gas exploitation industry in the value-weighted Hushen-300 stock market, by applying the standard Capital Asset Pricing Model （CAPM） and nonlinear exchange rate exposure model to the Renminbi against US dollar. The results show that the currency exposure does vary in the oil-gas stock prices throughout the bull and bear market. The study suggests that the models of the equilibrium exchange rate exposure must be extended to considering the nonlinear exchange rate exposure, the regime periods of bull and bear market, and the industry types that is sensitive to the currency exposures. The nonlinear dynamic relationship between the exchange rate changes and the Chinese energy stock prices throughout the bull and bear market add to the recent empirical evidences that foreign exchange markets and stock markets are closely correlated.

Impact of Oil Price Fluctuations on Returns of Different Sectors of Malaysian Stock Market

Oil price fluctuations affect equity values in North American, European, and Gulf Cooperation Council （GCC） stock markets, as evidenced by prior studies. However, they only focus on market-wide level analysis. This study, through both market level and sector level analyses, examines the sensitivity of Malaysian stock returns to oil price fluctuations over the period from January 2000 to March 2014. A multifactor market model has been employed to capture this sensitivity. The regression results show a positive impact of oil price changes on the Financial Times Stock Exchange Kuala Lumpur Composite Index （FTSE KLCI） market return. Consumer staples and energy sector index returns were also positively affected by oil price changes. On the other hand, utilities and telecom services were negatively affected over the study period. Moreover, Granger causality analysis was performed to see if oil price fluctuations Granger cause the stock indices to change. With one month lag period, oil price fluctuations Granger cause consumer staple, energy, industrials, and telecommunication services return. Relevant policymakers and market caretakers （Ministry of Finance, Central Bank, and Security Commission） may use the fmdings of this study to develop and incorporate a preventive mechanism to minimize the unfavorable impacts of oil price fluctuations on different sectors of stock market, and Malaysian economy in general.

Stock Market Turnover and China’s Real Estate Market Price: An Empirical Study Based on VAR

Our analysis used the monthly data of the average sales price of commodity houses and stock turnover in the Shenzhen Stock Exchange from January 2016 to December 2020. We selected this data to establish a Vector Autoregression(VAR) model using the Granger causality test to investigate the correlation between the stock market and the real estate market. We found that there is a significant positive correlation between the stock market and the real estate market. We also found that the real estate market price is the one-way Granger cause for the stock market turnover, and that changes in the real estate market price have a significant role in forecasting changes in stock market turnover. Therefore, the linkage between the two markets should be considered in macro regulations, and the impact on one of the markets should be considered when regulating the other.

Effects of Financial Market Variables on Stock Prices:A Review of the Literature

Stock market plays a pivotal role in firms’expansion and turns economic growth.In the literature,because of the importance of stock markets to the real economy,the smooth and risk-free operation of the stock market has attracted significant attention.The finance literature contains a large number of studies that examine the stock price behaviour with some emphasis on the determinants of the relationship between the equity prices and the financial market activities.The present study reviews the previous works of the effect of financial market variables and stock price.Five selected financial market variables,market capitalization,earnings per share,price earnings multiples,dividend yield,and trading volume are reviewed in this study.In the past literature,there are the opinions of the positive significant relationship between market capitalization and stock price.To find the relationship between dividend yield and stock price,there are two broad schools of thoughts.Both of the relevance and irrelevance theory of Gordon and Modigliani have the strong evidence in the current literature that keeps on the dilemma and provides the scopes for future research.Price-earnings multiples are analyzed in the past literature by using different variables.Based on that,it is evidenced that price-earnings multiples have a negative significant effect on stock price.The reviewed studies state the cointegrating relationship between the stock price and the trading volume as the trading volume is a source of risk.

Markov-Switching Time-Varying Copula Modeling of Dependence Structure between Oil and GCC Stock Markets

This paper proposes a Markov-switching copula model to examine the presence of regime change in the time-varying dependence structure between oil price changes and stock market returns in six GCC countries. The marginal distributions are assumed to follow a long-memory model while the copula parameters are supposed to evolve according to the Markov-switching process. Furthermore, we estimate the Value-at-Risk (VaR) based on the proposed approach. The empirical results provide evidence of three regime changes, representing precrisis, financial crisis and post-crisis, in the dependence structure between energy and GCC stock markets. In particular, in the pre- and post-crisis regimes, there is no dependence, while in the crisis regime, there is significant tail dependence. For OPEC countries, we find lower tail dependence whereas in non-OPEC countries, we see upper tail dependence. VaR experiments show that the Markov-switching time- varying copula model performs better than the time-varying copula model.

