spread: Estimation of Bid-Ask Spreads from Open, High, Low, and Close...

In bidask: Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices

Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices

Description

This function implements several methods to estimate bid-ask spreads from open, high, low, and close prices and it is optimized for fast calculations over rolling and expanding windows.

Usage

spread(x, width = nrow(x), method = "EDGE", sign = FALSE, na.rm = FALSE)

Arguments

x	tabular data with columns named open, high, low, close (case-insensitive).
width	if an integer, the width of the rolling window. If a vector with the same length of the input prices, the width of the window corresponding to each observation. Otherwise, a vector of endpoints. By default, the full sample is used to compute a single spread estimate. See examples.
method	the estimators to use. See details.
sign	whether to return signed estimates.
na.rm	whether to ignore missing values.

Details

The method EDGE implements the Efficient Discrete Generalized Estimator described in Ardia, Guidotti, & Kroencke (JFE, 2024).

The methods OHL, OHLC, CHL, CHLO implement the generalized estimators described in Ardia, Guidotti, & Kroencke (JFE, 2024). They can be combined by concatenating their identifiers, e.g., OHLC.CHLO uses an average of the OHLC and CHLO estimators.

The method AR implements the estimator described in Abdi & Ranaldo (RFS, 2017). AR2 implements their 2-period version.

The method CS implements the estimator described in Corwin & Schultz (JF, 2012). CS2 implements their 2-period version. Both versions are adjusted for overnight (close-to-open) returns as described in the paper.

The method ROLL implements the estimator described in Roll (JF, 1984).

Value

A data.frame of spread estimates, or an xts object if x is of class xts. A value of 0.01 corresponds to a spread of 1%.

References

Ardia, D., Guidotti, E., Kroencke, T.A. (2024). Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices. Journal of Financial Economics, 161, 103916. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jfineco.2024.103916")}

Abdi, F., & Ranaldo, A. (2017). A simple estimation of bid-ask spreads from daily close, high, and low prices. Review of Financial Studies, 30 (12), 4437-4480. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/rfs/hhx084")}

Corwin, S. A., & Schultz, P. (2012). A simple way to estimate bid-ask spreads from daily high and low prices. Journal of Finance, 67 (2), 719-760. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.1540-6261.2012.01729.x")}

Roll, R. (1984). A simple implicit measure of the effective bid-ask spread in an efficient market. Journal of Finance, 39 (4), 1127-1139. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.1540-6261.1984.tb03897.x")}

Examples

# reduce number of threads to pass CRAN checks (you can ignore this)
data.table::setDTthreads(1)

# simulate open, high, low, and close prices with spread 1%
x <- sim(n = 1000, spread = 0.01)

# estimate the spread
spread(x)
# equivalent to
edge(x$Open, x$High, x$Low, x$Close)

# estimate the spread using a rolling window of 21 periods
s <- spread(x, width = 21)
tail(s)
# equivalent to
s <- edge_rolling(x$Open, x$High, x$Low, x$Close, width = 21)
tail(s)

# estimate the spread using an expanding window
s <- spread(x, width = 1:nrow(x))
tail(s)
# equivalent to
s <- edge_expanding(x$Open, x$High, x$Low, x$Close, na.rm = FALSE)
tail(s)

# estimate the spread using custom endpoints
ep <- c(3, 35, 100)
spread(x, width = ep)
# equivalent to
edge(x$Open[3:35], x$High[3:35], x$Low[3:35], x$Close[3:35])
edge(x$Open[35:100], x$High[35:100], x$Low[35:100], x$Close[35:100])

# use multiple estimators
spread(x, method = c("EDGE", "AR", "CS", "ROLL", "OHLC", "OHL.CHL"))

bidask documentation built on April 3, 2025, 8:49 p.m.