Applications of nonferrous metal price volatility to prediction of China's stock market

The aim of the present work is to examine whether the price volatility of nonferrous metal futures can be used to predict the aggregate stock market returns in China. During a sample period from January of 2004 to December of 2011, empirical results show that the price volatility of basic nonferrous metals is a good predictor of value-weighted stock portfolio at various horizons in both in-sample and out-of-sample regressions. The predictive power of metal copper volatility is greater than that of aluminum. The results are robust to alternative measurements of variables and econometric approaches. After controlling several well-known macro pricing variables, the predictive power of copper volatility declines but remains statistically significant. Since the predictability exists only during our sample period, we conjecture that the stock market predictability by metal price volatility is partly driven by commodity financialization.

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

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.

Evaluation of call options

The European and American call options, for which the prices of their underlying asset follow compound Poisson process, are evaluated by a probability method. Formulas that can be used to evaluate the options are obtained, which include not only the elements of an option: the price of the call option, the exercise price and the expiration date, but also the riskless interest rate, nevertheless exclude the volatility of the underlying asset. In practice, the evaluated results obtained by these formulas can provide references of making strategic decision for an investor who buys the call option and a company who sells the call option.

Japanese Stock Price Determination： What Is Important？

This paper analyzes empirically the relationship between recent Japanese stock prices and macroeconomic variables For the Japanese stock prices, the level and rate of that are both used for analysis. The results show that exchange rates have not been a significant determinant of the ＂level＂ of Japanese stock prices, but on the other hand, have been a significant determinant of its ＂rate＂. The ＂rate＂ has been used to analyze determinants of the stock prices. However, it is dangerous to use it without taking into account its level. Many stock traders usually look at the level. Interest rates, especially the domestic interest rate, have not impacted the Japanese stock prices. Japanese interest rates have been quite low as the Bank of Japan has implemented quantitative easing instead of interest-based policies. Recently, the U.S. stock prices, particularly in the first few days after a change, have been significantly influencing the Japanese stock prices.

An alternative lattice algorithm for option pricing

This paper proposes a dimension reduction technique on lattice model, an extension of the discrete CRR （1979） model, for option pricing. Applications are demonstrated on pricing some vulnerable options with the payoff functions including two stochastic processes： the underlying stock price and the assets value of the option writer. Instead of building a bivariate tree structure for these correlated processes, a univariate binomial tree for the underlying stock price is only constructed. The proposed univariate binomial tree model is sufficient to undertake, though two underlying assets are involved.

The Efficient Market Theory and Mergers and Acquisitions （M＆As） Puzzle： Evidence From Italy

The efficient market theory is a central point in finance. If the capital market is competitive, the investors cannot expect superior gains from their investment strategies with respect to the risk profile. Event studies are an approach to verify the impact of the information on the stock prices. In an efficient market, stock prices should fully, promptly, and quickly capture all the information. Instead, the market shows phenomena of an under-reaction and over-reaction for both the short and the long run. The mergers and acquisitions （M＆As） are examples of anomalies. Often, the bidder companies record the negative abnormal returns for both the short and the long run. In contrast to the efficient market theory, the empirical evidence shows that this phenomenon is widespread in all （or most of） the countries of the world. This work examines the long-run performance in M＆As. For this purpose, 40 bidders were observed in Italy during the period of 1994-2008 among listed companies. The buy and hold abnormal returns （BHARs） methodology was used, with which it was possible to observe the returns for three years following the deal.

Analysis of Economic Performance in Mergers and Acquisition

Based on the methods of financial analysis, the direct earnings in mergers and acquisition M&A, profit or loss from stock price fluctuation, influence on the earning per stock(EPS) and revenue growth after M&A were analyzed in detail. And several quantitative models were established in relevant part accordingly. It can be useful to improve the present low efficiency in the M&A performance in Chinese capital market.

Merger Announcement Effects and the Amendment of Insider Trading Laws in Brazil

Although Brazil has a long history of having insider trading laws （IT laws） in place and became the first emerging country to enforce the IT laws （Bhattacharya ＆ Daouk, 2002）, criminal sanctions and hefty monetary penalties were only made possible by the amendment of its laws against IT on October 31, 2001. We study the stock price effects of merger announcements made by 151 firms over two periods, before and after the change of IT laws. Our empirical results suggest that target firms attained positive price run-ups in pre-announcement windows before, but not after, the legal regime change. While acquiring firms had strong positive pre-announcement reactions in both legal regimes, the abnormal returns （AR） decreased in the more stringent legal regime. These results indicate that more stringent IT laws may deter IT and improve market efficiency in an emerging country.

Short Sellers Are Indeed Sophisticated Traders!

Current literature shows that short sellers earn positive returns on their trades and that the superior performance of short sellers is due to their better analytic skills. In this paper, we investigate, if it is possible for a short seller to make profits even if he does not have insider information or is not sophisticated. We use a one period model and assume that stock price follows a random walk with a positive drift to show that the＇ expected return for an uninformed short seller is always negative and his risks are always greater than the risks of a stock buyer. Hence a short seller would not trade unless he has superior trading skills and/or information. We also show that the market conditions when the stock＇s dividend yield is greater than the risk free rate gives the shortsellers advantage over stock buyers.

A Panel Data Analysis of Corporate Attributes and Stock Prices for Indian Manufacturing Sector

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.

