Financial Innovation volume 6, Article number: 27 (2020)
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The 21st issue of Financial Innovation (FIN), Volume 6, No. 3 (2020) presents six papers contributed by 14 authors and co-authors from seven countries and areas: Belgium, India, Malaysia, Taiwan, Tunisia and the USA.
The first paper, “Privacy-Preserving Analytics for the Securitization Market: a zero-knowledge distributed ledger technology application”, by Sophie Meralli, evaluates the potential for zero-knowledge distributed ledger technology to alleviate asymmetry of information in the asset-backed securitization market and introduces a new system which could enable all market participants in the securitization lifecycle to interact on a unique decentralized platform. The second paper, “Distributed ledger technology for securities clearing and settlement: benefits, risks, and regulatory implications”, by Randy Priem, outlines the benefits and risks of the distributed ledger technology (DLT) for the clearing and settlement of exchange-traded and OTC securities, followed by a description of the technology’s potential role for central counterparties and central securities depositories. The third paper, “Evaluating the exchange rate and commodity price nexus in Malaysia: evidence from the threshold cointegration approach”, by Shamaila Butt, Suresh Ramakrishnan, Nanthakumar Loganathan and Muhammad Ali Chohan, examines the long- and short-run dynamics of asymmetric adjustment between the nominal exchange rate and commodity prices, namely oil, palm oil, rubber, and natural gas prices, in Malaysia using monthly data from January 1994 to December 2017. The fourth paper, “Testing the governance-performance relationship for the Tunisian banks: a GMM in system analysis”, by Nesrine Djebali and Khemais Zaghdoudi, examines the impact of internal governance on bank performance and finds that the correlation between the size of the board of directors, the state’s inclusion, and the presence of independent directors is positive and significant. The fifth paper, “Portfolio optimization of credit risky bonds: a semi-Markov process approach”, by Puneet Pasricha, Dharmaraja Selvamuthu, Guglielmo D’Amico and Raimondo Manca, presents a semi-Markov process based approach to optimally select a portfolio consisting of credit risky bonds. The sixth paper, “Encoding candlesticks as images for pattern classification using convolutional neural networks”, by Jun-Hao Chen and Yun-Cheng Tsai, proposes a two-steps approach to recognize candlestick patterns automatically which outperforms the LSTM model.
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Kou, G. Editor’s introduction. Financ Innov 6, 27 (2020). https://doi.org/10.1186/s40854-020-00189-y