Adaptive Order Flow Forecasting with Multiplicative Error Models

Mihoci, A., Ting, CA., Lu, MJ. et al. Adaptive order flow forecasting with multiplicative error models. Digit Finance 4, 89–108 (2022). https://doi.org/10.1007/s42521-021-00047-1

25 Pages Posted: 5 Jan 2017 Last revised: 5 May 2022

See all articles by Andrija Mihoci

Andrija Mihoci

Humboldt University of Berlin - C.A.S.E., Center for Applied Statistics and Economics

Christopher Hian-Ann Ting

Singapore Management University

Meng-Jou Lu

National Chiao-Tung University

Kainat Khowaja

International Research Training Group 1792, School of Business and Economics, Humboldt University of Berlin

Date Written: July 8, 2014

Abstract

A flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e., the buyer and the seller-initiated trading volumes and the order flow dynamics. Analysing order flow series and its information content of mini Nikkei 225 index futures traded at the Osaka Securities Exchange in 2012 and 2013, a data-driven optimal length of local windows up to approximately 1-2 hours is reasonable to capture parameter variations and is suitable for short-term prediction. Our proposed trading strategies achieve statistical arbitrage opportunities and are therefore beneficial for quantitative finance practice.

Keywords: multiplicative error models, trading volume, order flow, forecasting

JEL Classification: C41, C51, C53, G12, G17

Suggested Citation

Mihoci, Andrija and Hian-Ann Ting, Christopher and Lu, Meng-Jou and Khowaja, Kainat, Adaptive Order Flow Forecasting with Multiplicative Error Models (July 8, 2014). Mihoci, A., Ting, CA., Lu, MJ. et al. Adaptive order flow forecasting with multiplicative error models. Digit Finance 4, 89–108 (2022). https://doi.org/10.1007/s42521-021-00047-1, Available at SSRN: https://ssrn.com/abstract=2892620 or http://dx.doi.org/10.2139/ssrn.2892620

Andrija Mihoci

Humboldt University of Berlin - C.A.S.E., Center for Applied Statistics and Economics ( email )

Unter den Linden 6
Berlin, AK 10099
Germany

Christopher Hian-Ann Ting

Singapore Management University ( email )

Li Ka Shing Library
70 Stamford Road
Singapore 178901, 178899
Singapore

Meng-Jou Lu

National Chiao-Tung University

1001 Da Hsueh Road
East District
Hsinchu 300, 30050
Taiwan

Kainat Khowaja (Contact Author)

International Research Training Group 1792, School of Business and Economics, Humboldt University of Berlin

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

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