Derivative

• Prepared by Lena Boneva, Benjamin Bninghausen, Linda Fache Rousov and Elisa Letizia Data on derivatives transactions have recently become available at a number of central banks, including the ECB, and have opened up new avenues for analysis.
• Collected as a result of reforms of the over-the-counter (OTC) derivatives market, which were primarily designed to counter systemic risk, the data have numerous applications beyond the domain of financial stability.
• It demonstrates how data gathered under the European Market Infrastructure Regulation (EMIR) can be used to better understand two types of derivatives market that are of particular importance for central bank analysis, namely the interest rate derivatives and inflation-linked swap markets.
• Such quantity-based indicators can complement other, more established indicators of interest rate expectations, such as forward rates or survey-based measures.

1 Introduction

• In response, G20 leaders pledged at the Pittsburgh summit in September 2009 to reform OTC derivatives markets to improve their transparency, prevent market abuse and reduce systemic risks.
• In Europe, this initiative was formalised in 2012 in the European Market Infrastructure Regulation (EMIR).
• [2] Following a brief introduction to the EMIR data (see Section 2), this article presents two examples of such uses.
• Second, the article looks at structural activity patterns in euro area inflation-linked swap markets (see Section 4).
• Both applications demonstrate the wide potential for the use of EMIR data in central bank analysis.

2 The EMIR data

• Daily transaction-by-transaction derivatives data are then made available to over 100 authorities in the EU, depending on their mandate and jurisdiction.
• For example, the ECB obtains a subset of the data reported by euro area counterparties.
• Owing to their volume, velocity and variety, the EMIR data can be classified as big data, which poses many challenges for using them.
• In cooperation with the European Systemic Risk Board (ESRB), the ECB has developed an EMIR-dedicated IT infrastructure to store and access the data received from all trade repositories.
• Despite the significant improvement in data quality since the launch of EMIR reporting in 2014, a careful data cleaning procedure has to be applied before the data can be used for policy analysis; for example, observations are deleted when both the market and notional values are missing or when the notional value is considered an outlier.
• [5] This article focuses on data between 2 May 2018 and 12 June 2019, as the cleaned data even as a time-series are of sufficiently good quality and easily accessible through the EMIR IT infrastructure.

