Carbon stock and sink economic values of forest ecosystem in the forest industry region of Heilongjiang Province, China

The values of forest carbon stock (CSV) and carbon sink (COV) are important topics in the global carbon cycle. We quantitatively analyzed the factors affecting changes in both for forest ecosystem in 2000−2015. With multiple linear stepwise regression analysis, we obtained the factors that had a significant impact on changes of CSV and COV, and then the impacts of these variables on CSV and COV were used for further quantitative analysis using the vector autoregressive model. Our results indicated that both stand age and afforestation area positively affect CSV and COV;however, the forest enterprise gross output value negatively affects CSV. Stand age has the largest long-term cumulative impact on CSV and COV, reaching 40.4% and 9.8%, respectively. The impact of enterprise gross output value and afforestation area on CSV and COV is the smallest, reaching 4.0% and 0.3%, respectively.

Total Carbon Stock and Potential Carbon Sequestration Economic Value of Mukogodo Forest-Landscape Ecosystem in Drylands of Northern Kenya

Carbon sequestration is one of the important ecosystem services provided by forested landscapes. Dry forests have high potential for carbon storage. However, their potential to store and sequester carbon is poorly understood in Kenya. Moreover, past attempts to estimate carbon stock have ignored drylands ecosystem heterogeneity. This study assessed the potential of Mukogodo dryland forest-landscape in offsetting carbon dioxide through carbon sequestration and storage. Four carbon pools (above and below ground biomass, soil, dead wood and litter) were analyzed. A total of 51 (400 m2) sample plots were established using stratified-random sampling technique to estimate biomass across six vegetation classes in three landscape types (forest reserve, ranches and conservancies) using nested-plot design. Above ground biomass was determined using generalized multispecies model with diameter at breast height, height and wood density as variables. Below ground, soil, litter and dead wood biomass;carbon stocks and carbon dioxide equivalents (CO2eq) were estimated using secondary information. The CO2eq was multiplied by current prices of carbon trade to compute carbon sequestration value. Mean ± SE of biomass and carbon was determined across vegetation and landscape types and mean differences tested by one-way Analysis of Variance. Mean biomass and carbon was about 79.15 ± 40.22 TB ha-1 and 37.25 ± 18.89 TC ha-1 respectively. Cumulative carbon stock was estimated at 682.08 TC ha-1;forest reserve (251.57 TC ha-1) had significantly high levels of carbon stocks compared to ranches (209.78 TC ha-1) and conservancies (220.73 TC ha-1, P = 0.000). Further, closed forest significantly contributed to the overall biomass and carbon stock (58%). The carbon sequestration potential was about 19.9MTCO2eq with most conservative worth of KES 39.9B (US$40M) per annum. The high carbon stock in the landscape shows the potential of dryland ecosystems as carbon sink for climate change mitigation. However, for communities to benefit from bio-carbon funds in future, sustainable landscape management and restorative measures should be practiced to enhance carbon storage and provision of other ecosystem services.

Estimation of Dynamic VaR in Chinese Stock Markets Based on Time Scale and Extreme Value Theory

The accuracy and time scale invariance of value-at-risk （VaR） measurement methods for different stock indices and at different confidence levels are tested. Extreme value theory （EVT） is applied to model the extreme tail of standardized residual series of daily/weekly indices losses, and parametric and nonparametric methods are used to estimate parameters of the general Pareto distribution （GPD）, and dynamic VaR for indices of three stock markets in China. The accuracy and time scale invariance of risk measurement methods through back-testing approach are also examined. Results show that not all the indices accept time scale invariance; there are some differences in accuracy between different indices at various confidence levels. The most powerful dynamic VaR estimation methods are EVT-GJR-Hill at 97.5% level for weekly loss to Shanghai stock market, and EVT-GARCH-MLE （Hill） at 99.0% level for weekly loss to Taiwan and Hong Kong stock markets, respectively.

ASP-Based Programs of Best Linear Unbiased Prediction-Estimated Breeding Values in Breeding Stock

In order to improve the breeding effect of livestock, the data were read from an Excel file with Active Server Page （ASP） programs, and the breeding values of breeding stock were calculated by best linear unbiased prediction （BLUP） method.

The Effect of Dividends and Earnings per Share on the Stock Market Value by Moderating Bank Size

The aim of this study was to investigate the effect of dividend distributions and earnings per share by moderating bank size as measured by its total assets on the stock market value of banks operating in Jordan during the period between 2011 and 2016.The hypotheses of the study were tested based on multiple and hierarchical regression method.The most important result of the study is that the earnings per share is the strongest variable that helps in predicting the stock market value of the bank shares,in addition to the significant effect of bank size as measured by its total assets.

