Hortense Santos – School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Rui Dias – School of Business and Administration, Polytechnic Institute of Setúbal, Portugal and CEFAGE-UE, IIFA,
University of Évora, Portugal
Cristina Vasco – School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Paulo Alexandre – School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Paula Heliodoro – School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
DOI: https://doi.org/10.31410/EMAN.S.P.2021.1
5th International Scientific Conference – EMAN 2021 – Economics and Management: How to Cope With Disrupted Times, Online/Virtual, March 18, 2021, SELECTED PAPERS published by: Association of Economists and Managers of the Balkans, Belgrade, Serbia; ISBN 978-86-80194-44-8, ISSN 2683-4510
Abstract:
This paper aims to analyze the predictability of the stocks of Apple, Microsoft Amazon.com,
Tesla, Facebook, Samsung, Electronics, Johnson & Johnson, Walmart, in the period from October 1,
2019 to January 11, 2021. To carry out such an analysis, it is intended to answer two research questions,
namely: (i) is there predictability in the stock prices of the companies under analysis? (ii) Can investors
diversify risk by incorporating these companies’ shares into their portfolios? The results of the Exponents
Detrended Fluctuation Analysis (DFA) show that Apple (0.51) Microsoft (0.49), Amazon.com (0.53),
Samsung Electronics (0.53), Johnson & Johnson (0.53) do not have long memories in their time series,
that is, investors cannot obtain abnormal profitability without incurring additional risk. Walmart (0.41)
has anti-persistence, while Tesla (0.60), Facebook (0.55) indicate some predictability, meaning investors
adjusting their trading strategies to the necessary missteps may have some above-average profitability,
which partly rejects the first question of the research. To answer the second research question, we estimated
the Detrended cross-correlation coefficient (pDCCA) model, which indicates 17 mean correlation
coefficients (≈ 0.333 → ≈ 0.666), 7 strong cross-trend correlation coefficients (0.666 → ≈ 1,000), 4 weak
correlation coefficients (≈ 0.000 → ≈ 0.333). These results show that investors should be careful to incorporate
the shares of these companies into a single portfolio; the suggestion would be to group only the
shares of companies that do not present predictability and have low rhoDCCA. The authors consider that
this evidence will be important for institutional investors when carrying out trading strategies based on
maximizing profitability, but also mitigating risk when diversifying.
Keywords:
Covid-19, Predictability of stock prices, Diversification of portfolios.
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