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Volume Synchronized Probability of Informed Trading

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VPIN

Volume Synchronized Probability of Informed Trading

Introduction

  • The VPIN method intends to measure the probability of market informed transaction.
  • Although VPIN method is viewed for the HFT environment. But the result suggests that certain VPIN model with Linear Regression provides proxies for adverse selection risk
  • 주식시장에서의 매수, 매도는 50:50으로 이루어진다는 가정하에 거래량의 불균형을 계산하는 방법입니다.
  • 보고자 하는 주식 종목의 일일 평균 거래량을 잘 파악해서 버켓의 크기와 VPIN 계산하기 위한 버캣개수 개수를 잘 설정 해줘야합니다.

Info

  • Version - Written in Python 3.7.3
  • Keywords
    • VPIN
    • Market micro structure

Prerequisite

  • pandas
  • numpy
  • matplotlib.pyplot
  • time
  • train_test_split
  • LinearRegression

Correspondence

Please do not hesitate to submit an issue or contact via [email protected].

Usage

dataset

  • kakaostock.csv
  • Sampling time: 2021-March-17
  • Data sample in time period between 1000 and 1400.

Methodology

  • For transactions in the sampling date, the entile volume is divided into 1000 buckets.
  • Filling Procedure: Filling of bucket starts when transaction starts. When volume of transaction exceeds the upper bound, calculate vol_bucket with buy volume, which indicates the rest of transaction amount Loop of aforementioned process generate a series of baskets.
  • image

Sample Output

스크린샷 2021-04-11 오후 9 13 13

  • Price change per VPIN gradient

스크린샷 2021-04-12 오후 7 07 51