Webinar #2 Introduction to IAS-39 hedge accounting with Fairmat Fairmat Srl 18/07/2013
Agenda Brief notes on IAS-39 hedge accounting 1 Brief notes on IAS-39 hedge accounting 2 3
Introduction Prospective test IAS-39 Hedge accounting Prospective test Retrospective test
IAS-39: Introduction Introduction Prospective test The IAS-39 accounting rules discipline the representation and the valuation of financial instruments on the balance sheet. IAS-39 states that the fair value is the best measure for representing financial instruments. Besides innovation in the valuation process, the IAS principle introduces relevant advances in the hedging operations accounting. Hedge accounting The Hedge accounting rules try to ensure a correct representation in the balance sheet of the relationships between hedged items and hedging instrument. These rules allows to jointly evaluate the effects, at income statement level, derived by fair value changes in the hedging instrument and hedged item.
IAS-39: Introduction Introduction Prospective test Hedge accounting is an exception with respect to the standard accounting principles: its goal is to account only the efficient part of the hedge. Therefore, in order to apply hedge accounting, IAS-39 requires hedging instruments to satisfy given criteria. Necessary conditions for the hedge accounting implementation The company must provide risk management objectives and hedging strategies. Formal documentation containing the following elements is required: The identification of the hedging instrument, The target instrument or the operation (hedged item), The nature of the hedged risk, How the hedging instrument efficacy will be evaluated. The hedging must be highly effective. The hedging must be repeated at every scheduled reporting date and Hedge accounting must terminate whenever the hedging instrument loses its efficacy.
IAS 39: Effectiveness test Introduction Prospective test The possibility of implementing hedge accounting depends on the satisfying of the prospective and retrospective tests which are designed to validate the the hedging goals. Efficacy test At the stipulation date and at each reporting date the company must perform the following tests: Prospective test: designed to assess the hedging expected efficacy until its maturity, by measuring the value changes of the hedging instrument with respect to the value changes of hypothetical changes in the underlying driver of the hedged item. Retrospective test: designed to verify the effectiveness over the history of the operation, verifying that the changes of the values of the hedging instrument with respect to the fluctuations of the hedged item. If results fall within the range 80-125%, the hedge accounting rules can be used, otherwise standard accounting rules will be employed.
IAS-39: Effectiveness test Introduction Prospective test With the objective of testing efficacy, the hedged item can be modeled as an hypothetical derivative. Hypothetical Derivative Method The hypothetical derivative (or hedged item) should be identified right from the beginning of hedging operation and represents a perfect hedging for the risks the company wants to cover in terms of contract specifications (payments and reset dates, principal etc.) and market conditions.
IAS-39: Prospective test Introduction Prospective test The prospective test is performed by comparing the effects of the fair value changes of the hedging instrument (i.e. a derivative product) and the hypothetical derivative (hedged item). IAS-39 doesn t specify a unique method to evaluate the expected effectiveness of hedging. The more common methods are : Methods for Effectiveness test CRITICAL TERMS COMPARISON: this method does not require pricing, the hedging is considered highly effective if the hedging instrument features match the hedged item ones; DOLLAR OFFSET METHOD: quantitative method that evaluates the effectiveness by calculating the ratio between the hedging instrument cash-flows deltas and the hedging items cash-flows deltas; VARIABILITY REDUCTION METHOD quantitative method based on hedging strategies designed to reduce volatility.
IAS-39: Prospective test Introduction Prospective test Methods for expected effectiveness test REGRESSION ANALYSIS: statistic method adopted to express the relation between the changes in the fair-value of the hedging element w.r.t. the changes in the fair value of the hedging instrument (under several scenarios). Hedging = α + β Hedged + ε Hedging: the dependent variable, the changes of fair-value of the hedging item. Hedged: the independent variable, variation of fair-value of hedged item. α: intercept of the regression. β: regression slope. ε: statistic error. Statistic parameters to check the effectiveness of hedging: 1 β must be negative: 1.25 β 0.8; 2 R 2 > 0.96; 3 F -statistic must be significant.
IAS-39: Retrospective test Introduction Prospective test Check the prospective effectiveness of contract using test retrospective that calculate the variation of fair-value or net cash-flows during the contract period. Methods for retrospective effectiveness test IAS 39 provides a formula for verifying the retrospective effectiveness of the hedging strategy (with the dollar offset method): Ratio = fair value hedging instrument fair value hedged item with fair-value as difference between fair-value at start hedging date and fair-value at testing date. The hedging is effective if Ratio stands between 80%-125%.
