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Indicators, Predictive Analytics        & Forecasting        Evangelos Otto Simos, Ph.D.                                  ...
Outline• Going Beyond Raw Data• Forecasting with Hundreds of  Drivers• Case: Forecasting a Hotel  Market• US & Global Outl...
GoingBeyondRawData         April 11, 2013   4
Types of Indicators• Quantitative     •   GDP, Industrial Production, Employment• Qualitative     •   NAPM Survey, Consume...
Case: PMI: NAPM Diffusion Index                                                  NAPM History  80.0  70.0  60.0  50.0  40....
A closer Look at PMI Analytic                 Closer Look: NAPM 2012-13 56.0                                              ...
Housing Sales: Is that a Recovery?                               April 11, 2013   8
Consumer Confidence• Media pays attention to composite indices• Consumer spending is about 70% of GDP• Overall indices fou...
Consumer Confidence (continued)•   Consumers are not forecasters•   Overall indices are loaded with answers on questions  ...
Economic Policy: Fed in a printing modeagain                               April 11, 2013   11
Nominal Vs. Real•   Retail Sales•   Construction Spending•   Orders (for Durables, Capital Goods)•   Average Wage Rate ($ ...
Dealing With InformationA modern data infrastructure            Analytics for predictive                                  ...
Many Drivers: Blessing or Curse?• Advances in information technology provide  access to thousands of economic and  busines...
Modeling Hundreds of Predictors• Classical VS. Modern Modeling• Let y denote a business indicator to be  forecast (like Ho...
Forecasting with Hundreds ofPredictors• Let Z be a set of a few “composite” or so-called  “diffusion” indicators that capt...
The Modern Approach•         The General Modern Econometric Model is           y = αX + βZ + ε•   Origins of the methodolo...
Predictive Intelligence Modeling                      Forecasting Model                          Composite                ...
Case: Forecasting Hotel Market• History• Deloitte (London), Hotel Benchmark  Division• STR Global• TRI & e-forecasting    ...
Who Visits a Major City (London)?And, Stays in a Hotel             London                           April 11, 2013   20
Purpose of Trip: Why you visit acity? And, Stay in a Hotel Tourists     Business     Government Affairs                   ...
Where do Visitors come from? Domestic &International Feeders to a Destination (Milan, Italy)    Origins of visitors – who ...
What Drives Determine Visitors Volume for aDestination?•   Drivers for Tourism-Related Visitors       •   Personal Income,...
Forecasting with Hundreds ofDrivers?                                                 The Challenge                   20   ...
Case: Modeling London HotelMarket• Modeling Approach  •   Refining large information (indicators) into a      small set of...
Adjustment of Hotel MarketIndicators• To identify the “best fit” and generate most  accurate forecasts, hotel-market indic...
Composite Drivers •   Foreign Composites: Combine activity, current and future,     from all countries that feed London ac...
London Forecasts: Occupancy &Room Rate          London Hotel Market: Occupancy Forecast                                 Ro...
US Economic Outlook •   Measuring long-term economic performance     with stud metrics •   USA 1980-2007 model: 4x2       ...
30    Growth in Monthly GDP•   Looking @ growth rate, can    see depth of previous    recession, upswing, and now    slow ...
Current Risks•   Ineffectiveness of low interest rates•   Asset inflation•   Deficits, Debts, Uncertainty and Fear – The E...
Dynamic Sector: US Manufacturing                        Manufacturing recovery                         will slowly return ...
Monetary Policy on the Horizon     3-Month Treasury Bill: Secondary Market        •   Look for the Fed8    Percent        ...
Global Outlook• Looking @ major economic blocs and their  leading indicators helps give an idea of turning  points, which ...
Long-Term Global Outlook  • Market Size Measured by GDP in $PPP    Billion in 2011                                  April ...
Emerging Asia shows continued dominance in globaleconomy                                     CONTRIBUTION OF REGIONS TO GL...
-1                               0                               1                               2                        ...
Long-term global forecast  8  7                                                                    EURO AREA (16)  6      ...
Q&A      April 11, 2013   39
Thank YouFor questions related to this presentationplease contact     mesimos@e-forecasting.com                           ...
The Importance of Economic Conditions When Building Forecast Models
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The Importance of Economic Conditions When Building Forecast Models

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In his presentation, The Importance of Economic Conditions When Building Forecast Models, Chief Economist of e-forecasting.com Dr Evangelos Simos covers a wide variety of key economic concepts and the possible direct and indirect impacts each has on forecast accuracy.

