CapFloor.help (OCTARISK Documentation)

4.15 CapFloor.help

Octarisk Class: object = CapFloor(id)

Octarisk Class: object = CapFloor()

Class for setting up CapFloor objects. Plain vanilla caps and floors (consisting of caplet and floorlets) can be based on interest rates or inflation rates. Cash flows are generated according to different models (Black, Normal, Analytic) and subsequently discounted to calculate the CapFloor value.

CAP: Plain Vanilla interest rate cap. Valuation model either [’black’,’normal’,’analytic’]
FLOOR: Plain Vanilla interest rate floor. Valuation model either [’black’,’normal’,’analytic’]
CAP_CMS: CMS interest rate cap. Valuation model either [’black’,’normal’,’analytic’]
FLOOR_CMS: CMS interest rate floor. Valuation model either [’black’,’normal’,’analytic’]
CAP_INFL: Cap on inflation expectation rates (derived from inflation index values). Analytical model only (cash flow value based on difference of inflation rate and strike rate)
FLOOR_INFL: Floor on inflation rates (derived from inflation index values). Analytical model only (cash flow value based on difference of inflation rate and strike rate)

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

Methods for CapFloor object obj:

CapFloor(id) or CapFloor(): Constructor of a CapFloor 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, discount_curve): Calculate the net present value of cash flows of Caps and Floors.
obj.rollout(valuation_date,scenario, reference_curve, vola_surface): used for (CMS) Caps and Floors
obj.rollout(valuation_date,scenario, inflation_exp_rates, historical_inflation, consumer_price_index): used for Inflation Caps and Floors Cash flow rollout for (Inflation) Caps and Floors.
obj.calc_sensitivity(valuation_date,scenario, reference_curve, vola_surface, discount_curve) Calculate numerical sensitivities (durations, vega, theta) for the given CapFloor instrument.
obj.calc_vola_spread(valuation_date,scenario, discount_curve, volatility_surface) Calibrate volatility spread in order to match the CapFloor price with the market price. The volatility spread will be used for further pricing.
obj.getValue(scenario): Return CapFloor value for given scenario. Method inherited from Superclass Instrument
CapFloor.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 CapFloor 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: ’derivative’)
type: Type of instrument, specific for class. Set to ’CapFloor’.
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.
model: Valuation model for (CMS) Caps and Floors can be either [’black’,’normal’,’analytic’]. Inflation Caps and Floors are valuated by analytical model only.

For illustration see the following example: A 2 year Cap starting in 3 years is priced with Black model. The resulting Cap value (137.0063959386) and volatility spread (-0.0256826614604929)is retrieved:


disp('Pricing Cap Object with Black Model')
cap = CapFloor();
cap = cap.set('id','TEST_CAP','name','TEST_CAP','issue_date','30-Dec-2018', ...
'maturity_date','29-Dec-2020','compounding_type','simple');
cap = cap.set('term',365,'term_unit','days','notional',10000, ...
'coupon_generation_method','forward','notional_at_start',0, ...
'notional_at_end',0);
cap = cap.set('strike',0.005,'model','Black','last_reset_rate',0.0, ...
'day_count_convention','act/365','sub_type','CAP');
c = Curve();
c = c.set('id','IR_EUR','nodes',[30,1095,1460],'rates_base',[0.01,0.01,0.01], ...
'method_interpolation','linear');
v = Surface();
v = v.set('axis_x',365,'axis_x_name','TENOR','axis_y',90, ...
'axis_y_name','TERM','axis_z',1.0,'axis_z_name','MONEYNESS');
v = v.set('values_base',0.8);
v = v.set('type','IRVol');
cap = cap.rollout('31-Dec-2015','base',c,v);
cap = cap.calc_value('31-Dec-2015','base',c);
base_value = cap.getValue('base')
cap = cap.set('value_base',135.000);
cap = cap.calc_vola_spread('31-Dec-2015',c,v);
cap = cap.rollout('31-Dec-2015','base',c,v);
cap = cap.calc_value('31-Dec-2015','base',c);
vola_spread = cap.vola_spread

Dependencies of class:

CapFloor