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Biases and Forecast Efficiency in Corporate Finance

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Biases and Forecast Efficiency in Corporate Finance Biases and Forecast Efficiency in Corporate Finance Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakultät für Wirtschaftswissenschaften am Karlsruher Institut für Technologie (KIT) genehmigte DISSERTATION von Dipl.-Inform. Florian Knöll Tag der mündlichen Prüfung: 11.12.2017 Referent: Prof. Dr. Thomas Setzer Korreferent: Prof. Dr. Hansjörg Fromm Karlsruhe, 2017 Contents List of Abbreviationsv List of Figures vii List of Tables ix I Foundations1 1 Introduction3 1.1 Motivation.................................3 1.2 Research Outline.............................6 1.3 Structure of the Thesis.......................... 10 2 Forecast Revision Processes and Influences 13 2.1 Forecast and Revision Process...................... 13 2.2 Forecast Efficiency............................ 14 2.3 Forecast Correction............................ 15 2.4 Individual Influences........................... 16 2.4.1 Anchoring and Adjustment................... 17 2.4.2 Optimism, Pessimism and Overreaction, Underreaction.. 19 2.4.3 Revision Concentration..................... 19 2.5 Organizational Influences........................ 20 2.5.1 Earnings Management...................... 22 2.5.2 Earnings Target.......................... 23 II Business Characteristics Extraction 25 3 Individual Level Characteristics 27 3.1 Forecast Efficiency............................ 30 3.1.1 Forecast Efficiency: Lead Time................. 30 3.1.2 Forecast Efficiency Hypothesis: Increased Accuracy..... 31 3.2 Anchoring and Adjustment....................... 33 3.3 Optimism, Pessimism and Overreaction, Underreaction....... 37 i ii Contents 3.4 Revision Concentration.......................... 38 4 Aggregate Level Business Characteristics 43 4.1 Ratio Metric................................ 43 4.1.1 Construction Process....................... 43 4.1.2 Ratio Metric: Validity...................... 46 4.1.3 Ratio Metric: Earnings Target Existence............ 47 4.1.4 Ratio Metric: Subsidiary Specific Revision.......... 48 4.2 Efficiency at Aggregate Level...................... 48 4.2.1 Reasoning Beneficial Inefficiency in Individual Forecasts.. 48 4.2.2 Testing Aggregate Level Efficiency............... 49 4.3 Organizational Relations......................... 49 4.3.1 Error Dependencies on Earnings Target............ 50 4.3.2 Dependencies on Revision.................... 52 4.3.3 Impact on Organizational Goals................ 55 5 Predictive Value 59 5.1 Predictions on Individual Level..................... 60 5.1.1 Correction: Anchoring and Adjustment............ 60 5.1.2 Correction: Concentration Measures.............. 60 5.2 Predictions on Aggregate Level..................... 61 5.3 Improvement of Aggregate Efficiency................. 64 5.3.1 Weak Forecast Efficiency Analysis............... 65 5.3.2 Extended Weak Forecast Efficiency Analysis......... 66 III Application in Practice and Empirical Evaluation 71 6 Case for Data Evaluation 73 6.1 Information System: Landscape and Workload............ 75 6.2 Corporate Reporting Structure..................... 76 6.3 The Business Importance of Forecasting................ 78 6.4 Domain Expert Knowledge....................... 79 6.5 Data Preprocessing in Practice...................... 81 6.6 Individual Level Business Descriptives................. 84 6.7 Aggregate Level Business Descriptives................. 84 6.8 Framework for Data Evaluation..................... 85 7 Evaluation of Individual Level Characteristics 87 7.1 Forecasting Efficiency........................... 87 7.1.1 Forecast Efficiency: Lead Time................. 89 7.1.2 Forecast Efficiency Hypothesis: Increased Accuracy..... 90 7.2 Anchoring and Adjustment....................... 91 Contents iii 7.3 Optimism, Pessimism and Overreaction, Underreaction....... 97 7.4 Revision Concentration.......................... 99 7.5 Summary.................................. 101 8 Evaluation of Aggregate Level Business Characteristics 105 8.1 Ratio Metric: Validity........................... 105 8.2 Ratio Metric: Earnings Target Existence................ 107 8.3 Ratio Metric: Subsidiary Specific Revision............... 109 8.4 Efficiency at Aggregate Level...................... 110 8.4.1 Reasoning Beneficial Inefficiency for Individual Forecasts. 111 8.4.2 Testing Aggregate Level Efficiency............... 114 8.5 Organizational Relations......................... 114 8.5.1 Error Dependencies on Earnings Target............ 115 8.5.2 Dependencies on Revision.................... 118 8.5.3 Impact on Organizational Goals................ 121 8.6 Summary.................................. 122 9 Evaluation of Predictive Value 127 9.1 Predictions on Individual Level..................... 