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Sentiment-Based Commercial Real Estate Forecasting with Google Search Volume Data Marian Alexander Dietzel | Nicole Braun | Wolfgang Schaefers ERES Conference.

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Presentation on theme: "Sentiment-Based Commercial Real Estate Forecasting with Google Search Volume Data Marian Alexander Dietzel | Nicole Braun | Wolfgang Schaefers ERES Conference."— Presentation transcript:

1 Sentiment-Based Commercial Real Estate Forecasting with Google Search Volume Data Marian Alexander Dietzel | Nicole Braun | Wolfgang Schaefers ERES Conference Bucharest 2014

2 2 Textmasterformate durch Klicken bearbeiten Sentiment-Based Commercial Real Estate Forecasting with Google Search Volume Data AGENDA 1. Motivation and Theoretical Background 2.Research Design and Methodology 2.1. Data 2.2.Models 4.Empirical Results 5.Conclusion

3 3 Textmasterformate durch Klicken bearbeiten Beracha, E. and Wintoki, J. (2012), “Predicting Future Home Price Changes Using Current Google Search Data,” Journal of Real Estate Research, forthcoming. Hohenstatt, R., Käsbauer, M. and Schäfers, W. (2011), “’Geco’ and its Potential for Real Estate Research: Evidence from the U.S. Housing Market”, Journal of Real Estate Research, Vol. 33 No. 4., pp Hohenstatt, R. and Käsbauer, M. (2013), “GECO’s Weather Forecast’ for the U.K. Housing Market: To What Extent Can We Rely on Google ECOnometrics?”, Journal of Real Estate Research, forthcoming. Wu, L. and Brynjolfsson, E. (2009), “The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales”, Working papers, Wharton School, University of Pennsylvania Housing Market Predictions with Google Trends Data Motivation and Theoretical Background  All studies find empirical evidence that Google Trends data have predictive power and improve the forecast accuracy for housing markets (USA and UK).

4 4 Textmasterformate durch Klicken bearbeiten Motivation and Theoretical Background Can Google Trends data also improve Commercial Real Estate Market Forecasts? Research Question

5 5 Textmasterformate durch Klicken bearbeiten Motivation and Theoretical Background CoStar Composite Index Google

6 6 Textmasterformate durch Klicken bearbeiten Motivation and Theoretical Background CoStar Composite transactions Google

7 7 Textmasterformate durch Klicken bearbeiten unspecific: internet search for market/investment climate and comparables (yields, rents etc.) listing services real estate agents/property news websites specific: internet search for market/investment climate and comparables (yields, rents etc.) comparison of other analyses internet search for actual properties listing services real estate agents (JLL, CBRE etc.) setting of initial investment goals and decision criteria formulation of investor specific strategy Stage 1 formulation of a decision-making strategy choosing rational criteria for asset selection Stage 2 search for suitable properties detailed search for alternative investment opportunities Stage 3 prediction of outcomes investment appraisal Stage 5 information input (analysis of market conditions) analysis of economic, political and investment climate for national and regional markets Stage 4 market related interest object related interest: Stage 6: application of decision criteria; Stage 7: trade-off between properties; Stage 8: project screening; Stage 9: investment selection; Stage 10: deal resolution and post investment activity Transaction Process and Internet Research Motivation and Theoretical Background Investment Process after Roberts and Henneberry (2007)

8 8 Textmasterformate durch Klicken bearbeiten Google Data Research Design and Methodology  Search Volume Indices (SVI) derived from Google Trends (http://www.google.com/trends/)http://www.google.com/trends/  Normalized values, scaled measured between 0 and 100  The weekly data covers search queries conducted from Sunday to Saturday.  Google Trends makes the newest weekly data available with an approximate two day delay.

9 9 Textmasterformate durch Klicken bearbeiten Macro Data Research Design and Methodology Commercial Real Estate Data: CoStar Commercial Repeat-Sale Indices CCRSI Moody‘s/RCA Commercial Property Price Indices CPPI Macroeconomic Data: US unemployment initial claims US construction expenditures National Financial Conditions Index (NFCI) Chicago Fed National Activity Index (CFNAI)

10 10 Textmasterformate durch Klicken bearbeiten Google IndexSearch InterestSearch Terms general interest g_inv_subcat "Commercial and Investment Real Estate" subcategory Google does not report the exact search terms that were aggregated in the subcategory g_commGeneral search terms for commercial real estate commercial property+commercial real estate+commercial property sale+property for sale+lease commercial property+commercial lease g_agents+list Commercial real estate service providers and listing services jll+cbre+jones lang lasalle+ colliers+dtz+ cushman and wakefield +knight frank+savills+grubb ellis+newmark grubb+cb richard ellis+marcus millichap+cimls+loopnet+xceligent+ "propertyline"+catylist specific interest g_offOffice property related search terms office for sale+office space+office space rent+commercial office space+office rental+office lease g_retRetail property related search terms retail space+commercial retail+retail lease+retail sale space+retail property+rent retail space+retail space for sale g_indusIndustrial-property- related search terms industrial property+industrial for sale+industrial leases+commercial industrial property+industrial building+warehouse for sale+industrial property for sale g_apart"Apartments & Residential Rentals" subcategory Google does not report the exact search terms that were aggregated in the subcategory Research Design and Methodology

11 11 Textmasterformate durch Klicken bearbeiten Research Design and Methodology modelforecasted variableindependent variables Macro DataTransactionsGoogle Data Prices baseline b1 Pricesx b2 Pricesxx google g1 Prices x g2 Pricesxxx Macro DataPricesGoogle Data Transactions baseline b1 Transactionsx b2 Transactionsxx google g1 Transactions x g2 Transactionsxxx

12 12 Textmasterformate durch Klicken bearbeiten Research Design and Methodology VAR (6)-Model endogenous variables exogenous variables

13 13 Textmasterformate durch Klicken bearbeiten Empirical Results * The reduction of the MSE and U1 Theil is always measured in relation to the best baseline model (usually b2). A positive value stands for an improvement in forecasting accuracy in comparison to the baseline model.

