157 resultados para volatility spillover


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This paper develops a model of exchange rate determination within an error correction framework. The intention is to identify both long and short term determinants that can be used to forecast the AUD/US exchange rate. The paper identifies a set of significant variables associated with exchange rate movements over a twenty year period from 1984 to 2004. Specifically, the overnight interest rate differential, Australia's foreign trade-weighted exposure to commodity prices as well as exchange rate volatility are variables identified that are able explain movements in the AUDIUS dollar relationship. An error correction model is subsequently constructed that incorporates an equilibrium correction term, a short-term interest rate differential variable, a commodity price variable and a proxy for exchange rate volatility. The model is then used to forecast out of sample and is found to dominate a naIve random walk model based on three different metrics.

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Purpose – The purpose of this paper is to provide a better understanding of the antecedents of organisational performance (OP), both financial and marketing, and the influence of holding a strategic market orientation (MO) where customer-base volatility is taken into account.

Design/methodology/approach –
A sample of 167 marketing organisations in Australia was surveyed to test the hypothesised model. Structural equation modelling was employed in the data analysis.

Findings – Use of the world wide web (Web) reported by organisations in this study indicates that there is still separate use of the Web and that it has yet to be fully integrated into the marketing strategy of many organisations. The study finds that traditional marketing effort mediates the relationship between holding a MO and OP in terms of financial indicators.

Research limitations/implications – A major limitation of this study is that it surveys organisations from many industries rather than selected industries. This tends to mask some of the possible outcomes.

Practical implications – The findings in this study suggest that traditional and online elements of marketing effort each mediate the influence of holding a MO on OP, but differently. Innovation culture is found to influence both marketing practice and marketing performance, directly. A single measure of environmental turbulence – customer-base turbulence or churn – negatively affects marketing performance, and ultimately financial performance.

Originality/value –
A major contribution of this study is the examination of use of the Web in marketing effort and how this usage influences financial and marketing performance.

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This paper aims at examining the correlation structure, co-integration relationship and volatility linkage between stock and bond market indices over a period from January 1994 to June 2004. This study uses Johansen Cointegratoin test, VECM-X model and GARCH (1,1) with MDH model to examine the existence of long-term relation and volatility linkage between stock and bond market. The findings shed some light on the existence of mean-reverting pattern of correlation across different economic environments.  Findings on co-movement of stock and bond indices suggest an equilibrium relationship with short-term error correction. While evidence from volatility linkage also suggests that bond market cannot provide a meaningful explanation for conditional volatility in stock market, therefore, rejecting the mixture of distribution hypothesis.

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The performance of different information criteria - namely Akaike, corrected Akaike (AICC), Schwarz-Bayesian (SBC), and Hannan-Quinn - is investigated so as to choose the optimal lag length in stable and unstable vector autoregressive (VAR) models both when autoregressive conditional heteroscedasticity (ARCH) is present and when it is not. The investigation covers both large and small sample sizes. The Monte Carlo simulation results show that SBC has relatively better performance in lag-choice accuracy in many situations. It is also generally the least sensitive to ARCH regardless of stability or instability of the VAR model, especially in large sample sizes. These appealing properties of SBC make it the optimal criterion for choosing lag length in many situations, especially in the case of financial data, which are usually characterized by occasional periods of high volatility. SBC also has the best forecasting abilities in the majority of situations in which we vary sample size, stability, variance structure (ARCH or not), and forecast horizon (one period or five). frequently, AICC also has good lag-choosing and forecasting properties. However, when ARCH is present, the five-period forecast performance of all criteria in all situations worsens.

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In this paper, we examine the relationship between oil price and the Fiji–US exchange rate using daily data for the period 2000–2006. We use the generalised autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) models to estimate the impact of oil price on the nominal exchange rate. We find that a rise in oil prices leads to an appreciation of the Fijian dollar vis-à-vis the US dollar.

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This paper considers 15 minute records of trading volume and traded prices coinciding with the reporting intervals required by the Commodity Futures Trading Commission. Records are extracted from trade records for market trade and also two way trade between market makers (CT1) and the general public (CT4) from January 1994 to June 2004. Futures price records are matched with S&P500 cash index price records. Simultaneous volatility models are specified and estimated to test trading volume to futures volatility lead/lag effects and also futures volatility to cash index volatility lead/lag effects. As we disaggregate from the market records to CT1 and CT4 records and further into year to year samples volume to futures volatility leading effects and also futures volatility to cash volatility leading effects dominate. The results raise important issues for risk management and dynamic hedging models employing intra-day trader data. A number of important issues for further analysis are also raised in this paper.

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In the recent years, a new wave of interest spurred the involvement of complexity in finance which might provide a guideline to understand the mechanism of financial markets, and researchers with different backgrounds have made increasing contributions introducing new techniques and methodologies. In this paper, Markov-switching multifractal models (MSM) are briefly reviewed and the multi-scaling properties of different financial data are analyzed by computing the scaling exponents by means of the generalized Hurst exponent H(q). In particular we have considered H(q) for price data, absolute returns and squared returns of different empirical financial time series. We have computed H(q) for the simulated data based on the MSM models with Binomial and Lognormal distributions of the volatility components. The results demonstrate the capacity of the multifractal (MF) models to capture the stylized facts in finance, and the ability of the generalized Hurst exponents approach to detect the scaling feature of financial time series.

