4.14 Stochastic.help

Octarisk Class: object = Stochastic(id)

Octarisk Class: object = Stochastic()

Class for setting up Stochastic objects. A Stochastic instrument uses a risk factor with random variables (either uniform, normal or t-distributed) to draw values from a 1D Surface. The surface has exactly one value per given quantile [0,1]. This instrument type can be used to pre-calculate values in another risk system for a given risk factor distribution.

• STOCHASTIC: Stochastic instrument type is the default value.

In the following, all methods and attributes are explained and a code example is given.

Methods for Stochastic object obj:

• Stochastic(id) or Stochastic(): Constructor of a Stochastic object. id is optional and specifies id and name of new object.
• obj.set(attribute,value): Setter method. Provide pairs of attributes and values. Values are checked for format and constraints.
• obj.get(attribute): Getter method. Query the value of specified attribute.
• obj.calc_value(valuation_date,scenario, riskfactor, surface) Calculate the value of Stochastic instruments. Quantile values from a 1-dimensional surface are drawn based on (transformed) risk factor shocks.
• obj.getValue(scenario): Return Stochastic value for given scenario. Method inherited from Superclass Instrument
• Stochastic.help(format,returnflag): show this message. Format can be [plain text, html or texinfo]. If empty, defaults to plain text. Returnflag is boolean: True returns documentation string, false (default) returns empty string. [static method]

Attributes of Stochastic objects:

• id: Instrument id. Has to be unique identifier. (Default: empty string)
• name: Instrument name. (Default: empty string)
• description: Instrument description. (Default: empty string)
• value_base: Base value of instrument of type real numeric. (Default: 0.0)
• currency: Currency of instrument of type string. (Default: ’EUR’) During instrument valuation and aggregation, FX conversion takes place if corresponding FX rate is available.
• asset_class: Asset class of instrument. (Default: ’stochastic’)
• type: Type of instrument, specific for class. Set to ’Stochastic’.
• value_stress: Line vector with instrument stress scenario values.
• value_mc: Line vector with instrument scenario values. MC values for several timestep_mc are stored in columns.
• timestep_mc: String Cell array with MC timesteps. If new timesteps are set, values are automatically appended.
• quantile_base: Base quantile of stochastic curve. (Default: 0.5)
• stochastic_riskfactor: underlying risk factor objects. Shocks are transformed according to stochastic_rf_type
• stochastic_curve: underlying 1-dim surface with values per quantile.
• stochastic_rf_type: Risk factor transformation. Type can be [’normal’,’t’,’uniform’] (Default: ’normal’)
• t_degree_freedom: degrees of freedom for t distribution (Default: 120)

For illustration see the following example: A stochastic value object is generated. Quantile values are given by a 1-dim volatility surface. The resulting Stress value ([95;100;105]) is retrieved:

disp('Pricing Pricing Stochastic Value Object')
r = Riskfactor();
r = r.set('value_base',0.5,'scenario_stress',[0.3;0.50;0.7],'model','BM');
value_x = 0;
value_quantile = [0.1,0.5,0.9];
value_matrix = [90;100;110];
v = Surface();
v = v.set('axis_x',value_x,'axis_x_name','DATE', ...
'axis_y',value_quantile,'axis_y_name','QUANTILE');
v = v.set('values_base',value_matrix);
v = v.set('type','STOCHASTIC');
s = Stochastic();
s = s.set('sub_type','STOCHASTIC','stochastic_rf_type','uniform', ...
't_degree_freedom',10);
s = s.calc_value('31-Mar-2016','base',r,v);
s = s.calc_value('31-Mar-2016','stress',r,v);
stress_value = s.getValue('stress')

Dependencies of class: