Algorithms comparison on intraday index return prediction：evidence from China
We introduce the fading memory recursive least squares (FM-RLS) and rolling window ordinary least squares (RW-OLS) methods to predict CSI 300 intraday index return in Chinese stock market. Empirical results show that the performances are better than that of same sign method. The additional profit is...
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| Vydané v: | Applied economics letters Ročník 28; číslo 12; s. 995 - 999 |
|---|---|
| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Routledge
12.07.2021
Taylor & Francis LLC |
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| Abstract | We introduce the fading memory recursive least squares (FM-RLS) and rolling window ordinary least squares (RW-OLS) methods to predict CSI 300 intraday index return in Chinese stock market. Empirical results show that the performances are better than that of same sign method. The additional profit is mainly from two conflict signals, with one amplitude far greater than the other. |
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| AbstractList | We introduce the fading memory recursive least squares (FM-RLS) and rolling window ordinary least squares (RW-OLS) methods to predict CSI 300 intraday index return in Chinese stock market. Empirical results show that the performances are better than that of same sign method. The additional profit is mainly from two conflict signals, with one amplitude far greater than the other. |
| Author | Yuan, Xianghui Li, Xiang Yuan, Jin Xu, Hailun |
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| Cites_doi | 10.1016/j.jeconom.2006.05.023 10.1093/rfs/hhm014 10.1002/for.2417 10.1109/LSP.2008.2001559 10.1016/j.frl.2019.04.002 10.1016/j.econmod.2018.08.009 10.1080/14697688.2019.1571682 |
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| SubjectTerms | Economic analysis Economic theory Economics fading memory recursive least squares model Indexes Least squares model predictability Recursion rolling window ordinary least squares model same sign model Securities markets Stock exchanges |
| Title | Algorithms comparison on intraday index return prediction：evidence from China |
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