A股指数波动对投资者交易心理的影响——基于VAR模型的实证分析

股票价格的涨跌对于投资者的交易心理有很大的影响,投资者的交易心理可以用每周参与A股交易的账户数的变化来表示。通过选取2010年-2013年A股周价格指数和每周参与A股交易账户数数据,建立VAR模型,检验模型的稳定性,并分析二者是否具有长期稳定的均衡关系、利用Granger因果检验以及脉冲响应函数分析方法,得出结论:股票市场投资者根据A股价格指数的波动来调整各自的交易频率。受交易心理影响,当A股价格指数上涨时,投资者会增加交易频率,而当A股价格指数下跌时,则减少交易频率。

股价运动、投资者交易策略与信息

以深圳证券市场的高频数据为研究对象，大公司的股价变化与投资者的交易频数以及交易规模均呈显著的正相关关系，而小公司的股价仅与交易频数呈正相关关系。因此，交易频数能作为信息质量的信号；另外，所有的股票都对公司特定信息敏感，而对市场信息不敏感。

移动互联网改变商业环境:产品的颠覆

随着商业环境的不断变化,尤其是进入移动互联网时代后,传统商家提供的广义产品价值出现了明显的结构性分化,主要表现为产品的功能价值衰落,而产品的信息价值、体验与文化价值明显增长。前者使传统商业遭遇巨大挑战,而后者则使传统企业的价值再生。一经发生即不可逆转,如同呼啸的巨浪一样推动传统企业的转型发展。一、产品的功能价值不断下滑以电信行业为例,首先,技术升级速度越来越快,每代通信技术成为商用主流的时间越来越短。移动通信技术从模拟技术演进到以GSM为标志的第二代移动通信技术用了30年。

Application of Tradable Emission Permits in Europe

The purpose of this study is merely to review the current situation in the designing and implementation of the emission trading programs in Europe. Historical data show that although there is a series of shortcomings in their current functioning, employing such instruments for GHG reduction policy making is strongly expected to be efficient and effective. The European Union Emission Trading Scheme (EU ETS), Clean Development Mechanism (CDM) and Joint Implementation (JI) are just a few examples of the ambitious EU initiative that heavily relies on such instruments. We dwell on their operations and achievements by far and all the content in this article is expected to convince the Chinese government and regional public authorities to take positive actions and attitudes in promoting these instruments.

Data Flow&Transaction Mode Classification and An Explorative Estimation on Data Storage&Transaction Volume

The public has shown great interest in the data factor and data transactions,but the current attention is overly focused on personal behavioral data and transactions happening at Data Exchanges.To deliver a complete picture of data flaw and transaction,this paper presents a systematic overview of the flow and transaction of personal,corporate and public data on the basis of data factor classification from various perspectives.By utilizing various sources of information,this paper estimates the volume of data generation&storage and the volume&trend of data market transactions for major economies in the world with the following findings:(i)Data classification is diverse due to a broad variety of applying scenarios,and data transaction and profit distribution are complex due to heterogenous entities,ownerships,information density and other attributes of different data types.(ii)Global data transaction has presented with the characteristics of productization,servitization and platform-based mode.(iii)For major economies,there is a commonly observed disequilibrium between data generation scale and storage scale,which is particularly striking for China.(i^v)The global data market is in a nascent stage of rapid development with a transaction volume of about 100 billion US dollars,and China s data market is even more underdeveloped and only accounts for some 10%of the world total.All sectors of the society should be flly aware of the diversity and complexity of data factor classification and data transactions,as well as the arduous and long-term nature of developing and improving relevant institutional systems.Adapting to such features,efforts should be made to improve data classification,enhance computing infrastructure development,foster professional data transaction and development institutions,and perfect the data governance system.

