# YZ: Yan and Zhang (2012) Grid-Search based PIN Estimates In InfoTrad: Calculates the Probability of Informed Trading (PIN)

## Description

It estimates PIN using Yan and Zhang (2012) algorithm.

## Usage

 ```1 2 3``` ```YZ(data, likelihood = c("LK", "EHO")) ## S3 method for class 'YZ_class' print(obj) ```

## Arguments

 `data` Data frame with 2 variables `likelihood` Character strings for likelihood algorithm. Default is "LK". `obj` object variable

## Details

Argument for data must be a data frame with 2 columns that only contain numbers. Not any other type. You do not have to give names to the columns. We will assign first one as "Buy" and second as "Sell", therefore you should put order numbers with respect to this order.

## Value

Returns a list of parameter estimates (output)

 `alpha` A Number `delta` A Number `mu` A Number `eb` A Number `es` A Number `LikVal` A Number `PIN` A Number

## Warning

This function does not handle NA values. Therefore the datasets should not contain any missing value

## Author(s)

Duygu Celik and Murat Tinic

## References

Y. Yan and S. Zhang. An improved estimation method and empirical properties of the probability of informed trading. Journal of Banking & Finance, 36(2):454-467, 2012.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46``` ``` # Sample Data # Buy Sell #1 350 382 #2 250 500 #3 500 463 #4 552 550 #5 163 200 #6 345 323 #7 847 456 #8 923 342 #9 123 578 #10 349 455 Buy<-c(350,250,500,552,163,345,847,923,123,349) Sell<-c(382,500,463,550,200,323,456,342,578,455) data<-cbind(Buy,Sell) # Parameter estimates using the LK factorization of Lin and Ke (2011) # with the algorithm of Yan and Zhang (2012). # Default factorization is set to be "LK" result=YZ(data) print(result) # Alpha: 0.3999999 # Delta: 0 # Mu: 442.1667 # Epsilon_b: 263.3333 # Epsilon_s: 424.9 # Likelihood Value: 44371.84 # PIN: 0.2004457 # Parameter estimates using the EHO factorization of Easley et. al. (2010) # with the algorithm of Yan and Zhang (2012). result=YZ(data,likelihood="EHO") print(result) # Alpha: 0.9000001 # Delta: 0.9000001 # Mu: 489.1111 # Epsilon_b: 396.1803 # Epsilon_s: 28.72002 # Likelihood Value: Inf # PIN: 0.3321033 ```

InfoTrad documentation built on Aug. 21, 2017, 9:02 a.m.