scholarly journals The Relationship of Stock Prices and Stock Market Performance Ratios in Companies Trading on Borsa Istanbul: An Application in Companies with the Highest Trading Volume

2021 ◽  
Author(s):  
Bilgehan Tekin ◽  
Seda Nur Bastak
Keyword(s):  
Regression Analysis ◽  
Stock Market ◽  
Stock Prices ◽  
Trading Volume ◽  
Market Price ◽  
Share Price ◽  
Panel Regression ◽  
Market Prices ◽  
Positive Direction ◽  
Stock Market Performance

In this study, the effect of certain ratios that investors pay attention to on stock prices in Borsa Istanbul is examined. For this purpose, 30 of the stocks with which the investors traded the most were taken as a sample. In the study, 30 companies with the highest average trading volume in the analysis period were selected according to their transactions in Borsa Istanbul. The study covers the period between 2010: 1Q-2019: 4Q. Variables included in the study are stock market price, P/E ratio, trading volume, market to book ratio, beta, free float percentage. In this study, it has been tried to understand at what level the stock market prices of companies' publicly traded stocks are affected by the indicators that emerge as a result of the transactions realized in the stock exchange, rather than the ratios discussed within the scope of financial analysis and ratio analysis, examples of which are very common in the literature. Panel regression analysis was performed in the study. Before proceeding to the panel regression analysis, preliminary tests were carried out and the model was tried to be given its most suitable form. For this purpose, multicollinearity tests, cross section dependency test, second generation unit root tests, varying variance test, panel regression model selection were made. The model created in the last stage was estimated. As a result of the study, it was seen that the Price/Earnings, Transaction Volume, Market Value/Book Value and Beta variables were significantly effective on the stock market prices of the companies' stocks. Among these variables, BETA affects negatively, while other variables affect positively. The variable with the highest effect on the share price is the negative BETA coefficient and the positive direction is the trading volume.

scholarly journals Weibo Attention and Stock Market Performance: Some Empirical Evidence

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Minghua Dong ◽  
Xiong Xiong ◽  
Xiao Li ◽  
Dehua Shen
Keyword(s):  
Regression Analysis ◽  
Stock Market ◽  
Quantile Regression ◽  
Empirical Evidence ◽  
Trading Volume ◽  
Market Performance ◽  
Correlation Coefficients ◽  
Investor Attention ◽  
Stock Market Performance ◽  
Quantile Regression Analysis

In this paper, we employ Weibo Index as the proxy for investor attention and analyze the relationships between investor attention and stock market performance, i.e., trading volume, return, and volatility. The empirical results firstly show that Weibo attention is positively related to trading volume, intraday volatility, and return. Secondly, there exist bidirectional causal relationships between Weibo attention and stock market performance. Thirdly, we generally find that higher Weibo attention indicates higher correlation coefficients with the quantile regression analysis.

scholarly journals Modelling Macroeconomic Determinants Of Stock Market Prices: Evidence From Namibia

2012 ◽  
Vol 28 (5) ◽  
pp. 871 ◽  
Author(s):  
Joel Hinaunye Eita
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Money Supply ◽  
Stock Prices ◽  
Economic Activity ◽  
Market Price ◽  
Font Size ◽  
Market Prices ◽  
Econometric Methodology ◽  
Macroeconomic Determinants

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none;" class="MsoNormal"><span lang="EN-GB" style="color: black; font-size: 10pt; mso-ansi-language: EN-GB; mso-themecolor: text1;"><span style="font-family: Times New Roman;">This paper investigates the macroeconomic determinants of stock market prices in Namibia. The investigation was conducted using a VECM econometric methodology and revealed that Namibian stock market prices are chiefly determined by economic activity, interest rates, inflation, money supply and exchange rates.<span style="mso-spacerun: yes;"> </span>An increase in economic activity and the money supply increases stock market prices, while increases in inflation and interest rates decrease stock prices.<span style="mso-spacerun: yes;"> </span>The results suggest that equities are not a hedge against inflation in Namibia, and contractionary monetary policy generally depresses stock prices.<span style="mso-spacerun: yes;"> </span>Increasing economic activity promotes stock market price development.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

scholarly journals influence of rumors and its consequences in dynamics of stock market prices

2013 ◽  
Vol 7 ◽  
Author(s):  
Fábio Marques da Cruz ◽  
Maria Yêda Falcão Soares de Filgueiras Gomes
Keyword(s):  
Stock Market ◽  
Information Asymmetry ◽  
Stock Prices ◽  
Trading Volume ◽  
Stock Exchange ◽  
Spot Market ◽  
Perfect Competition ◽  
Market Prices ◽  
The Press

