Corporate Risk Management and Hedge Accounting Under the Scope of IFRS 9

The prospective (resp. retrospective) hedge effectiveness test is a forward-looking (resp. backward-looking) evaluation of whether or not the changes in the fair value or cash flows of the hedging item are expected to be highly effective in offsetting the changes in the fair value or cash flows of the hedged item over the term of the relationship (resp. since the date of designation).

As rebalancing does not result in de- (or -re) designation of a hedge when it changes, the hedging relationship is maintained while hedge ineffectiveness is recognised immediately before adjusting the hedge relationship.

The MRS-LR-DCC model leads to estimate a long run relationship between spot and futures prices and DCC-GARCH errors to connect to the idea of a disequilibrium measured by a lagged basis with this of uncertainty modelled by DCC-GARCH, across market regimes.

Kleindorfer and Li (2011) model portfolio strategies of power firms that choose a portfolio of electricity and carbon derivatives to maximise their expected profit under the constraint of minimizing its VaR exposure.

The credit risk can take the form of either the counterparty’s credit risk or the company’ credit risk.

For a hedging relationship with a correlation between the hedged item and the hedging instrument that differs from the 1:1 relationship, risk managers will generally adjust the hedge ratio to improve its effectiveness.

The FASB considers a hedge relationship, which is rebalanced as a new relationship that implies a fresh start to hedge documentation and hedge effectiveness assessment.

Berta et al. (2017) show that the distinction between hedging and speculation is irrelevant in the case of carbon derivatives. Every hedging position of EU ETS companies requires a speculative position to bear the risk as a counterparty; so every hedging transaction is simultaneously a speculative one. While speculation is regarded as necessary to help firms to hedge against price volatility, speculation creates price volatility. Accordingly, we consider that both hedging and speculative derivatives trades as financial instruments.

The nine sectors covered by the EU ETS are the following: combustion, cement, ceramics, coke ovens, glass, iron and steel, metal ore, paper and board, refineries. Power firms that hold individual factories and cogeneration plants belong to the ‘combustion’ sector.

The economic crisis, which reduced carbon emissions more than anticipated and high imports of CERs, has generated a 2 billion surplus of EUAs at the end of 2014. This has led a significant fall in carbon prices. In July 2015, the EC has decided to postpone the auctioning of 500 million EUAs in 2016 and 2017. Given that this decision reduces drastically the volume of EUAs auctioned, the spot (auction) EUA market becomes much less liquid than previously and EUA spot prices become artificially much more volatile. Therefore, the variance of spot (unhedged) and futures (hedged) EUA portfolio that we estimate would have been necessarily affected after 2015. In this respect, we have considered the period 2013–2015 in order to study the carbon hedging strategies in Phase III given a EUA spot market offering comparable conditions of liquidity and price volatility.

We follow the rules applied by Berta et al. (2017) to correct missing data related to verified emissions and new entrants when it impacts the short positions of installations. See Berta et al. (2017) for more details.

Since Bluenext closed their activities in December 2012, we use EEX spot prices between 2013 and 2015.

Before using the Johansen trace test for detecting cointegration, we apply the Augmented Dickey-Fuller and Phillips-Perron unit root tests to all series. The results show that the series have a stochastic trend in their univariate time-series presentations (non-stationary), while first differences are stationary.

If the position taken in the EUA or CER futures changes over time, the hedging strategy is dynamic implying that the optimal hedge ratio is time-varying and the position in the futures market continuously rebalanced.

After interviewing 13 experts and managers of power companies, Schopp and Neuhoff (2013) conclude that annual rollover strategies are largely employed to hedge long-term commitment through the purchase of EUA December futures on annual basis.

Since EUA and CER futures are affected by daily marking-to-market cash requirements, adjustments might be made as “tailing” the hedge. These adjustments reduce the size of hedge ratios especially for longer hedges.

Since the optimal hedge ratio is obtained by dividing the covariance between spot and futures returns by the variance of the futures return, any impact on the variance of the futures returns will affect the value of hedge ratios.

The hedge effectiveness percentages estimated from the second nearest EUA and CER December futures are very similar to those estimated from the front EUA and CER December futures both in Phase II and III.

The IASB issued a discussion paper on ‘Accounting for dynamic risk management: a portfolio revaluation approach to macro hedging’ in April 2014 (IASB, 2014). After having received comments of experts, the IASB expects to release the core IFRS 9 model of macro hedging by the second half of the year 2019.