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FX Market Dynamics Methods for Trading, Forecasting Risk Assessment

1. Disclaimer. The information contained herein, including any expression of opinion, and any information which accompanies this presentation or which is supplied subsequently, has been obtained from or is based upon sources believed to be reliable but has not been independently verified and is not

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FX Market Dynamics Methods for Trading, Forecasting Risk Assessment

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    1. 0 FX Market Dynamics Methods for Trading, Forecasting & Risk Assessment

    2. 1 Disclaimer The information contained herein, including any expression of opinion, and any information which accompanies this presentation or which is supplied subsequently, has been obtained from or is based upon sources believed to be reliable but has not been independently verified and is not guaranteed as to accuracy or completeness, although Société Générale and its affiliated companies (“SG”) believe it to be fair and not misleading SG is not, and will not be, responsible for ascertaining whether all risks associated with the transactions contemplated herein have been identified or disclosed, nor for providing advice to you as to whether you should enter into the transaction or on the documentation to be used for the transaction or on the merits of purchasing any investment or otherwise. You must make your own assessment of the transaction and the risks and benefits associated with it and of all the matters referred to in the preceding sentence. Neither SG nor any of its officers or employees makes any representation as to, or assumes any responsibility or liability for, the merits, suitability, expected or projected success, profitability, performance or benefit of any such transaction. SG recommends you enter into transactions only after having considered, with the assistance of external advisors, without reliance upon SG, the specific risks of any transaction, including but not exclusively, the legal, tax and accounting implications so as to enable you to appraise and understand the financial and legal terms of such transaction and to enter into such transaction in reliance on your own judgment and that of your advisers and not on any views expressed by SG This presentation was prepared exclusively for your benefit and your internal use. Neither the presentation nor any of its contents may be disclosed to, reproduced or used or relied upon by, any other person or used for any other purpose without the prior written consent of SG

    3. 2 Forex Markets – Deep, Liquid and Accessible $1.9trn average daily turnover Almost continuous trading 24/7 Growth in currency overlay mandates Broad “understanding” of market

    4. 3 Analysts Comes in All Shapes and Sizes Commentators Economists Technical Analysts Quant analysts

    5. 4 Styles of Analysis - All Are Important Commentary Econometrics / Statistical methods Technical Analysis Quantitative trading Signal generation using all available datasets Beg, borrow and steal from other areas of expertise News interpretation Data interpretation News interpretation Data interpretation

    6. 5 A Combined Approach to FX - A Scorecard Build a committee / agenda / process Set up infrastructure for FX views Asset allocation made from aggregating views Deploy trades and risk management

    7. 6 Pitfalls of the Scorecard Market timing and forecast objectives Arbitrary weighting scheme Balancing the number of trades More of a management tool than trading tool Budget rate versus hedging targets Netting and cash flow considerations “Consensus” risk from the panel Budget rate versus hedging targets Netting and cash flow considerations “Consensus” risk from the panel

    8. 7 The Commentators Approach News for market consumption Sensitivity to ‘new’ information Broader knowledge of ‘anecdotal’ information Typically hard to quantify Selling a view Is there a dataset to test the hypothesis Scheduled or otherwise Will not stick their neck out Backward looking Is there a dataset to test the hypothesis Scheduled or otherwise Will not stick their neck out Backward looking

    9. 8 Economic Analysis for Markets Data released each week, month or quarter Monetary policy is decided by people Inflation targeting regime versus growth models Huge debate about market relevance Markets can deviate from the economic backdrop Markets are volatile Economics may not be the largest driving force

    10. 9 Econometrics and Statistical Methods Linear regression Many variables feed into economy Only so many are relevant Forecast target: average or volatility

    11. 10 Examples Include… ARMA, ARIMA family of models Seasonality Multiple VAR models Multifactor models ARCH GARCH type models Volatility models Parametric and non-parametric approaches Distribution assumptions

