Investigating other leading indicators influencing Australian domestic tourism demand.

In the tourism demand literature, much of the research focuses on income and price variables as demand determinants for travel. Nevertheless, the literature has neglected other possible indicators such as consumers' perceptions of the future course of the economy, household debt and the number of hours worked in paid jobs. In fact, several studies found that these indicators could influence consumers in making decisions to travel. In this paper, we intend to examine whether there are other indicators that can influence future Australian domestic tourism demand. The research employs panel data with a total of 252 observations. For the dependent variables, the disaggregated data for domestic visitor nights will be used, namely the visitor nights by holiday-makers (HOL), business travellers (BUS) and visitors who visited friends and relatives (VFR). In terms of the independent variables, we employ the following proxy variables for this research: (1) the consumer sentiment index; (2) business confidence index; (3) interest repayments for household debt; and (4) average actual worked hours in paid jobs. The econometric model used in this study is a panel three-stage least square (3SLS) model. The empirical results reveal several points. First, it is found that the consumer sentiment index has significant impacts on VFR but not on holiday tourism. Furthermore, the business confidence index has no influence on business tourism demand. The study also finds that an increase in household debt could encourage more Australians to travel domestically, indicating that Australians may consider increasing debt as their confidence to spend increases. Lastly, working hours have a statistically significant effect in the case of holiday tourism data.Consumers sentiment index, Inflation expectations, Household debt, Working hours, Australian domestic tourism demand Acknowledgements: We are grateful to the School of Accounting, Finance and Economics, Faculty of Business and Law, Edith Cowan University for providing travel funding to present this paper in the 18th World IMACS/MODSIM Congress. The second author would like to thank Sustainable Tourism Cooperative Research Centre (STCRC) for financial supports to produce this paper as part of her PhD thesis.

Stock Returns and Equity Premium Evidence Using Dividend Price Ratios and Dividend Yields in Malaysia

The empirical findings of Goyal and Welch (2003) and Cochrane (2006) suggested that dividend yields and dividend ratios are robust predictors of annual stock returns and annual equity premia. However, Goyal and Welch (2003) asserted that many researchers considered dividend yields to be a good predictor for the equity premium before the 1990s but not after the 1990s. We apply these models to the Malaysian market. Our general findings suggest that the in-sample performances of the KLCI Malaysian datasets present similar results to those predicted by Goyal and Welch (2003, 2006). Meanwhile, the Mincer-Zarnowitz (1969) regression forecast tests for out of sample performances illustrate poor predictability of stock returns and equity premiums using both dividend price ratios and dividend yields. Cochrane (2006) suggested that if stock returns and dividend growth are not predictable, then price growth must be forecastable to bring the dividend yields back to equilibrium after any shock given that the dividend yields are stationary. We find that the growth of dividends is predictable using data deflated by changes in the consumer price index. Thus, the overall results suggest that both dividend price ratio and dividend yield models have significant effects though the dividend yield model is a superior predictor of stock returns and equity premiums in the Malaysian context.Dividend yields, Dividend price ratios, Stock returns, Equity premium, Asian financial crisis 1997

Modelling Australian Domestic Tourism Demand: A Panel Data Approach.

This study estimates the income and tourism price elasticities of demand for Australian domestic tourism using a panel data approach. Given that about 76% of total tourism revenue in Australia is generated by domestic tourism, it is worthwhile examining whether changes in Australian households income and the prices of domestic travel can influence the demand for domestic travel. The research employs a panel data approach. This method has been widely employed in the literature on international tourism demand, but thus far, has not appeared in the context of the domestic tourism demand literature. The model used for this study is panel Three-Stage Least Square (3SLS). The data employed are based on quarterly time-series from 1999 to 2007 across seven Australian States. The paper reveals some notable results. First, the income elasticity for domestic visiting friends and relatives (VFR) trips in Australia is negative, implying that Australian households will not choose to travel domestically when there is an increase in household income. Second, the national income variables are positively correlated with domestic business tourism demand, indicating that the demand is strongly responsive to changes in Australia s economic conditions. Third, an increase in the current prices of domestic travel can cause the demand for domestic trips to fall in the next one or two quarters ahead. Finally, the coefficients for lagged dependent variables are negative, indicating perhaps, that trips are made on a periodic basis.Domestic tourism demand, Australia, Panel data Acknowledgements: We are grateful to the School of Accounting, Finance and Economics, Faculty of Business and Law, Edith Cowan University for providing travel funding to present this paper in the 18th World IMACS/MODSIM Congress. The second author would like to thank Sustainable Tourism Cooperative Research Centre (STCRC) for financial supports to produce this paper as part of her PhD thesis.

