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Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators. (2019). Gabbouj, Moncef ; Kanniainen, Juho ; Iosifidis, Alexandros ; Ntakaris, Adamantios.
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RePEc:arx:papers:1907.09452.

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  15. Forecasting commodity prices out-of-sample: Can technical indicators help?. (2020). Wang, Yudong ; Liu, LI ; Wu, Chongfeng.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:2:p:666-683.

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  16. Beta dispersion and market timing. (2020). Kuntz, Laura-Chloe.
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:59:y:2020:i:c:p:235-256.

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  17. Equity premium prediction and optimal portfolio decision with Bagging. (2020). Yin, Anwen.
    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:54:y:2020:i:c:s1062940820301686.

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  18. Deeply Equal-Weighted Subset Portfolios. (2020). Il, Sang.
    In: Papers.
    RePEc:arx:papers:2006.14402.

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  19. Equity Premium Prediction with Structural Breaks: A Two-Stage Forecast Combination Approach. (2019). Yin, Anwen.
    In: International Journal of Economics and Finance.
    RePEc:ibn:ijefaa:v:11:y:2019:i:12:p:50.

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  20. Out-of-sample equity premium prediction in the presence of structural breaks. (2019). Yin, Anwen.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:65:y:2019:i:c:s1057521918304745.

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  21. Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?. (2019). Zhang, Yaojie ; Wang, Yudong ; Ma, Feng.
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:54:y:2019:i:c:p:97-117.

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  22. Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators. (2019). Gabbouj, Moncef ; Kanniainen, Juho ; Iosifidis, Alexandros ; Ntakaris, Adamantios.
    In: Papers.
    RePEc:arx:papers:1907.09452.

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  23. Forecasting stock market returns by summing the frequency-decomposed parts. (2018). Verona, Fabio ; Faria, Gonçalo.
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:45:y:2018:i:c:p:228-242.

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  24. Forecasting the aggregate oil price volatility in a data-rich environment. (2018). Zhang, Yaojie ; Wahab, M. I. M., ; Liu, Jing ; Ma, Feng.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:72:y:2018:i:c:p:320-332.

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  25. Forecasting stock market returns by summing the frequency-decomposed parts. (2017). Verona, Fabio ; Faria, Gonçalo.
    In: CEF.UP Working Papers.
    RePEc:por:cetedp:1702.

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  26. Forecasting stock market returns by summing the frequency-decomposed parts. (2016). Verona, Fabio ; Faria, Gonçalo.
    In: Bank of Finland Research Discussion Papers.
    RePEc:zbw:bofrdp:rdp2016_029.

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  27. Optimized Indicators of Technical Analysis on the New York Stock Exchange. (2016). Sirucek, Martin ; Irek, Martin ; Ima, Karel.
    In: Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis.
    RePEc:mup:actaun:actaun_2016064062123.

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  28. Forecasting stock market returns by summing the frequency-decomposed parts. (2016). Verona, Fabio ; Faria, Gonçalo.
    In: Working Papers de Economia (Economics Working Papers).
    RePEc:cap:wpaper:052016.

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  29. Forecasting stock market returns by summing the frequency-decomposed parts. (2016). Faria, Gonalo ; Verona, Fabio.
    In: Research Discussion Papers.
    RePEc:bof:bofrdp:2016_029.

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