| Abstract: |
The paper uses daily data on financial stock index returns, tourism stock
sub-index returns, exchange rate returns and interest rate differences from 1
June 2001 – 28 February 2014 for Taiwan to construct a novel latent daily
tourism financial indicator, namely the Tourism Financial Conditions Index
(TFCI). The TFCI is an adaptation and extension of the widely-used Monetary
Conditions Index (MCI) and Financial Conditions Index (FCI) to tourism stock
data. However, the method of calculation of the daily TFCI is different from
existing methods of constructing the MCI and FCI in that the weights are
estimated empirically. Alternative versions of the TFCI are constructed,
depending on the appropriate model and method of estimation, namely Ordinary
Least Squares (OLS) or Quasi-Maximum Likelihood Estimation (QMLE) of
alternative conditional volatility models. Three univariate conditional
volatility models are considered, namely GARCH, GJR and EGARCH, in an attempt
to capture the inherent volatility in the daily tourism stock index returns.
The empirical findings show that TFCI is estimated quite accurately using the
estimated conditional mean of the tourism stock index returns, especially when
conditional volatility is incorporated in the overall specification. The new
daily TFCI is straightforward to use and interpret, and provides interesting
insights in predicting the current economic and financial environment for
tourism stock index returns, especially as it is based on straightforward
calculations and interpretations of publicly available information. |