Prospective Test : IAS-39 Plug-in (Free) + Fairmat Academic (Free) with Data-Link (On-Demand) or Fairmat Professional (Subscription)
Prospective Test Example: hedging of interest rate risk using an Interest Rate Swap Company A have an indexed debt (the Hedged Item). Variable rate mortage Principal: 12,250,000 e amortizing; Effective Date: 30/09/2011; End Date: 30/06/2014; Payment freq. : monthly; Indexed Rate: Euribor 6m (act/365); Fixing mode: arithmetic average rounded to the 0.05 of preceding 30 days calendar.
Example: Hedging Instrument Prospective Test Company A decides to hedge the 80% of the amount with the following IRS (Hedging Instrument). Hedging Instrument - IRS amortizing IRS amortizing Initial Notional 10,000,000 amortizing Trade Date 20/09/2011 Effective Date 30/09/2011 Expire Date 30/06/2014 Issuer payment frequency Monthly Company payment frequency Monthly Flows Company Issuer 1.65% Eur6 Conventions Company Issuer Fixing Rate Advance day count adjustment act/360 act/360
Example: Hypothetical Derivative Prospective Test The Hypothetical Derivative (which may be considered a proxy of the company debt) replicates the risk management desk decision in according with the notional amount and the underlying to hedge. Hypothetical Derivative - Hedged Item IRS hypothetical (perfect hedging) Initial Notional 10,000,000 amortizing Trade Date 20/09/2011 Effective Date 30/09/2011 Expire Date 30/06/2014 Issuer payment frequency Monthly Company payment frequency Monthly Flows Company Issuer 1.60% average Eur6 rounded 0.05 Conventions Company Issuer Fixing Rate monthly average day count adjustment act/360 act/360
Prospective Test IAS-39 Test can be performed on Fairmat projects by following this steps: Step #1 The first step is to enter in the panel Parameters & Functions the contract s specific parameters (i.e. notional, reset and payment dates with a specific day count convention etc.) and the market values required for the assessment of the contract fair-value (i.e. Zero Rate curve etc.)
Prospective Test Step #2 The second step is to model in the Option Map the payoff of hedged items and hedging instruments. In Fairmat the two derivatives must be mapped into two different option map scenarios.
Prospective Test Figure : Representation of the two scenarios representing the Hedging Instrument and the Hedged Item.
Prospective Test Figure : Details of a payoff which calculated the rounded mean of the one-month six months euribor average.
Prospective Test Figure : User defined Rounding function defined as ceil(x1/scale) * Scale where Scale is 0.05%.
Prospective Test Step #3 After contracts modeling, we can generate the reports, but let s check out the IAS-39 Analysis options: 1 Prospective test mode: - Custom Parallel Shifts: Zrs extracted uniformly from a defined interval. - Historical Parallel Shifts: Zrs extracted from a normal distribution calibrated from historical data. - Exogenous Shifts: Zrs shifts loaded from an external file. - Historical Principal Component Shifts: Zrs shifts calculated using the Principal Component Analysis (PCA). 2 Number of replications: the number of independent ZRs scenarios. 3 Custom parallel shift range: the range withing Zrs will be shifted. Enter R to obtain shifts taken from R U( R, R). 4 Exogenous TS realizations XML file: paths to the XML file. 5 Historical Zero Rate Time Series Depth (days): specifies the length of ZR time series used in the two historical analyses. 6 PCA % explained variance: how much variance must be explained by the PCA.
Prospective Test Figure : IAS-39 Plug-in preferences form.
Prospective Test Step #4 Run the IAS-39 analyses which can be found under the /Analysis/IAS-39/ menu: Prospective Test: the output of the prospective test plug-ins is the regression analysis (with dollar offset). : the plug-in calculates the retrospective effectiveness using the formula specified in the dollar offset method.
Prospective Test Figure : Launch of IAS-39/Prospective Test from the available analyses in Fairmat.
