FX Manipulation

Challenge:

  • To determine in which ways and in which currency periods manipulation may have been taking place in FX markets
  • To then estimate the amount of damages caused by FX manipulation and who was impacted by said damages

Methodology:

  • Built statistical model to capture FX dynamics and determine anomalous moves around the daily 4pm WM/Reuters fixing that could have been caused by manipulative behavior, front-running, banging the close or painting the screen
  • Analyzed 27 currency pairs. These include all major G10 currency pairs as well as a selection of emerging market currencies
  • Extended damage theories to include manipulation of other fixings, (WM/Reuters, ECB fixing) manipulation of bid/ask spreads as well as manipulation in the futures market

Result:

  • Estimated frequency and quantum of alleged manipulation across a basket of the most frequently traded currencies
  • Conducted damages analysis on both a class-wide basis, as well as for a selection of large institutional investors, arising from manipulation of the WM/Reuters fixing, the ECB fixing, bid/ask spreads and the futures market

Swap Mis-selling Cases

Challenge:

  • Advise clients on suitability of swap transactions, alternative hedging strategies, market practice aspects and damages calculation.

Methodology:

  • Relied on Fideres’ direct market experience and expertise in the structuring and pricing of OTC derivatives, to model and price swap transactions and alternative hedging strategies
  • Reviewed transaction documentation and marketing material with respects to the relevant circumstances

Result:

  • Identified alternative suitable hedging strategies
  • Provided estimate of damages suffered by claimants under different scenarios and at different points in time, for the purpose of the pleadings
  • Identified failures by defendants in complying with good market practice standards

Libor Manipulation

Challenge:

  • To estimate the amount of suppression of panel banks’ respective LIBOR submissions during and post the great financial crisis and develop a damages model to determine damages suffered by investors.

Methodology:

  • Leveraging on Fideres’ knowledge of financial markets and the industry, we developed innovative approaches integrating numerous sources of banks’ borrowing pricing data
  • Elaborated cross-infection theory to estimate LIBOR suppression in different currencies

Result:

  • Estimated that LIBOR manipulation continued until the middle of 2012
  • Generated model for estimating “correct” LIBOR levels in different currencies
  • Estimated daily banks’ borrowing costs between 08 and 12
  • Determined daily amount of LIBOR suppression during the period analysed

Shareholder Dispute

Challenge:

  • Identify missing or mis-leading disclosure or relevant financial information in the rights-issue prospectus issued by the defendant.

Methodology:

  • Cross referenced information disclosed by defendant in the rights-issue prospectus with other sources to identify potential inconsistences, missing disclosure and mis-categorisation of financial liabilities and write-down provisions.

Result:

  • Provided detailed technical input in the particulars of claim which allowed claimants to issue detailed proceedings against the defendant.

CDS Antitrust Case

Challenge:

  • Develop preliminary damages model to estimate excess transaction costs caused by the alleged collusion.

Methodology:

  • Study benefits brought by transparency created through introduction of central clearing houses and regulated exchanges in other financial products.

Result:

  • Estimated class-wide damages resulting from the anti-trust behaviour
  • Estimated the approximate damages suffered for individual claimants

Precious Metals Markets

Challenge:

  • Identify signs of market manipulation and benchmark rigging in precious metal markets.

Methodology:

  • Developed new methodologies to analyse trading data in the physical and futures markets
  • Develop suite of methodologies including traditional collusion filters and financial market models to identify anomalous market behaviour/trading patterns
  • Applied game theory methodology to analyse benchmark panel members’ submission patterns

Result:

  • Elaborated market manipulation theory used in class-action complaints filed in the US on Gold, Silver, Platinum/palladium cases
  • Developed preliminary damages model

Drug Cartels

Challenge:

  • To identify the extent of collusion among pharmaceutical manufacturers in the generic prescription drug market
  • Develop economic analysis on collusive markers and plus factors that help distinguish collusion from competition

Methodology:

Analyse drug pricing and use quantitative measures to identify potential price collusion using:

  • Structural break tests,
  • Market concentration measures,
  • Price and quantity markers, eg the degree of correlation amongst manufacturers,
  • Various other plus factors and collusive markers

Result:

  • Identified over 90 generic drugs that experienced an average price increase of 1,350% and showed a similar timing of sales increases between manufactures
  • Developed economic analysis used for the filing of four drug collusion complaints based on economic evidence with total damage estimates in the region of USD 5.2 billion
  • Identified a number of potentially new issues in regards to the role of Pharmacy Benefit Managers (PBMs) including the potential conflicts of interest, complex rebate structures and general lack of regulation

Closet Indexers

Challenge:

  • Replicate the methodology and results of the European Securities and Markets Authority (ESMA) study into Closet Index Tracking Funds (funds which advertise as actively managed, but in reality, track a benchmark)
  • Provide detailed analysis and a report on the methodology used and results

Methodology:

  • Filter the universe of actively managed funds for the same criteria used by ESMA to produce a sample of 2333 funds.
  • Further filtering removed funds without available data to analyse, resulting in a final sub-sample of 1014 funds.
  • Classify the sub-sample of funds into categories based thresholds for each of the key statistical metrics: Active Share, Tracking Error and R-Squared.
  • Analyse the performance of the worst offenders by stripping out the effect of management fees to identify variances between the fund and its benchmark’s performance

Result:

  • Fideres found that over 16% of European UCITs funds of the sample analysed show characteristics that may indicate they are potential closet indexers
  • The study was mentioned in a Financial Times article
  • Results of the study closely approximated the results published by ESMA (within one percent for each classification)