Opening Price Research Articles

Post-hit dynamics of price limit hits in the Chinese stock markets

Abstract Price limit trading rules are useful to cool off traders short-term trading mania on individual stocks. The price dynamics approaching the limit boards are known as the magnet effect. However, the price dynamics after opening price limit hits are not well investigated. Here, we provide a detailed analysis on the price dynamics after the hits of up-limit or down-limit is open based on all A-share stocks traded in the Chinese stock markets. A “W” shape is found in the expected return, which reveals high probability of a continuous price limit hit on the following day. We also find that price dynamics after opening limit hits are dependent on the market trends. The time span of continuously hitting the price limit is found to an influence factor of the expected profit after the limit hit is open. Our analysis provides a better understanding of the price dynamics around the limit boards and contributes potential practical values for investors.

A SPATIAL ANALYSIS ON GIS-HEDONIC PRICING MODEL ON THE INFLUENCE OF PUBLIC OPEN SPACE AND HOUSE PRICE IN KLANG VALLEY, MALAYSIA

Presently, it is noticeable that there is a significant influence of public open space about house price, especially in many developed nations. Literature suggests the relationship between the two aspects give impact on the housing market, however not many studies undertaken in Malaysia. Thus, this research was initiated to analyse the relationship of open space and house price via the techniques of GIS-Hedonic Pricing Model. In this regards, the GIS tool indicates the pattern of the relationship between open space and house price spatially. Meanwhile, Hedonic Pricing Model demonstrates the index of the selected criteria in determining the housing price. This research is a perceptual study of 200 respondents who were the house owners of double-storey terrace houses in four townships, namely Bandar Baru Bangi, Taman Melawati, Subang Jaya and Shah Alam, in Klang Valley. The key research question is whether the relationship between open space and house price exists and the nature of its pattern and intensity. The findings indicate that there is a positive correlation between open space and house price. Correlation analysis reveals that a weak relationship (rs < 0.1) established between the variable of open space and house price (rs = 0.91, N = 200, p = 0.2). Consequently, the rate of house price change is rather small. In overall, this research has achieved its research aims and thus, offers the value added in applying the GIS-Hedonic pricing model in analysing the influence of open space to the house price in the form of spatially and textually.

New evidence of short-run underpricing in Australian IPOs

The short-run market performance of initial public offerings (IPOs) indicates that the prices are often underpriced. This is widely accepted as a universal phenomenon. To find out whether Australian IPOs are underpriced, this paper analyzes the short-run market performance of 254 IPOs by industry, listing year and issue year. To measure the performance, the first-day returns are divided into the opening price primary market and the closing price secondary market, and the post-listing returns are also examined. The study found that, overall, Australian IPOs were underpriced by 25.47% based on abnormal returns and 26.43% on raw returns on the first-day primary market, which was statistically significant at the 1% level. However, analysis of the secondary market indicates that the Australian IPOs were overpriced by 1.55% and 1.54% on abnormal and raw returns, respectively, which was statistically significant at the 5% level. The examination of post-listing returns shows that Australian IPOs were underpriced based on cumulative abnormal returns (CARs) on the 3rd, 6th, and 10thdays by 24.63%, 24.06%, and 23.34%, respectively. The primary and post-listing analysis shows that IPOs in the industrial sector are more attractive to investors, whereas those in the chemical and materials sector are less attractive compared to other sectors. As far as the investors’ wealth is concerned, the study concludes that the short-run market performance analysis should consider both the first-day and post-listing returns

Twitter Sentiment and IPO Performance: A Cross-Sectional Examination

In this article, the authors examine the cross-sectional relationships between 325 IPOs’ first-day returns and their corresponding tweet sentiment, as defined by iSENTIUM LLC’s sentiment engine over the period from 2013 through 2014. They find that tweet sentiment is positively correlated to contemporaneous IPO returns. Interestingly enough, the authors document a positive relationship between prior days’ (1 day, 2 days, and 3 days) tweet sentiment and next-day IPO returns from offering price to opening price, along with a negative relationship between prior days’ (1 day, 2 days and 3 days) tweet sentiment and next-day IPO returns from opening price to closing price. Nevertheless, their examination of the relationship between intraday tweet sentiment and intraday IPO returns yields insignificant results. They find that tweet sentiment matters for IPO first-day performances, but the nature of this relationship appears very complex.

