Using Financial Analysis Techniques for Non-Profit Fundraising

Using Financial Analysis Techniques

in non-profit fundraising

Data Analytics SymposiumAugust 7 – 8, 2013 • Baltimore, Maryland

By Tommy TavennerNational Wildlife Federation

Data Analytics SymposiumAugust 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


• 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

Why you should study it



• Prospect Research = Fundamental Analysis

• Analytics = Technical Analysis

How It Relates



Fundamental Analysis

• Determine the value of a company by looking at it’s principal components

> Financial Statements

> Management Team

> Competitive Environment



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



Some caveats

• Our information is less complete

• The amount we invest in a donor is more highly correlated with their giving



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)



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.



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



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 )



Concepts

• Calculating Beta for a donor

β = CoVar

=Var

$ 100 $ 80

$120 $ 94

$120 $ 90

$115 $ 93

$ 80

$ 94

$ 90

$ 93

55.417

40.917= 1.354



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 thepopulation

β > 1 The size of the donor’s gift moves in the same direction but more dramatically as the population



CAPITAL ASSETS PRICING MODEL


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




• 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




• 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)




• 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



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




• 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:

— Excel FORECAST function

4. Risk Free Rate: Base giving level - $1,000




= $1,000 + 1.08( $1,030 – $1,000 )

= $1,032.26

Risk Free Rate: $1,000

Market Forecast: $1,030

Donor 1 β: 1.08

Estimated Return for Donor 1




= 0 + 1.08( $1,030 –0 )

= $1,107.46

Risk Free Rate: $0

Market Forecast: $1,030

Donor 1 β: 1.08

Estimated Return for Donor 1




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 $ 987 $ (423.62)



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.




• Requirements:

> an estimate of the overall portfolio’s return

> Understanding the correlation of the component assets




• 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




• 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



Modern Portfolio TheoryPortfolio Correlation

$-

$20

$40

$60

$80

$100

$120

$140

$160

Year 1 Year 2 Year 3 Year 4

Donor 1

Donor 2

Donor 3

Donor 4

Donor 5




• Portfolio Correlation

Donor 1 Donor 2 Donor 3 Donor 4 Donor 5

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 % 0.00 %




• The Efficient Frontier

> Created by Harry Markowitz

> Finds the lowest risk portfolio for a target return

> Accomplishes this by minimizing standard deviation




• Covariance Matrix

Donor 1 Donor 2 Donor 3 Donor 4 Donor 5

Donor 167.1875 46.875 125 39.0625 93.75

Donor 246.875 106.25 31.25 109.375 0

Donor 3125 31.25 312.5 0 156.25

Donor 439.0625 109.375 0 117.1875 0

Donor 593.75 0 156.25 0 312.5




• The Efficient Frontier

Average Gift $ 31.25 $ 35.00 $ 40.00 $ 45.00 $ 50.00 $ 55.00

Standard Deviation 16.298 16.421 16.583 16.744 16.903 17.060

Slope 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%



Modern Portfolio – The Efficient Frontier

$-

$20.00

$40.00

$60.00

$80.00

$100.00




• 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



Other Measures to Explore


Sharpe Ratio

• Measures the return of an asset per unit of deviation.

• How much reward for how much risk



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.



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



Sortino Ratio


• Just like in finance, we are usually only concerned with volatility that causes giving to decrease.



Treynor Ratio

• Returns subtracted from the risk free rate and divided by beta



Treynor Ratio


• 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.



Jensen’s Alpha

• Measures the additional return over a theoretical return.

• The theoretical return is typically the value derived from CAPM



Jensen’s Alpha


• Use to compare performance against both your CAPM value and projected value to see how closely it performed.


Technology

Using Financial Analysis Techniques for Non-Profit Fundraising