Relation Between Relative Efficiencies and Brand Values of Global Turkish Banks Trading on Istanbul Stock Exchange

The global competition in banking sector, global capital flows, and proliferation of financial markets have been forcing banks to utilize their resources in an efficient way and use various methods to determine and increase their performances against the competitors. Within this context, the relative efficiency measurement and statistical （parametric） efficiency measurements that employ （non-parametric） mathematical programming based on Data Envelopment Analysis （DEA） method are such instruments and they are used to determine brand value and financial performance that are pivotal factors in company mergers, acquisitions, and joint venture activities. This study works with Turkish banks whose brand values have been calculated by Brand Finance and whose brand values have been listed in Global Banking 500 for the years between 2010 and 2012. Firstly, using the banks＇ data published by Public Disclosure Platform （PDP/KAP）, a non-parametric model with three inputs and four outputs has been developed. Relative and super efficiencies of the banks have been measured by mathematical programming based DEA and the efficiency scores that come out of this analysis have been ranked, resulting in an ＂efficiency ranking of the banks＂. Following this, the efficiency ranking of these banks has been compared with brand value ranking of Brand Finance and their similarity/correspondence has been assessed.

Impact Analysis of Macroeconomic Factors on Stock Value of Shanghai Pudong Development Bank under PCA Regression

When we consider the factors affecting the stock market,we often consider the impact of macroeconomic factors on it.On the basis of the academic achievements of predecessor scholars on macroscopic factors affecting the overall stocks,this article selects six macroeconomic influencing factors:money supply,USDCNY exchange rate,GDP,national fiscal revenue,price index and interest rate,and uses PAC regression analysis method to construct a regression model.Analyze the influencing factors of Shanghai Pudong Development Bank stock;then conduct heteroscedasticity,autocorrelation,and multicollinearity tests to modify and adjust the regression model;finally,make relevant recommendations based on the analysis results.

Research on the Relationship Between Macroeconomic Indicators and Stock Market Value

The article first addresses the following questions:“Why does gross domestic product(GDP)rises,but the stock market value falls?”;“Among the macroeconomic factors,which factor has a greater impact on the promotion of investment value in the securities market?”.With these questions in mind,we put forward a hypothesis emphasizing on the impact of macroeconomic factors on the value of the stock market based on existing research and used the regression method to verify this hypothesis.The following conclusions were drawn:(1)variables that have a positive nonlinear relationship with stock market value include balance of payments surplus,rising GDP level,M1,the whole society’s fixed asset investment,and national per capita disposable income;(2)variables that have a negative nonlinear relationship with stock market value include deposit,loan interest rate,new RMB loan amount,consumer price index(CPI),and producer price index;(3)deposit reserve ratio has an S-shaped curve relationship with stock market value;(4)exchange rate has an inverted U-shaped curve relationship with stock market value.

Booming or sinking: How does an emission trading scheme affect enterprise value?

Unlike prior research that shows climate policy improves enterprise value,this study reveals the negative im‐pact of emission trading schemes(ETSs)on enterprise value under China’s unique institutional backdrop and identifies the mechanism through which this impact occurs.Data from a sample of 1267 listed companies in the Chinese stock market from 2005 to 2018 models are analyzed using difference-in-differences(DID)and propensity score matching methods(PSM).The results suggest that ETSs have an average short-term negative impact on enterprise value,which peaks in the second year of the ETS and diminishes from the fourth year.Further analysis reveals that ETSs did not cause significant operating losses for firms but reduced their value through the market response mechanism.ETS enterprises experienced significant declines in their annual stock transaction amounts and in returns on individual shares.This indicates that investors expect ETSs to ad‐versely affect pilot enterprises and accordingly adopt disinvestment strategies.Despite the short-term negative effect,ETSs effectively encourage enterprises to innovate green technologies to mitigate long-term carbon risk.

Importance of Generalized Logistic Distribution in Extreme Value Modeling

We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are the classical distributions for this problem. However, from 2004, [1] and many other researchers have been empirically showing that generalized logistic (GL) distribution is a better model than GEV and GP distributions in modeling extreme movement of stock market data. In this paper, we show that these results are not accidental. We prove the theoretical importance of GL distribution in extreme value modeling. For proving this, we introduce a general multivariate limit theorem and deduce some important multivariate theorems in probability as special cases. By using the theorem, we derive a limit theorem in extreme value theory, where GL distribution plays central role instead of GEV distribution. The proof of this result is parallel to the proof of classical extremal types theorem, in the sense that, it possess important characteristic in classical extreme value theory, for e.g. distributional property, stability, convergence and multivariate extension etc.

Exploring the growth value equity valuation model with data visualization

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 return.Although 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 processes.This article uses visualization techniques to help intuitively explore GVM.The 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 visualization.The coefficients in the formula can be determined by the quantile regression analysis with market data.The 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 formed.Furthermore,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 quarter.The 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.

