International Finance

Permanent URI for this collectionhttps://hdl.handle.net/10679/314

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    ArticlePublicationOpen Access
    Big data–enabled sign prediction for Borsa Istanbul intraday equity prices
    (Elsevier, 2023-12) Kılıç, A.; Güloğlu, B.; Yalçın, Atakan; Üstündağ, A.; International Finance; YALÇIN, Atakan
    This paper employs a big data source, the Borsa Istanbul's “data analytics” information, to predict 5-min up, down, and steady signs drawn from closing price changes. Seven machine learning algorithms are compared with 2018 data for the entire year. Success levels for each method are reported for 26 liquid stocks in terms of macro-averaged F-measures. For the 5-min lagged data, nine equities are found to be statistically predictable. For lagged data over longer periods, equities remain predictable, decreasing gradually to zero as the markets absorb the data over time. Furthermore, economic gains for the nine equities are analyzed with algorithms where short selling is allowed or not allowed depending on these predictions. Four equities are found to yield more economic gains via machine learning–supported trading strategies than the equities' own price performances. Under the “efficient market hypothesis,” the results imply a lack of “semistrong-form efficiency.”
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    ArticlePublicationOpen Access
    Product market competition and the value of diversification
    (Elsevier, 2023-12) Şahin, Cansu İskenderoğlu; International Finance; ŞAHİN, Cansu Iskenderoğlu
    I examine how industry concentration affects the value of diversification. I find that con- glomerates that operate mainly in concentrated industries (concentrated conglomerates) have higher diversification values. Using tariff reductions as competitive shocks, I show that concentrated conglomerates experience significant decline in their valuations and respond aggressively to threats in less-competitive industries.