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Keynes Fund


Summary of Project Results

Many financial markets (for example stock markets, FX, treasury bonds, commodities) involve electronic order book trading at very high frequency. This produces a vast amount of complex data, the order book itself reflects many different "messages" such as different order types, cancellations, and executions. This makes its analysis very challenging. At the same time, this data allows one to ask fundamental questions about market efficiency, competition between intermediaries, market manipulation, the efficacy of regulatory and policy changes and so on.

We introduced the Realized moMents of Disjoint Increments (ReMeDI) paradigm to measure microstructure noise (the deviation of the observed asset prices from the fundamental values caused by market imperfections). We proposed consistent estimators of arbitrary moments of the microstructure noise process based on high‐frequency data, where the noise process could be serially dependent, endogenous, and nonstationary. We characterize the limit distributions of the proposed estimators and construct confidence intervals under infill asymptotics. Our simulation and empirical studies show that the ReMeDI approach is very effective to measure the scale and the serial dependence of microstructure noise. Moreover, the estimators are quite robust to model specifications, sample sizes, and data frequencies.

We are currently applying this to a large sample of stocks obtained from the database funded by the Keynes fund.


Impact and outputs

A ReMeDI for microstructure noise (with Z. Merrick Li) Cambridge working paper in Economics 1908. Econometrica Vol. 90, No. 1 (January, 2022), 367-389.

Robust estimation of integrated volatility (with M. Li). Cambridge working paper in Economics no 20115. Revised and Resubmitted to the Journal of Econometrics.


This work has been presented at academic conferences and seminar series around the world. It will form the basis of Prof. Linton's Cowles Lecture at the Econometric Society North American meetings in Los Angeles, June 2023.



Dr. Merrick Li and Prof. Oliver Linton


Dr Merrick Li is a Cambridge-INET Postdoctoral Research Fellow at the Faculty of Economics, University of Cambridge. His research expertise is in Analysis of High-Frequency Financial Data.


Professor Oliver Linton is the Professor of Political Economy in the Faculty of Economics and a Fellow of Trinity College, University of Cambridge. His research is focussed on nonparametric and semiparametric methods with an interest in Financial Econometrics.





Cambridge Working Papers in Economics (CWPE)



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