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Nicolas Maystre (joint work with David Bicchetti) UNCTAD Bank of England, London, 25 May 2012

The synchronized and long-lasting structural change on commodity markets: evidence from high frequency data. Nicolas Maystre (joint work with David Bicchetti) UNCTAD Bank of England, London, 25 May 2012.

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Nicolas Maystre (joint work with David Bicchetti) UNCTAD Bank of England, London, 25 May 2012

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  1. The synchronized and long-lastingstructural change on commodity markets:evidence from high frequency data Nicolas Maystre (joint work with David Bicchetti) UNCTAD Bank of England, London, 25 May 2012 Disclaimer: the views and opinions expressed herein are those of the author and do not necessarily reflect those of the United Nations Conference on Trade and Development.

  2. Motivation Intense debate regarding the causes of the recent sharp price movements of many primary commodities • Economic fundamentals • Rising global demand (rapid and steady growth in large developing economies) • Supply shocks (adverse weather; export bans) • ‘Financialization’ of commodity marketsi.e. the increasing role of financial motives, financial markets and financial actors in the operation of commodity markets(UNCTAD, Trade and Development Report, 2009)

  3. Non-exhaustive literature review

  4. Some limitations of previous studies • Use of daily data (at best) • Look at passive investment strategy (index funds) • Unrecorded participants What happens during the day? • Need to look at intraday data • Consider actual trades & most liquid futures Main findings • Identify a synchronized structural change across commodities in the course of 2008 (sharp increase after Lehman’s collapse) • Link to high frequency and algo trading

  5. Thomson Reuters Tick History database • Provides millisecond-time stamped tick data since 1996 • Trades and Quotes messages (level 1) • Market depth (level 2) • All asset classes • Equities • Fixed Income • FX • Futures • Options • Covers more than 45 million unique instruments across 400+ exchanges

  6. Electronic trading caused trading activities to increase dramatically…

  7. The presence of HFT & AlgoMonthly WTI front month contract volumes and tick, as well as the ratio between the two, 2007m1-2011m12 Source: Bicchetti & Maystre (2012) calculations based on Thomson Reuters Tick History database

  8. Methodology 1. We compute the log returns of the mean prices at 1-hour, 5-minute, 10-second and 1-second intervals. 2. We calculate a moving-window correlation coefficient (MWC) at time (t) between two series (rx and ry) at frequency (f) with a window width set to 15: where and N.B. We exclude weekend observations (avoid composition effect, no trade in the years prior to the introduction of electronic trading)

  9. Distribution of the MWC coefficients WTI and the E-mini S&P 500 futures (front month) Source: Thomson Reuters Tick History database

  10. Source: Thomson Reuters Tick History database

  11. Annual distribution of rolling correlationsreturns on the WTI and the E-mini S&P 500 futures (front month)1997-2011 Source: Bicchetti & Maystre (2012) calculations based on Thomson Reuters Tick History database

  12. Monthly median of rolling correlationsreturns on the WTI and the S&P 500 futures, 2007-2011

  13. Monthly medians of 5-min rolling correlationsreturns on selected soft commodities and the E-mini S&P 500

  14. Results discussion • The structural break remarkable in many aspects: • The wide range of commodities involved • The synchronization of this phenomenon • The similarity of the evolution across commodities

  15. Similarities on non-commodity marketsMonthly distribution of the 5-minute rolling correlations between the returns on the EUR/USD and the E-mini S&P 500 futures (front month), 2007m1-2011m12 Source: Bicchetti & Maystre (2012) calculations based on Thomson Reuters Tick History database

  16. We identify 3 inflection points on the EURUSD/E-mini S&P500: • 2007m8, 2008m3, 2008m9 • Coincides with major financial shocks: • Country Wide Financial/Subprime burst • Bear Stearns • Lehman Brothers • Investigate by looking at WTI/EURUSD relation

  17. Monthly distribution of the 5-minute rolling correlationsreturns on the EUR/USD and the WTI futures Source: Bicchetti & Maystre (2012) calculations based on Thomson Reuters Tick History database

  18. Similarities with the EURUSD futures • Increasing correlation between WTI and EURUSD starts around summer 2007 • Gradual change, not sharp like WTI & SP500 • Temporary decline before Libyan uprising. Probably due to a new phase of the eurozone crisis starting in Nov 2010 • Return to positive correlation between EURUSD&WTI afterwards What does that mean? • Root cause of the structural change beyond stock & commodity markets • Although commodities traded in USD, it is unlikely that commodity traders have a significant and permanent effect on FX markets. Daily turnover on currency markets was estimated to be $3.98 trillion (BIS, 2010).

  19. What does that mean? • Questions to consider: • Why do the median correlation depart from zero and become negative at the end of the 2008Q1, and why this trend then switch into positive territories in late Sept 2008? • Why do the median correlations remain so high from Sept 2008 onwards? • What is the driving force behind this structural change?

  20. Several hypothesis: • Decoupling? Not very convincing • Risk on/risk off? Maybe, but why at such high frequency? • Inflation fears? unlikely • Liquidity/volatility changes? Marginal, cf. VIX chart. Again, why at such high frequency? • Shift from supply to demand shocks? why at such high frequency? Why does it last? • Shift in composition of markets participants? Probably • Driven by Algo & HFT? Very likely, especially when one consider the 1-second correlation

  21. What does that mean? Source: Bicchetti & Maystre (2012) calculations based on Thomson Reuters Tick History database

  22. Europe catching up Source: Bicchetti & Maystre (2012) calculations based on Thomson Reuters Tick History database

  23. Reactions to Bicchetti & Maystre (2012) • HFT fund in NY: • “HFT can refer to any of a very broad range of strategies, most of which are faster versions of non-fundamental value strategies which have been employed in the markets for decades”

  24. Reactions to Bicchetti & Maystre (2012) • HFT fund in Hong Kong: • “Yes, you are probably right that the increase in short term correlation is caused by HFT! I do think that also there, there is some kind of a herd behaviour or trend following. In my opinion, due to some trigger (maybe the introduction of electronic exchanges, like u mentioned) commodities start to be more correlated, so some HFT try to take advantage, because of that there is more correlation which attracts more HFT, this again drives up correlation and draws in more HFT etc etc”

  25. Conclusion • Recent financial innovations on commodity futures exchanges have an impact on the price discovery process • This result questions the diversification strategy and portfolio allocation in commodities pursued by financial investors • Trend following strategiesShift market away from fundamentals (Frankel & Froot 1990) • Positive feedback characteristics (Smith 2010) • As commodity markets become financialized, they can be more prone to external destabilizing effects. Deviation from their fundamentals exposed them to sudden and sharp corrections.

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