Lagging behind? Emotions in newspaper articles and stock market prices in the Netherlands

This study investigates emotions in Dutch newspaper articles and their effects on, and responses to, opening prices of 21 stocks listed on the Amsterdam Exchange index for twelve years (2002–2013). With regard to the financial context, we employed a selection of the Dutch Linguistic Inquiry and Word Count dictionary to automatically content analyze emotional tone in news articles (N=128,507). Neither positive nor negative emotions in news articles show consistent effects on the opening prices of stocks the following day. Granger causality tests suggest, however, that newspapers rather reflect movements on the stock market the following days by using more negative emotional words after an increase in the change of the opening prices.

Sudden breaks in drift-independent volatility estimator based on multiple periods open, high, low, and close prices

Sudden breaks in drift-independent volatility estimator based on multiple periods open, high, low, and close prices

The Spot Price Discovery of Put-call Ratio of KOSPI200 Nighttime Options

Trading of KOSPI200 options on Eurex launched in 2010 starts at 17:00 after market and closes at 05:00 in the next morning. This paper attempts to examine the role of put-call ratio of KOSPI200 nighttime options in price discovery process of spot market. The main findings of this paper are summarized as followings; The information content of put-call ratio of nighttime options is significantly incorporated in opening price of spot market next trading day but not delayed to the daytime spot market. Specifically, all put-call ratios measured in terms of total volume, total value, and cleared volume of nighttime options has strongly positive correlation with returns of KOSPI200 next trading day but put-call ratio of daytime option market has no predictive power of next daily return during sample period. This implies that the nighttime options market shows more leading role than daytime options in opening price discovery. This relationship between put-call ration and spot market return remains statistically significant during the period of the multiplier for KOSPI200 options increased. However, the change in put-call ratio of nighttime options is significantly explained by precedent put-call ratio of daytime market. This Overall empirical evidence indicates that traders of KOSPI200 options have tendency to implement strategy of linkage between price movement of daytime and nighttime market.

Linked Open Economy: Take Full Advantage of Economic Data

For decades, information related to public finances was out of reach for most of the people. Gradually, public budgets and tenders are becoming openly available and global initiatives promote fiscal transparency and open product and price data. But, the poor quality of economic open data undermines their potential to answer interesting questions (e.g. efficiency of public funds and market processes). Linked Open Economy (LOE) has been developed as a top-level conceptualization that interlinks the publicly available economic open data by modelling the flows incorporated in public procurement together with the market process to address complex policy issues. LOE approach is extensively used to enrich open economic data ranging from budgets and spending to prices. Developers, professionals, public administrations and any other interested party use and customize LOE model to develop new systems, to enable information exchange between systems, to integrate data from heterogeneous sources and to publish open data related to economic activities.

Optimal hedging ratio modeling using interday and intraday risk estimation: Moving window regression vs. cointegration approach

We considered the problem of choosing optimal hedging ratio taking into account interday and intraday return de- composition. It was shown that the standard hedging approach which uses only close prices (i.e. daily returns) is inefficient in comparison with hedging strategy based on open and close prices, i.e. when differentiating hedging ratio for interday and intra- day periods. Results are confirmed both by applying Moving Window Regression and Error Correction Model for major world indexes for 1992-2012.

Can Commodity Futures Margin Requirements Control Risks Effectively? Evidence from China

This paper differentiates two types of margin requirement increase in Chinese futures market: regular margin increase and risk margin increase. We use SVAR model to study the relationship among open interests, price volatility and margin level of six kinds of futures traded on SHFE. The result demonstrates that the volatility and open interests both decline after regular margin increase while they do not decrease as expected after risk margin increase. The result suggests that while the current Chinese margin system can reduce default risk related to deliveries, it has limited effects on controlling the markets risks.

Price Discrimination Based on Buyers’ Purchase History

We consider a repeated sales situation in which a seller sells one unit of a good each period to the same buyer. Having incomplete information about the buyer’s valuation, the seller responds to the buyer’s behavior, meaning, whether she bought previous units and at what price. We characterize the equilibrium of the no-commitment game for a uniform distribution and show that the seller discriminates between buyers based on their purchase history. Moreover, we show that the buyer’s ex-ante expected payoff is higher in the no-commitment game than in a game in which the seller can commit in advance to the prices he will charge (the commitment game). We also demonstrate that the buyer’s ex-post payoff is higher for each type of buyer in the no-commitment game. Social welfare is also higher in the no-commitment game. As the number of periods (units) increases, the opening prices decline, but fewer types of buyers accept the opening price.