3 Inferring market expectations for future interest rates from EMIR data

• The interest rate derivatives market allows market participants to trade financial products linked to future interest rates.
• The market value of these contracts changes as interest rates move, and investors can use them to hedge against movements in interest rates or for speculative purposes.
• By analysing the positioning of participants in the market, some inference can be made about their views on the outlook for interest rates.
• The market positioning indicators based on EMIR data help to inform central bank analysis.
• Information on the positioning of certain groups of investors in interest rate derivatives can complement price-based indicators and surveys, which are both commonly used to infer financial market expectations for monetary policy or the macroeconomic outlook.
• An investors net long (or net short) position captures how and to what extent they may profit from future interest rate movements.
• Where an investor simultaneously holds long and short positions, exposure to future interest rate movements is determined by netting all positions.
• [7] The positioning indicator constructed here aims to single out informed investors who actively take positions in interest rate derivatives on the basis of their expectations for future interest rates.
• Since the positioning indicators are intended to capture exposure to general interest rate movements rather than unusual developments, this suggests a preference for derivatives with linear payoffs.
• The full interest rate derivatives market in the euro area is very large in terms of both volume and the number of instruments it contains (Chart 1).
• As of June 2019 the total outstanding notional amount in interest rate derivatives was around 200 trillion, which accounted for two-thirds of the total euro area derivatives market.
• [13] Interest rate swaps and futures are key instruments in the interest rate derivatives market.
• The futures market is smaller than the swaps market, but is exchange-traded and hence much more standardised and extremely liquid.
• Chart 1 The euro area interest rate derivatives market (EUR trillions)
• The positioning indicators are based on EURIBOR futures contracts, owing to their significant information content as regards euro area interest rate developments.
• As suggested by market intelligence, informed investors make extensive use of EURIBOR futures, primarily on account of their substantial liquidity and high degree of standardisation.
• Investors that need to adjust their positions may often prefer futures contracts to interest rate swaps, since it is easier to close out existing positions.
• Moreover, futures on the three-month EURIBOR are attractive because of their direct link to euro area short-term interest rate developments at specific horizons.
• The basis risk of tracking EONIA through a EURIBOR futures contract is fairly limited at present given the stable spreads between the two.
• [15] The net long position (long minus short) of each investor is normalised by their gross position (long plus short).
• Net long positioning has trended upwards since the start of 2019, consistent with market expectations of a more accommodative monetary policy (Chart 3).
• The one-year EONIA forward rate one year ahead provides another approximation of how interest rate expectations have evolved over the period under consideration.
• Consistent with these developments, informed investors have increased their net long positions over the same period.
• Further data analysis may also help identify sectors whose positioning, on average, appears to be the most indicative of the markets price formation mechanism.
• This box explains how EMIR data are enriched to obtain such a classification.
• While EMIR data contain a field with information on the sector of a reporting counterparty, this information suffers from some limitations.
• The first relates to data quality: the sector reported by some counterparties varies over time, and in some cases the sector is missing.
• The second limitation is conceptual: the EMIR sector classification is not sufficiently detailed for many central bank purposes and does not single out entities with key roles in the derivatives market.
• [18] To overcome these limitations, EMIR data are enriched with eight data sources to obtain a sector classification.
• As a last source in the hierarchy, the sector given in the EMIR data is used, but only if reported consistently.
• Chart A Identifying counterparty sector in EMIR data: breakdown by notional value (percentages of gross notional value of outstanding contracts)

4 Examining euro area inflation-linked swap markets

• Inflation expectations play a central role for the ECB, since its primary objective is to maintain price stability in the euro area.
• [20] EMIR data allow a first quantitative look at the structure of the euro area inflation-linked swap (ILS) market.
• The EMIR data complement this type of information and allow it to be cross-checked by offering a quantitative, more systematic look at trading activity in euro area ILS markets.
• [21] The data suggest that activity in the euro area ILS market is dominated by swaps linked to aggregate euro area inflation rather than national consumer price indices.
• [23] On that basis and in light of the above observations, monitoring aggregate euro area inflation expectations in ILS markets seems most reliable.
• Chart 4 Euro area inflation-linked swap market activity, by underlying reference index
• EMIR data also show that activity is relatively concentrated in the ten-year, five-year, two-year and one-year maturity segments.
• Chart 5 shows that the four most active points on the curve account for around 50% of all activity in euro area HICPxT-linked swaps.
• The fact that almost a quarter of activity is clustered at the ten-year spot point, with the second-largest share at the five-year spot point, has an interesting corollary.
• Chart 5 Activity in euro area HICPxT-linked inflation swaps, by maturity
• Chart 6 sorts transactions into different maturity buckets instead of focusing on individual maturity points.
• It further shows sector pairs involving banks on at least one side of the transaction.
• Apart from highlighting the dominance of bank-bank and bank-investment fund transactions across maturity buckets, Chart 6 shows notable activity of hedge funds at short maturities.
• Chart 6 Shares of euro area HICPxT-linked swap transactions for selected sector pairs, by maturity
• More precisely, while the article has shown that activity in longer-dated euro area ILSs of 15 years and beyond is not negligible compared with shorter-dated maturities, the sectoral analysis indicates that a relatively large share of that activity stems from pension funds.
• Thus, when price sensitivity is also factored in, the information content of longer-dated ILS rates may be lower than suggested by overall activity in that maturity bucket.
• Overall, EMIR data help uncover a number of interesting structural features of euro area ILS markets, suggesting that further EMIR-based analysis can help the ECB better assess future developments in these markets.
• EMIR data are thus an important addition to the ECBs toolbox for analysis of euro area ILS markets.

5 Conclusions

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