ESTIMATING A LOGISTIC REGRESSION MODEL ON THE ROLE OF ARTIFICIALINTELLIGENCE ON DERIVATIVE MARKETS

ESTIMATING A LOGISTIC REGRESSION MODEL ON THE ROLE OF ARTIFICIALINTELLIGENCE ON DERIVATIVE MARKETS

WILBERT KUDAKWASHE CHIDAUSHE

PROFESSOR TAVONGA NJAYA

The study explored the role of Artificial intelligence on the stability, efficiency, depth, and access
of derivative markets during the period 2009 to 2021. The study used mixed method research.
Cross sectional data of 60 countries from North America, Latin America and the Caribbean,
Western Europe, Eastern Europe, Middle East and North Africa, Sub-Sahara Africa, South
and Central Asia, East Asia, and the Pacific. Simple random sampling was used to select the 60
countries according to their Government Artificial Intelligence Index. Logistic regression was
applied on the cross-section data to determine the effect of Artificial Intelligence on derivative
markets in terms of financial efficiency, financial depth, financial access, and financial stability.
The proven role of Artificial Intelligence on derivative markets is to enhance financial inclusion
and financial stability through the provision of derivative trading platforms. The results of the
study showed that the use of Artificial intelligence on derivative markets is significantly and
positively related to financial access as measured by the percentage of digital payments. Further,
the test revealed that the use of Artificial Intelligence on derivative markets is significantly and
negatively related to financial stability as measured by stock price volatility. The study showed
that there was no effect on financial depth and efficiency arising from the use of Artificial Intel-
ligence on derivative markets. The study recommended that governments should put in place
adequate financial infrastructure as well as vibrant regulations prior to the use of Artificial
Intelligence on the derivative markets to avoid systemic risk build ups.

MET Mangement Review - MMR

2024