Example: Prospective Test Results Prospective Test Prospective Test - at 31/12/2011 The plug-in calculates the Prospective Test using linear regression. In this example the scenarios are generated assuming parallel shifts of the term structure within in the range R U( 1%, +1%). The output is represented by fit line and by the three critical test statistics to determine an effective hedge relationship: 1 Slope: 1.25 β 0.8; 2 R-Squared: R 2 > 0.96 3 F-Statistic: must be significant. The two following Figures show the Fairmat Prospective Test output.
Example: Prospective Test Results Prospective Test Figure : Fairmat s Prospective Test output: deltas on hedged item and hedging instrument calculated in different scenarios of interest rate evolution. The solid line represents the regression ( Hedging = α + β Hedged + ε), while the dashed line represents the optimal angular coefficient (-1).
Example: Prospective Test Results Prospective Test Figure : Fairmat s Prospective Test output: number of scenarios and the three critical test statistics to determine the prospective effectiveness hedging relationship when using regression analysis.
Prospective Test Example: Results - at 31/12/2011 The plug-in calculates the at testing data (31/12/2011) using the dollar offset method. Ratio = Fair Value Hedging Instrument Fair Value Hedged Item where fair value is the difference between fair-value at the testing date (Valuation Date) and fair-value at the beginning of the hedging (Trade Date). The test is passed if delta Ratio falls within the required range of 80%-125%. Note that in order to execute the retrospective test correctly, the Fairmat model must be linked to market data, because Fairmat needs to calibrate models and evaluate the contracts either at the actual Valuation Date and at the Trade/Effective Date. Fairmat uses the effective date as a trade date unless a constant called TradeDate is found on the Parameters & Function list. The following Figure shows the Fairmat output.
Prospective Test Example: Results Figure : Fairmat s output.
Fairmat Solutions
Fairmat Products overview (1/2) Fairmat Academic is a reduced-functionality free version for performing analyses for non-commercial purposes. It is also suitable for plug-in development. Fairmat Data-Link is a on demand pricing service for Fairmat Academic. Subscription periods are designed for letting you access market data and the remote valuation services only when you need them, making Data-Link an affordable SaaS solution for derivative pricing.
Fairmat products overview (2/2) Fairmat Professional is a desktop version for modeling contracts/projects and performing all related analyses such as Valuation, Greeks, Stress Tests, risk management and IAS-39 hedge accounting. Fairmat Server is an enterprise browser-based suite which allows multiple users to perform on-line and scheduled valuations/analyses/ and control on a number of contracts or portfolios.
Model calibration: example
Data-Link: Features Swap & FRA rates, Euro/Dollar futures, historical Libor/Euribor. Remote calibration (on the cloud) of interest rate models (Hull and White, Pelsser Gaussian Squared Model, Libor Marker Model) using Cap/Floor/Swap volatility matrices. Closed form pricing (using the Black Model) using above data. Data-Link is included in Fairmat Professional and available separately with Fairmat Academic.
Data-Link + Fairmat Academic Alternative (for interest rate products valuations) to suites like Bloomberg and Thomson Reuters. Ideal Tool for parties which occasional derivative pricing (i.e 10 times per year). Privacy: pricing is made on the user PC. With Data-Link (Monte Carlo Simulation), Fairmat Srl will not host sensitive data.
Data-Link: access and costs Use mode: on demand / short subscriptions, i.e. pay only when you need market data! Payment: electronic (trough credit card or wire transfer) form the url www.fairmat.com/buy Subscription length One day One week One month Cost 49.00 e + VAT* 149.00 e + VAT* 399.00 e + VAT* * VAT is applied only to Italian costumers.
Fairmat Professional Access to market data (Data-Link subscription included), Blomberg Professional integration. Additional Analysis (i.e Greeks Derivatives, Back Testing, Model Risk Analysis and others). Additional Models: Inflation, Credit Risk Modeling, Equity. Templates: availability of pre-loaded project templates (skip modeling and start pricing immediately). In addition a valuation oriented GUI is available. Access to commercial support and consulting on replication products and financial modeling. Cost: Yearly subscription (5,900.00 e + VAT*) includes support and market-data. * VAT is applied only to Italian costumers.
Thanks for attending! Fairmat Products: www.fairmat.com/solutions www.fairmat.com/plugins/documentation/ias-39-hedgeaccounting Related tutorials and examples: www.fairmat.com/resources/view/implementing-ias-39-withfairmat For any questions just write to matteo.tesser@fairmat.com or use our forums www.fairmat.com/forums Check out our upcoming webinars at www.fairmat.com/webinars