عنوان انگلیسی مقاله:
Algorithmic sign prediction and covariate selection across eleven international stock markets
ترجمه فارسی عنوان مقاله:
پیش بینی علائم الگوریتمی و انتخاب متغیرها در یازده بورس بین المللی سهام
Sciencedirect - Elsevier - Expert Systems With Applications, 115 (2019) 256-263: doi:10:1016/j:eswa:2018:07:061
Markku Karhunen 1
I investigate whether an expert system can be used for profitable long-term asset management. The trad- ing strategy of the expert system needs to be based on market predictions. To this end, I generate binary predictions of the market returns by using statistical and machine-learning algorithms. The methods used include logistic regressions, regularized logistic regressions and similarity-based classification. I test the methods in a contemporary data set involving data from eleven developed markets. Both statistical and economic significance of the results are considered. As an ensemble, the results seem to indicate that there is some degree of mild predictability in the stock markets. Some of the results obtained are highly significant in the economic sense, featuring annualized excess returns of 3.1% (France), 2.9% (Netherlands) and 0.8% (United States). However, statistically significant results are seldom found. Consequently, the re- sults do not completely invalidate the efficient-market hypothesis.
Keywords: Stock market indices | S&P 500 | Sign prediction | Efficient-market hypothesis | Regularized regression | Similarity-based classification