A Study on Similar Financial Models in Manufacturing Sector

In this paper, we subdivide the sample of manufacturing companies listed in two stock exchanges in China from the year 2000 to 2009 into two categories： the firms which adopted the similar financial models and those which did not. Then we use t-test and nonparametric test to explore the differences between the two sub-samples in cash management, assets and liabilities structures, assets turnover ratios, profitability, liquidity and growth rates. The results show that the former has shorter Cash Conversion Cycle （CCC）, quicker assets turnover, higher Debt Ratio （DR）, higher growth rate and thus has better profitability. In addition, the regression analysis results further demonstrate that Return on Invested Capital （ROIC） of similar-financial-model firms are positively related to Net Profit Margin （NPM） （p 〈 0.01）, and negatively to CCC （p 〈 0.01）, Interest Expense Ratio （IER） （p 〈 0.01）, the Ratio of Interest-Bearing Debt to Total Liabilities （IBDR） （p 〈 0.01） and the ratio of Net Receivables to Sales Revenue （NRSR） （p 〈 0.01）. Moreover, negative relationship between ROIC and dummy variable GROUP implies that the former has better profitability than the latter.

Barter Trade Exchange to the Rescue of the Tourism and Travel Industry

South Africa＇s tourism and travel industry is a key sector in its economy as well as a significant job creator. The recent global economic turmoil is threatening the tourism industry; at the same time, global experts claim that tourism may be a key to overcoming economic difficulties and play a vital role in the green new deal. The purpose of the study is to introduce a new strategic option that has become increasingly attractive for troubled businesses-barter. While the study focuses on the advantages of this concept＇s recent refinements for South Africa＇s tourism and travel industry, its findings are also applicable to other countries. A survey of small and medium-sized enterprises （SME） from Europe and Turkey, as well as graduate students at an Israeli university, demonstrate the gap between familiarity with barter processes and their advantages and the actual scale of barter transactions in the supply chain, in order to enhance the economic performance of their tourism enterprises as well as the entire economy, providing evidence for the potential of adapting old proven concepts to the modem digital world.

Crossover Phenomena in Detrended Fluctuation Analysis Used in Financial Markets

A systematic analysis of Shanghai and Japan stock indices for the period of Jan. 1984 to Dec. 2005 is performed. After stationarity is verified by ADF （Augmented Dickey-Fuller） test, the power spectrum of the data exhibits a power law decay as a whole characterized by 1/f^β processes with possible long range correlations. Subsequently, by using the method of detrended fluctuation analysis （DFA） of the general volatility in the stock markets, we find that the long-range correlations are occurred among the return series and the crossover phenomena exhibit in the results obviously.Further, Shanghai stock market shows long-range correlations in short time scale and shows short-range correlations in long time scale. Whereas, for Japan stock market, the data behaves oppositely absolutely. Last, we compare the varying of scale exponent in large volatility between two stock markets. All results obtained may indicate the possibility of characteristic of multifractal scaling behavior of the financial markets.

Consumers'privacy data sharing between the seller and the e-commerce platform

Due to the fact that consumers'privacy data sharing has multifaceted and complex effects on the e-commerce platform and its two sided agents,consumers and sellers,a game-theoretic model in a monopoly e-market is set up to study the equilibrium strategies of the three agents(the platform,the seller on it and consumers)under privacy data sharing.Equilibrium decisions show that after sharing consumers'privacy data once,the platform can collect more privacy data from consumers.Meanwhile,privacy data sharing pushes the seller to reduce the product price.Moreover,the platform will increase the transaction fee if the privacy data sharing value is high.It is also indicated that privacy data sharing always benefits consumers and the seller.However,the platform's profit decreases if the privacy data sharing value is low and the privacy data sharing level is high.Finally,an extended model considering an incomplete information game among the agents is discussed.The results show that both the platform and the seller cannot obtain a high profit from privacy data sharing.Factors including the seller's possibility to buy privacy data,the privacy data sharing value and privacy data sharing level affect the two agents'payoffs.If the platform wishes to benefit from privacy data sharing,it should increase the possibility of the seller to buy privacy data or increase the privacy data sharing value.

Investigating Voluntary Risk Disclosure： The Case of Jordanian Banks

The aim of the study is to investigate whether banks in Jordan are compliant with the International Financial Reporting Standards （IFRS） 7 requirement for mandatory disclosure and to find out the extent to which the banks provide voluntary risk disclosures. To achieve the objectives of the study, we collected data from all 15 banks listed on the Amman Stock Exchange for the year ending December 2013. The findings of the study suggest that there is strong compliance with respect to mandatory risk disclosure, as required by IFRS. However, the results generally signal a need for further improvement in the voluntary risk disclosure area, since most of the banks do not provide adequate information that can be of use to stakeholders. We also suggest future avenues of research into the topic to determine progress.

