From a talk given at the 2013 APRA Symposium on Data Analytics in Baltimore, MD.

1. Data Analytics Symposium
August 7 – 8, 2013 • Baltimore, Maryland
Using Financial Analysis
Techniques
in non-profit fundraising
By Tommy Tavenner
National Wildlife Federation

2. Data Analytics Symposium
August 7-8, 2013
Financial Engineering
•
Application of theoretical mathematics and computer
science to the study of financial data
•
The basis for many of our analysis applications
•
Uses the same basic mathematics techniques and
requires the same cautions
© 2013 Tommy Tavenner

3. Data Analytics Symposium
August 7-8, 2013
Why you should study it
•
A different way of thinking about our donors
•
The balance of risk vs. reward
•
Focus on minimizing risk, defined as volatility
•
Finding the right mix of donors for the outcome we are
trying to achieve
© 2013 Tommy Tavenner

4. Data Analytics Symposium
August 7-8, 2013
How It Relates
•
Prospect Research = Fundamental Analysis
•
Analytics = Technical Analysis
© 2013 Tommy Tavenner

5. Data Analytics Symposium
August 7-8, 2013
Fundamental Analysis
•
Determine the value of a company by looking at it’s
principal components
> Financial Statements
> Management Team
> Competitive Environment
© 2013 Tommy Tavenner

6. Data Analytics Symposium
August 7-8, 2013
Technical Analysis
•
Based on the idea that all information about a company
is contained in it’s share price
> Location of a company share price within the larger market
> Future price
> Relationship of movements within prices of multiple companies
© 2013 Tommy Tavenner

7. Data Analytics Symposium
August 7-8, 2013
Some caveats
•
Our information is less complete
•
The amount we invest in a donor is more highly
correlated with their giving
© 2013 Tommy Tavenner

8. Data Analytics Symposium
August 7-8, 2013
Definitions
•
Asset/Security – an individual stock or fund; equivalent
to the donor
•
Alpha – A measure of the risk adjusted return
•
Beta – A measure of risk; The volatility of an asset (i.e.
how much the price swings) in relation to a benchmark
(i.e. the overall market)
© 2013 Tommy Tavenner

9. Data Analytics Symposium
August 7-8, 2013
Concepts
•
Market Rate
> Historical – The average gift for your overall population in each
measured period, i.e. average per year, per quarter, per month,
etc.
> Estimated – A forecast of what the average gift will be in the
next measured period.
© 2013 Tommy Tavenner

10. Data Analytics Symposium
August 7-8, 2013
Concepts
•
Risk Free Rate
> The safest investment you can make with a nearly 100%
guarantee return. (treasury bonds)
> Low risk generally means low returns as well.
> What size gift would we receive if we made little to no effort at
all
1. Unsolicited/White mail gifts
2. Base level giving or membership fee
© 2013 Tommy Tavenner

11. Data Analytics Symposium
August 7-8, 2013
Concepts
•
Calculating Beta for a donor
Donor’s Gifts per Year
Average Giving per Year
$ 100
$ 80
$120
$ 94
$120
$ 90
$115
$ 93
β = CoVar( Donor’s Gifts, Average Giving )
Var( Average Giving )
© 2013 Tommy Tavenner

12. Data Analytics Symposium
August 7-8, 2013
Concepts
•
Calculating Beta for a donor
β = CoVar
$ 100 $ 80
$120
$ 94
$120
$ 90
$115
$ 93
Var
$ 80
=
55.417
40.917
$ 94
$ 90
$ 93
© 2013 Tommy Tavenner
= 1.354

13. Data Analytics Symposium
August 7-8, 2013
Concepts - Beta
β<0
The size of the donor’s gift moves inverse to the
overall population
β=0
The size of the donor’s gift is uncorrelated to the
population
0<β<1
The size of the donor’s gift moves in the same
direction but not as dramatically as the overall
population
β=1
The size of the donor’s gift is exactly correlated the
population
β>1
The size of the donor’s gift moves in the same
direction but more dramatically as the population
© 2013 Tommy Tavenner

14. Data Analytics Symposium
August 7-8, 2013
CAPITAL ASSETS PRICING MODEL

15. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model
•
Based on the work of Harry Markowitz
•
Introduced by Jack Treynor, William Sharpe, John
Lintner, and Jan Mossin independently over the course
of several studies between 1961 and 1966
•
A method for determining an assets required rate of
return given its inherent risk
© 2013 Tommy Tavenner

16. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model
•
A method for determining an assets required rate of
return given its inherent risk
> Requires knowing a benchmark rate of return and a risk free
rate of return
> Also depends on the asset’s beta (β), a measure of the
volatility of that asset
© 2013 Tommy Tavenner

17. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model
•
Expected Market Rate
>
Average Return for all donors
>
Average Return for the specific population being studied
>
Major Donors: conversion rate (gifts over asks or dollars received over dollars
asked)
© 2013 Tommy Tavenner

18. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model
•
Risk Free Return Rate = What activities have set returns?
>
Treasury Bonds
>
Benchmarking Studies (i.e. CASE, Blackbaud)
>
Donors with close to 100% response rate
>
White mail
© 2013 Tommy Tavenner

19. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model – An example
•
Annual Giving – Gifts of $1,000 or more
>
Set a fixed time for your study. Requires a minimum of two values (i.e. the first
of two consecutive years, but more is generally better
1.
Past performance of the target population
2.
Past performance of your benchmark
3.
Estimate of benchmark performance in your prediction period
4.
Risk Free Rate
© 2013 Tommy Tavenner

20. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model – An example
•
Annual Giving – Gifts of $1,000 or more
>
Study period: The past four years
1.
Past performance of the target population: Giving per individual by year
2.
Past performance of your benchmark: Average giving by year
3.
Estimate of benchmark performance in your prediction period:
—
4.
Excel FORECAST function
Risk Free Rate: Base giving level - $1,000
© 2013 Tommy Tavenner

21. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model – An example
Risk Free Rate:
$1,000
Market Forecast: $1,030
Donor 1 β:
Estimated Return for Donor 1
= $1,000 + 1.08( $1,030 – $1,000 )
= $1,032.26
© 2013 Tommy Tavenner
1.08

22. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model – An example
Risk Free Rate:
$0
Market Forecast: $1,030
Donor 1 β:
Estimated Return for Donor 1
= 0 + 1.08( $1,030 –0 )
= $1,107.46
© 2013 Tommy Tavenner
1.08

23. Data Analytics Symposium
August 7-8, 2013
Capital Assets Pricing Model – An example
β
Giving Forecast
CAPM Forecast
($1,000 RFR)
CAPM Forecast
($0 RFR)
Donor 1
1.08
$ 1,250
$ 1,032
$ 1,107
Donor 2
0.46
$ 775
$ 1,014
$ 472
Donor 3
1.67
$ 1,250
$ 1,050
$ 1,725
Donor 4
2.20
$ 750
$ 1,066
$ 2,269
Donor 5
-0.41
$ 1,125
$
$ (423.62)
987
© 2013 Tommy Tavenner

24. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory

25. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
Attempts to maximize the return of a portfolio for a
given amount of risk
•
Focuses on diversification of assets based on their
individual volatility.
© 2013 Tommy Tavenner

26. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
Requirements:
> an estimate of the overall portfolio’s return
> Understanding the correlation of the component assets
© 2013 Tommy Tavenner

27. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
Expected Return
> Many methods to forecast future returns
1. Linear/Non linear regression
2. Simple averaging
3. Seasonality and Time Series Analysis
> Depends on the giving patterns of your donors
© 2013 Tommy Tavenner

28. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
Portfolio Correlation
> Looking at the observations for each donor, how closely related
is the movement of their giving.
> Example
Year 1
Year 2
Year 3
Year 4
Donor 1
$ 100
$ 120
$120
$ 115
Donor 2
$ 75
$ 100
$ 80
$ 75
Donor 3
$ 100
$ 125
$ 150
$ 125
Donor 4
$ 50
$ 75
$ 50
$ 50
Donor 5
$ 75
$ 100
$ 100
$125
© 2013 Tommy Tavenner

29. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
Portfolio Correlation
$160
$140
$120
Donor 1
Donor 2
Donor 3
Donor 4
Donor 5
$100
$80
$60
$40
$20
$Year 1
Year 2
Year 3
© 2013 Tommy Tavenner
Year 4

30. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
Portfolio Correlation
Donor 1
Donor 2
Donor 3
Donor 4
Donor 1
Donor 2
55.48 %
Donor 3
86.27 %
17.15 %
Donor 4
44.02 %
98.02 %
0.00 %
Donor 5
64.70 %
0.00 %
50.00 %
© 2013 Tommy Tavenner
0.00 %
Donor 5

31. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
The Efficient Frontier
> Created by Harry Markowitz
> Finds the lowest risk portfolio for a target return
> Accomplishes this by minimizing standard deviation
© 2013 Tommy Tavenner

32. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
Covariance Matrix
Donor 1
Donor 1
Donor 2
Donor 3
Donor 4
Donor 5
Donor 2
Donor 3
Donor 4
Donor 5
67.1875
46.875
125
39.0625
93.75
46.875
106.25
31.25
109.375
0
125
31.25
312.5
0
156.25
39.0625
109.375
0
117.1875
0
93.75
0
156.25
0
312.5
© 2013 Tommy Tavenner

33. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
The Efficient Frontier
Average Gift $ 31.25 $ 35.00
Standard
Deviation
16.298 16.421
Slope
$ 40.00
$ 45.00
$ 50.00
$ 55.00
16.583
16.744
16.903
17.060
1.917
2.131
2.412
2.687
2.958
3.223
Donor 1
0%
0%
0%
0%
0%
0%
Donor 2
0%
14%
33%
52%
71%
90%
Donor 3
0%
0%
0%
0%
0%
0%
Donor 4
100%
86%
67%
48%
29%
10%
Donor 5
0%
0%
0%
0%
0%
0%
© 2013 Tommy Tavenner

34. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio – The Efficient Frontier
$100.00
$80.00
$60.00
$40.00
$20.00
$-
© 2013 Tommy Tavenner

35. Data Analytics Symposium
August 7-8, 2013
Modern Portfolio Theory
•
Minimizing Beta
> Calculate the beta of each donor
> Portfolio Beta = β₁ω₁
+ β2ω2 + … + βnωn
> Option 1: Find top X donors who produce the lowest β
> Option 2: Find the appropriate weights for a given set of donors
that minimizes overall β
© 2013 Tommy Tavenner

36. Data Analytics Symposium
August 7-8, 2013
Other Measures to Explore

37. Data Analytics Symposium
August 7-8, 2013
Sharpe Ratio
•
Measures the return of an asset per unit of deviation.
•
How much reward for how much risk
© 2013 Tommy Tavenner

38. Data Analytics Symposium
August 7-8, 2013
Sharpe Ratio
•
How it applies to fundraising
•
Unlike β, the Sharpe Ratio does not compare a donor’s
volatility to that of a benchmark
•
Useful for comparing the relative volatility of donors
across different giving circles.
© 2013 Tommy Tavenner

39. Data Analytics Symposium
August 7-8, 2013
Sortino Ratio
•
A modification of the Sharpe ratio that only penalizes
downside volatility
•
Requires a minimum acceptable return (MAR)
•
Only values which fall below the MAR are counted in
the formula
© 2013 Tommy Tavenner

40. Data Analytics Symposium
August 7-8, 2013
Sortino Ratio
•
How it applies to fundraising
•
Just like in finance, we are usually only concerned with
volatility that causes giving to decrease.
© 2013 Tommy Tavenner

41. Data Analytics Symposium
August 7-8, 2013
Treynor Ratio
•
Returns subtracted from the risk free rate and divided
by beta
© 2013 Tommy Tavenner

42. Data Analytics Symposium
August 7-8, 2013
Treynor Ratio
•
How it applies to fundraising
•
More granular than Sharpe, you can see how a donor
or marketing effort’s independent return (i.e. in addition
to the benchmark) compares to its independent
volatility.
© 2013 Tommy Tavenner

43. Data Analytics Symposium
August 7-8, 2013
Jensen’s Alpha
•
Measures the additional return over a theoretical return.
•
The theoretical return is typically the value derived from
CAPM
© 2013 Tommy Tavenner

44. Data Analytics Symposium
August 7-8, 2013
Jensen’s Alpha
•
How it applies to fundraising
•
Use to compare performance against both your CAPM
value and projected value to see how closely it
performed.
© 2013 Tommy Tavenner