Search results

The purpose of this paper is to examine, whether or not, the residuals of the market model (MM) are conditionally heteroscedastic; to examine, whether or not, there exists an intervalling effect in conditional heteroscedasticity in the residuals of the MM; to propose a simple data‐driven conditional capital asset pricing model (CAPM); and to examine the effect of conditional heteroscedasticity on the estimation of systematic risk.

Systematic risk coefficients (betas) are estimated at first using data of various frequencies from the Athens stock exchange without taking into account conditional heteroscedasticity. The same procedure is repeated, but this time taking into consideration conditional heteroscedasticity, which is found to exist. The results of the two approaches are compared.

Empirical evidence is provided for the existence of: conditional heteroscedasticity in MM residuals; a pronounced intervalling effect on autoregressive conditional heteroscedasticity (ARCH) in MM residuals; and generalized autoregressive conditional heteroscedasticity in mean type of conditional heteroscedasticity for the majority of cases where ARCH was present in MM residuals. These findings are conducive to a conditional CAPM, which takes into account the effect of conditional variance on expected returns, rather than the standard CAPM.

Better estimates of financial risk.

The intervalling effect in ARCH in the residuals of the MM is examined for the first time.

This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany and Japan) from January 2000 to December 2011 by examining the interbank interest rates from each market.

To the volatility of interest rates returns, the study used models of auto-regressive conditional heteroscedasticity, autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), exponential generalized autoregressive conditional heteroscedasticity (EGARCH), threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and periodic generalized autoregressive conditional heteroscedasticity (PGARCH), and a combination of these with autoregressive integrated moving average (ARIMA) models, checking which of these processes were more efficient in capturing volatility of interest rates of each of the sample countries.

The results suggest that for most markets, studied volatility is best modelled by asymmetric GARCH processes – in this case the EGARCH – demonstrating that bad news leads to a higher increase in the volatility of these markets than good news. In addition, the causes of increased volatility seem to be more associated with events occurring internally in each country, as changes in macroeconomic policies, than the overall external events.

It is expected that this study has contributed to a better understanding of the volatility of interest rates and the main factors affecting this market.

Este estudio analiza la volatilidad del mercado de renta fija de once países (Brasil, Rusia, India, China, Sudáfrica, Argentina, Chile, México, Estados Unidos, Alemania y Japón) de enero de 2000 a diciembre de 2011, mediante el examen de las tasas de interés interbancarias de cada mercado.

Para la volatilidad de los retornos de las tasas de interés, se utilizaron modelos de heteroscedasticidad condicional autorregresiva: ARCH, GARCH, EGARCH, TGARCH y PGARCH, y una combinación de estos con modelos ARIMA, comprobando cuáles de los procesos eran más eficientes para capturar la volatilidad de interés de cada uno de los países de la muestra.

Los resultados sugieren que para la mayoría de los mercados estudiados la volatilidad es mejor modelada por procesos GARCH asimétricos —en este caso el EGARCH— demostrando que las malas noticias conducen a un mayor incremento en la volatilidad de estos mercados que las buenas noticias. Además, las causas de una mayor volatilidad parecen estar más asociadas a eventos que ocurren internamente en cada país, como cambios en las políticas macroeconómicas, que los eventos externos generales.

Se espera que este estudio contribuya a un mejor entendimiento de la volatilidad de las tasas de interés y de los principales factores que afectan a este mercado.

Ingreso fijo, Volatilidad, Países emergentes, Modelos ARCH-GARCH

Artículo de investigación

This paper aims to test whether the latest global financial crisis propagated contagiously from the USA to the rest of the world.

If the reason of the propagation of a crisis is a normal time interdependence with the crisis origin country due to real linkages, the spread of crisis can be limited by implementing well-defined preventive policies. On the other hand, if a crisis propagates because of the speculative attacks or irrational behaviors, the “national policymakers will face difficulties in protecting their markets from such a crisis” (Kleimeier et al., 2003, p. 2). Therefore, separation of contagion and interdependence may provide crucial insights for policymakers to implement appropriate policies to prevent and/or stop the financial crisis. Hence, this paper compares the heteroscedasticity-corrected conditional correlations and dynamic conditional correlations in the tranquil and shock periods.

The findings were quite straightforward and consistent for both Forbes and Rigobon heteroscedasticity correction technique and dynamic conditional correlation (DCC) model. The Forbes and Rigobon technique failed to reject the null of no contagion for 25 countries in our data sample, while the DCC model failed to reject the null of no contagion for 21 countries. While heteroscedasticity-corrected correlation technique confirmed the presence of a contagion for six countries, the DCC technique confirmed the presence of a contagion for ten countries.