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This paper considers the Samuelson hypothesis, which argues that the futures price volatility increases as the futures contract approaches its expiration. Utilizing intraday data from 20 futures markets in six futures exchanges, we find strong support for the Samuelson hypothesis in agricultural futures. However, the Samuelson hypothesis does not hold for other futures contracts. We also provide supporting evidence that the ‘negative covariance’ hypothesis is the key factor for the empirical support of the Samuelson hypothesis. In addition, our findings remain largely unaltered even after we control for seasonality and liquidity effects.

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This paper considers 15 minute records of trading volume and traded prices coinciding with the reporting intervals required by the Commodity Futures Trading Commission. Records are extracted from trade records for two way trade between market makers (CTI1) and the general public (CTI4) from January 1994 to June 2004. Futures price records are matched with S&P500 cash index price records. Simultaneous volatility models are specified and estimated to test trading volume to futures volatility lead/lag effects and also futures volatility to cash index volatility lead/lag effects. There is evidence that existing theoretical models of the general public trading behaviour do not explain such behaviour in these very actively traded markets. These effects can depend more on market conditions than what is suggested in theoretical models.

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According to Cheung, common challenges such as currency depreciation, share market volatility and export competition brought by the financial crisis helped to accelerate economic integration between Hong Kong, Taiwan and mainland China. According to Cheung, these mechanisms pull the island in a different direction - namely, the internationalisation of Taiwan.

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The continuous debate between the radical and the conservative approaches on which one is more suitable for a successful economic transition seems to be in favour of the latter. With the recent upswing in the property market in Hainan, the review of the 1990s property cycle in Hainan is linked with economic transition in China. A case study approach is used to establish the importance of the 1990s Hainan property cycle to the formation process of the Chinese property market system. The analytical framework is an integration of the theories of property cycles and economic transition, using the conceptual model of typical commercial property markets modified according to the historical settings in Hainan. It is found that the 1990s Hainan property cycle is unique in that the economic transition has been the key driving force. The structural imbalance caused by the equally imbalanced reform process in different sectors in Hainan has been proved an unsuccessful practice. By and large, the 1990s cycle in Hainan lasted for about 10 years and was state-driven. It was considered an experiment conducted by the state in testing the radical approach of economic transition in the property and urban land sectors. It is suggested that current knowledge of emerging commercial property markets, especially their cyclical behaviour, is limited at both theoretical and empirical levels. Evidence from the past 15 years seems to suggest that the structural and investment imbalance in the economic transition was the main cause of the high volatility in the Hainan property market in the 1990s. The emergence of a commercial property market seems to require choosing the right places to start reform with great caution on investment structure and the fundame ntals of the real economy. Eventually, it is essential to adopt a systematic view to assess and to make decision in the process of emergence of property cycles, based on the basic demand and supply patterns in a city’s transitional economy.

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This article examines the volatility in Fiji’s foreign reserves—in particular, whether shocks have an asymmetrical effect on volatility and whether shocks have a  persistent impact on volatility. In the pre-coup period (1975–86), shocks had a temporary effect on volatility; in the coup period (1987–2006), shocks had a more lasting impact. In the pre-coup period, negative shocks contributed more to  foreign reserves volatility than positive shocks; but in the period including the  coups, positive shocks increased the volatility of foreign reserves more than  negative shocks. The reasons for, and the policy implications of, this  asymmetrical behaviour are explored.

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In this article we examine several hypotheses relating to output and inflation dynamics in China. The hypotheses tests are based on the exponential  generalised autoregressive conditional heteroskedasticity (EGARCH) model of Nelson [Nelson, D. (1991). Conditional heteroskedasticity in asset return: A new approach, Econometrica, 59, 347–370]. Our findings suggest that Chinese output–inflation behaviour is consistent with the hypothesis that increased inflation uncertainty lowers average inflation; the hypothesis that inflation volatility reduces economic growth and the hypothesis that higher output volatility increases economic growth. However, we find no support for the hypothesis that higher output volatility increases the average inflation rate.

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Approximately 70% of Australian Teaching and Learning Centres have been restructured and/or have undergone leadership changes in the last three years. The volatility of this environment reflects the number of significant challenges faced by Teaching and Learning Centres. In determining what makes Centres successful, the issues that are likely to impact on their ability to succeed were examined. It emerged that a myriad of factors influence whether or not a Centre was recognised as being an integral and valued part of the university’s teaching and learning community – a hallmark of having reached maturity. This paper identifies four factors as being critical to the ability of Centres to succeed, noting that a combination of other factors, appropriate to each unique context, must also be in place in order for Centres to maximise their value.