File
systemic_expected_shortfall.m
Name
systemic_expected_shortfall
Synopsis
systemic_expected_shortfall - Calculates the systemic expected shortfall for a firm.
Introduction
NOTE: PART OF A SET OF 3 RELATED FILES:
Acharya, Pedersen, Philippon, and Richardson (2010) argue that each financial institutions contribution to systemic risk can be measured as its systemic expected shortfall (SES), i.e., its propensity to be undercapitalized when the system as a whole is undercapitalized. SES is a theoretical construct and the authors use the following 3 measures to proxy it:
Given these proxies, the authors seek to develop leading indicators which predict an institutions SES; these leading indicators are marginal expected shortfall (MES) and leverage (LVG).
License
=============================================================================
Copyright 2011, Dimitrios Bisias, Andrew W. Lo, and Stavros Valavanis
COPYRIGHT STATUS: This work was funded in whole or in part by the Office of
Financial Research under U.S. Government contract TOSOFR-11-C-0001, and is,
therefore, subject to the following license: The Government is granted for
itself and others acting on its behalf a paid-up, nonexclusive, irrevocable,
worldwide license to reproduce, prepare derivative works,
distribute copies to the public, perform and display the work.
All other rights are reserved by the copyright owner.
THIS SOFTWARE IS PROVIDED "AS IS". YOU ARE USING THIS SOFTWARE AT YOUR OWN RISK. ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHORS, CONTRIBUTORS, OR THE UNITED STATES GOVERNMENT BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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Inputs
Outputs
Code
% Run warning message
warning('OFRwp0001:UntestedCode', ...
['This version of the source code is very preliminary, ' ...
'and has not been thoroughly tested. Users should not rely on ' ...
'these calculations.']);
num_firms = length(mes_training_sample);
% Regressors
X = [ones(num_firms,1) mes_training_sample lvg_training_sample];
% Regress systemic expected shortfall on marginal expected shortfall and
% leverage
betas = regress(ses_training_sample, X);
b = betas(2);
c = betas(3);
ses = (b*mes_firm + c*lvg_firm)/(b+c);
Examples
NOTE: Numbers used in the examples are arbitrary valid values.
They do not necessarily represent a realistic or plausible scenario.
mes_training_sample = [ -.023, -.07, .01 ]';
lvg_training_sample = [ 1.8, 1.5, 2.2 ]';
ses_training_sample = [ .3, .4, -.2 ]';
mes_firm = .04;
lvg_firm = 1.7;
ses = systemic_expected_shortfall(mes_training_sample, ...
lvg_training_sample, ses_training_sample, mes_firm, lvg_firm);
References
Acharya, Pedersen, Philippon, & Richardson. (2010). Measuring systemic risk.