Although several forecast packages and methodologies exist, we all operate in the same economic environment and the changing conditions impact demand. Even if current corporate forecast processes do not take into account economic conditions, Dr. Simos' presentation will leave the audience with basic guidelines of how to interpret key economic events and their likely outcome on business.

For instance, what are the implications of oil prices spiking to $150 this summer? How much worse are conditions expected to get in Europe and how will that impact exports and foreign demand? Will further Mid East tensions bring violence and political instability? What happens in the US if Obama is re-elected?

e-forecasting.com, an international economic research and consulting firm, offers forecasts of the economic environment using proprietary, real-time economic indicators to produce customized solutions for what’s next. e-forecasting.com collaborates with domestic and international clients and publications to provide timely economic content for use as predictive intelligence to strengthen its' clients competitive advantage.

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The Importance of Economic Conditions When Building Forecast Models

  1. 1. Indicators, Predictive Analytics & Forecasting Evangelos Otto Simos, Ph.D. Economic Research e-forecasting.com April 11, 2013 2
  2. 2. Outline• Going Beyond Raw Data• Forecasting with Hundreds of Drivers• Case: Forecasting a Hotel Market• US & Global Outlook April 11, 2013 3
  3. 3. GoingBeyondRawData April 11, 2013 4
  4. 4. Types of Indicators• Quantitative • GDP, Industrial Production, Employment• Qualitative • NAPM Survey, Consumer Surveys• Analytics (Diffusion Indices) • Aggregates of Quantitative and/or Qualitative Indicators• Predictive Analytics • Fact-based forward-looking analytics (composite leading indicators) April 11, 2013 5
  5. 5. Case: PMI: NAPM Diffusion Index NAPM History 80.0 70.0 60.0 50.0 40.0 30.0 20.0 Jan-59 Jan-64 Jan-69 Jan-74 Jan-79 Jan-84 Jan-89 Jan-94 Jan-99 Jan-04 Jan-09 April 11, 2013 6
  6. 6. A closer Look at PMI Analytic Closer Look: NAPM 2012-13 56.0 • Last three months of 55.0 2012 average: 50.6 54.0 53.0 • Manufacturing was stagnant in the last 52.0 51.0 50.0 quarter of 2012 49.0 48.0 Jan-12 Apr-12 Jul-12 Oct-12 Jan-13New Orders % Better % Same % Worse Net IndexJan 2013 28 51 21 +7 53.3Dec 2012 24 45 31 -7 49.7Nov 2012 26 43 31 -5 51.1Oct 2012 24 47 29 -5 52.8 April 11, 2013 7
  7. 7. Housing Sales: Is that a Recovery? April 11, 2013 8
  8. 8. Consumer Confidence• Media pays attention to composite indices• Consumer spending is about 70% of GDP• Overall indices found to coincide even to lag overall economic activity (GDP)• Q: Are they useless predictive analytics?• A: Not at all• Why? April 11, 2013 9
  9. 9. Consumer Confidence (continued)• Consumers are not forecasters• Overall indices are loaded with answers on questions about the economy• Look at answers to survey’s questions related to individual consumer activity, i.e. about them • Are you going to buy a car over the next six months? New? Used? etc • Are you going to buy a house over the next six months? New, Existing? etc • Are you going to travel over the next six months? Domestic? Foreign? By Plane? By Car? April 11, 2013 10
  10. 10. Economic Policy: Fed in a printing modeagain April 11, 2013 11
  11. 11. Nominal Vs. Real• Retail Sales• Construction Spending• Orders (for Durables, Capital Goods)• Average Wage Rate ($ per hour)• Personal Income• Exports April 11, 2013 12
  12. 12. Dealing With InformationA modern data infrastructure Analytics for predictive intelligence• Internal vs. external • Eliminate transitory outliers,• Timely and effective seasonally adjust and smooth out collection or updating tools noise• Well-designed mining • Identify hidden trends in software economic, business and financial patterns• Analytics processes to tap • Refine large information into a into meaningful & useful data small set of market-centric for predictive intelligence composite predictors April 11, 2013 13
  13. 13. Many Drivers: Blessing or Curse?• Advances in information technology provide access to thousands of economic and business indicators• In forecasting, "having many time series is a blessing not a curse”, James Stock1• A new frontier in forecasting proposes to pool the information of all available predictorsDepartment of Economics, Harvard University1 April 11, 2013 14