Water Resource and Regional Economic Growth Study Based on Panel Data

Empirical analysis to the relationship between water resource scarcity degree and economic growth were done by building relationship model between water resource scarcity degree and regional economic growth with provincial panel data of 30 provinces during 2000-2009. The analysis results show that, in water resource scarcity regions, the shortage of water resource is the key factor of restricting economic development. In order to alleviate the shortage of water resource and meet the needs of economic development to water resource, it is necessary to speed up the establishment of water right trading market and finally achieve the goal of water-saving and regulation of water resource by economic leverage. The specific countermeasures include： first, comprehensively considering the endowment difference of water resource when carrying out industrial planning and layout; second, speeding up the establishment of water right trading market and revising water-saving incentive mechanism; third, increasing fiscal transfer payment ability to the provinces of outputting water resource; fourth, strengthening industrial guidance, making moderate industrial transfer and population movement; fifth, paying attention to science, technology and education investment, to improve utilization efficiency of water resource.

Circuit breakers： Development of testable hypothesis

In October 1996, The Dhaka Stock Exchange （DSE） adopted trading halts for individual stocks, collectively known as ＂circuit breakers＂, to reduce the stock market volatility. This paper reviews the existing circuit breakers literature and developed five hypothesis--＂Magnet Effect＂, ＂Cool off-Heating （C-H） Effect＂, ＂Information Hypothesis＂, ＂Volatility Spillover Hypothesis＂ and ＂Trading Interferences Hypothesis＂--which could be tested empirically not only in the Dhaka Stock Exchange but any stock exchanges around the world. This paper also suggests most appropriate econometric models for empirical testing. GARCH for inter day data and Event Study methodology for intra day data. Moreover, to test the robustness non-parametric tests need to use along with parametric one. Considering the stock market bubbles in 1996, it has been found that it was optimal for the regulators to adopt this trading halt, but not for the market. It failed to protect the market. However, this might be the consequences of misconceptions about the purpose and effectiveness of circuit breakers. Despite many arguments contrary to this mechanism and absence of any conclusive empirical evidence for a fragile stock exchange like DSE, it may be useful sometimes to replace the ＂invisible hand of the marketplace＂ with the ＂visible hand of the market regulators＂.

Accounting variables and stock returns： Evidence from Istanbul stock exchange

The fundamental relationship between accounting variables and stock returns is a recurring theme in financial research. One of the major purposes of accounting is to help investors provide reliable, comparable and accurate information. If accounting data are informative about fundamental values and changes in values, they should be correlated with stock price changes. This study provides theory and evidence showing how accounting variables explain stock returns and examines the relationship between the stock returns and accounting variables of listed non financial companies in ISE-100 Indice for 2006-2008 period by using panel data methodology. Empirical analysis consists of 192 observations of 64 companies in years 2006-2008 to examine the effects of inventory, accounts receivable, gross margin, operating expense, return on assets, cash flow, leverage, liquidity, price/earnings, return on equity on stock returns. The results of the study confirm that the predicted roles of fundamental factors and stock returns are significantly related to gross margin, cash flow, leverage and equity variables. The model explains about 13.35 % of the variation of annual stock returns with the leverage variable with most of the significant power.

Effect of Trader Composition on Stock Market

In this study, we build a double auction market model, which contains two types of agent traders, i.e., the noise traders and fundamentalists, to investigate the effect of the trader composition on the stock market. It is found that, the non-trivial Hurst exponent and the fat-tailed distribution of transaction prices can be observed at any ratio of the noise traders. Analyses on the price variation properties, including the Hurst exponent and the price variation region, show that these properties are stable when the ratio is moderate. However, the non-price variation properties, including the trading volume and the profitability of the two kinds of agents, do not keep stable untrivially in any interval of the ratio of noise traders.

