Assessment of the Financial Trading Efficiency Under Globalization

Abstract

The efficiency of financial trading is a fundamental concept in finance, essential to effective price discovery, minimising transaction costs, and maintaining market liquidity. Despite the theoretical robustness of concepts like the Efficient Market Hypothesis, empirical evidence reveals persistent inefficiencies, particularly in financial trading in emerging markets under globalisation and newer asset classes such as cryptocurrencies. The purpose of this article is to evaluate the efficiency of financial trading in the context of globalisation. To achieve this, ARIMA-GARCH time-series modelling was used. The empirical analysis incorporated data from developed financial markets (S&P 500, FTSE 100) and emerging financial markets (Shanghai Composite Index) from 2010 to 2023, focusing on transaction costs, liquidity, and volatility. The mathematical model incorporated components such as market price dynamics, transaction costs, liquidity, and flow rates information to construct a combined efficiency metric. The results demonstrate significant disparities in efficiency among markets. Financial trading in the developed markets exhibited lower volatility clustering and higher price predictability, indicative of greater efficiency. In contrast, financial trading in the emerging markets showed pronounced inefficiencies due to higher transaction costs and volatility. The proposed model enables us to quantify market efficiency and highlights the impact of liquidity and transaction costs on price alignment. It also provides a holistic view of market efficiency and serves as a tool for traders, policymakers, and regulators. Further research is recommended to empirically validate the model across different asset classes and assess its implications for regulatory frameworks.