    12. 11 Problems Associated With Statistical Methods Over fitting and parameterisation Sample bias Unstable correlation structures Explanation factor

    13. 12 Investigating Anecdotal Evidence

    14. 13 Case Study – Gold & AUD/USD

    15. 14 Case Study Conclusions

    16. 15 Extending the Case Study Framework

    17. 16 Statistical Models – Multiple VAR Make the assumption of normal relationships Assume stable relationship over time Most used explain use instantaneous relations Weighting scheme problematic

    18. 17 Technical Analysis Trend following tendencies of markets Contrarian indicators to pick turning points Chartist approaches – market price determined Self fulfilling prophecies on levels

    19. 18 Trading Technically in 2006

    20. 19 Trading Technically - Highlights

    21. 20 Herding, Behavior and Vol Clustering Taking a position because everyone else is Being a ‘tracker’ not an ‘outlier’ Never typically used in a positive sense Often associated with ‘stops’ Psychology plays a large part Datasets on other variables

    22. 21 Speculative Positioning Speculative positions reports are useful Positions are explained by momentum & carry Market can stay extreme for significant periods Deployed as a contrarian indicator

    23. 22 Speculative FX Positions

    24. 23 Price Action Problems Many indicators to choose from Split into trend following or mean reverting Quantitative trading possible Benchmarking issues / slippage

    25. 24 Fuzzy Logic and GA GA = genetic algorithm Learning by simplifying inputs Garbage in – garbage out Fuzzy Logic Loosening strict conditions of GA – conditionality Theoretical way to handle large state space Tools and expertise required Deep into ‘black box’ territory

    26. 25 Ex-post Rationalization, Hindsight Economics

    27. 26 Moving Into the Quantitative Space

    28. 27 Quantitative Trading

    29. 28 Market Forces That Are Quantifiable Price action Economic news Monetary policy decisions Political calendar events

    30. 29 Markets Are Volatile - But Have Structure

    31. 30 A Random Walk With Drift

    32. 31 Mathematically Speaking… We live in a “normal” world Confidence intervals in all estimations Market prices are “non-stationary” Make mathematical tests on returns

    33. 32 But the Short Term Markets Know… Money made in non-normal times event risks Timing of trades is imperative Data and event risks matter How to frame the problem is critical There is a microstructure to the market

    34. 33 Cyclical Activity

    35. 34 Last Weeks “Microstructure” Details

    36. 35 Impact of Economic News Economic data is much more predictable Key economic data typically has a “consensus” There are ways to re-frame economic news Better / Worse than expected Slowing or accelerating

    37. 36 Economic Data and Ways to Re-frame

    38. 37 We Can Re-base or Re-frame Time Series Price based Classical time series analysis Technical analysis Tick based Volume rebased price series Economic based Economic calendar known in advance

    39. 38 Event Horizons Analysis Can use an implied distribution Can use historical data VaR and extreme value theory Can be used to estimate volatility

    40. 39 Empirical Distribution of EUR/USD

    41. 40 Data Mining – A Useful Tool A technique that has a bad name Empirical results based research Non-parametric Often not benchmarked

    42. 41 Monetary Policy Decisions Policy communication is important Made through regular meetings & publications How can the impact of this news be understood This is typically not the same over time

    43. 42 Sterling & UK Rate Decisions ‘Surprise’ rate decisions How does the market react Build the reaction function Risk over over interpretation

    44. 43 What About Sterling Seasonality? Cable has had a bias to appreciate in December Must have to see a rational for the seasonal Once discovered much easier to push story This year was very similar to 2004

    45. 44 Political Uncertainty Meetings & elections are known in advance Uncertainty is disliked by the markets Sentiment around future event risks is not inefficiently priced in by derivative markets Data mining lends itself to these problems

    46. 45 Conclusions and Thoughts Many ways to undertake FX analysis No one way better than another But there are many pitfalls to be avoided Simply look forward and for the next big issue

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