This work is part of an ongoing study that aims to analyze the influence of rumors on the price dynamics in the stock market, through a case study of companies whose shares are traded much among financial agents. For this purpose we used historical prices of securities traded in the spot market of Sao Paulo Stock Exchange in the years 2007 to 2011, from files available in its website. A sample of 10 companies was selected among the stocks with higher trading volume during this period to collect the documents presented for communication of relevant facts and clarifications in stock exchange’s site. Only communications presented on the period specified that provide clarification related to news and unverified information disclosed in the press were brought within the scope of data collection. Until now, only the company communications with the most actively traded stocks were collected, whose analysis allowed the categorization of information and creation of a diagram for representing information about the rumors treated on these documents. This diagram was applied to a database where the information collected was stored for later retrieval and analysis. From this information, asset prices were retrieved to analyze the influence of rumors reported by the press in the price fluctuation of the asset. The authors Kapferer, Müller and Martins form the theoretical framework. As a result, the research has identified some rumors that interfered in the stock prices, as well as classified the rumors about the issues they address. So, as many times the rumor rises from the void of knowledge and information asymmetry, it is noted that there is no perfect competition among financial agents.

scholarly journals Fractional differencing in stock market price and online presence of global tourist corporations

2019 ◽  
Vol 24 (48) ◽  
pp. 194-204 ◽  
Author(s):  
Francisco Flores-Muñoz ◽  
Alberto Javier Báez-García ◽  
Josué Gutiérrez-Barroso
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Market Price ◽  
Google Trends ◽  
Data Sets ◽  
Market Prices ◽  
Content Type ◽  
Search Results ◽  
Online Presence ◽  
Fractional Differencing

Purpose This work aims to explore the behavior of stock market prices according to the autoregressive fractional differencing integrated moving average model. This behavior will be compared with a measure of online presence, search engine results as measured by Google Trends. Design/methodology/approach The study sample is comprised by the companies listed at the STOXX® Global 3000 Travel and Leisure. Google Finance and Yahoo Finance, along with Google Trends, were used, respectively, to obtain the data of stock prices and search results, for a period of five years (October 2012 to October 2017). To guarantee certain comparability between the two data sets, weekly observations were collected, with a total figure of 118 firms, two time series each (price and search results), around 61,000 observations. Findings Relationships between the two data sets are explored, with theoretical implications for the fields of economics, finance and management. Tourist corporations were analyzed owing to their growing economic impact. The estimations are initially consistent with long memory; so, they suggest that both stock market prices and online search trends deserve further exploration for modeling and forecasting. Significant differences owing to country and sector effects are also shown. Originality/value This research contributes in two different ways: it demonstrate the potential of a new tool for the analysis of relevant time series to monitor the behavior of firms and markets, and it suggests several theoretical pathways for further research in the specific topics of asymmetry of information and corporate transparency, proposing pertinent bridges between the two fields.

scholarly journals The Dynamics of Gold Prices, Gold Mining Stock Prices and Stock Market Prices Comovements

2009 ◽  
Vol 1 (1) ◽  
Author(s):  
Claire G. Gilmore ◽  
Ginette M. McManus ◽  
Rajneesh Sharma ◽  
Ahmet Tezel
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Gold Mining ◽  
Market Prices

scholarly journals Is Abnormally Large Volume a Clue?

2016 ◽  
Vol 8 (9) ◽  
pp. 226
Author(s):  
Tsung-Hsun Lu ◽  
Jun-De Lee
Keyword(s):  
Stock Market ◽  
Large Volume ◽  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Sensitive Analysis ◽  
Support Level ◽  
Out Of Sample ◽  
Sample Test ◽  
Abnormal Trading Volume

This paper investigates whether abnormal trading volume provides information about future movements in stock prices. Utilizing data from the Taiwan 50 Index from October 29, 2002 to December 31, 2013, the researchers employ trading volume rather than stock price to test the principles of resistance and support level employed by technical analysis. The empirical results suggest that abnormal trading volume provides profitable information for investors in the Taiwan stock market. An out-of-sample test and a sensitive analysis are conducted for the robustness of the results.

scholarly journals International Real Estate Review

2010 ◽  
Vol 13 (3) ◽  
pp. 282-322
Author(s):  
Massimo Biasin ◽  
◽  
Anna Grazia Quaranta ◽  
Keyword(s):  
Real Estate ◽  
Financial Risk ◽  
Market Price ◽  
Policy Implications ◽  
Share Price ◽  
Prudential Regulation ◽  
Market Prices ◽  
Capital Theory ◽  
Bankruptcy Risk ◽  
Almost All