14 14 Textmasterformate durch Klicken bearbeiten Empirical Results * The reduction of the MSE and U1 Theil is always measured in relation to the best baseline model (usually b2). A positive value stands for an improvement in forecasting accuracy in comparison to the baseline model.

15 15 Textmasterformate durch Klicken bearbeiten Robustness Check * The reduction of the MSE and U1 Theil is always measured in relation to the best baseline model (usually b2). A positive value stands for an improvement in forecasting accuracy in comparison to the baseline model.

16 16 Textmasterformate durch Klicken bearbeiten Robustness Check * The reduction of the MSE and U1 Theil is always measured in relation to the best baseline model (usually b2). A positive value stands for an improvement in forecasting accuracy in comparison to the baseline model.

17 17 Textmasterformate durch Klicken bearbeiten Robustness Check

18 18 Textmasterformate durch Klicken bearbeiten Main Findings Findings and Conclusion  Google data help in improving the forecast accuracy for the commercial real estate market  g2-models have the lowest mean squared forecast errors  a combination of macro and Google data yields the best forecasting results  Models based on Google data only outperform non-Google models in most cases (78%)  Google data by itself has significant explanatory power towards the commercial real estate market

19 19 Textmasterformate durch Klicken bearbeiten Sentiment-Based Commercial Real Estate Forecasting with Google Search Volume Data Questions Thank you for your attention! Questions?

20 20 Textmasterformate durch Klicken bearbeiten Granger Causality Test BACK UP

21 21 Textmasterformate durch Klicken bearbeiten Lag Order BACK UP

22 22 Textmasterformate durch Klicken bearbeiten Clark-West Forecast Significance Test BACK UP Prices t-statp-value Transactions t-statp-value Cluster 1 co_comp *** Cluster 1 co_comp_tra *** co_gen *** co_gen_tra *** co_inv *** co_inv_tra *** mo_alprop *** mo_alprop_tra *** mo_core *** mo_core_tra *** Cluster 2 mo_off *** Cluster 2 mo_off_tra *** mo_off_cbd *** mo_off_cbd_tr a *** mo_off_sub *** mo_off_sub_tr a *** Cluster 3mo_ret *** Cluster 3mo_ret_tra *** Cluster 4mo_indus *** Cluster 4mo_indus_tra *** Cluster 5mo_apart *** Cluster 5mo_apart_tra *** Notes: H=0: improvement of g2 over b2 model is insignificant. Sample: 2007m m01; 73 observations Significant at: * p < 0.10, ** p < 0.05 and *** p < 0.01.

23 23 Textmasterformate durch Klicken bearbeiten Impulse Response Function BACK UP PricesDependent VariableGoogle SVI TransactionsDependent VariableGoogle SVI g_agents_listg_inv_subcatg_comm g_agents_listg_inv_subcatg_comm Cluster 1 co_gen Cluster 1 co_gen_tra co_comp co_comp_tra co_inv co_inv_tra mo_alprop mo_alprop_tra mo_core mo_core_tra g_agents_listg_inv_subcatg_off g_agents_listg_inv_subcatg_off Cluster 2 mo_off Cluster 2 mo_off_tra mo_off_cbd mo_off_cbd_tra mo_off_sub mo_off_sub_tra g_agents_listg_inv_subcatg_ret g_agents_listg_inv_subcatg_ret Cluster 3mo_ret Cluster 3mo_ret_tra g_agents_listg_inv_subcatg_indus g_agents_listg_inv_subcatg_indus Cluster 4mo_indus Cluster 4mo_indus_tra g_agents_listg_inv_subcat g_apartren t g_agents_listg_inv_subcat g_apartren t Cluster 5mo_apart Cluster 5mo_apart_tra

24 24 Textmasterformate durch Klicken bearbeiten Macro Data Transactions co_comp_traTransactions underlying CoStar CompositeCoStar co_gen_traTransactions underlying CoStar General CommercialCoStar co_inv_traTransactions underlying CoStar Investment GradeCoStar mo_alprop_traTransactions underlying Moody's/RCA Tier 1 NationalMoody's/RCA mo_core_tra Transactions underlying Moody's/RCA Tier 2 Core CommercialMoody's/RCA mo_off_traTransactions underlying Moody's/RCA Tier 4 OfficeMoody's/RCA mo_off_cbd_traTransactions underlying Moody's/RCA Tier 4 Office CBDMoody's/RCA mo_off_sub_tra Transactions underlying Moody's/RCA Tier 4 Office Suburban MarketsMoody's/RCA mo_ret_traTransactions underlying Moody's/RCA Tier 4 RetailMoody's/RCA mo_indus_traTransactions underlying Moody's/RCA Tier 4 IndustrialMoody's/RCA mo_apart_traTransactions underlying Moody's/RCA Tier 2 ApartmentMoody's/RCA Macro Data mcr_constConstruction ExpendituresUS Census Bureau mcr_unemp U.S Labor Department report of initial state jobless benefit claims US Department of Labor mcr_nfciNational Financial Conditions Index (NFCI)** Federal Reserve Bank of Chicago mcr_cfnai Chicago Fed National Activity Index (CFNAI), a monthly index designed to gauge overall economic activity and related inflationary pressure *** Federal Reserve Bank of Chicago BACK UP


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