scholarly journals The Influence of Trading Volume, Market Trend, and Monetary Policy on Characteristics of the Chinese Stock Exchange: An Econophysics Perspective

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 985-998
Author(s):  
Meng Ran ◽  
Zhenpeng Tang ◽  
Weihong Chen
Keyword(s):  
Monetary Policy ◽  
Trading Volume ◽  
Stock Exchange ◽  
Composite Index ◽  
Policy Formulation ◽  
Time Intervals ◽  
Monetary Policies ◽  
Policy Cycles ◽  
Trading Volumes ◽  
Healthy Growth

Abstract The paper adopts the financial physics approach to investigate influence of trading volume, market trend, as well as monetary policy on characteristics of the Chinese Stock Exchange. Utilizing 1-minute high-frequency data at various time intervals, the study examines the probability distribution density, autocorrelation and multi-fractal of the Shanghai Composite Index. Our study finds that the scale of trading volume, stock market trends, and monetary policy cycles all exert significant influences on micro characteristics of Shanghai Composite Index. More specifically, under the conditions of large trading volumes, loose monetary policies, and downward stock trends, the market possesses better fitting on Levy’s distribution, the volatility self-correlation is stronger, and multifractal trait is more salient. We hope our study could provide better guidance for investment decisions, and form the basis for policy formulation aiming for a healthy growth of the financial market.

scholarly journals PENJELASAN POLA VOLUME PERDAGANGAN TRADER DENGAN DATA TRANSAKSI ORDER SAHAM DI BURSA EFEK INDONESIA

2009 ◽  
Vol 9 (2) ◽  
pp. 21
Author(s):  
Ghazali Syamni ◽  
Aiyub , ◽  
Juilimursyida Ganto ◽  
Azhar ,
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Investor Behavior ◽  
Regression Result ◽  
Time Intervals ◽  
Transaction Data ◽  
Trading Volumes ◽  
Different Response ◽  
Stock Transaction

<p class="Style1"><strong><em>The objectives of this research is to explain pattern of behavior of trading </em></strong><strong><em>volume intraday investor inform and investor uninformed, and analysis </em></strong><strong><em>contribution of the both investors in explaining pattern behavior of investors </em></strong><strong><em>trading volume in Indonesia Stock Exchange. Regression analysis result </em></strong><strong><em>indicates that investor or trader informed is more contributionly in explaining </em></strong><strong><em>trading volume pattern in all time intervals, but not all investors or traders </em></strong><strong><em>uninformed contributions in all time intervals. Only order informed is more </em></strong><strong><em>can explain trading volume pattern compared with order uninformed. </em></strong><strong><em>Regression result finds that order status match have to share is determine </em></strong><strong><em>trading volume pattern intraday. The role of more determined by INFBM and </em></strong><strong><em>INFSM compared with UNFBM and UNFSM. While order status amend, open </em></strong><strong><em>and withdraw is less have casting for determining trading volume pattern intraday. Some possibility of this development of researchs in the future, </em></strong><strong><em>between the are test the relation of behavior of investors at trading volumes by </em></strong><strong><em>dividing investor inform with block tradings. This division anticipated to give </em></strong><strong><em>different response at trading volume pattern. usage of stock transaction data </em></strong><strong><em>intraday before applying ofpre-opening in Indonesia Stock Exchange.</em></strong></p><p class="Style1"><strong><em>Keywords: trading volume, investor behavior,</em></strong></p>

Disposition effect at the market level: evidence from Indian stock market

2019 ◽  
Vol 12 (2) ◽  
pp. 69-82
Author(s):  
Sravani Bharandev ◽  
Sapar Narayan Rao
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Reference Points ◽  
Disposition Effect ◽  
Content Type ◽  
Ex Post ◽  
Abnormal Trading Volume ◽  
The Difference ◽  
Trading Volumes ◽  
Indian Stock Market

Purpose The purpose of this paper is to test the disposition effect at market level and propose an appropriate reference point for testing disposition at market level. Design/methodology/approach This is an empirical study conducted on 500 index stocks of NSE500 (National Stock Exchange). Winning and losing days for each stock are calculated using 52-week high and low prices as reference points. To test disposition effect, abnormal trading volumes of stocks are regressed on their percentage of winning (losing) days. Further using ANOVA, the difference between mean of percentage of winning (losing) days of high abnormal trading volume deciles and low abnormal trading volume deciles is tested. Findings Results show that a stock’s abnormal trading volume is positively influenced by the percentage of winning days whereas percentage of losing days show no such effect. Findings are consistent even after controlling for volatility and liquidity. ANOVA results show the presence of high percentage of winning days in higher deciles of abnormal trading volumes and no such pattern in case of losing days confirms the presence of disposition effect. Further an ex post analysis indicates that disposition prone investors accumulate losses. Originality/value This is the first study, which proposes the use of 52-week high and low prices as reference points to test the market-level disposition effect. Findings of this study enhance the limited literature available on disposition effect in emerging markets by providing evidence from Indian stock markets.

scholarly journals Hubungan Perilaku Perdagangan Investor Dengan Volume Perdagangan Di Bursa Efek Indonesia