ARIMA and Facebook Prophet Model in Google Stock Price Prediction

We use the Autoregressive Integrated Moving Average(ARIMA)model and Facebook Prophet model to predict the closing stock price of Google during the COVID-19 pandemic as well as compare the accuracy of these two models’predictions.We first examine the stationary of the dataset and use ARIMA(0,1,1)to make predictions about the stock price during the pandemic,then we train the Prophet model using the stock price before January 1,2021,and predict the stock price after January 1,2021,to present.We also make a comparison of the prediction graphs of the two models.The empirical results show that the ARIMA model has a better performance in predicting Google’s stock price during the pandemic.

SIMPLEST DIFFERENTIAL EQUATION OF STOCK PRICE,ITS SOLUTION AND RELATION TO ASSUMPTION OF BLACK-SCHOLES MODEL

Two kinds of mathematical expressions of stock price, one of which based on certain description is the solution of the simplest differential equation (S.D.E.) obtained by method similar to that used in solid mechanics,the other based on uncertain description (i.e., the statistic theory)is the assumption of Black_Scholes's model (A.B_S.M.) in which the density function of stock price obeys logarithmic normal distribution, can be shown to be completely the same under certain equivalence relation of coefficients. The range of the solution of S.D.E. has been shown to be suited only for normal cases (no profit, or lost profit news, etc.) of stock market, so the same range is suited for A.B_ S.M. as well.

Exploring Apple’s Stock Price Volatility Using Five GARCH Models

The financial market is the core of national economic development,and stocks play an important role in the financial market.Analyzing stock prices has become the focus of investors,analysts,and people in related fields.This paper evaluates the volatility of Apple Inc.(AAPL)returns using five generalized autoregressive conditional heteroskedasticity(GARCH)models:sGARCH with constant mean,GARCH with sstd,GJR-GARCH,AR(1)GJR-GARCH,and GJR-GARCH in mean.The distribution of AAPL’s closing price and earnings data was analyzed,and skewed student t-distribution(sstd)and normal distribution(norm)were used to further compare the data distribution of the five models and capture the shape,skewness,and loglikelihood in Model 4-AR(1)GJR-GARCH.Through further analysis,the results showed that Model 4,AR(1)GJR-GARCH,is the optimal model to describe the volatility of the return series of AAPL.The analysis of the research process is both,a process of exploration and reflection.By analyzing the stock price of AAPL,we reflect on the shortcomings of previous analysis methods,clarify the purpose of the experiment,and identify the optimal analysis model.

Risk Management via Measuring Impacts of Micro and Macro Economic Factors on Financial Firm Stock Price—A Case of Mitsubishi UFJ in Japan

Mitsubishi UFJ(MUFJ)has made very positive contributions to the overall achievements of the banking industry,deserving its position as one of the leading financial groups in Japan,contributing to helping government stabilizes the market and successfully implement monetary policy.MUFJ is aiming for growth of approximately¥250 billion in net operating profits,with MUFG Group companies,business groups,and the corporate center.Movement of stock price in financial groups such as MUFJ will reflect the business health of bank and financial system and the whole economy.Good business management requires us to consider the impacts of multi micro and macro factors on stock price,and it contributes to promoting business plan and economic policies for economic growth and stabilizing macroeconomic factors.By data collection method through statistics,analysis,synthesis,comparison,quantitative analysis to generate qualitative comments and discussion;using econometric method to perform regression equation and evaluate quantitative results,the article analyzed and evaluated the impacts of six(6)micro and macro economic factors such as:cost,net sale,lending rate,inflation,GPD growth,S&P 500,etc.on stock price of a big financial group,MUFJ in Japan in the period of 2010-2019,both positive and negative sides.The results of quantitative research,in a seven-factor model,show that the decrease in inflation,GDP,and high lending rate has a significant effect on reducing MUFJ stock price with the highest impact coefficient,the second is increase in cost.This research finding and recommended policy also can be used as reference in policy for commercial bank and financial system in many developing countries.