Conditional Beta Capital Asset Pricing Model (CAPM) and Duration Dependence Tests

This paper uses a sample of 50 companies continuously listed on Main Board of Bursa Malaysia from January 1994 until December 2001 and uses duration dependence tests whilst applying two asset pricing models based on the CAPM; the two Factor Model developed by Fama and French (F&F)(1998) and Ferson, Sarkissian and Simin's (FSS) (2008) conditional beta model applied to estimate the conditional beta of CAPM as to generate the positive and negative abnormal returns. The findings suggest that both the Log Logistic and Weibull hazard models seem to support the existence of negative duration dependence for both positive and negative runs of abnormal returns, consistent with the presence of bubbles theory as predicted by McQueen and Thorley (1994). The negative runs of abnormal returns for both the F&F and FSS models show that more than 80% of the sample seems to support the existence of negative duration dependence using both hazard models. Meanwhile the positive runs show that not more than 80% of the sample rejects the null hypothesis based on LR tests of the absence of duration dependence. Therefore, the analysis and results suggest that the negative runs of abnormal returns are consistent for both hazard models.Duration dependence, Two factor models, Rational bubbles, Log logistic and Weibull hazard models

Is the Australian Forex Market Efficient? A Test of the Forward Rate Unbiasness Hypothesis

This paper features a test of the forward rate unbiasedness hypothesis (FRUH), using the Australian dollar with the United States and Japanese currencies using daily frequencies. We evaluate the FRUH on the 1-month forward rate, for both currencies, and the 3-month and 6-month forwards rates for the US dollar only. We adopt a cointegration framework for assessing the FRUH applying a cointegrating VAR model involving Johansen's ML approach. Our results indicate that in all cases the spot and forward rates are integrated of order 1. Furthermore there is evidence of cointegration and in all but one case the cointegrating vector is (1, -1). The error correction term in all cases is statistically significant and has the correct sign.Interest parity, Exchange rates, Market efficiency, Cointegration

Credit Risk and Real Capital: An Examination of Swiss Banking Sector Default Risk Using CVaR

The global financial crisis (GFC) has placed the creditworthiness of banks under intense scrutiny. In particular, capital adequacy has been called into question. Current capital requirements make no allowance for capital erosion caused by movements in the market value of assets. This paper examines default probabilities of Swiss banks under extreme conditions using structural modeling techniques. Conditional Value at Risk (CVaR) and conditional probability of default (CPD) techniques are used to measure capital erosion. Significant increase in probability of default (PD) is found during the GFC period. The market asset value based approach indicates a much higher PD than external ratings indicate. Capital adequacy recommendations are formulated which distinguish between real and nominal capital based on asset fluctuations.Real capital; Financial crisis; Conditional value at risk; Credit risk; Banks; Probability of default; Capital adequacy

Hedging with interest rate caps compared with a policy of maintaining a balanced portfolio of loans (PLA) and averaging the borrowing costs