This study particularly investigates whether the subprime mortgage crisis spilled over contagiously to the rest of the world. To investigate whether there is a significant increase in the cross-market correlations between the crisis origin country, the USA and the rest of the world markets during the latest financial crisis, both heteroscedasticity-corrected correlation technique and DCC model are used.Therefore, this study possibly contributes well to the literature using a large country set and conducting the analysis from different angles for important properties.

This paper tries to empirically investigate whether the jump risk of Korean stock market may be statistically useful in explaining the Korean CDS (5Y) premium rate. This paper uses the jump-diffusion model with heteroscedasticity to estimate the conditional volatility of KOSPI from 7/2/2007 to 7/30/2010.

The total volatility of Korean stock market is decomposed into a heteroscedasticity and a jump risk by using the jump-diffusion model. The finding is that the jump risk in stead of heteroscedasticity in Korean stock market can explain the Korean CDS premium rate.

This study examines whether KOSPI200 intra-day return has jump risk and heteroscedasticity and we compare the estimation result of intra-day return and that of daily return. The sample covers from January 2, 2004 to July 31, 2014. We use 30-minute intervals for measuring KOSPI200 intra-day return. It seems this study finds the importance of the consideration of the intra-day data in Korean Stock Market. While some of the parameters of the daily returns for the jump are not significant, but those of intra-day returns are significant over the sample period. Also, the intra-day volatility has shown U-shaped or reverse J-shaped curve. In particular the pattern of intra-day volatility seems to come from the jump risk, which is interpreted as the information inflow in the market.

This study aims to investigate the response of green investments of emerging countries to own-market uncertainty, oil-market uncertainty and COVID-19 effect/geo-political risks (GPRs), using the tail risks of corresponding markets as measures of uncertainty.

This study employs Westerlund and Narayan (2015) (WN)-type distributed lag model that simultaneously accounts for persistence, endogeneity and conditional heteroscedasticity, within a single model framework. The tail risks are obtained using conditional standard deviation of the residuals from an asymmetric autoregressive moving average – ARMA(1,1) – generalized autoregressive conditional heteroscedasticity – GARCH(1,1) model framework with Gaussian innovation. For out-of-sample forecast evaluation, the study employs root mean square error (RMSE), and Clark and West (2007) (CW) test for pairwise comparison of nested models, under three forecast horizons; providing statistical justification for incorporating oil tail risks and COVID-19 effects or GPRs in the predictive model.

Green returns responds significantly to own-market uncertainty (mostly positively), oil-market uncertainty (mostly positively) as well as the COVID-19 effect (mostly negatively), with some evidence of hedging potential against uncertainties that are external to the green investments market. Also, incorporating external uncertainties improves the in-sample predictability and out-of-sample forecasts, and yields some economic gains.

This study contributes originally to the green market-uncertainty literature in four ways. First, it generates daily tail risks (a more realistic measure of uncertainty) for emerging countries’ green returns and global oil prices. Second, it employs WN-type distributed lag model that is well suited to account for conditional heteroscedasticity, endogeneity and persistence effects; which characterizes financial series. Third, it presents both in-sample predictability and out-of-sample forecast performances. Fourth, it provides the economic gains of incorporating own-market, oil-market and COVID-19 uncertainty.

Compares stock market returns behaviour for six stock markets in order to find out whether nonlinearities are a result of conditional heteroscedasticity or of previous performance. Uses LeBaron’s exponential generalized autoregressive conditional heteroscedasticity model to link conditional variance with first order correlation. Applies it to daily stock market indexes from 1986 to 1991 in Canada, France, Germany, Italy, Japan and the United Kingdom. Finds that the links exist in all the markets, with high autocorrelation during stable periods, and none under high volatility, for daily but not weekly returns. Concludes that nonsynchronous trading leads to an inverse relationship between volatility and autocorrelation.

With reference to the methodology of Prof Choudhry in his book “Tawhidi Epistemology and its Applications: Economics, Finance, Science, and Society” in 2014, in a different context, this study aims to present the conceptual fundamental of Islamic finance investment, where investment decisions are governed by Divine law and Islamic jurisprudence, followed by the empirical nature of real-world issues where investment decisions are governed by only financial indicators, using the Amman Stock Exchange as a case study.

As pointed out by Raderbauer (2011), research and industry initiatives mainly focus on environmental measures while ignoring the economic and socio-cultural dimension of sustainability. Recognizing the importance of a holistic understanding to define sustainable business practices for the accommodation industry. Financial markets are no exception; moral and values either coming from secular or religious understanding help to examine relationships between attitudes and actions, as well as differences in attitudes and actions related to the business’ characteristics. In business, ethical considerations apply to a broad list of virtues that companies, their managers and employees customarily seek to adopt. These include, but are not limited to, the encouragement of honesty, integrity and efficiency, as well as diversity and communication skills. One of the most common sources of ethical considerations is religion. In these cases, religious doctrine imparts a sense of applied ethics, where one considers what right conduct is, how to live a life pleasing to the Divine and how one should treat him/herself and others in accordance with those teachings. Again, as ethical considerations is a broad philosophical concept, it can apply to any situation where the person ponders the nature of right and wrong, how to recognize the difference and the meaning those conclusions carry for everyday life.