2009 ◽  
Vol 2 (1) ◽  
Author(s):  
Ghazali Syamni
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Time Interval ◽  
Time Intervals ◽  
Using Data ◽  
Changes Over Time ◽  
Relationship Of ◽  
The Relationship ◽  
Order Pattern ◽  
Over Time

This paper examines the relationship of behavior trading investor using data detailed transaction history-corporate edition demand and order history in Indonesia Stock Exchange during period of March, April and May 2005. Peculiarly, behavior placing of investor order at trading volume. The result of this paper indicates that trading volume order pattern to have pattern U shape. The pattern happened that investors have strong desires to places order at the opening and close of compared to in trading periods. While the largest orders are of market at the opening indicates that investor is more conservatively when opening, where many orders when opening has not happened transaction to match. In placing order both of investor does similar strategy. By definition, informed investors’ orders more large than uninformed investors. If comparison of order examined hence both investors behavior relatively changes over time. But, statistically shows there is not ratio significant. This implies behavior trading of informed investors and uninformed investors stable relative over time. The result from regression analysis indicates that informed investors to correlate at trading volume in all time intervals, but not all uninformed investors correlates in every time interval. This imply investor order inform is more can explain trading volume pattern compared to uninformed investor order in Indonesia Stock Exchange. Finally, result of regression also finds that order status match has greater role determines trading volume pattern intraday especially informed buy match and informed sale match. While amend, open and withdraw unable to have role to determine intraday trading volume pattern.

scholarly journals Trading Volume as a Predictor of Market Movement

2019 ◽  
Vol 8 (2) ◽  
pp. 57-69
Author(s):  
Edson Kambeu
Keyword(s):  
Logistic Regression ◽  
Stock Market ◽  
Regression Model ◽  
Trading Volume ◽  
Logistic Regression Model ◽  
Predictive Analytics ◽  
Stock Exchange ◽  
Stock Market Index ◽  
Trading Volumes ◽  
Popular Language

A logistic regression model is has also become a popular model because of its ability to predict, classify and draw relationships between a dichotomous dependent variable and dependent variables. On the other hand, the R programming language has become a popular language for building and implementing predictive analytics models. In this paper, we apply a logistic regression model in the R environment in order to examine whether daily trading volume at the Botswana Stock Exchange influence daily stock market movement. Specifically, we use a logistic regression model to find the relationship between daily stock movement and the trading volumes experienced in the recent five previous trading days. Our results show that only the trading volume for the third previous day influence current stock market index movement. Overall, trading volumes of the past five days were found not have an impact on today’s stock market movement. The results can be used as a basis for building a predictive model that utilizes trading as a predictor of stock market movement.

scholarly journals EFFECT OF MACROECONOMIC FACTORS ON TRADING VOLUMES OF MANUFACTURING AND ALLIED COMPANIES LISTED IN NAIROBI SECURITIES EXCHANGE

2020 ◽  
Vol 5 (2) ◽  
pp. 27
Author(s):  
Gabriel Njogu Chege ◽  
Stanley Kirika
Keyword(s):  
Negative Correlation ◽  
Trading Volume ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Negative Relationship ◽  
Unique Contribution ◽  
Stock Trading ◽  
Treasury Bill ◽  
Lending Rate ◽  
Trading Volumes

Purpose: The purpose of this study was to establish the effect of inflation, lending rate, exchange rates and Treasury bill interest rate on trading volumes of manufacturing and allied companies listed in the Nairobi Stock Exchange. Materials and Methods: The research adopted a quantitative descriptive design that focuses on nine manufacturing and allied companies listed in NSE and make up in the list of 25-share index companies. The nine manufacturing and allied companies were selected through purposive sampling techniques, where samples were selected based specific factors. The data used in the research was collected from Central Bank of Kenya, Nairobi Security Exchange and Kenya Bureau of Statistics. This research employed a panel data analysis using STATA software.  Treasury bill rate was dropped from the model due to multicollinearity. Results: The analysis found that there was a negative relationship between inflation on trading volume, exchange rate had a negative correlation with stock trading, lending rate had a negative correlation with stock trading volume of manufacturing and allied companies listed in the Nairobi Stock Exchange.  Unique contribution to theory, practice and policy: The study recommends the government should initiate policies that will lower the lending rate in Kenya as lower lending rate may translate to higher stock trading volumes. Further studies should research on other factors affecting stock trade volume which may include the value of the stocks and the information size in the market.

scholarly journals Investigating Expiration Day Effects in Stock Index Futures in India

2010 ◽  
Vol 1 (1) ◽  
pp. 9-19 ◽  
Author(s):  
Sathya Swaroop Debasish
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Stock Index ◽  
Stock Index Futures ◽  
Sample Period ◽  
Complete Sample ◽  
Index Futures ◽  
Trading Volumes ◽  
Price Distortions ◽  
Return Process