Optimization of Portfolio of Stocks at ZSE through the Analysis of Historical Data

Decision-making of investors at the stock exchange can be based on the fundamental indicators of stocks, on the technical indicators, or can exist as a combination of these two methods. The paper gives emphasis to the domain of technical analysis. In the broader sense the technical analysis enables the dynamics of the expected future values of the shares estimation. This can be performed on the basis of the data on historical trends of the revenues, profits and other indicators from the balance sheet, but also on the basis of historical data on changes in the values of the shares. Companies generally belong to the different sectors that have different presumptions of development resulting from the global market trends, technology and other characteristic. Processing of historical data values of the outstanding shares of the Zagreb Stock Exchange （ZSE） is origination of this research. Investors are interested to know the estimation of future returns for the stocks as well as the size of the risk associated with the expected returns. Research task in this paper is finding the optimal portfolio at the ZSE based on the concept of dominant portfolio by Markowitz approach. The portfolio is created by solving non-linear programming problem using the common software tools. The results of obtained optimal portfolios contain relevant conclusions about the specifics of the shares as well as the characteristics of the industrial sectors but also provide a further knowledge about diverse sectors treatment at the stock exchange in a multi-year period.

The Value Relevance of Foreign Currency Translation Adjustments （FCTAs） in the Italian Stock Exchange

The main aim of this paper is to test whether the foreign currency translation adjustments （FCTAs）, the largest components of other comprehensive income （OCI） for most firms, are incrementally value-relevant for investors with respect to the net income （NI）. Previous archival research on the value relevance of FCTAs has documented a weak or non-existent link between FCTAs and firm valuation （Pinto, 2005）. The hypothesized reasons could reside in the econometric method employed, in the use of as-if numbers, and in the missing consideration of the differential effect that exchange rate changes have on firms of varying levels of capital intensiveness. This study adds to the existing literature by empirically testing the value relevance of as-reported FCTAs numbers in the earnings and book value model the Ohlson-like interacted model through panel data techniques. The main finding of this study is that as-reported FCTAs are significantly and incrementally value-relevant, when their parameter estimates are allowed to vary in the cross-section.

中国股市指数与投资者情绪指数的相互关系

选取"新开交易账户数"作为投资者情绪的代理变量,应用ARMA-GARCH类模型研究了投资者情绪与股市收益率之间的相互关系.结果显示ARMA-GARCH类模型能有效拟合投资者情绪变化率和上证综合指数收益率的自相关性和异方差性.Granger因果检验表明上证综合指数收益率是投资者情绪变化率的一个显著影响因子,而并没有发现投资者情绪的变化率对上证综合指数的收益率Granger因果显著.根据市场表现的不同特征,投资者利用这一信息调整情绪.当市场处于上升阶段时,投资者情绪会更为乐观,有更多新的投资者进入股市;当市场处于下降阶段时,投资者就会转变为较为悲观,场外的投资者就会处于观望状态,不急于进入股市,这样反映在股市上就是"新开交易账户数"减少.

Agricultural Trading among BRICS Countries

This paper analyzes the characteristics of BRICS＇s agricultural trading in four ways： export market competition, revealed comparative advantage, trade specialization index, and export similarity index. It shows that BRICS countries export different agricultural goods in the same market, so they do not have real competition in agricultural trading markets. BRICS countries have a comparative advantage in different products; especially Brazil with having total different RCA products. In BRICS countries, China and Brazil are the closest trading partners. Compared with other BRICS countries, China and India have a higher similarity in agricultural trading.

A scalar dynamic conditional correlation model:Structure and estimation

The dynamic conditional correlation(DCC) model has been widely used for modeling the conditional correlation of multivariate time series by Engle(2002). However, the stationarity conditions have been established only recently and the asymptotic theory of parameter estimation for the DCC model has not yet to be fully discussed. In this paper, we propose an alternative model, namely the scalar dynamic conditional correlation(SDCC) model. Sufficient and easily-checked conditions for stationarity, geometric ergodicity, andβ-mixing with exponential-decay rates are provided. We then show the strong consistency and asymptotic normality of the quasi-maximum-likelihood estimator(QMLE) of the model parameters under regular conditions.The asymptotic results are illustrated by Monte Carlo experiments. As a real-data example, the proposed SDCC model is applied to analyzing the daily returns of the FSTE(financial times and stock exchange) 100 index and FSTE 100 futures. Our model improves the performance of the DCC model in the sense that the Li-Mc Leod statistic of the SDCC model is much smaller and the hedging efficiency is higher.