News - Comment. Money & Markets. Stock Market - Tech companies' share prices racing ahead in market uncertainty

2020 ◽  
Vol 15 (10) ◽  
pp. 13-13
Author(s):  
C. Chambers
Keyword(s):  
Stock Market ◽  
Market Uncertainty ◽  
Money Markets ◽  
Share Prices

scholarly journals Investigating the Links between UK House Prices and Share Prices with Copulas

2021 ◽  
Author(s):  
Rakesh K. Bissoondeeal ◽  
Leonidas Tsiaras
Keyword(s):  
Stock Market ◽  
House Prices ◽  
National Level ◽  
Tail Dependence ◽  
Share Prices ◽  
Property Prices ◽  
Left Tail ◽  
The Uk ◽  
The Relationship ◽  
Shared Characteristic

AbstractWe investigate the nonlinear links between the housing and stock markets in the UK using copulas. Our empirical analysis is conducted at both the national and regional levels. We also examine how closely London house prices are linked to those in other parts of the UK. We find that (i) the dependence between the different markets exhibits significant time-variation, (ii) at the national level, the relationship between house prices and the stock market is characterised by left tail dependence, i.e., they are more likely to crash, rather than boom, together, (iii) although left tail dependence with the stock market is a prominent feature of some regions, it is by no means a universally shared characteristic, (iv) the dependence between property prices in London and other parts of the UK displays widespread regional variations.

scholarly journals Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 93
Author(s):  
Pavel Kotyza ◽  
Katarzyna Czech ◽  
Michał Wielechowski ◽  
Luboš Smutka ◽  
Petr Procházka
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Financial Market ◽  
Structural Breaks ◽  
Structural Changes ◽  
Global Financial Crisis ◽  
Market Uncertainty ◽  
Volatility Index ◽  
The Global Financial Crisis ◽  
The Relationship

Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial market uncertainty in a crisis time. In more detail, using sequential Bai–Perron tests for structural breaks, we check whether the global financial crisis and the COVID-19 pandemic have induced structural breaks in that relationship. Sugar prices are represented by the S&P GSCI Sugar Index, while the S&P 500 option-implied volatility index (VIX) is used to show stock market uncertainty. To investigate the changes in the relationship between sugar prices and stock market uncertainty, a regression model with a sequential Bai–Perron test for structural breaks is applied for the daily data from 2000–2020. We reveal the existence of two structural breaks in the analysed relationship. The first breakpoint was linked to the global financial crisis outbreak, and the second occurred in December 2011. Surprisingly, the COVID-19 pandemic has not induced the statistically significant structural change. Based on the regression model with Bai–Perron structural changes, we show that from 2000 until the beginning of the global financial crisis, the relationship between the sugar prices and the financial market uncertainty was insignificant. The global financial crisis led to a structural change in the relationship. Since August 2008, we observe a significant and negative relationship between the S&P GSCI Sugar Index and the S&P 500 option-implied volatility index (VIX). Sensitivity analysis conducted for the different financial market uncertainty measures, i.e., the S&P 500 Realized Volatility Index confirms our findings.

The Impact of Policy Uncertainty on Macro Variables – An SVAR-Based Empirical Analysis for EU Countries

2017 ◽  
Vol 68 (2) ◽  
Author(s):  
Dominik Kronen ◽  
Ansgar Belke
Keyword(s):  
Stock Market ◽  
Policy Uncertainty ◽  
Stock Market Volatility ◽  
Market Uncertainty ◽  
Vector Autoregressive ◽  
Svar Model ◽  
Negative Effect ◽  
Macro Variables ◽  
The Impact ◽  
Structural Vector

AbstractIn light of the rising political and economic uncertainty in Europe, we aim to provide a basic understanding of the impact of policy and stock market uncertainty on a set of macroeconomic variables such as production and investment. In this paper, we apply a structural vector autoregressive (SVAR) model to gain first insights that may help to identify avenues for further research. We find that stock market volatility shows a fairly consistently negative effect. However, the implications of policy uncertainty for Europe and the euro area in particular are not so straightforward.

scholarly journals Effect Of Macroeconomic Variables On Stock Market Returns For Four Emerging Economies: Brazil, Russia, India, And China

2011 ◽  
Vol 7 (3) ◽  
Author(s):  
Robert D. Gay, Jr.
Keyword(s):  
Stock Market ◽  
Emerging Economies ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Share Prices ◽  
Market Index ◽  
The Relationship ◽  
India And China

The relationship between share prices and macroeconomic variables is well documented for the United States and other major economies. However, what is the relationship between share prices and economic activity in emerging economies? The goal of this study is to investigate the time-series relationship between stock market index prices and the macroeconomic variables of exchange rate and oil price for Brazil, Russia, India, and China (BRIC) using the Box-Jenkins ARIMA model. Although no significant relationship was found between respective exchange rate and oil price on the stock market index prices of either BRIC country, this may be due to the influence other domestic and international macroeconomic factors on stock market returns, warranting further research. Also, there was no significant relationship found between present and past stock market returns, suggesting the markets of Brazil, Russia, India, and China exhibit the weak-form of market efficiency.

scholarly journals A Note on ‘What Drives Share Prices in the Middle East?’