It can be concluded that the overall the quantitative and qualitative statistics showed that accommodation business manager’s decision has had a very little positive attitude toward sustainability and the implementation of sustainable business practices in ASE financial transaction, no matter what classification, type of business, ownership or size of business. Only rules and regulations govern the attitude and behavior when making financial transactions with profit is the main target. Moral indicators could not be seen throughout the analysis and test used to achieve objectives of the study at hand. One can imagine that the combined two factors together “Moral-Material” in implementing financial transactions will produce a more beneficial outcome. Achieving a material and holistic objective will produce an optimum situation, which can contribute positively to sustainable development.

Islamic alternatives to traditional investment tools have been driven by the fact that such tools do not conform to the Islamic general principles of the Shari’ah (Usmani, 2002). There has been a growing desire to have funds in which profits are not based on riba or interest, which is prohibited in Islam. Muslims deem that profit should come because of efforts; this is not the case in interest-dominated investments. In addition, there is a desire to have investment portfolios, which are morally purified. Thus, investments in companies that are not in compliance with the Shari’ah are not permitted and are eliminated from the portfolio. To ensure compliance with the forgoing condition, Shari’ah advisory boards whose role is mainly to give assurance that money is managed within the framework of Islamic laws govern Islamic mutual funds (Hassan, 2001; Hassan, 2002). On the other hand, dealing with the applied part, the paper will deal with a case study from Jordan (Amman Stock Exchange), where, code of ethics is issued by virtue of the provisions of Article 26 (e) of the Securities Law No. 23 of 1997. The Amman Stock Exchange operates as an exchange for the trading of securities. The company lists securities such as equities and bonds. Its activities include providing enterprises with a means of raising capital by listing on the exchange; encouraging an active market in listed securities based on the determination of prices and trading; providing facilities and equipment for trading the recoding of trades and publication of prices; monitoring and regulating market trading; and coordinating with the Jordan Securities Commission as necessary. The company’s activities also include ensuring compliance with the law, fair market and investor protection; setting out and enforcing a professional code of ethics.

Studies on the performance of agribusiness cooperatives in Brazil focus on economic and financial aspects. The purpose of this paper is to further delve into such studies by investigating which commonly measurable structural production factors (horizontal, vertical and lateral diversification; operating area; number of associates; and time in operation) have greater impacts on the financial performance of such cooperatives.

To achieve such a goal, a survey was conducted with a sampling pool divided by size (annual net revenues of US$ 50 million or higher), and the questionnaire was employed as a method of data collection. The sample was concentrated in the southern, south-eastern and mid-western regions of Brazil; classified by size; and deemed adequate after several adequacy tests.

The results were analysed using Spearman’s correlation, which showed that there were no significant correlations between the structural production factors considered in this study and the economic-financial performance of agricultural cooperatives, which leads to questions about the effectiveness of employing diversification strategies with a conjoint approach. Nonetheless, it was possible to identify several relationships not mentioned in the original hypotheses that might be addressed further in future studies.

The data obtained should be interpreted with caution because heteroscedasticity was detected. Although the cause could not be clearly identified, the presence of heteroscedasticity could mean that smaller and similar cooperatives present similar variation in their diversification and production base strategies.

This work sought to generate knowledge regarding operations management, which was achieved by demonstrating that production diversification in a dynamic and relevant economic sector, that is, agricultural cooperatives, is limited in terms of financial return when performed in an isolated mode. Hence, cooperatives’ production managers should take into account the totality of structural production factors during their planning activities.

The purpose of this paper is to deal with the different phases of volatility behavior and the dependence of the variability of the time series on its own past, models allowing for heteroscedasticity like autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), or regime‐switching models have been suggested by reserachers. Both types of models are widely used in practice.

Both regime‐switching models and GARCH are used in this paper to model and explain the behavior of crude oil prices in order to forecast their volatility. In regime‐switching models, the oil return volatility has a dynamic process whose mean is subject to shifts, which is governed by a two‐state first‐order Markov process.

The GARCH models are found to be very useful in modeling a unique stochastic process with conditional variance; regime‐switching models have the advantage of dividing the observed stochastic behavior of a time series into several separate phases with different underlying stochastic processes.

The regime‐switching models show similar goodness‐of‐fit result to GARCH modeling, while has the advantage of capturing major events affecting the oil market. Daily data of crude oil prices are used from NYMEX Crude Oil market for the period 13 February 2006 up to 21 July 2009.