Reinvestigating the Oil Price-Stock Market Nexus： Evidence from Chinese Industry Stock Returns

The present study investigates the influence of international oil prices on China＇s stock market returns across 29 different industries. The paper attempts to account for any structural breaks and nonlinearity in this relationship. The results reveal that the effect of changes in the international price of oil on stock returns differs substantially across industries. The stock returns of the coal chemical mining and oil industries are found to be positively affected by crude oil price movements. Conversely, electronics, food manufacturing, general equipment, pharmaceuticals, retail rubber and vehicle industries are found to be negatively affected by movements in the price of crude oil. The results of the estimations also suggest that the majority of Chinese industries have been significantly affected by oil prices since 2004. The influence of international oil prices on Chinese stocks also has a stronger effect in the presence of high volatility but the effect varies across industries.

The capital market spillover effect of product market advertising:Evidence from stock price synchronicity

We analyze whether product market advertising has a spillover effect on stock price synchronicity by transmitting firm-specific information to the capital market and attracting more investor attention.Using a sample of Chinese listed firms from 2009 to 2017,we find that firms with greater advertising expenditures have lower stock price synchronicity.The results are robust after we address endogeneity concerns.In accord with our hypothesis that product market advertising increases the amount of firm-level information capitalized into stock prices through the information channel,we find that the impact of advertising on synchronicity is more pronounced for firms with a higher degree of information asymmetry and firms in the consumer-product industry.Further tests show that product market advertising enhances the ability of current period returns to reflect future earnings,and thus rules out that the negative relationship between advertising and synchronicity is driven by noise trading.Our results imply that product market advertising plays an informative role and improves information efficiency in a capital market.

Does a national industrial policy promote financial market stability?A study based on stock price crash risk

Whether the implementation of a national industrial policy can maintain stability in the financial market is a question of theoretical and practical significance. Using data from China’s non-financial listed firms from 2007 to 2020,we find that a national industrial policy lowers stock price crash risk. We find that the effect of an industrial policy on lowering stock price crash risk is more pronounced in regions with low levels of regional marketization and if firms have high external uncertainty, low total asset turnover, greater earnings management and receive small increments of long-term loans and fewer government subsidies, suggesting that industrial policies lower stock price crash risk by improving firm fundamentals and reducing external uncertainty,agency costs and information asymmetry.

Institutional environment and risk of a stock price crash:evidence from China

Stock price crashes damage China’s macro-financial stability,restrict economic growth,and can lead to huge losses in wealth for investors.Therefore,how to reduce the risk for stock price crashes is an important theoretical and practical issue.This paper mainly studies the effects of the institutional environment that creates risks for stock price crashes.Using China’s non-financial A-share listed companies from 1997 to 2012 as an example,this paper finds that the lower the level of government intervention is,the better the legal environment is,the faster the market process in business area is,then the lower the risks for stock price crashes will be.To solve the endogenous problem between the institutional environment and the risk of a stock price crash,this paper uses the number of seaports and whether the commercial ports or leased territories are opened after the first Opium War in Qing Dynasty as instrumental variables of the institutional environment.We find that the above conclusion is still valid with the method of 2SLS regression.Furthermore,this paper also finds that the government intervention index,the legal environment index,and the market index are negatively related to stock price synchronicity to a significant degree.These conclusions illustrate that the institutional environment is an important factor in the healthy and stable development of the capital market,which has important implications for policy markers or regulators to develop policies to promote the stable development of the stock market,to control market risk of listed companies,and to make investment decisions.

Determinants of market price of stock： A study on bank leasing and insurance companies of Bangladesh

Financial firms make up a substantial fraction of the domestic equity market. A number of studies subsequently used different conceptual and methodological approaches to model equity return of financial services firms. Movement of the stock price as the consequence of the movement of the micro and macroeconomic factors is strongly supported by the literature review. Dhaka Stock Exchange in Bangladesh is inefficient in weak form. Multiple regression analysis is conducted to find out the relationship microeconomic factors with the stock price. In this study found a significant linear relationship among market return and some microeconomic factors such as net asset value per share, dividend percentage, earning per share of bank leasing and insurance companies. Also found non-linear relationship among the variables is insignificant at 95 percent level of significance.