Short-run underpricing and its determinants: Evidence from Australian IPOS

To find out whether the Australian IPOs are underpriced and what the determinants are, this study investigates the short-run market performance of 254 IPOs by industry, listing year and issue year over the period 2006 to 2011.To measure the short-run performance, the first listing day returns are divided into the primary market which is calculated based on the first day beginning prices and issue prices, the secondary market which is estimated based on the first day closing and opening prices and total market which is calculated based on the first day closing prices and issue prices. Then it is extended to the post-day listing analysis which includes returns up to 10 days. To find out the determinants of underpricing, this study estimates binary and multiple regression models with the offer, firm and market characteristics. The marginal probability analysis was also carried out to estimate the associated probability of each determinant which shows a directional change in the short-run market performance. The study found that overall the Australian IPOs are underpriced by 25.47% and 23.11% based on the average abnormal return (AAR) in the primary and total market, which is statistically significant at 1% and 5% level respectively. However, the secondary market analysis indicates that the Australian IPOs are overpriced by 1.55% on the AAR and it is statistically significant at 5% level. The examination of post listing returns shows that Australian IPOs are underpriced based on the average cumulative abnormal return (CAR) and it signals that investors’ wealth can be diluted due to overpricing in the long-run. The primary, total and post listing analysis shows that the industrial sector IPOs are more attractive to investors whereas the chemical and material sector IPOs are less attractive compared to other sectors. The IPO period, time to listing, listing delays, total net proceeds ratio, issue price, attached share option and the market volatility are the main determinants for the observed underpricing. The marginal probability analysis also shows that market volatility and total net proceeds ratio have a significant impact on the level of underpricing. As far as the investors’ wealth is concerned, the study shows that the short-run market performance analysis should consider both the first day return including primary and secondary market and the post-day return. Study concludes that short-run market performance is sensitive to the market, industry and listing & issue year and determinants to the model.

A cointegration analysis of price diffusion amid ADRs and dually listed Indian stocks

The aim of this study is to provide empirical support to global investors who are intending participation in stock markets using American Depositary Receipts (ADRs) as the investment vehicle. This study explores the degree of integration between ADRs and dually listed Indian Stocks using daily data for the period from January 2001 to May 2012. Further, the dynamics of price diffusion between the ADRs of Indian stocks pertaining to telecommunication sector cross listed in the US markets is examined by applying econometric tools like cointegration test, vector error correction model and Granger causality test. The findings reveal that both long run cointegration relationships and short run causality relationships exist between domestic stock price series and ADR prices. Further, we find evidence of strong error correction of ADR open and close to domestic stock open and close prices, and weak error correction of domestic market open index returns to foreign market open index returns. This implicates that ADRs appear to overreact to the US market index but underreact to changes in underlying share prices.

Predicting Closing Stock Price using Artificial Neural Network and Adaptive Neuro Fuzzy Inference System (ANFIS: The Case of the Dhaka Stock Exchange

Stock market prediction plays a vital rule in taking financial decisions. Various factors affecting the stock market makes stock prediction somewhat complex and difficult. Different data mining techniques such as Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) etc are being widely used for predicting stock prices of different stock exchange cases. But there is no good work on stock prediction using ANN and ANFIS for Bangladesh Stock Markets. The goal of this paper is to find out an efficient soft computing technique for Dhaka Stock Exchange (DSE) closing data prediction. In this paper, ANN and ANFIS have been applied on different companies previous data such as opening price, highest price, lowest price, total share traded. The day end closing price of stock is the outcome of ANN and ANFIS model. Our experiment shows that, ANFIS is more effective and efficient technique to predict Dhaka Stock exchange (DSE) data.

Information transmission between U.S. and China index futures markets: An asymmetric DCC GARCH approach

The Chinese stock market and its impacts on other stock markets have attracted a lot of attention and have been of a great concern to many countries. This paper aims to shed light on the issue by examining the information transmission between the S&P 500 and the CSI 300 index futures markets. The empirical results reveal that news from one market significantly affects the volatilities of open prices of the other and the impact from U.S. to China is stronger than the other way round. Further, past news of the U.S. has a significant impact on the volatilities of daily trading in China, but not vice versa. These findings indicate that the U.S. stock index futures market is more efficient in impounding information from other markets.

