scholarly journals Language Consistency and Stock Market Trading Volume

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402091977
Author(s):  
Jameson K. M. Watts
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Positive Influence ◽  
Biotechnology Industry ◽  
Trade Journal ◽  
Journal Articles ◽  
Information Theoretic ◽  
Stock Market Trading

An information-theoretic measure of language consistency is constructed from the text of 13 years of trade journal articles on the biotechnology industry. This measure is then related to the trading volume of a representative portfolio of biotechnology stocks. Findings indicate that language consistency and trading volume have a joint (positive) influence on each other over the long term; however, sharp drops in consistency are also predictive of transient spikes in trading volume. The significance of these findings is discussed in relation to modern theories of legitimation and the economics of surprise.

Single step estimation of ARMA roots for non-fundamental nonstationary fractional models

2022 ◽  
Author(s):  
Ignacio N Lobato ◽  
Carlos Velasco
Keyword(s):  
Stock Market ◽  
Strong Evidence ◽  
Long Memory ◽  
Trading Volume ◽  
Moving Average ◽  
Single Step ◽  
Arma Process ◽  
Dow Jones Industrial Average ◽  
Fractional Models ◽  
Stock Market Trading

Abstract We propose a single step estimator for the autoregressive and moving-average roots (without imposing causality or invertibility restrictions) of a nonstationary Fractional ARMA process. These estimators employ an efficient tapering procedure, which allows for a long memory component in the process, but avoid estimating the nonstationarity component, which can be stochastic and/or deterministic. After selecting automatically the order of the model, we robustly estimate the AR and MA roots for trading volume for the thirty stocks in the Dow Jones Industrial Average Index in the last decade. Two empirical results are found. First, there is strong evidence that stock market trading volume exhibits non-fundamentalness. Second, non-causality is more common than non-invertibility.

scholarly journals Long Memory in Stock-Market Trading Volume

2000 ◽  
Vol 18 (4) ◽  
pp. 410-427 ◽  
Author(s):  
Ignacio N. Lobato ◽  
Carlos Velasco
Keyword(s):  
Stock Market ◽  
Long Memory ◽  
Trading Volume ◽  
Stock Market Trading

Relationship Between FIIs’ Herding and Returns in the Indian Equity Market: Further Empirical Evidence

2019 ◽  
pp. 097215091984522
Author(s):  
Kapil Choudhary ◽  
Parminder Singh ◽  
Amit Soni
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Trading Volume ◽  
Negative Relationship ◽  
Positive Association ◽  
Vital Role ◽  
Market Volatility ◽  
Market Returns ◽  
Stock Market Returns ◽  
Stock Market Trading

Empirical evidence indicates that foreign institutional investors (FIIs) play a vital role in financial markets, and being the major players, they demonstrate positive feedback trading behaviour and usually follow one another’s actions. In order to examine this phenomenon, the present study endeavoured to unearth the relationship between foreign institutional investments (FIIs) and returns in the Indian stock market, trading volume and volatility. The return of the Nifty50 index has surrogated market returns, while volatility is represented by conditional volatility computed from Nifty50, from January 1999 to May 2017. The vector autoregression (VAR) results indicate a positive association between herding among FIIs and lagged market returns, while information asymmetry has no impact on herding. On the other hand, previous-day volatility has a significant bearing on the herding measure. Overall, the results portray a significant relationship between herding and stock market returns in India. The results of multivariate regression exhibit that market return was a primary factor for FII herding during the study period under consideration, while trading volume bore no relationship with herding. In case of market volatility, the empirical results are in congruence with the fact that during the period of the volatile market, FIIs prefer to not indulge in herding. Furthermore, the results of three sub-periods, that is, before, during and after the crisis, are similar to the results of the whole study period which indicates that the return is a prime and vital force for herding; on the contrary, market volatility appears to have a negative relationship with herding.

scholarly journals A Linear Regression Approach to Prediction of Stock Market Trading Volume: A Case Study

2013 ◽  
Vol 4 (3) ◽  
pp. 25-31 ◽  
Author(s):  
Farhad Soleimanian Gharehchopogh ◽  
Tahmineh Haddadi Bonab ◽  
Seyyed Reza Khaze
Keyword(s):  
Linear Regression ◽  
Stock Market ◽  
Trading Volume ◽  
Regression Approach ◽  
Stock Market Trading

