f_circular_bloc_bootstrap {DiversificationR}

Function computing a circular block bootstrap

Description

This function computes a circular block-resampling bootstrap of a matrix of returns.

Usage

f_circular_bloc_bootstrap(m_input_data_series, input_c, input_b, input_prob)

Arguments

m_input_data_series

A matrix of assets or portfolios returns (one per column)

input_c

A numerical value (number of wrapping the data around in a circle)

input_b

A numerical value (length of block size - time dimension)

input_prob

A numerical value (probability)

Value

RSRL

A numerical value (bootstrapped RSRL)

mRSRL

A numerical value (bootstrapped mRSRL)

bootstapped_series

A matrix of numerical values (bootstrapped returns)

Author(s)

Jean-Baptiste Hasse

References

Efron, B. "Bootstrap methods: another look at the jackknife." The Annals of Statistics 7 (1979): 1-26.

Hall, Peter, Joel L. Horowitz, and Bing-Yi Jing. "On blocking rules for the bootstrap with dependent data." Biometrika 82.3 (1995): 561-574.

Politis, Dimitris N., and Joseph P. Romano. "A circular block-resampling procedure for stationary data." Exploring the limits of bootstrap 2635270 (1992).

Examples

# NOT RUN {

  # Load data
  data("data_efficient_portfolios_returns")
  m_example_returns <- data_efficient_portfolios_returns[,1:2]

  # Compute Circular bootstap
  f_circular_bloc_bootstrap(m_example_returns, 10, 2, 0.95)

# }