In contrast to the US experience, most international (European) real estate investments trusts (REITs) are subject to prudential regulation. This paper investigates the effects of prudential regulation on capital structures and consequently, the REIT share values of major legal and market constraints (i.e. leverage limitations, market discount on net asset value (NAV), tax controls) that affect non-US REITs. Italian market data are used for an empirical analysis. Our hypothesis is that in a constrained environment, the effects on share price significantly depend on the adopted valuation perspective, i.e. if shares are valued by following a NAV or a financial approach. The logic for this hypothesis is that the two valuation methodologies perceive leverage and implied financial risk differently. In particular, we argue that NAV valuation techniques incentivise REITs to maximize leverage regardless of the financial theory which indicates a contrasting impact of debt on the market value of shares. Differences in financial risk perception could also partially explain market price discounts on NAVs.The empirical results seem to support these expectations. Almost all Italian REITs tend to increase debt ratios over time. NAV discounts are significantly related to leverage. The discount effect is largely attributable to NAV increases that result from rising debt levels. On the contrary, share market prices tend to be independent from leverage. The latter result may indicate that the classic capital theory applies and current debt ratios do not imply bankruptcy risk. The results have significant policy implications in terms of an optimal regulatory design.

scholarly journals The Dynamic Relationship between Crude Oil Prices and Stock Market Price Volatility in Nigeria: A Cointegrated VAR-GARCH Model

2019 ◽  
pp. 1-12
Author(s):  
David Adugh Kuhe
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Market Price ◽  
Garch Model ◽  
Price Volatility ◽  
Oil Prices ◽  
Market Prices ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Long Run

This study investigates the dynamic relationship between crude oil prices and stock market price volatility in Nigeria using cointegrated Vector Generalized Autoregressive conditional Heteroskedasticity (VAR-GARCH) model. The study utilizes monthly data on the study variables from January 2006 to April 2017 and employs Dickey-Fuller Generalized least squares unit root test, simple linear regression model, unrestricted vector autoregressive model, Granger causality test and standard GARCH model as methods of analysis. Results shows that the study variables are integrated of order one, no long-run stable relationship was found to exist between crude oil prices and stock market prices in Nigeria. Both crude oil prices and stock market prices were found to have positive and significant impact on each other indicating that an increase in crude oil prices will increase stock market prices and vice versa. Both crude oil prices and stock market prices were found to have predictive information on one another in the long-run. A one-way causality ran from crude oil prices to stock market prices suggesting that crude oil prices determine stock prices and are a driven force in Nigerian stock market. Results of GARCH (1,1) models show high persistence of shocks in the conditional variance of both returns. The conditional volatility of stock market price log return was found to be stable and predictable while that of crude oil price log return was found to be unstable and unpredictable, although a dependable and dynamic relationship between crude oil prices and stock market prices was found to exist. The study provides some policy recommendations.

Modeling Financial Bubbles and Market Crashes

2017 ◽  
Author(s):  
Didier Sornette
Keyword(s):  
Stock Market ◽  
Hazard Rate ◽  
Market Price ◽  
Imitative Behavior ◽  
Rational Model ◽  
Basic Principles ◽  
Market Prices ◽  
Speculative Bubbles ◽  
Financial Bubbles ◽  
Market Crashes

This chapter considers two versions of a rational model of speculative bubbles and stock market crashes. According to the first version, stock market prices are driven by the crash hazard that may increase sometimes due to the collective behavior of “noise traders.” The second version assumes the opposite: the crash hazard is driven by prices that may soar sometimes, again due to investors' speculative or imitative behavior. The chapter first provides an overview of what a model is before discussing the basic principles of model construction in finance. It then describes the basic ingredients of the two models of speculative bubbles and market crashes, along with the main properties of the risk-driven model. It also examines how imitation and herding drive the crash hazard rate and concludes with an analysis of the price-driven model, how imitation and herding drive the market price, and how the price return drives the crash hazard rate.

scholarly journals Capital Gains Overhang with a Dynamic Reference Point

2020 ◽  
Vol 66 (10) ◽  
pp. 4726-4745
Author(s):  
Christopher Riley ◽  
Barbara Summers ◽  
Darren Duxbury
Keyword(s):  
Stock Prices ◽  
Reference Point ◽  
Trading Volume ◽  
Reference Points ◽  
Capital Gains ◽  
Share Price ◽  
Purchase Price ◽  
Cross Sectional ◽  
Market Data ◽  
Salient Points

Financial models incorporating a reference point, such as the Capital Gains Overhang (CGO) model, typically assume it is fixed at the purchase price. Combining experimental and market data, this paper examines whether such models can be improved by incorporating reference-point adjustment. Using real stock prices over horizons from 6 months to 5 years, experimental evidence demonstrates that a number of salient points in the prior share price path are key determinants of the reference point, in addition to the purchase price. Market data testing is then undertaken by using the CGO model. We show that composite CGO variables, created by using a mix of salient points with weights determined in the experiment, have greater predictive power than the traditional CGO variable in both cross-sectional U.S. equity-return analysis and when analyzing the performance of double-sorted portfolios. In addition, future trading volume is more sensitive to changes in the composite CGO variables than to the traditional CGO, further emphasizing the importance of adjusting reference points. This paper was accepted by Tyler Shumway, Finance.

Sign in / Sign up

Export Citation Format

Share Document