The behavior of daily stock market trading volume

1989 ◽  
Vol 11 (4) ◽  
pp. 331-359 ◽  
Author(s):  
Bipin B. Ajinkya ◽  
Prem C. Jain
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Stock Market Trading

scholarly journals ANALISIS DETERMINAN VOLUME PERDAGANGAN SUKUK NEGARA RITEL SERI SR-007

El Dinar ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 119
Author(s):  
Laily Farikhatun Ni'mah ◽  
Ahmad Sidi Pratomo
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Positive Influence ◽  
The State ◽  
State Budget ◽  
Vector Error Correction ◽  
Vector Error ◽  
Negative Effect ◽  
Vector Error Correction Models

<p><em>Trading volume of retail sukuk is the number of sheets of the State retail sukuk listed on the stock exchange. The country's retail sukuk issued to finance a deficit Budget of income and Expenditure of the State (STATE BUDGET) the purpose of this research is to examine and analyze the influence of internal factors and external factors against a trading volume of sukuk country retail series SR-007. This research uses descriptive kuantitaif approach. Researchers use the data monthly April 2015 period until March 2018. The variables used in this study is the price, the Yield to Maturity (YTM), exchange rates, For the results of Mudharabah Deposits, the BI rate, inflation and trading Volume of Sukuk Retail Series SR-007. The research analytical tool is Vector Error Correction models (VECM) using Eviews 9. The results of this research show that there is a short-term relationship between variables that influence positive YTM against trading volume of sukuk retail series SR-007. In a long term relationship variables YTM, the exchange rate, the BI Rate, and inflation provide a positive influence against the trading volume of sukuk retail series SR-007. Variable YTM on long term negative effect against the trading volume of sukuk retail series SR-007.</em></p>

scholarly journals Analyzing Microblogging Activity and Stock Market Behavior through Artificial Neural Networks

2020 ◽  
Vol 2 (2) ◽  
pp. 1
Author(s):  
Piñeiro-Chousa Juan ◽  
López-Cabarcos M Ángeles ◽  
Pérez-Pico Ada M ◽  
Vizcaíno-González Marcos
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Stock Market ◽  
Risk Premium ◽  
Trading Volume ◽  
Network Activity ◽  
Future Research ◽  
Artificial Neural ◽  
Negative Sentiment ◽  
Stock Market Trading

This paper attempts to analyze the relationship between social network activity (message sentiment) and stock market (trading volume and risk premium). We used Artificial Neural Networks to analyze 87,511 stock-related microblogging messages related to S&P500 Index posted between October 2009 and October 2014. The results obtained suggest that there is a direct relationship between trading volume and negative sentiment, and between risk premium and negative sentiment. The paper concludes with several directions for future research.

scholarly journals Long term Covid-19 terhadap Pasar Saham di Indonesia

POINT ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 1-9
Author(s):  
Imam Nur Hidayat ◽  
Ilham Maulana ◽  
Mohammad Arif
Keyword(s):  
Stock Market ◽  
Structural Equation ◽  
Trading Volume ◽  
Research Method ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Structure Equation Modeling ◽  
Positive Effect

ABSTRAK Penelitian ini bertujuan meneliti pengaruh dari perkembangan penyebaran covid-19 di Indonesia terhadap pasar saham di Indonesia. Metode penelitian menggunakan data kasus baru dan kematian baru akibat covid-19, dan data penutupan dan Volume perdagangan IHSG yang kami kumpulkan dari periode tanggal 2 Maret sampai – 7 Januari 2021. Data tersebut kemudian kami uji menggunakan structure equation modeling (SEM) Partial Least Square (PLS) dengan bantuan aplikasi WarpPLS 7.0. Dalam penelitian ini kami temukan bahwa penyebaran Covid-19 di Indonesia berpengaruh Positif terhadap kinerja pasar saham (IHSG) di Indonesia. Kata kunci : Covid-19, Pasar Saham. ABSTRACT This study aims to examine the effect of the spread of covid-19 in Indonesia on the stock market in Indonesia. The research method used data on new cases and new deaths due to covid-19, and the closing data and trading volume of the JCI that we collected from the period March 2 to January 7, 2021. We then tested the data using the Partial Least Square structural equation modeling (SEM). (PLS) with the help of the WarpPLS 7.0 application. We find this investigation that the spread of Covid-19 in Indonesia has a positive effect on the performance of the stock market (IHSG) in Indonesia. Keywords: Covid-19, Stock Market.

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