This paper compares two different strategies for managing interest rate exposure. One involves maintaining a borrowing portfolio using short and long term debt lines in order to maintain an average borrowing cost. The second involves using interest rate caps to manage exposure to interest rate risk. The two strategies are compared using a set of daily quarterly rates from three months out to 10 years (120 months) of BBSW zero rates, par rates and forward rates from June 2000 to September 2006. The data set of implied volatilities (Appendix I used for interest cap quoting and pricing) consists of volatilities for 1, 2, 3, 4, 5, 7 and 10 year maturities; the data set is made up of daily closing mid-quotes for the period. We examine whether interest rate caps would be a better alternative for minimising interest rate risk as compared to a structure that combines a portfolio of rolling short-term debt with one of rolling long-term debt lines. Using principal component analysis (PCA) we explore the behaviour of, and the number of factors driving volatilities. As caps are quoted in terms of implied volatilities, and we know BlackÃŒs (1976) model is very sensitive to changes in these volatilities. We use PCA to examine the factors driving cap price volatilities. We explore the best way of using caps to manage interest rate risk. This should help us understand what factors affect cap prices and how many factors might be used in the interest rate models used to price interest rate derivatives such as caps and floors. We use Sharpe ratios to assess the relative borrowing costs of different strategies in relation to the volatility of their outcomes. We examine whether interest rate caps would be a more efficient method for minimising interest rate risk as compared to the a portfolio of loans.Hedging with interest rate caps, Vegas, Sharpe ratios, Principle components analysis

Industry Market Value at Risk in Australia

Value at Risk (VaR) is an important issue for banks since its adoption as a primary risk metric in the Basel Accords and the requirement that it is calculated on a daily basis. Relative industry risk measurement is also very important to Banks in their management of risk, such as for setting risk concentration limits and developing investment and credit policy. This paper examines market Value at Risk (VaR) and Conditional VaR (CVaR) in Australia from an industry perspective using a set of Australian industries. VaR and CVaR are compared between these industries over time, and a variety of metrics are used including diversified and undiversified VaR, as well as parametric and nonparametric CVaR methods. There has been no prior investigation of industry based VaR metrics in Australia to the authorsÌ knowledge. The relative riskiness of different industry sectors is examined and using diversified VaR, the study .nds the highest risk is in the Technology Sectors, whilst the lowest risk is found in the Finance and Utilities Sectors. Composite riskiness is also explored and the existence of correlation between industry risk rankings over time is found to depend on the number of years of data used. There is evidence of rank correlation over time using a 7 year window approach, but not when using 1 year data tranches. This highlights the importance of using both short and long time frames in order to cover different economic cycles as well as consider current conditions. It is important to note that there is found to be no significant difference between diversified and undiversified industry VaR rankings, or between parametric and nonparametric CVaR approaches. This means that bankers can be reasonably confident of the robustness of any one of these metrics when calculating and applying them, not only for the purposes of Basel compliance, but also for the determination of relative industry risk.Conditional value at risk (CVaR), Industry risk, Basel compliance

CVaR and Credit Risk Measurement

The link between credit risk and the current financial crisis accentuates the importance of measuring and predicting extreme credit risk. Conditional Value at Risk (CVaR) has become an increasingly popular method for measuring extreme market risk. We apply these CVaR techniques to the measurement of credit risk and compare the probability of default among Australian sectors prior to and during the financial crisis. An in depth understanding of sectoral risk is vital to Banks to ensure that there is not an overconcentration of credit risk in any sector. This paper demonstrates how CVaR methodology can be applied in different economic circumstances and provides Australian Banks with important insights into extreme sectoral credit risk leading up to and during the financial crisis.Conditional Value at Risk (CVaR), Banks, Structural modelling, Probability of default (PD)

The Fluctuating Default Risk of Australian Banks

Australian banks are widely considered to have fared far better during the Global Financial Crisis (GFC) than their global counterparts, continuing to display solid earnings, good capitalisation and strong credit ratings. Nonetheless, Australian banks experienced significant deterioration in the market values of assets. We use the KMV/Merton structural methodology, which incorporates market asset values, to examine default probabilities of Australian banks. We also modify the model to incorporate conditional probability of default which measures extreme credit risk. We find that, during the GFC, based on extreme asset value fluctuations, Australian bank default probabilities fare only slightly better than their global counterparts.Financial crisis; Credit risk; Banks; Default; Capital adequacy