Quantum Portfolio Optimization : a Multi-Level Perspective Study of the Swedish Fund Management Industry

University essay from KTH/Industriell ekonomi och organisation (Inst.); KTH/Industriell ekonomi och organisation (Inst.)

Abstract: In recent years, quantum computers have achieved new levels of sophistication and are by some estimates only a few years from being used in production. A growing body of literature points toward their potential uses within various industries, with the finance industry identified as exceptionally full of prospective applications. One application that has seen recent experimental success is Quantum Portfolio Optimization (QPO), where researchers have successfully mapped the optimization task onto existing quantum hardware. As classical Portfolio Optimization (PO) algorithms often have high computational costs, achieving a quantum speed-up could bring major benefits for various stakeholders. One industry that makes use of PO is fund management. Considering the diversity that exists between funds, with regard to strategy and methods, it is likely that sociological factors play a part in selecting which technical solutions are employed. The interplay between sociological and technical factors will be central to this study, as it investigates the conditions for QPO within the Swedish fund management through a socio-technical perspective. First, semi-structured qualitative interviews are conducted with industry actors and quantum computer stakeholders. This is followed by a two-step thematic analysis, structured on the socio-technical dimensions of Geels’ Multi-Level Perspective (MLP). After coding statements, four key themes are created to describe characteristics of the industry. Second, these themes are analyzed together with the niche of QPO through the lens of System Innovations theories, to evaluate the readiness of QPO and its potential socio-technical effects on the industry. The key findings characterizing the fund management industry are summarized through four themes. In particular, the trade-off between quantitative and qualitative methods, the inadequacy of historical data, the importance of third-party suppliers, and the poorly functioning and rigid competitive landscape are key characteristics. The current state of QPO is not considered to have reached a commercially viable price-to-performance ratio but has built a strong support that will help it improve over time. Furthermore, the results point toward QPO being introduced in a limited fashion, but may over time cause significant disruption, as it contributes to reshaping the socio-technical architecture of the industry.

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