The Regression Analysis of Stock Returns at MSE

The linear regression and correlation analysis of daily returns of several stocks and stock-exchange index at Macedonian Stock Exchange （MSE） provide evidence for statistical significance of the stocks＇ daily returns at MSE. Statistical analysis was focused to determine the character of relationship between the 10 most liquid stocks at MSE using ten-year time-series of daily stocks＇ closing price and for the Macedonian Stock Exchange Index （MBI-IO）. The analysis of daily stock returns provided R2 values and confirmed that the proportion of the total correlation in the dependent variable （one stock price） can be explained by the independent variable （other stock price） as well as that accurate forecasting of one stock price movements enables reliable prediction of other stock future price at MSE. Some implications for stock valuation are drawn.

Dividend policy determinants of Indian FMCG sector： A factorial analysis

Profitability has always been considered as a primary indicator of dividend payout by a company. There are factors other than profitability namely cash flows, debt equity ratio, retained earnings, sales growth, share prices of a company, capital expenditure and beta etc. that also affect dividend decisions of an organization. Existing literature suggests that dividend payout is positively related to profits, cash flows while CAPEX （capital expenditure） retained earnings, sales growth, share prices, beta, interest paid and debt equity ratio have inverse relationship. A set of 21 key variables have been identified that affect the dividend payout of a firm. Researchers in the past have used several proxies to represent these determinants. Authors have tried to find out which proxy variable is most relevant in the present scenario. The paper attempts to give a focused overview of the important dividend theories and empirically analyze the determinants of dividend behavior of Indian FMCG （Fast moving consumer goods） sector. The relationship between key variables has been explored with the aid of statistical techniques of factor analysis. Thus, the main theme of this study is to examine the various factors that influence the dividend policy decisions of FMCG firms in India.

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.

Stock Market Reaction to ECFA Announcement in Taiwan Chemicals Listed Stock

Taiwan and China's Mainland signed the Economic Cooperation Framework Agreement （ECFA） on 29th June, 2010. The ECFA is a landmark bilateral trade agreement that can make Taiwan a new gateway to China's Mainland. However, the Taiwan Residents petrochemical industry would be very disappointed with the early harvest list as it excluded some critical export items. The purpose of this paper is to amend the understanding of the possible impact on petrochemical market after ECFA is enacted. The authors examine the cumulative daily response of stock prices to five announcements about the ECFA and evaluate the existence of the abnormal return. The authors use daily data from January 2010 to February 2011 to employ an event study approach. The empirical results suggest that the three ECFA announcement dates, as well as the signing date, show significantly negative abnormal return due to the prior positive cumulative response of Taiwan chemicals listed stock prices. This paper can provide the petrochemical industry manufacturer, owners, and investors with further insights into how chemicals stock returns react to a big event like ECFA.

An Empirical Study on the stock Price of Modeling

the model in time series analysis are widely used in the field of economy. We often use the model in time series to analyze data, but without regard to the rationality of the model. In this paper, we introduce and analyze Ping An Of China（601318） shares at the opening price（2013/01/04-2013/07/04）.The model is established by analyzing data. Modeling steps of ARIMA model and GARCH model are presented in this paper. The data whether ARIMA model is suitable by white noise. Or the data whether GARCH model is suitable by since the correlation of variance test. By comparing the analysis, it selects a more reasonable model.

Statistics in Stock Day Trading

Price volatility in stock market brings potential profile positions to the traders. How to predict the direction of the stock market or stock price becomes the primary job for traders＇ trading model. We are looking for the direction of the market in a given timeframe. High-frequency traders will consider the potential profile-out position in millisecond level. Long-term holder will look into month time scale. For most of average traders, the ideal timeframe will be on daily base. In this paper, for a non-news trading day, the author will introduce statistics method to predict the stock prices and bid-ask spread for day trading.

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.

Nonparametric estimation of employee stock options

We proposed a new model to price employee stock options （ESOs）. The model is based on nonparametric statistical methods with market data. It incorporates the kernel estimator and employs a three-step method to modify Black- Scholes formula. The model overcomes the limits of Black-Scholes formula in handling option prices with varied volatility. It disposes the effects of ESOs self-characteristics such as non-tradability, the longer term for expiration, the eady exercise feature, the restriction on shorting selling and the employee＇s risk aversion on risk neutral pricing condition, and can be applied to ESOs valuation with the explanatory variable in no matter the certainty case or random case.

Option Strike Price and Managerial Investment Decisions

The manager′s investment decisions is modeled when the manager is risk averse and has stock options as compensation. It is found that the strike price of options is crucial to the investment incentives of managers, and that the correct value, or interval of values, of managerial stock option strike price can bring stockholder and manager interests in agreement.

Stock Liquidity Risk Pricing Model Driven by Systematic and Unsystematic Risk

In the stock pricing, liquidity risk has become one of the important factors that affect the stock realizable value. Systematic and unsystematic risk decided a stock＇s liquidity risk. The author uses the stock price index growth rate and net outer disk ratio to describe a systematic and unsystematic risk faced by investors. With the help of correlation and regression analysis in SPSS software, the paper tries to establish the systematic and unsystematic risk-driven stock liquidity risk pricing model. Empirical study shows that systematic and unsystematic risk has significant influence on stock liquidity risk. The bigger circulation stock, the greater the systemic risk influence; the less the circulation stock, the larger the non-system risk influence. Calendar factor on stock returns ratio has no significant effect. Trading volume on the stock returns ratio of small companies had no significant effect. The model has important reference value for the measure of stock liquidity risk value loss.