...: Either multiple objects of class firm or a list of such objects
who: Whether to take into account: (ownership) co-ownership ; (management) board interlocks, or both (recognises minimum unambiguous strings).
ties: Type of ties to create. Possible values: binary; naive; share (see Details).
id_as_firm_name: Whether to use the ticker as the firm's name. Defaults to TRUE if all firms' id is neither NULL nor NA.
Matrix: Whether to use the c("list("Matrix")", " package"). Defaults to TRUE when any matrix in the pipeline contains more than 10,000 cells and the package is installed.
self_ties: Whether to allow self-ties (a 'loop' in graph theory). Defaults to FALSE.
Returns
A matrix object of class financial_matrix(possibly using the c("list("Matrix")", " package"))
Details
See more specific functions for a detailed overview:
for board interlocks (who == 'management'):
FF.binary.management, if ties = 'binary';
FF.binary.management, if ties = 'naive';
FF.norm.management, if ties = 'share'.
for co-ownership (who == 'ownership'):
FF.binary.ownership, if ties = 'binary';
FF.naive.ownership, if ties = 'naive';
FF.norm.ownership, if ties = 'share'.
for both co-ownership and board interlocks (who == 'both'):
FF.binary.both, if ties = 'binary';
FF.naive.both, if ties = 'naive';
FF.norm.both, if ties = 'share'.
Examples
# Create the normalised FF matrix of Berkshire Hathaway's holdings by boards interlocksdata('firms_BKB')FF <- FF(firms_BKB, who ='man', ties ='share')