Italian Banking Sector and Value Creation

The finn value is the fundamental topic of corporate finance. The value creation is the aim of economic initiatives, strategies, corporate policies, and all business activities, including banking. It depends, among other things, on size, legal form, and business model. Therefore, this paper wants to demonstrate and explain the differences about the value created in the Italian banking sector, where there is much diversity regarding size, legal form, and business model. This paper estimated and compared the value of Italian listed companies from 2010 to 2012 and found the result： Banks create more value if they are big and operate in investment banking. Furthermore, it proved that legal form hasn＇t influenced performance and value of banks.

An Extreme Value Approach to Test the Effect of Price Limits on Volatility

Many stock exchanges around the world enforcing daily price limits on the amount asset prices can change to prevent the market from overreacting and to reduce volatility. Price limits are artificial boundaries set by market regulators who restrict price changes of a stock to a pre-specified range during a trading day or a single trading session. The primary aim of price limit rules is to stabilize the markets during panic trading, to moderate vitality by repressing excessive speculation, and to allow stocks to be traded at prices close to their fair value. However, their impact on the market is a somewhat unresolved issue （Harris, 1998）. Using a methodology of comparing volatility based on the extreme value technique, the authors empirically investigate the impact of price limits on the volatility of the Stock Exchange of Thailand. The empirical results support price limits advocates, suggesting that price limits rules moderate stock price volatility.

A Preliminary Analysis of Accounting Confirmation and Measurement on Stock Option

股票期权作为一种长期激励机制雇我国虽已有一定的发展，但由于会计处理研究相对滞后，与国际惯例存在一些差距，这些问题包括股票期权会计确认观的选择、初始确认时间的确定、计量方法的选择等。对此，我国应借鉴国外会计处理理念和充分考虑我国国情。采取将股票期权确认为无形资产，拓宽所有者权益内涵，借助中介机构对股票期权进行估值，对于股票期权采用授予日作为计量日，使用公允价值计量经理股票期权，对股票期权的会计确认和计量进行补充和完善。以便股票期权这一长期激励机制在我国经济建设中更好地发挥应有作用。

Banking Industry Valuation Analysis in the Context of China’s

China’s stock market has experienced more than 20 years of development.Despite the concept of value investment has already been reflected in stock investment,many investors,especially small and medium investors,still do not pay much attention to value investment.Blindness and speculative thinking still affect investment.This paper chooses the banking industry as the analysis object and uses the relative valuation approach to evaluate the price-earnings ratio(P/E ratio),price-to-book value ratio(P/B ratio),and price-earnings to growth(PEG)of the 10 listed banks,then judges the investment value of each bank and focuses on the valuation and pricing of the banking with rapid growth.Based on this,the choice of value investment decisions is made,trying to provide a demonstration for investors to make value investment decisions.Finally,it is recommended to invest in China Merchants Bank(CMB),Minsheng Bank,Shanghai Pudong Development Bank(SPDB),Industrial and Commercial Bank of China(ICBC),HSBC Bank,and Bank of China.It is not recommended to invest in Ping An Bank,Bank of Communications,Industrial Bank,and China CITIC Bank.

河南省森林固碳量与碳汇价值评估

为了解当前黄河中下游森林固碳量及碳汇价值现状,助力黄河流域生态保护和高质量发展,基于全国森林清查和国土调查数据,以河南省为例,结合蓄积量转换法原理运用改进后的生物量转换因子连续函数法来测算森林固碳量动态变化和碳汇价值。结果表明:河南省森林固碳量由2008年的1.76×10^(8)t上升至2018年的2.78×10^(8)t,年固碳量较高的森林类型为阔叶混和栎类,固碳量按龄级分布状况为幼龄林最大、过熟林最小,森林固碳量的空间格局表现为“西、南高,东、北低”,主要分布在南阳、洛阳和三门峡;森林碳汇价值由2008年的492.47亿元增加至2018年的778.68亿元,年均增长28.62亿元,2018年阔叶混、栎类和杨树的碳汇价值占碳汇总价值的79.93%。针对当前河南省森林建设存在的问题,提出提升森林固碳能力和推动森林碳汇价值实现的建议,可为促进黄河流域高质量发展提供强劲动力。

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.

Risk management of stock index futures

The Hong Kong Hang Seng index futures is taken as a study object and a method of empirical analysis is adopted in order to verify the validity of the application of the value-at-risk (VaR) method in the risk measurement of the stock index futures market. The results suggest that under normal market conditions it is feasible to apply the VaR method in the measurement of the market risks of stock index futures. The daily VaR value of the stock index futures provides a foreseeable profit and loss of the stock index futures. Financial supervisors can adjust their supervising strategies according to the daily VaR value. The speculators can adjust risk capital reserve rates in the same way. The application of this method in China's stock index futures market requires the solutions to specific problems: the absence of historical data, the difficult confirmation of non-risk interest rates etc.