  14. 14. Modeling Hundreds of Predictors• Classical VS. Modern Modeling• Let y denote a business indicator to be forecast (like Hotel Occupancy)• Let X be a small number of typical or important variables that “classical” forecasters use as predictors, given statistical limitations (like GDP, Inflation, Unemployment) April 11, 2013 15
  15. 15. Forecasting with Hundreds ofPredictors• Let Z be a set of a few “composite” or so-called “diffusion” indicators that capture a large number (several hundreds) of individual predictors, which • are individually unimportant • collectively become important • provide useful “missed” information, when properly grouped • their “combined” contribution to predicting y may be as good as or better than the typical set of predictors X April 11, 2013 16
  16. 16. The Modern Approach• The General Modern Econometric Model is y = αX + βZ + ε• Origins of the methodology • Burns and Mitchell (1947) in studying business cycle indicators with composites • Sargent and Sims (1977) on factor analysis • Stock and Watson (1989, 2004) on" forecasting using many predictors” • Bernanke and Boivin (2002) on monetary policy in a data-rich environment In their research works Forecasting using diffusion indexes, and Forecasting using many predictors. 1 April 11, 2013 17
  17. 17. Predictive Intelligence Modeling Forecasting Model Composite Drivers Composite Regional ForeignNational Industry Engine Metrics MetricsMetrics Metrics April 11, 2013 18
  18. 18. Case: Forecasting Hotel Market• History• Deloitte (London), Hotel Benchmark Division• STR Global• TRI & e-forecasting April 11, 2013 19
  19. 19. Who Visits a Major City (London)?And, Stays in a Hotel London April 11, 2013 20
  20. 20. Purpose of Trip: Why you visit acity? And, Stay in a Hotel Tourists Business Government Affairs April 11, 2013 21
  21. 21. Where do Visitors come from? Domestic &International Feeders to a Destination (Milan, Italy) Origins of visitors – who stays in hotels - in a typical destination city: Milan • 41 percent of all visitors – 3 million - come from Italy (domestic feeder) • 59 percent, or 4.3 million visitors come from the rest of the world • Majority of foreign visitors (76 percent) come from 31 countries. Sample of some feeding countries: • 7.6% from the United Kingdom • 7.2% from the United States • 6.7% from Germany • 5.7% from France • 1.8% from Sweden • 0.6% from Mexico April 11, 2013 22
  22. 22. What Drives Determine Visitors Volume for aDestination?• Drivers for Tourism-Related Visitors • Personal Income, Employment Stability, Consumer Confidence, Inflation, Capital Gains/Losses like Stock & Housing Prices, Interest Rates, Value of Domestic Currency (Exchange Rates) etc• Drivers for Business-Related Visitors • Measures of Business Sentiment (Future production, Sales, Incoming Orders), Investors Financial Optimism, Profitability, Interest Rates, Taxation, Energy costs, etc• Drivers for Government-Related Visitors • Measures Affecting Revenues (Income, Employment and Sales Taxes), Cyclical Spending (Unemployment), Public Investment, etc April 11, 2013 23
  23. 23. Forecasting with Hundreds ofDrivers? The Challenge 20 Domestic • Multifaceted Drivers Drivers • Domestic 15 15 • Many countries (TopGermany USA Drivers Drivers 30) Hotel Market • Type of visitors (three) • Indicators per 15 15 dimension (about 10) India Brazil Drivers Drivers • The Upshot: Hundreds of Drivers April 11, 2013 24
  24. 24. Case: Modeling London HotelMarket• Modeling Approach • Refining large information (indicators) into a small set of composite drivers (predictors) for the London hotel market • Drivers are observable economic and business composites that influence business activity in London’s hotel market • Occupancy (OCCU) and room rates (ADR) are interrelated • Domestic and international drivers influence demand for and supply (including costs) of hotel services to determine future hotel performance April 11, 2013 25
  25. 25. Adjustment of Hotel MarketIndicators• To identify the “best fit” and generate most accurate forecasts, hotel-market indicators are brought to conformity with single drivers and composites, which are seasonally adjusted by source or e−forecasting.com• Hotel market indicators are adjusted for seasonality and special “transitory” events such as Royal weddings, sport events, political events, etc. Events are also treated in the future for prediction of performance metrics. April 11, 2013 26
