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| Comparing Inflation Forecasts Using an $\varepsilon$-wavelet Twin Support Vector Regression |
| Yafen Ye, Yuanhai Shao, Weijie Chen |
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Abstract Different from the RBF kernel and the polynomial kernel, the wavelet
kernel can approach any curve in quadratic continuous integral
space. Based on this advantage of wavelet kernel, we propose wavelet
kernel $\varepsilon$-twin Support Vector Regression
($\varepsilon$-WTSVR) in this paper to predict inflation for US,
Euro and Canada. Compared with forecasts generated from the Vector
Autoregression (VAR) model, our $\varepsilon$-WTSVR derives the
lower Root Mean Squared Error (RMSE), which indicates that our
$\varepsilon$-WTSVR is an efficient method for the inflation
forecasts.
DOI: 10.12733/jics20101681
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