An Improved Version of the Volume-Synchronized Probability of Informed Trading

Ke, Wen-Chyan; Lin, Hong-Wen

doi:10.1561/104.00000046

Cited by 4 publications

(3 citation statements)

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“…They have also explained the VPIN metric is sometimes unexpectedly correlated with other usual ones (such as VIX or RV) [9] [10]. Moreover, it has been shown [14] [15] that the VPIN does not approximate the PIN, as the PIN was built on a time-clock theoretical framework, and the VPIN with a volume-clock paradigm. In this study, we propose another way to estimate the PIN within its original time-clock framework.…”

Section: Probability Of Informed Trading (Pin) a High Value Of The Pmentioning

confidence: 99%

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A New Way to Compute the Probability of Informed Trading

Bambade¹

2019

JMF

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Volume-Synchronized Probability of Informed Trading (VPIN) is a tool designed to predict extreme events like flash crashes in high-frequency trading. Its aim is to estimate the Probability of Informed Trading (PIN), which was built from a probabilistic framework. Some concerns have been raised about its theoretical foundations and its reliability. More precisely, it has been shown that theoretically the VPIN does not approximate the PIN as the PIN has been built with a time-clock framework and the VPIN with a volume clock one. On a practical point of view, the VPIN has been found to be sensitive to the starting point of computation of a data set and to different parameters, such as the classification rule. In this paper, in order to improve the PIN theoretical framework, we firstly analyze the theoretical foundations of the PIN and the VPIN models to have a better view of all its different assumption subtleties. It secondly makes it possible to point out some approximation flaws in the formula used to approximate the PIN and to propose another exact way to compute the PIN. All different results are illustrated with simulations.

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Section: Probability Of Informed Trading (Pin) a High Value Of The Pmentioning

confidence: 99%

“…. Now, we synthetise and refer to the great ideas of the proof of Kin and Le [14]. Remark first the following:…”

Section: A New Computation Ofmentioning

confidence: 99%

A New Way to Compute the Probability of Informed Trading

Bambade¹

2019

JMF

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show abstract

“…They have also explained that VPIN metric is sometimes unexpectedly correlated with other usual ones (such as VIX or RV) [7,8]. More recently, it has been shown theoretically that the volume-clock paradigm of VPIN framework does not enable to really approximate fully the PIN value, although the proposed formula is close [15,16].…”

Section: Modelmentioning

confidence: 99%

An Assessment of the Prediction Quality of VPIN

Bambade¹,

Wu²

2019

Advanced Analytics and Artificial Intelligence Applications

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VPIN is a tool designed to predict extreme events like flash crashes. Some concerns have been raised about its reliability. In this chapter we assess VPIN prediction quality (precision and recall rates) of extreme volatility events including its sensitivity to the starting point of computation in a given data set. We benchmark the results with the ones of a "naive classifier." The test data used in this study contains 5.6 year's worth of trading data of the five most liquid futures contracts of this time period. We found that VPIN has poor "flash crash" prediction power with the traditional 0.99 decision threshold. Increasing the decision threshold does not significantly improve overall prediction quality. Nevertheless we found VPIN has a more interesting predictive power for flash events of lower amplitude. Finally, we found that, for practice, the last bar price structure is the least sensitive to the starting point of computation.

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A note of techniques that mitigate floating-point errors in PIN estimation

Chen

Lin

2019

Finance Research Letters

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An Improved Version of the Volume-Synchronized Probability of Informed Trading

Cited by 4 publications

References 0 publications

A New Way to Compute the Probability of Informed Trading

A New Way to Compute the Probability of Informed Trading

An Assessment of the Prediction Quality of VPIN

A note of techniques that mitigate floating-point errors in PIN estimation

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