2008 ◽  
Author(s):  
Panos Priftakis ◽  
M. Ishaq Bhatti
Keyword(s):  
Middle East ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Predictive Ability ◽  
Oil Prices ◽  
Unobserved Components ◽  
Market Prices ◽  
Share Prices ◽  
Unobserved Components Model

There are several hypotheses suggesting that some properties of oil prices make it interesting to focus on the predictive ability of oil prices for stock returns. This paper reviews some models recently used in the literature and selects the most suitable one for measuring the relationships and/or linkages of oil prices to the stock markets of the selected five oil producing countries in the Middle East. In particular, the paper uses two methodologies to test for the presence of a cointegrating relationship between the two variables and an unobserved components model to find a relationship between the two variables. The results rejects convincingly that there is no linkage between the prices of oil and the stock market prices in these oil-based economies.  

scholarly journals The effects of dividend policy to stock prices of listed companies in Vietnam stock market

2020 ◽  
Author(s):  
Thị Lam Hồ ◽  
Thùy Phương Trâm Hồ
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Dividend Policy ◽  
Corporate Value ◽  
Business Managers ◽  
Dividend Payment ◽  
Share Prices ◽  
Finance Management ◽  
The Impact

Dividend policy is one of the most important policies in corporate finance management. Understanding the impact of dividend policy on the distribution of profits, corporate value and thus on the stock price is important for business managers to make policies and for investors to make investment decisions. This study is conducted to evaluate the impact of dividend policy on share prices for companies listed on Vietnam’s stock market in the period from 2010 to 2018, based on the availability of continuous dividend payment data. Using the FGLS method with panel data of 100 companies listed on the HoSE and HNX, we find evidence of the impact of dividend policy on stock prices, supporting supports the bird in the hand and the signal detection theories. The findings of this study help to suggest a few recommendations for business managers and investors.

An Examination of the Effect of IT Investments on Firm Value: The Case of Y2K-Compliance Costs

2000 ◽  
Vol 14 (2) ◽  
pp. 95-108 ◽  
Author(s):  
Gopal V. Krishnan ◽  
Ram S. Sriram
Keyword(s):  
Information Technology ◽  
Stock Market ◽  
Firm Value ◽  
Market Value ◽  
Annual Reports ◽  
Equity Valuation ◽  
Compliance Costs ◽  
Book Value ◽  
It Investments ◽  
Share Prices

In this study, using the recent Y2-compliance expenditures as an example, we examine whether disclosures relating to investments in information technology (IT) were relevant to investors in assessing the market value of equity. We use a sample of 190 firms that disclosed estimates of total Y2K-compliance costs in their 1997 annual reports to examine the association between Y2K-compliance costs and share prices. We test the joint hypothesis that Y2K-compliance costs were relevant to equity valuation of firms that chose to become Y2K-compliant and that these costs were sufficiently reliable to be reflected in share prices. We find that estimates of Y2K-compliance costs were positively and significantly related to share prices after controlling for earnings, book value of equity, and other factors. We find that the stock market is not shortsighted, and consider investments in Y2K-remediation efforts a significant and value-increasing activity for the average firm.

Bombay Stock Exchange of India

2017 ◽  
pp. 181-212
Author(s):  
Sachin Kamley ◽  
Shailesh Jaloree ◽  
R. S. Thakur
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Efficient Market Hypothesis ◽  
Share Price ◽  
Share Prices ◽  
Election Results ◽  
Combination Of Methods ◽  
Prediction Techniques ◽  
A Company ◽  
Financial Issues

Stock market nature is considered to be dynamic and susceptible to quick changes because it depends on various factors like share price, fundamental variables like P/E ratio, dividend yield etc. election results, rumors etc. Now a day's prediction is an important process which determines the future worth of a company. The successful prediction brings motivation and awareness in stock community as well as economic growth of the country. In past various theories and methods like Efficient Market Hypothesis (EMH), Random Walk Theory, fundamental and technical analyses have been proposed. These methods or combination of methods have not got as much success even yet because these methods are very complex and time consuming and performed well on short data. These days stock market users mostly rely on intelligent trading system which would be help them to predict share prices based on various situations and conditions. Data mining is a broad area and also supports various business intelligence techniques. It has mastery to raise various financial issues like buying/selling security, bond analysis, contract analyses etc. in this study various prediction techniques like linear regression, multiple regression, association rule mining, clustering, neural network have been proposed and their significant performances will be compared by Bombay Stock Exchange (BSE) data.

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