Asynchronous Markets – Effects and Solutions

Introduction: Global financial markets are asynchronous, that is they close at different times through the day. Consequently, data with the same date stamp is not fully aligned. This asynchrony is often overlooked in both academic and industry research, an implicit assumption that it immaterial. We show this assumption is incorrect and the asynchrony can have significant effects on the reliability of results. We demonstrate that not allowing for this asynchrony can cause problems in both industry and academic practice. Practitioners working with daily data will both underestimate correlation and volatility, leading to inaccuracies in both risk modelling and performance analysis. The problem will also affect academic research based on monthly data. It will bias regression results and can create lag lead effects where none exist. The effect gets worse as more data is added. We develop a model of asynchronous markets and compare the predictions with financial data to verify the model. We then use the model to identify the effects of asynchronous data. Once verified the model is used to understand the issues caused by asynchronous data and where possible to identify solutions.