Lucas Finco NY INFORMS October 2014

Transcription

1 Lucas Finco NY INFORMS October

2 Table of Contents I. Leading Indicators II. Previous Analysis III. New Direction IV. Limitations and Future Directions 2

3 Table of Contents I. Leading Indicators II. Previous Analysis III. New Direction IV. Limitations and Future Directions 3

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5 Leading Indicators A time series that changes before the variable of interest changes E.g., the measure of working hours of existing employees is a leading indicator for changes in unemployment 5

6 Leading Indicators Useful as short-term predictors Example: U.S. Leading Economic Index produced by The Conference Board 6

7 Table of Contents I. Leading Indicators II. Previous Analysis III. New Direction IV. Limitations and Future Directions 7

8 The Company Regionally focused company NY State Sells technology products to building owners 8

9 Previous Analysis Team tasked with finding external, economic leading indicators for business revenues Initial analysis found only weak correlations with revenue data Investigated: Consumer Price Index (CPI) Small Business Lending Index (SBLI) Empire State Manufacturing General Business Conditions Index (ESM GBC) 9

10 Previous Analysis , , , , , , Jan-11 Feb-11 Mar-11 Apr-11 May-11 Jun-11 Jul-11 Aug-11 Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12-10

11 Table of Contents I. Leading Indicators II. Previous Analysis III. New Direction IV. Limitations and Future Directions 11

12 New Direction Indicators may have been too broad nationwide ESM GBC may have also been too broad index is average of many components Solution - Look at ESM components individually: 88 ESM components Individually, they are very specific More relevant to co. service territory than national indicators 12

13 Empire State Manufacturing Survey Monthly survey in New York State conducted by the Federal Reserve Bank of New York Survey 200 executives in New York State, typically the president or CEO Approx. 100 responses are received Participants from across the state in a variety of industries Report the change in a variety of indicators from the previous month Respondents also state the likely direction of these same indicators six months ahead Asked about orders, shipments, prices, spend, etc. 13

14 Correlation Offset Team used a correlation offset procedure to find leading indicators for revenues Correlation derived between monthly revenues and the possible indicator The indicator is then offset by different months Negative offset produces a leading indicator Pearson Correlation Coefficient: 1 = perfectly correlated -1 = inverse perfectly correlated 0 = no correlation 14

15 Revenues ($ 000) Correlation Offset Example Revenues 15

16 Revenues ($ 000) Correlation Offset Example Revenues 16

17 Revenues ($ 000) Correlation Offset Example Revenues 17

18 Past Experience Months Leading ESMGBC (unadj) CPI-U SBLI

19 Top Leading Indicators Found 8 Leading Indicators 3 Positively correlated 5 Negatively correlated Threshold Correlation coefficients: above 0.65 or below

20 Correlation Offset Example 0.8 TSFINA Months Leading

21 Multi-Variable Regression Use ESM components for predictors Find optimal set of ESM predictors that will model revenue Identify predictors that are related (multicollinearity) i.e. contribution to the model is mostly explained by one of the multicollinear variables Eliminate excess / unnecessary terms Looked at 18 unique combinations of variables 21

22 Top Leading Indicators PPCINA TSFINA PRFDINA Months Leading

23 3-Variable Model: PRFDINA: Future Prices Received, Diffusion Index GAFDNA: Future General Business Conditions, Percent Reporting Decreases TSFNNA: Regression Results Future Technology Spending, Percent Reporting No Change Least-squares fit to revenue data: R 2 = 69% We can explain 69% of the variance in revenue by knowing the values of PRFDINA, GAFDNA, TSFNNA. 23

24 Revenues ($ 000) SBDI Savings (MWh/month) 6 Month Prediction Model Revenue = *GAFDNA *PRFDINA *TSFNNA SBDI Revenues SBDI II Model Revenue Leading Indicators Model Sep-09 Apr-10 Oct-10 May-11 Nov-11 Jun-12 Jan-13 Jul-13 Feb-14 24

25 Table of Contents I. Leading Indicators II. Previous Analysis III. New Direction IV. Limitations and Future Directions 25

26 Limitations Do not have adequate number of observations to construct a multivariable model Can only ascertain relationships, but not determine underlying causal mechanism E.g., relationship of damage caused by a fire and the number of firefighters involved Confounding factors unrelated to our predictor variables E.g., One off company events 26

27 Future Directions Build upon model to include different sets of possible indicators Explore predicting leads or applications instead of revenues Investigate internal leading indicators for revenues (website hits, leads, applications, etc.) Analyze by customer business type (NAICS) Investigate seasonality and its effects on the model 27

28 Conclusion Found leading indicators Multiple regression is a standard approach 3-variable optimal model used to forecast revenues Take note of model limitations Future directions 28

29 QUESTIONS 29

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32 Pearson Correlation Coefficient 32

33 Pearson Correlation Coefficient Plot showing the minimum value of Pearson's sample correlation coefficient that would be significant at the 0.05 level for a given sample size. 33

34 Top Leading Indicators 0.6 PPCNNA 0.4 TSFNNA SHFDNA 0.2 GAFDNA 0 NOFDNA Months Leading

35 Top Leading Indicators Positively correlated: PRFDINA Future Prices Received, Diffusion Index, 7 months leading TSFINA Future Technology Spending, Percent Reporting Increases, 6 months leading PPCINA Current Prices Paid, Percent Reporting Increases, 3 months leading 35

36 Top Leading Indicators Negatively correlated: PPCNNA Current Prices Paid, Percent Reporting No Change, 3 months leading GAFDNA Future General Business Conditions, Percent Reporting Decreases, 7 months leading NOFDNA Future New Orders, Percent Reporting Decreases, 7 months leading SHFDNA Future Shipments, Percent Reporting Decreases, 7 months leading TSFNNA Future Technology Spending, Percent Reporting No Change, 6 months leading 36

37 Leading Indicators GAFDNA PRFDINA TSFNNA Linear (GAFDNA) Linear (PRFDINA) Linear (TSFNNA)