Incorporating financial market volatility to improve forecasts of directional changes in Australian share market returns

被引:0
|
作者
Riza Erdugan
Nada Kulendran
Riccardo Natoli
机构
[1] Victoria University,Victoria University Business School
关键词
Binary regression model; Volatility estimates; Marginal probability; Forecast comparison; G17;
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学科分类号
摘要
This study examines whether incorporating volatility improves the forecast of directional changes in the returns of Australia’s banking, industrial and resource sectors. This study first estimates a benchmark non-volatility logit regression model and assesses it against four estimated volatility logit models measured by mean absolute deviation, standard deviation, return squared (U2) and range. An out-of-sample prediction performance, assessed by Brier’s QPS statistic and hit ratio, confirms that volatility improves the prediction of directional changes of returns. A simple trading strategy is utilized to provide practical improvement in investors’ market timing decisions.
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页码:417 / 445
页数:28
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