Could the Stock Market Adjust Itself? An Empirical Study Based on Mean Reversion Theory

This paper mainly studies whether and how stock prices fluctuate around their intrinsic values.Based on data from 10 stock markets for the period between 2000 and 2018,we demonstrate that the relative price fluctuates around and approaches the intrinsic value in the long term.For the ten markets,the relative price crosses the intrinsic value on average once in 3~4 years.Profitability growth is a key factor in rising stock prices,but the level of valuations in the market has a regulatory effect to the growth of price in the future:For every 1%increase in valuation,the price tends to decline by 0.26%in the next year,0.74%in the next 3 years.

Brent prices and oil stock behaviors: evidence from Nigerian listed oil stocks

Background:Given the shale oil glut that culminated in the most recent and continuing oil price drop from June 2014 and the global financial crisis of 2008 that triggered a cyclical downturn in oil prices and stock market activity,this study investigates the impact of Brent oil price shocks on oil related stocks in Nigeria.Methods:This study uses a vector autoregressive(VAR)model with the impulse response function and the forecast variance decomposition error.Findings:The empirical evidence reveals that oil price shocks have a negative impact on Nigerian oil and gas company stocks.In theory,this situation should apply to oil importing countries and is therefore uncharacteristic of an oil exporting country like Nigeria.Conclusions:The findings suggest that oil companies operating in Nigeria should diversify their investments to protect their business from single-sector market forces,and can also embrace the advantages of outsourcing some of their operations to specialist providers to increase flexibility and reduce operating costs.Finally,for vertically integrated oil and gas companies,oil price hedging and energy risk management will be beneficial because it will mean that these companies will take a position in the crude oil futures market.This will allow for better cash flow management and flexibility.Originality/value:This study extends the existing literature in two distinct ways.First,it provides,to the best of our knowledge,the first examination of the impact of oil price shocks on stock market activities with a focus on the market returns of oil and gas companies listed in the Nigerian Stock Exchange.Second,this study uses daily data because high frequency data contain more information than lower frequency data does,and lower frequency data average out too much important information.

Harmonious Stock Prices

Stock price movements in China still remain highly harmonious, in spite of the many significant regulatory and structural changes over the recent years. A survey of the literature reveals that harmony in the stock price movements is related to a few salient features in China＇s capital market： high ownership concentration, high incidence of the use of pyramidal ownership structure, significant state ownership, and a lack of active institutional investors. In addition, we also point out that harmonious stock prices may generally result from low intensity of private information acquisitions by risk arbitrageurs.

Analysis of Stock Splits Based on Risk Theory: Empirical Evidence from the Chinese Stock Markets

The paper first analyzes price change due to stock splits in Chinese stock markets,which shows stock prices typically go up for stock splits.Then theoretical analyses based on risk theory are presented to explain the reason,where the method comes from a new perspective and obtained theoretical conclusions show that stock splits typically make stock price go up if risk-compensation function is convex,and go down if risk-compensation function is concave.Stock prices typically go up for stock splits because risk-compensation functions are mainly convex.The obtained conclusions are consistent with the known results in the last three decades.

Starts and refutations of the Covid-19 rumors:Evidence from the reaction of the stock market

By manually collecting data on Internet-based rumors concerning COVID-19,we investigate the market reactions to the spread of such rumors and the government’s refutation of them.We find that frightening(reassuring)rumors have a negative(positive)impact on investors.The refutation of frightening rumors triggers a positive market response,whereas the refutation of reassuring rumors does not cause a significant market reaction.Further analysis shows that there is a stock price drift when frightening rumors are refuted by governments.Our conclusions remain robust after considering endogeneity.Our findings support the notion that epidemic-related rumors affect investors’decisions,which add to literatures of the market responses of companies in the context of the COVID-19 pandemic and provide incremental evidence for the“the spiral of silence”theory.

Dependencies between price duration, volatility, volume and return on the Warsaw Stock Exchange

The successive changes of asset prices are the most visible manifestation of financial markets dynamics. There exist different views about factors generating these changes, but many researchers and practitioners agree that the most important among them is the impact of information flow. According to the market microstructure theories, it depends mainly on the behavior of informed and uniformed traders. In the paper, we investigate dependencies between the possible proxies of information process： price duration and corresponding to it volume change and return. Our main objective is to answer the question about the most important factor in the process of discovering information by uniformed traders. We apply a set of models for volatility, volume and duration data. Our analysis is performed for selected equities listed on the Warsaw Stock Exchange and uses tick-by-tick data. The obtained results show that the stock liquidity on this leading stock market in Central and Eastern Europe is the most important factor influencing the process of discovering information by uninformed traders.