This study attempts to examine whether potential expiration effects exist on the NSE Nifty index by comparing the trading volume and return process at expiration with a comparison group. The period of analysis covers index futures expirations from June 2001 to May 2009. The trading volume and return process on expiration days and during expiration weeks were compared with a set of comparison days and comparison weeks. The current study used the pooled t-test and Wilcoxon rank sum test to investigate whether mean returns, price ranges, and adjusted trading volumes (i.e. time-independent trading volumes) were significantly different at expiration. The procedure as used by Stoll and Whaley (1987) was used to examine if price reversals existed during expiration days and comparison days.The evidence indicates that the trading volume on expiration days and in expiration weeks was significantly larger than on comparison days and during comparison weeks. Further, the results suggest that there were no price distortions on the expiration day or during the expiration week for the complete sample period and the second sub-period. For the first sub-period, however, evidence suggesting that expiration days and weeks experienced higher volatility than normal does exist. No evidence of significantly different mean returns, volatility, or price reversals at expiration was found. This could be due to the longer settlement period in India. However, when the complete sample period was divided into two sub-periods it was found that expiration day (weeks) during the first sub period may have experienced price distortions. The results of this study are crucial to investors, stock exchange officials, and regulators.

scholarly journals REAKSI PASAR SAHAM PERUSAHAAN FARMASI SEBELUM DAN SESUDAH COVID-19 DI INDONESIA

2021 ◽  
Vol 6 (1) ◽  
pp. 67-79
Author(s):  
Kartika Pradana Suryatimur ◽  
Nibras Anna Khabibah
Keyword(s):  
Stock Prices ◽  
Trading Volume ◽  
Stock Exchange ◽  
Test Results ◽  
Pharmaceutical Sector ◽  
Economic Activities ◽  
Stock Trading ◽  
The World ◽  
Before And After ◽  
Trading Volumes

The COVID-19 pandemic has had an impact on social and economic activities that have an impact on stock market conditions in the world, including Indonesia. This study identified differences in stock prices and stock trading volumes (TVA) of companies in the pharmaceutical sector before and after the announcement of the first COVID-19 case in Indonesia. The sample used is 10 pharmaceutical sector companies listed on the Indonesia Stock Exchange (IDX). The method used in this research is an event study using paired sample t-test. Based on the test results, there was a difference in prices before and after the announcement of the first COVID-19 case in Indonesia, but there was no difference in trading volume testing.

scholarly journals The Impact of Weather Factors on Quotations of Energy Sector Companies on Warsaw Stock Exchange

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1536
Author(s):  
Waldemar Tarczyński ◽  
Sebastian Majewski ◽  
Małgorzata Tarczyńska-Łuniewska ◽  
Agnieszka Majewska ◽  
Grzegorz Mentel
Keyword(s):  
Behavioral Finance ◽  
Trading Volume ◽  
Stock Exchange ◽  
Sunshine Duration ◽  
Energy Sector ◽  
Weather Factors ◽  
The Best Approximation ◽  
Warsaw Stock Exchange ◽  
Trading Volumes ◽  
The Impact

Recent researches on behavioral finance have tested for, among others, evidence for the relations between weather, investors’ mood, and investment decisions. Many of the researches related to the influence of some weather factors, such as sunshine duration on stock exchange returns, but there is no complex research taking into account a wide group of weather factors determining investors’ mood. The main goal of the article is to verify the influence of weather factors on basic market parameters of energy sector companies quoted on the Warsaw Stock Exchange. Rates of return, trading volumes, and values of trading volume are taken into account during the research. All analyses are based on econometric models assuming the existence of typical problems of estimation such as: autocorrelation of residuals, heteroskedasticity, or abnormality of residuals. The best approximation of models was obtained for GARCH (Generalized Autoregressive Conditional Heteroskedasticity) type models.

META-ANALYSIS ON AMERICAN PRESIDENTIAL ELECTION - 2016 AND AMERICAN STOCK MARKET

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Farhan Ahmed ◽  
Salman Bahoo ◽  
Sohail Aslam ◽  
Muhammad Asif Qureshi
Keyword(s):  
Content Analysis ◽  
Stock Market ◽  
Event Study ◽  
Presidential Election ◽  
Republican Party ◽  
Stock Exchange ◽  
Meta Analysis ◽  
Composite Index ◽  
Stock Index ◽  
Political Event

This paper aims to analyze the efficient stock market hypothesis as responsive to American Presidential Election, 2016. The meta-analysis has been done combining content analysis and event study methodology. The all major newspapers, news channels, public polls, literature and five important indices as Dow Jones Industrial Average (DJIA), NASDAQ Stock Market Composit Indexe (NASDAQ-COMP), Standard & Poor's 500 Index (SPX-500), New York Stock Exchange Composite Index (NYSE-COMP) and Other U.S Indexes-Russell 2000 (RUT-2000) are critically examined and empirically analyzed. The findings from content analysis reflect that stunned winning of Mr Trump from Republican Party worked as shock for American stock market. From event study, findings confirmed that all the major indices reflected a decline on winning of Trump and losing of Ms. Clinton from Democratic. The results are supported empirically and practically through the political event like BREXIT that resulted in shock to Global stock index and loss of $2 Trillion.

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