Audi 2015 Annual Report Download - page 273

NOTES TO THE CONSOLIDATED FINANCIAL STATEMENTS
ADDITIONAL DISCLOSURES
>> 273
/// OTHER MARKET RISKS
The measurement of other market risks pursuant to IFRS 7 is
also carried out using sensitivity analyses within the Audi Group.
Hypothetical changes to risk variables on the balance sheet date
are examined to calculate their impact on the corresponding
balance sheet items and on the result after tax.
Depending on the type of risk, there are various possible risk
variables (primarily share prices, commodity prices, market
interest rates and market prices of used cars).
The sensitivity analyses carried out enable the following other
market risks to be quantified for the Audi Group:
EUR million 2015 2014
+10% – 10% +10% – 10%
Fund price risks
Effects on equity with change in share prices 20 – 23 21 – 30
Commodity price risks
Effects on equity with change in commodity prices 13 – 13 18 – 18
Effects on profit after tax with change in commodity prices 26 – 26 42 – 42
Residual value risks of used cars
Effects on profit after tax with change in market prices 219 – 219 194 – 194
+100 bps – 100 bps +100 bps – 100 bps
Interest rate change risks
Effects on equity with change in market interest rate – 65 65 – 74 74
Effects on profit after tax with change in market interest rate 14 – 14 3 –3
36.5 / METHODS OF MONITORING THE
EFFECTIVENESS OF HEDGING RELATIONSHIPS
Within the Audi Group, the effectiveness of hedging relation-
ships is evaluated prospectively using the critical terms match
method, as well as by means of statistical methods in the form
of a regression analysis. The retrospective evaluation of the
effectiveness of hedges involves a test in the form of the dollar
offset method or in the form of a regression analysis.
In the case of the dollar offset method, the changes in value of
the underlying transaction, expressed in monetary units, are
compared with the changes in value of the hedge, expressed in
monetary units. All hedge relationships were effective within
the range specified in IAS 39 (80 to 125 percent).
In the case of regression analysis, the performance of the
underlying transaction is viewed as an independent variable,
while that of the hedging transaction is regarded as a depend-
ent variable. The transaction is classed as effective hedging if
the coefficients of determination and escalation factors are
appropriate. All of the hedging relationships verified using this
statistical method proved to be effective as of the reporting date.
The ineffectiveness resulting from cash flow hedges in 2015
led to a EUR 19 million decrease in the financial result. In 2014
the ineffectiveness amounted to EUR 15 million, which led to
an increase in the financial result.