127 9.1.1 Correction: Anchoring and Adjustment............ 127 9.1.2 Correction: Concentration Measures.............. 128 9.2 Predictions on Aggregate Level..................... 129 9.2.1 Forecast Correction........................ 129 9.2.2 Error Distribution of Forecast Correction........... 130 9.3 Improvement of Aggregate Efficiency................. 131 9.3.1 Correction of Weak Forecast Efficiency............. 131 9.3.2 Correction of Extended Weak Forecast Efficiency....... 134 9.4 Summary.................................. 138 IV Finale 141 10 Conclusion and Outlook 143 10.1 Summary.................................. 143 10.2 Contributions............................... 144 10.3 Future Outline............................... 145 10.3.1 Forecast Efficiency........................ 145 10.3.2 Formalized Bias Extraction................... 146 10.3.3 Managerial Implications..................... 147 10.3.4 Forecast Correction........................ 147 iv Contents V Appendix 149 A Research Overview 151 B Sample Data 155 C Analytical Results 157 References 159 List of Abbreviations A&A Anchoring and Adjustment AP Agricultural Products ape Absolute Percentage Error BWM Bandwidth Model CoFiPot Corporate Financial Portal Cor Correlation DV Diverse EBIT Earnings Before Interest and Taxes EBITDA Earnings Before Interest, Taxes, Depreciation, and Amortization exp Exponential Function GDP Gross Domestic Product G7 Group of Seven HP Health and Pharmaceuticals ID Identification II Invoices Issued IM Industrial Materials IR Invoices Received KPI Key Performance Indicator LBWM Logistic Bandwidth Model mape Mean Absolute Percentage Error mrse Root Mean Squared Error mse Mean Squared Error Obs Observations pe Percentage Error RQ Research Question v List of Figures 1.1 Structure of the thesis........................... 11 3.1 Temporal structure of cash flow forecast process............ 28 3.2 Logistic assigning function for anchoring probability......... 36 4.1 Temporal structure of ratio forecast process............... 46 4.2 Hypothesized relationship between the magnitude of revision and target within the fiscal year........................ 53 4.3 Required adjustment-pattern for information concealment...... 55 5.1 Graphic presentation of the “extended weak forecast efficiency” concept.................................... 67 6.1 The technical landscape of the corporate forecast support system.. 76 6.2 Validation process for the delivered forecast data of the subsidiary. 77 6.3 Dependencies of reporting units in the corporate structure...... 78 7.1 Anchor and adjustment detection for an example forecast series... 94 7.2 Interactions of volume and direction within the revision processes. 101 7.3 Interactions of timing and volume within the revision processes of division “health and pharmaceuticals”................. 102 8.1 Temporal development of the median ratio for business divisions.. 109 8.2 Relation between not normalized revisions and not normalized er- ror of entities................................ 110 8.3 Relation between normalized revisions and normalized error of entities.................................... 111 8.4 Interaction of the knowledge for past and future earnings manage- ment with the forecasting process.................... 112 9.1 Error quantiles for the forecasts of experts, the basic statistical model, and the organizational model.................. 131 9.2 Correlation plot of expert inefficiencies on aggregate level...... 132 9.3 Improvement plot of the basic statistical model over the baseline of expert forecasts on aggregate level.................. 132 9.4 Improvement plot of the organizational model over the basic sta- tistical model on aggregate level..................... 133 vii List of Tables 3.1 Common error functions for forecast processes............. 28 3.2 Notation used for the individual characteristics............ 29 4.1 Notation used for the aggregate characteristics............. 45 6.1 Temporal structure of a single revision process in the corporation.. 75 6.2 Importance of data cleaning: Comparison of absolute percentage error metric for different stages of uncleaned and cleaned data... 83 6.3 The summary of available individual invoice data........... 84 6.4 The summary of available aggregate invoice data........... 85 7.1 Correlations and significance levels of percentage error and rela- tive revision................................. 88 7.2 Mean absolute percentage error by division for all months...... 89 7.3 Mean absolute percentage error by division for December...... 90 7.4 Bivariate correlation tests for testing the efficiency hypothesis.... 91 7.5 Indication of anchoring effects on cash flow forecasts......... 93 7.6 Comparison of anchoring and adjustment models on different time series..................................... 96 7.7 Indication of optimism, pessimism
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