The Impact of Regulatory Standards, Interest Rates and Trading Volume on Volatility Transmission between Cross-Listed European Equities

2009 ◽  
Vol 10 (1) ◽  
pp. 89-105
Author(s):  
Koulakiotis Dasilas ◽  
Tolikas Molyneux
Keyword(s):  
Interest Rates ◽  
Stock Markets ◽  
Trading Volume ◽  
Positive Impact ◽  
Stock Exchanges ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
Regulatory Standards ◽  
European Stock Markets ◽  
The Impact

This paper investigates the relationship between volatility transmission and stock market regulatory structures, interest rates and trading volume for European securities which are cross-listed on stock exchanges of higher, lower or similar regulatory standards compared to their home stock markets. The empirical results suggested that the regulatory environment has a significant impact on volatility spillovers and the level of interest rates and trading volume have a positive impact on the magnitude and persistence of these volatility spillovers. These findings have potentially important implications for both regulators and investors who are concerned with the effectiveness of legislation aiming to harmonise the European stock markets and the effects of volatility transmission on investment positions across European stock markets.

scholarly journals How US wages effect post-socialist European stock markets: an empirical study

2018 ◽  
Vol 7 (4) ◽  
pp. 179 ◽  
Author(s):  
Deniz Ilalan
Keyword(s):  
Monetary Policy ◽  
Empirical Study ◽  
Stock Markets ◽  
Stock Exchanges ◽  
Hourly Wage ◽  
Fed Funds Rate ◽  
Average Hourly Wage ◽  
Wage Increases ◽  
European Stock Markets ◽  
The Impact

Following the famous tapering speech of Bernanke on 2013, US non-farm payroll data became the leading indicator for the monetary policy of Fed. After midst of 2014 Fed shifted its attention to average hourly wage increases which was regarded as the determinant of inflation. As inflation is closely linked with possible increments of Fed funds rate, investors began to follow US wages more closely. We investigate the impact of US wages especially through concentrating on some Post-Socialist European stock markets. As US wages are found to Granger cause these stock exchanges, interestingly with domestic wages, a similar causation relation could not be achieved. This brings out the question whether wages are indeed an indicator for stock markets or not. 

scholarly journals Lessons for Euro markets from the first wave of COVID-19

2021 ◽  
Vol 18 (1) ◽  
pp. 285-298
Author(s):  
Costas Siriopoulos ◽  
Argyro Svingou ◽  
Jagadish Dandu
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Impulse Response Function ◽  
Decomposition Methods ◽  
Var Model ◽  
Stock Exchanges ◽  
Panel Var ◽  
Chinese Stock Market ◽  
European Stock Markets ◽  
The Impact

Although the coronavirus pandemic hit Europe in the early days of 2020, European stock markets had signaled fluctuations in the days before. This paper assesses the observed volatility on European stock exchanges and searches for its sources during the first four months of 2020. To investigate the issue, a panel VAR model is adopted, and the generalized impulse response function and the variance decomposition methods are used. The estimations show that about 34% of the volatility in European stock markets is due to the Chinese stock market, while 7% is due to international uncertainty, as measured by VIX. The impact of pandemic cases and deaths on European stock markets is negligible, below 1%. This means that the European stock market faced two risk elements: the first is the transmission volatility from the Chinese stock market, and the second is the international uncertainty. The findings also support the view that COVID-19 is more like a systematic risk.

scholarly journals Volatility Spillovers Arising from the Financialization of Commodities

2018 ◽  
Vol 11 (4) ◽  
pp. 72 ◽  
Author(s):  
Wing Chan ◽  
Bryce Shelton ◽  
Yan Wu
Keyword(s):  
Commodity Prices ◽  
Spillover Effects ◽  
Realized Volatility ◽  
Commodity Markets ◽  
Exchange Traded Funds ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
The Difference ◽  
Index Investment ◽  
The Impact

This paper examines whether the proliferation of new index products, such as commodity-tracking exchange-traded funds (ETFs), amplified the volatility transmission channel introduced by financialization. This paper focuses on the volatility spillover effects among crude oil, metals, agriculture, and non-energy commodity markets. The results show financialization has an impact on the volatility of commodity prices, predominantly for non-energy commodities. However, the impact on volatility is not symmetric across all commodities. The analysis of index investment and investors’ positions in futures markets shows that, when a relationship exists, it is generally negatively correlated with the realized volatility of non-energy commodities. Using realized volatility in the difference-in-difference model provides estimates that are inconsistent with other findings that non-energy commodities, traded as a part of indices, have experienced higher volatility. The results are similar to the index investment and futures market analysis, where increased participation by investors through new investment products has put download pressure on realized volatility.

