estimate_mrr: Estimates the model of Madhavan, Richardson, and Roomans...
In simonsays1980/tim: Estimation of Trade Indicator Models

Description Usage Arguments Details Value References

View source: R/MRR.R

Estimates the model of Madhavan, Richardson, and Roomans (1997)

1 2	estimate_mrr(price_diff, price, indicator, indicator_lag, midquote, midquote_lag, spread_quoted)

`price_diff`	a numeric vector containing the series of first price differences.
`price`	a numeric vector containing the price series.
`indicator`	an integer vector containing the trade direction with a buy as 1 and a sell as -1.
`indicator_lag`	an integer vector containing the first lag of the indicator series.
`midquote`	a numeric vector with the midquote price series.
`midquote_lag`	a numeric vector containing the first lag of the midquote series.
`spread_quoted`	a numeric vector containing the quoted spread series.

The function estimates for given data the trade indicator model of Madhavan, Richardson, and Roomans (1997). For estimation a GMM approach is used similar to the one desribed in the paper of the three authors. For application the gmm- package is used with a Bartlett-kernel, a heteroscedastic and autocorrelation consistent variance-covariance matrix with a Newey West bandwith. For details it is referred to the gmm-function.

A data.frame with the following values:

n: the number of observation used in estimation.
theta: the adverse selection component.
theta_std: the standard deviation of the adverse selection component.
theta_t: the t-value of the adverse selection component.
theta_p: the p-value of the adverse selection component.
phi: the transitory cost component.
phi_std: the standard deviation of the transitory cost component.
phi_t: the t-value of the transitory cost component.
phi_p: the p-value of the transitory cost component.
rho: the indicator first order autocorrelation.
rho_std: the standard deviation of the indicator autocorrelation.
rho_t: the t-value of the indicator autocorrelation.
rho_p: the p-value of the indicator autocorrelation.
r2: the coefficient of determination.
r2_adj: the adjusted coefficient of determination.
f_test: the value of the F-statistic.
f_pval: the p-value of the F-statistic.
theta_start: the start value for theta in the numerical optimization.
phi_start: the start value for phi in the numerical optimization.
rho_start: the start value for rho in the numerical optimization.
eps_std: the estimated standard deviation of the epsilon error term (order flow innovations).
eta_std: the estimated standard deviation of the eta error term (stochastic rounding errors).
spread_eff: the effective spread estimated from the model using the formula 2(θ+φ).
spread_eff_std: the standard deviation of the effective spread, calculated via the delta method.
spread_eff_emp: the empirical effective spread, calculated directly from the data by the arithmetic mean of the series q_t(p_t-m_t), where q_t is the trade direction, p_t the transaction price, and m_t the price midquote series.
spread_eff_emp_std: the standard deviation of the empirical effective spread calculated as the standard deviation of the series q_t(p_t-m_t).
spread_eff_emp_se: the standard error of the estimated empirical effective spread using the formula SE=STD/√ n.
spread_eff_emp_med: the median of the empirical effective spread calculated as the median of the series q_t(p_t-m_t).
spread_quoted: the mean quoted spread using the input quoted spread series.
spread_quoted_std: the standard deviation of the quoted spread using the input quoted spread series.
spread_quoted_se: the standard error of the quoted spread estimate using the formula SE=STD/√ n.
spread_quoted_med: the median of the quoted spread series.

Madhavan, Richardson & Roomans (1997), "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," Review of Financial Studies, Vol. 10, No. 4, pp. 1035-1064.

simonsays1980/tim documentation built on July 19, 2019, 7:35 a.m.