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Ichimoku cloud forecasting returns in the U.S.
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| Published in: | Global business and finance review volume:27; month:10; pages:17-26; 27(2022), 5 vom: Okt., Seite 17-26; year:2022; number:5 |
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| Authors and Corporations: | , |
| Other Authors: | Rayome, Dave [Author] |
| Type of Resource: | E-Book Component Part |
| Language: | English |
| published: |
2022
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| Series: |
Global business and finance review, 27(2022), 5 vom: Okt., Seite 17-26
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| Subjects: | |
| Source: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
| ISSN: | 2384-1648 |
| License: |
| Summary: | Purpose: We show that the Ichimoku Cloud can forecast stock returns in the U.S., Canada, Germany, and U.K. Design/methodology/approach: We use a regression of next months index return regressed on the Ichimoku Cloud entry signal for price crossing above 9 periods, 26 period, 52 periods and a crossover between 9 and 26 periods. The regression slope coefficient is recorded as the risk premium return. We also record the t-statistic and R2 of the model. We note that T-statistics of 1.65 are statistically significant. R2 is economically significant with a value above .5 percent. Findings: This is showing real-time application how the current Ichimoku Cloud signal can predict tomorrow’s stock return. The strongest results occur for lagged values one period in the U.S. which shows initial justification to using the Ichimoku Cloud. We additionally show the Ichimoku Cloud entry signals are strong in regards to T-statistics and R2 when benchmarked on each of the equity markets in the U.S., Canada, Germany, and U.K. Research limitation/implications: The model only considers technical indicators for forecasting risk premium and could benefit from additional indicators or macro fundamentals. Originality/value: This is the first paper to use Ichimoku Cloud in the risk premium forecast framework. |
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| ISSN: | 2384-1648 |
| DOI: | 10.17549/gbfr.2022.27.5.17 |
| Access: | Open Access |