The Volume Synchronized Probability of Informed Trading, commonly known as VPIN, is a mathematical model used in financial markets for multiple purposes.
- Version - Written in Python 2.7.1
- Keywords
- VPIN
- Random control
- Market micro-structure
- Numpy as np
- Pandas as pd
- Matplotlib as plt
- Data source: wind
- Sampling time range: Jan 2015-Oct 2018
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- Correlation between VPIN gap versus tick price
- Market volume and sample population
For high frequency trading, market maker need information to make a profit in an informed trading, because reverse selection may cause losses in transactions. The VPIN method intends to measure the probability of market informed transaction; as a predictive sign of the market liquidity risk.
For transactions in the sampling period, the entile volume is divided into 50 baskets. VBS (i.e. Volume of Basket) is defined as total transaction volume in each separate basket.
- Fill of basket starts when transaction starts
- When volume of transaction exceeds the upper bound, calculate r, which indicates the rest of transaction amount
- Loop of aforementioned process generate a series of baskets.
From a visualized perspective, time series remained stationary. Meanwhile, CSI-300 normally fluctuate dramatically after enlargement of VPIN index.
Please refer to the entire code project via this document, including sample outputs.
