Forecasting Market Liquidity by Dynamic Arrival Rates of Infomred and Uninformed Trades

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Mahdikhani, Ehsan | 2020

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 53011 (44)
University: Sharif University of Technology
Department: Economics and Management
Advisor(s): Zamani, Shiva; Hagh Panah, Farshad
Abstract:
In this research, we propose a dynamic econometric microstructure model of trading, and we investigate how the dynamics of trades and trade composition interact with the evolution of market liquidity. We estimate a bivariate generalized autoregressive intensity process for the arrival rates of informed and uninformed trades for fifty actively traded stocks in Tehran Stock Exchange over one year of transaction data. Our results show that both informed and uninformed trades are highly persistent, but that the uninformed arrival forecasts respond negatively to past forecasts of the informed intensity. Our estimation generates daily conditional arrival rates of informed and uninformed trades, which we use to construct forecasts of the probability of information-based trade (PIN). These forecasts are used in turn to forecast market liquidity as measured by bid-ask spreads. We observe that PINs vary across assets and over time, and most importantly that they are correlated across assets. Our analysis shows that two principal component explains much of the daily variation in PINs and that these systemic liquidity factors may be important for asset pricing
Keywords:
Liquidity ; Arrival Rates ; Informed Trades ; Uninformed Trades ; Dynamic Econometric Microstructure Model

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