PENAWARAN SAHAM PERDANA: PENGALAMAN DI BURSA EFEK JAKARTA 1990 – 1998

This study investigates initial and aftermarket performance of initial public offering (IPOs) for both short term and long term in the Jakarta Stock Exchange (JSE), from January 1990 to December 1998. This study considers market situation at the time of the issuance of IPOs. The short term performance measure of IPOs is tested using daily closing return (Rct), opening return (Rot), offering price to opening price, offering price to closing price and opening price to closing price criteria. The long term aftermarket performance of IPOs is measured using cumulative abnormal returns analysis, buy and hold market adjusted compounded returns, wealth relative, offering price to closing price and opening price to closing price. Using a sample of 233 IPOs in the Jakarta Stock Exchange (JSE), this study finds an average initial (offer-to-open) return of 10.948 percent (10.912 % adjusted return). The findings reveals a lower expected return from those found in developing and several developed markets. The short term aftermarket mean return based on daily closing mean return (Rct), opening mean return (Rot) and opening price to closing price, indicates that benefits of initial performance do not accrue to the secondary market traders. This result is consistent with studies of Barry and Jennings (1993) on the U.S. markets and Yong (1997) on the Malaysian market. The long run aftermarket performance of IPOs is found to be negative. This finding is supported by many IPOs results in the literature. Keywords: Opening-closing mean return, performance of IPO.

Open Price for Iran: The Bases for Reform

The rules of sale contract in many countries allow parties to conclude a contract without specifying the price at the time of formation. Such contracts are called open price sale (sale of goods) contracts and are of the needs of modern trade methods. As a result, parties enjoy the freedom to conclude their contract without contractual risks. The problem, however, is that under the Iranian rules on sale contracts, these possibilities do not exist. Such treatment by Iranian legislators on the issue of price in a sale contract has caused problems in national and transactional level. Adopting a doctrinal research method, the first aim of this study is to perform a review on the concept of open price term and the current Iranian law on this concept. The next objective is to explain the justifications for acceptance of open price term with regard to global evolutions, legal theories and Islamic theories and principles. DOI: 10.5901/mjss.2015.v6n4s3p166

Borsa Istanbul (BIST) daily prediction using financial news and balanced feature selection

In this paper, a novel method is proposed to predict the direction of Borsa Istanbul (BIST) 100 Index (BIST100) open prices using the news articles released, as well as the price data, from the day before. Although English news articles have been used for market-prediction before, to the best of our knowledge, Turkish news articles together with prices have not yet been used to predict the Turkish markets. Turkish text mining techniques are applied on news articles to form feature vectors for each trading day. The feature vectors are assigned three labels based on the direction of the price change from the closing price of the day before and whether the change is significant. News articles are represented using high dimensional features, some of which could be noisy or irrelevant for prediction. There is also the scarcity of training data. Therefore, this study incorporates feature selection methods to select features that could improve classification performance. By its nature, significant positive or negative changes in stock price happen much less than non-significant changes, resulting in an imbalanced data set. Most feature selection methods in literature aim to reduce the classification accuracy. However, for imbalanced datasets, other measures, such as macro-averaged F-measure need to be considered. The paper proposes a feature selection methods that is able to deal with the class imbalance problem through oversampling of the minority classes and consideration of an ensemble of selected features. In order to decide on importance of features, as the relevance criterion for each feature, the proposed methodology uses mutual information which can detect nonlinear dependencies between variables. Therefore, the proposed feature selection method is called Balanced Mutual Information (BMI) feature selection method. Experiments were performed based on news articles provided by two different news sources: Public Disclosure Platform of BIST and financial news websites. It was shown that, using Balanced Mutual Information feature selection method, the significant changes in the BIST100 Index were predicted with an accuracy of 0.74 and a macro-averaged F-measure of 0.68. The BMI feature selection method was compared with Mutual Information and Chi-square based feature selection methods and it was found out that BMI method results in higher performance using a smaller number of features.

Information Transmission between U.S. and China Index Futures Markets: An Asymmetric DCC GARCH Approach

The Chinese stock market and its impacts on other stock markets have attracted a lot of attention and have been of a great concern to many countries. This paper aims to shed light on the issue by examining the information transmission between the S&P 500 and the CSI 300 index futures markets. The empirical results reveal that news from one market significantly affects the volatilities of open prices of the other and the impact from U.S. to China is stronger than the other way round. Further, past news of the U.S. has a significant impact on the volatilities of daily trading in China, but not vice versa. These findings indicate that the U.S. stock index futures market is more efficient in impounding information from other markets.

Limited attention of individual investors and stock performance: Evidence from the ChiNext market

We explore the relationship between the individual investor's attention and stock performance based on the ChiNext stock market. Our findings indicate that individual investor's attention can affect the performance of the stock market. Limited attention of investors exerts a positive price pressure, and the reversal of this price pressure will occur in the short term. We also verify that investor attention on non-trading days has a significant impact on the price gap for the next week's opening price.