ALBERT

Description: Financial innovation by means of Fintech firms is one of the more disruptive business model innovations from the latest years. Specifically, in the financial advisor sector, worldwide assets under management of artificial intelligence (AI)-based investment firms, or robo-advisors, currently amount to US$975.5 B. Since 2008, robo-advisors have evolved from passive advising to active data-driven investment management, requiring AI models capable of predicting financial asset prices on time to switch positions. In this research, an artificial neural network modelling framework is specifically designed to be used as an active data-driven robo-advisor due to its ability to forecast with today’s copper prices five days ahead of changes in prices using input data that can be fed automatically in the model. The model, tested using data of the two periods with a higher volatility of the returns of the recent history of copper prices (May 2006 to September 2008 and September 2008 to September 2010) showed that the method is capable of predicting in-sample and out-of-sample prices and consequently changes in prices with high levels of accuracy. Additionally, with a 24-day window of out-of-sample data, a trading simulation exercise was performed, consisting of staying long if the model predicts a rise in price or switching to a short position if the model predicts a decrease in price, and comparing the results with the passive strategies, buy and hold or sell and hold. The results obtained seem promising in terms of both statistical and trading metrics. Our contribution is twofold: 1) we propose a set of input variables based on financial theory that can be collected and fed automatically by the algorithm. 2) We generate predictions five days in advance that can be used to reposition the portfolio in active investment strategies.

Description: (1) Social Impact Bonds (SIBs) foster the relationships between public and private sectors while adding value to new forms of investment that are closely linked to Socially Responsible Investments (SRIs). In this context, Sustainable Developments Goals (SDGs) aim to strengthen global partnerships in order to achieve the 2030 Agenda. Sustainable banking should consider its role in both new responsible investment products and the 2030 Agenda. This study aims to: (i) estimate the ROI of SIBS, (ii) define a financial formulation and a measurement system, and (iii) explain the relationship between SIBs and SDGs. (2) This research analyzes SIBs from an SDG approach, and proposes a valuation model based on a financial options valuation methodology that clarifies the financial value of the world’s first SIB (Peterborough Prison, UK). (3) Findings suggest that investors expect to have a negative return of 16.48%, and that this expected loss may be compensated for by the short- and long-term positive impact of an intervention in society. (4) It is shown that SIBs provide an opportunity to reach SDG 17 and improve sustainable investment portfolios, while providing an opportunity to strengthen a company’s Corporate Social Responsibility policy and its corporate reputation.