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Monitoring the Economy: an Application of Multivariate Real-Time Signal Extraction

Monitoring the Economy: an Application of Multivariate Real-Time Signal Extraction. http://blog.zhaw.ch/idp/sefblog http://www.idp.zhaw.ch/usri http://www.idp.zhaw.ch/MDFA-XT. Pot-Pourri Recent Experiences. Basic topics Real-time multivariate filtering What it is and what it isn‘t

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Monitoring the Economy: an Application of Multivariate Real-Time Signal Extraction

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  1. Monitoring the Economy: an Application of Multivariate Real-Time Signal Extraction http://blog.zhaw.ch/idp/sefblog http://www.idp.zhaw.ch/usri http://www.idp.zhaw.ch/MDFA-XT

  2. Pot-Pourri Recent Experiences • Basic topics • Real-time multivariate filtering • What it is and what it isn‘t • Customized optimization criteria • Performances (USRI) • Misspecification and the `financial crisis‘

  3. A Selection of Basic Topics USRI MDFA-XT

  4. List of Important Requirements • A priori knowledge: • Data selection, constraints • User requirements: customization • Minimize Revisions • Reliability: effective noise elimination • Timeliness: detecting relevant patterns fast • Revisions/publication strategy: • Reveal true historical performance

  5. Requirements • Consistency • Classical-, growth- and acceleration cycles • Various statistics emphasize a common target/proceeding • Replicability/transparency: • algorithm, no human intervention (subjective judgemental adjustments) • Real-Time Benchmarking: • Real-time comparisons

  6. USRI http://www.idp.zhaw.ch/usri • A priori knowledge: NBER-Design • User requirements: MDFA • Revisions: WYSIWYG-Design • Consistency: Unifying statistical design for all three cycles • Replicability: Excel sheet, USRI-site • Benchmarking: http://blog.zhaw.ch/idp/sefblog

  7. Real-Time Multivariate Filtering What it is What it isn‘t

  8. Estimation Problem

  9. Pseudo-Multivariate Filtering • Direct vs. Indirect Filtering: • aggregate data prior to univariate filtering or (univariate) filtering prior to aggregation? • Direct: filtering the output of a dynamic factor model • Linear univariate (HP, CF, X-12-ARIMA) • Non-linear univariate: MS-model • Indirect: Seasonal adjustment • It was/is impossible to find unadjusted US-macrodata for USRI • Inconsistency

  10. Objectives • Statistical agency: minimize revisions • Forecasting institute/fund manager/trader: detect turning-points • Neither problem is related directly to one-step ahead mean-square optimization • So why should we rely on maximum likelihood?

  11. Customized Optimization Criteria

  12. 1. Revisions Univariate • Minimize a (uniformly) superconsistent estimate of an (uniformly) efficient estimate of the filter mean-square error • (Customized) Efficiency enters explicitly in the Design of the Optimization Criterion

  13. 2. Operationalizing Fuzzy `Timeliness‘ • λ>1: emphasize the time delay in the pass-band • λ=1: best level filter

  14. 3. Operationalizing Timeliness and Reliability • Stronger damping of high-frequency noise in stop-band • Smaller time delays in pass-band • W(ω) is monotonic (increasing) and λ>1

  15. 4. Multivariate: Revisions Cointegration (Rank=1)

  16. 5. MultivariateTurning-Points • Insufficient space…

  17. Upshot • There are meaningful alternatives to the ubiquitous `one-step ahead‘ paradigm.

  18. Performances

  19. Look-Back • 2005/2006: KOF-economic barometer, Dainties • 2007/2008: Forecasting competitions • 2008: Health-care forecasts • 2008: Output-gap US- and Euro-GDP • March 2009: USRI • CIRET-conference Sept 2008 • MDFA Fall 2008 • Oct. 2009: MDFA-XT • 2010: EURI, competition • Collected evidences for systematic outperformance in various application fields

  20. Performances USRI • On-line since March 2009 • http://blog.zhaw.ch/idp/sefblog • CFNAI • OECD-CLI • LEI and CEI • ADS • MS-designs: Chauvet, Piger • Troughs of acceleration-, classical- and growth-cycles as early as December 2008, April 2009 and June 2009 without subsequent revisions

  21. MDFA-B and MDFA-EClassical and Acceleration Cycles

  22. USRI and Fundamental Trading

  23. Financial Trading Google for “MDFA-XT” First guess

  24. MDFA-XT Unfrequent

  25. MDFA-XT (Unfrequent to Mid)

  26. MDFA-XT Mid

  27. MDFA-XT Mid to Frequent

  28. MDFA-Frequent

  29. Model Misspecification OECD-CLI http://blog.zhaw.ch/idp/sefblog/index.php?/archives/35-Did-you-say-a-negative-trend-growth-How-traditional-bandpass-filters-distort-underestimate-and-shift-the-latest-2008-recession!.html

  30. 10 Year HP-filter

  31. GARCH(1,1) Log-Returns IPI

  32. Reconstructed HP-Compatible IPIRemove Variance Effect, Retain mean-Effect

  33. Conclusion

  34. Public Exposition • Welcome (positive) pressure for lazy minds • Public exposition `pusher’ • Careful prototypical setting • Mental presence • Frequent performance check • Discussions with users • Ideas for improvements

  35. Links • http://blog.zhaw.ch/idp/sefblog • http://www.idp.zhaw.ch/usri • http://www.idp.zhaw.ch/MDFA-XT

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