An empirical study on effect of financial accounting indicators towards stock market price volatility

Author(s):  
S. Umamaheswari ◽  
C.K. Suresh ◽  
Shilpa Sampathkumar
Author(s):  
David Adugh Kuhe

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.


2020 ◽  
Vol 9 (3) ◽  
pp. 107-121
Author(s):  
Roberto Ercegovac ◽  
Mario Pečarić ◽  
Ivica Klinac

AbstractCurrent research, especially after the financial crisis, highlights different key determinants of high risk bank profiles. The main aim of this paper is to test, through an empirical model, the impact of various determinants of bank business models on the bank risk with the purpose of enabling early identification of signals of risk and timely application of prudential measures. There are two basic business models for banks: market-oriented wholesale bank business model and client-oriented bank business model. In the wholesale model, a significant share of the assets is comprised of securities in the trade portfolio, the bank is strongly involved in the international financial markets, while on the income side of the bank profile, a large part is related to non-interest income. In the client related business model, classical banking is dominant, which is visible in the high share of loan-related assets, a larger share of self-financing and a larger share of income from interest-operational income in the total income structure of the bank. In the panel analysis of the empirical data, as an indicator of the bank risk profile, the stock market price to stock market price volatility ratio was used with the presumption that the market price and its volatility, with sufficiently liquid shares listed on public stock exchanges, is representative of bank risk. The analysis is conducted on a homogenous example of 20 European banks in the period 2002-2017. Following the econometric analysis, the conclusion is that banks in which business model wholesale characteristics are dominant are more exposed to business risk in periods of market shocks and, as such, represent a danger for the long-term stability of the financial sector.


Author(s):  
Thomas Plieger ◽  
Thomas Grünhage ◽  
Éilish Duke ◽  
Martin Reuter

Abstract. Gender and personality traits influence risk proneness in the context of financial decisions. However, most studies on this topic have relied on either self-report data or on artificial measures of financial risk-taking behavior. Our study aimed to identify relevant trading behaviors and personal characteristics related to trading success. N = 108 Caucasians took part in a three-week stock market simulation paradigm, in which they traded shares of eight fictional companies that differed in issue price, volatility, and outcome. Participants also completed questionnaires measuring personality, risk-taking behavior, and life stress. Our model showed that being male and scoring high on self-directedness led to more risky financial behavior, which in turn positively predicted success in the stock market simulation. The total model explained 39% of the variance in trading success, indicating a role for other factors in influencing trading behavior. Future studies should try to enrich our model to get a more accurate impression of the associations between individual characteristics and financially successful behavior in context of stock trading.


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