  26. 26. Composite Drivers • Foreign Composites: Combine activity, current and future, from all countries that feed London according to their relative importance (grouping of more than 1,000 indicators) • Business expectations • Consumer confidence • Incomes • Changing value of assets • Exchange rates • Domestic Composites: Combine activity, current and future, in the domestic economy • Consumers • Business • Financial markets • Costs (wages, prices, energy) April 11, 2013 27
  27. 27. London Forecasts: Occupancy &Room Rate London Hotel Market: Occupancy Forecast Room Rate Forecast Forecast of Baseline Actual Baseline, SA&S Forecast of Baseline Actual Baseline, SA&S Forecast of Occupancy Actual Occupancy Forecast of Room Rate Actual Room Rate £14595 £13585 £125 £11575 £10565 £95 £8555 01 02 03 04 05 06 01 02 03 04 05 06 April 11, 2013 28
  28. 28. US Economic Outlook • Measuring long-term economic performance with stud metrics • USA 1980-2007 model: 4x2 • 4% growth & 2% Inflation • European 1980-2007 model: 2x2 • 2% growth & 2% Inflation • Forecast: USA new reality: 2x2 or 2x4 ? April 11, 2013 29
  29. 29. 30 Growth in Monthly GDP• Looking @ growth rate, can see depth of previous recession, upswing, and now slow recovery in economy• When negative, recession; when positive, expansion• Six-month growth rate, which signals confirmation of turning points, went up 1.2% in January, after going up 1.4% in December April 11, 2013 30
  30. 30. Current Risks• Ineffectiveness of low interest rates• Asset inflation• Deficits, Debts, Uncertainty and Fear – The European experience has moved west• Free fall of dollar, panic, policy reversal, high interest rates, a “real” depression• Geopolitical factors, Middle East conflict & oil prices April 11, 2013 31
  31. 31. Dynamic Sector: US Manufacturing Manufacturing recovery will slowly return to peak of 08 by 2015 April 11, 2013 32
  32. 32. Monetary Policy on the Horizon 3-Month Treasury Bill: Secondary Market • Look for the Fed8 Percent Funds rate to remain near zero6 until 2015 • Bernanke’s4 ‘pledge’ to hold2 rates thru 20140-2 03:Jan 05:Jan 07:Jan 09:Jan 11:Jan 13:Jan 15:Jan April 11, 2013 33
  33. 33. Global Outlook• Looking @ major economic blocs and their leading indicators helps give an idea of turning points, which areas suffered more than others and which are recovering… April 11, 2013 34
  34. 34. Long-Term Global Outlook • Market Size Measured by GDP in $PPP Billion in 2011 April 11, 2013 35
  35. 35. Emerging Asia shows continued dominance in globaleconomy CONTRIBUTION OF REGIONS TO GLOBAL GROWTH Percentage Points Contribution Rel ative Contribution, P ercent REGION 2011 2012 2013 2014 2011 2012 2013 2014 EUROPEAN UNION (EU27) 0.35 -0.04 0.02 0.26 9.4 -1.4 0.7 8.1 Euro Area (euro17) 0.23 -0.07 -0.05 0.13 6.1 -2.5 -1.8 4.1 Non-Euro Members (10) 0.12 0.03 0.06 0.13 3.3 1.1 2.5 4.0 OTHER EUROPE 0.30 0.17 0.20 0.24 8.0 6.1 7.9 7.4 NORTH AMERICA 0.52 0.52 0.32 0.54 13.8 18.4 12.5 17.1 United States 0.38 0.39 0.22 0.42 10.1 14.0 8.9 13.3 SOUTH AMERICA 0.28 0.17 0.20 0.24 7.5 6.0 7.9 7.4 ASIA & PACIFIC INDUSTRIAL 0.06 0.19 0.14 0.19 1.7 6.6 5.5 5.8 EMERGING ASIA 2.03 1.67 1.52 1.56 54.1 59.4 59.7 48.9 China & India 1.76 1.42 1.26 1.28 46.8 50.5 49.5 40.1 MIDDLE EAST & AFRICA 0.15 0.09 0.10 0.13 3.9 3.1 3.9 4.2 WORLD GROWTH1 3.8 2.8 2.5 3.2 100.0 100.0 100.0 100.0 1 Sum of Regional Contributions Source: www.e-forecasting.com April 11, 2013 36
  36. 36. -1 0 1 2 3 4 5 6 7 8 EURO AREA (17) NON-EURO AREA (10) OTHER EUROPE NORTH AMERICA Short term global forecast SOUTH AMERICA % change in real GDP growth ASIA & PACIFIC INDUSTRIAL EMERGING ASIA MIDDLEApril 11, 2013 EAST & AFRICA 2014 2013 2012 201137
  37. 37. Long-term global forecast 8 7 EURO AREA (16) 6 NON-EURO AREA (11) 5 OTHER EUROPE 4 NORTH AMERICA 3 SOUTH AMERICA 2 ASIA & PACIFIC INDUSTRIAL 1 EMERGING ASIA 0 MIDDLE EAST & AFRICA -1 11 17 21 25 13 15 19 23 27 29 20 20 20 20 20 20 20 20 20 20 April 11, 2013 38
  38. 38. Q&A April 11, 2013 39
  39. 39. Thank YouFor questions related to this presentationplease contact mesimos@e-forecasting.com April 11, 2013 40

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