IMPACT OF DEVELOPMENT EXCHANGE CENTRE (DEC) MICROCREDIT PROGRAMME ON CROP OUTPUT AND STANDARD OF LIVING AMONG WOMEN FARMERS IN KADUNA STATE, NIGERIA

2021 ◽  
Vol 5 (1) ◽  
pp. 65-75
Author(s):  
B. D. Adamu ◽  
H. Y. Michael
Keyword(s):  
Interest Rates ◽  
Positive Impact ◽  
Women Farmers ◽  
Standard Of Living ◽  
Farm Size ◽  
Primary Data ◽  
Living Standard ◽  
Farming Communities ◽  
Multi Stage ◽  
The Impact

This study examined the impact of Development Exchange Centre microcredit programme on crops output and standard of living among women farmers in Kaduna State, Nigeria. A multi-stage sampling method was employed to select 420 respondents. Primary data were collected through the use of questionnaires and were subjected to both descriptive and inferential statistics. The mean farming experience was 22 years for DEC participants and 19 years for non-DEC participants while mean farm size for participants and non-DEC participants was 2.0 ha. Determinant of standard of living on programme participants, the study concludes that, age (0.0405, P<0.01), farm size (47.510, P<0.01), education, credit (0.6031, P< 0.01) and extension contact (0.002, P< 0.01), had direct relationship with the standard of living of programme  participants, This implies DEC, increase the standard of living of  programme participants in Kaduna State. Determinant of crops output of programme participants shows that, farm size (0.046, P<0.01), credit (0.821, P< 0.01), extension contact (0.0542, P< 0.05). F-chow statistics shows that DEC microcredit had positive impact on crops output of programme participants. Z – statistics also indicated positive impact on living standard of the participants. It was recommended that, DEC microcredit organization should increase the amount of loan disbursement to N100, 000, so as to increase participation; extend the repayment period, lowered interest rates and extend the programme to other farming communities in Kaduna State, there by improving the standard of living of women farmers in the state

HOW DOES BLOCKCHAIN PARTICIPATION AFFECT THE CRYPTOCURRENCY MARKET?

2020 ◽  
pp. 1-24
Author(s):  
YI LI ◽  
WEI ZHANG ◽  
PENGFEI WANG
Keyword(s):  
Trading Volume ◽  
Positive Impact ◽  
Granger Causality Test ◽  
Realized Volatility ◽  
Var Model ◽  
Alternative Measure ◽  
Theoretical Studies ◽  
Causality Test ◽  
Vector Autoregressive ◽  
The Impact

Taking the unique advantage of the cryptocurrency market setting, this paper examines the relationships between blockchain participation and returns, trading volume and realized volatility of main cryptocurrencies (i.e., Bitcoin, Ethereum and Litecoin). Dissimilar to previous theoretical studies that model the influencing factors on participation, we employ the number of unique from addresses 1 as the proxy for cryptocurrency investors’ blockchain participation and further explore the impact of such participation. By using vector autoregressive (VAR) model, we find that the blockchain participation has a significant and positive impact on the next day’s trading volume and realized volatility for the main cryptocurrencies. Our results are robust to the Granger causality test and alternative measure for blockchain participation.

The Effects of Institutional Corporate Social Responsibility on Bank Loans

2016 ◽  
Vol 57 (7) ◽  
pp. 1407-1439 ◽  
Author(s):  
Bill Francis ◽  
Pamela Harper ◽  
Shyam Kumar
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Interest Rates ◽  
Positive Impact ◽  
Bank Loans ◽  
Institutional Csr ◽  
Loan Spreads ◽  
Technical Csr ◽  
Corporate Social ◽  
The Impact

The authors study the impact of institutional corporate social responsibility (CSR)—defined as CSR targeted at a borrowing firm’s secondary stakeholders—on bank loans. Findings suggest that higher levels of institutional CSR are associated with lower levels of interest rates and loan spreads. In addition, institutional CSR also tempers the positive impact of loan maturity and firm leverage on interest rates and loan spread. These effects were strongest among firms that demonstrated sustained performance, rather than among firms that showed mixed performance in terms of their secondary stakeholder-related activities. This study indicates institutional CSR is valued by stakeholders for its risk mitigating and transaction cost reducing effects independent of technical CSR, defined as CSR targeted at primary stakeholders.

scholarly journals THE VOLATILITY TRANSMISSION OF MAIN GLOBAL STOCK'S RETURN TO INDONESIA

2017 ◽  
Vol 20 (2) ◽  
pp. 229-256
Author(s):  
Linda Karlina Sari ◽  
Noer Azam Achsani ◽  
Bagus Sartono
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Stock Return ◽  
Global Financial Crisis ◽  
Symmetric Model ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Volatility Transmission ◽  
The Impact

Stock return volatility is a very interesting phenomenon because of its impact on global financial markets. For instance, an adverse shocks in one country’s market can be transmitted to other countries’ market through a particular mechanism of transmission, causing the related markets to experience financial instability as well (Liu et al., 1998). This paper aims to determine the best model to describe the volatility of stock returns, to identify asymmetric effect of such volatility, as well as to explore the transmission of stocks return volatilities in seven countries to Indonesia’s stock market over the period 1990-2016, on a daily basis. Modeling of stock return volatility uses symmetric and asymmetric GARCH, while analysis of stock return volatility transmission utilizes Vector Autoregressive system. This study found that the asymmetric model of GARCH, resulted from fitting the right model for all seven stock markets, provides a better estimation in portraying stock return volatility than symmetric model. Moreover, the model can reveal the presence of asymmetric effects on those seven stock markets. Other finding shows that Hong Kong and Singapore markets play dominant roles in influencing volatility return of Indonesia’s stock market. In addition, the degree of interdependence between Indonesia’s and foreign stock market increased substantially after the 2007 global financial crisis, as indicated by a drastic increase of the impact of stock return volatilities in the US and UK market on the volatility of Indonesia’s stock return.

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