f_circular_bloc_bootstrap: Function computing a circular block bootstrap
In DiversificationR: Econometric Tools to Measure Portfolio Diversification

Description Usage Arguments Value Author(s) References Examples

View source: R/portfoliodiversificationR.R

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

1	f_circular_bloc_bootstrap(m_input_data_series, input_c, input_b, input_prob)

`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)

`RSRL`	A numerical value (bootstrapped RSRL)
`mRSRL`	A numerical value (bootstrapped mRSRL)
`bootstapped_series`	A matrix of numerical values (bootstrapped returns)

Jean-Baptiste Hasse

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).

# 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)

# }