Financial Risk Management Chris Droussiotis October 2011 Lecture Series #3

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Lecture Series #3
Financial Risk Management
Chris Droussiotis
October 2011
Table of Contents
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2
Managerial Strategies
Return, Risk, Asset Allocation and Time
Fundamental Analysis
Technical Analysis
Behavioral Analysis
Managerial Strategies – Value Creation
Economic Environment
EXIT
POINT
Exit Point
•Terminal
Value
ENTRY
POINT
3
VALUE CREATION – MANAGERIAL / INVESTMENT STRATEGIES
Entry Point
•Startup – Build
•Economic Studies
•Acquiring Initial Funds (Equity/Debt)
•The Right Price / Cost as compared to Future
Cash Flows
•Going Private/Public
Determinants of Value
 Cash Flow
 Timing of Cash Flow
 Risk
Managerial Strategies – Value Creation
Risk #1: Volatility
Standard Deviation (σ)
EXIT
POINT
Standard Deviation (σ)
ENTRY
POINT
4
Value Creation - Managerial Strategies

Operating Strategies
–
–

Transactional Strategies
–
–

–
–
Refinancing / Optimum Structure
Foreign Exchange Strategies – Hedge against FX moves – International
Lease or Buy (Equipment, Buildings, Trucks)
Social Responsibility / Ethical – Corporate Governance
–
–
–
–
5
Grow through acquisitions
Joint Ventures
Financial Strategies
–

Grow internally – manage Revenue, Expenses & Cash Flow –
Manage Systematic Risk / Credit Risk / Market Risk / Operational Risk
–
Shareholders
Employees
Community
Bankers/Creditors
Environmental
Financial Risk Management
6

Seeking Return

Identifying Risk

Achieving Diversification via Asset Allocation

Time is important
Seeking Return - Return Basic Analysis
RISK RETURN –
Traditionally, when you define return you refer to a bank savings account (risk free) plus a risky portfolio of
US stocks. Today, investors have access to a variety of asset classes and financial engineered
investments
HPR = (Ending Price – Beg. Price + Div) / Beg. Price
Example:
Current Price = $100, expected price to increase to $110 in a year. Within the year you are expected to
receive $4 dividend, therefore the HPR=(110-100+4)/$100 = 14%
7
RISK and Return
HOW DO WE QUANTIFY THE UNCERTAINTY OF INVESTMENT
To summarize risk with a single number we find VARIANCE, the expected
value of the squared Deviation for the mean, first. (I.e. the expected value of
the squared “surprise”: across scenarios.)
8
RISK and Return
HOW DO WE QUANTIFY THE UNCERTAINTY OF INVESTMENT
STANDARD DEVIATION DEFINITION: The Standard Deviation (σ) is a
measure of how spreads out numbers are. (Note: Deviation just means how
far from the normal). So, using the Standard Deviation we have a "standard"
way of knowing what is normal, and what is extra large or extra small.
9
VOLATILITY vs RETURN
Sharpe Ratio:
Risk Premium over the Standard Deviation of portfolio excess return
(E(r p) – r f ) / σ
8% / 20% = 0.4x. A higher Sharpe ratio indicates a better reward per unit of volatility,
in other words, a more efficient portfolio
10
VOLATILITY Vs RETURN and ASSET ALLOCATION
Building the Optimal Portfolio
+ Optimal Risky Portfolio (P)
+ Proportion of the Investment budget (Y) to be allocated to it.
+ The remaining portion (1-Y) is to be invested is the Risk-free Asset (rf)
+ Actual risk rate of return by rp on P by E(rp) and Standard Deviation
+ The rate on risk-free asset is denoted a rf
+ The portfolio return is E(rc)
E (rp)
= 15%
σ
= 22 %
Rf
=7%
E(rp – rf)
= 8%
11
RISK,RETURN, ASSET ALLOCATION AND DIVERSIFICATION
12
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DIVERSIFICATION AND PORTFOLIO RISK

From one stock to two stocks to three stocks….. sensitivity to external factors
(i.e. oil, non-oil stocks) – But even extensive diversification cannot eliminate
risk – MARKET RISK

Other Names for Market risk: Systematic risk, non-diversifiable risk

The Risk that can be eliminated by diversification is called:
– Unique Risk
– Firm-specific risk
– Non-systematic risk
– Diversifiable risk
RISK,RETURN, ASSET ALLOCATION, DIVERSIFICATION AND CORRELETION
Relationship between the return of two assets (-1 TO 1)

Tandem

Opposition
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13
E(rb) = 6.0%
E(rs) = 10%
σb= 12%
σs= 25%
Pbs = 0
Wb=0.5
Ws=0.5
σp^2= (Wb*σb)^2 + (Ws*σs)^2 + 2 (Wb*σb) (Ws*σs)* Pbs
σp^2=(0.5*12)^2 + (0.5*25)^2 + 2(0.5*12)(0.5*25)*0
σp = SqRt of 192.25 = 13.87%
RISK,RETURN, ASSET ALLOCATION, DIVERSIFICATION AND CORRELETION
10
6
2
5
1
2
Minimum Variance
Stocks
Bonds
14
100% Stocks
10.00
0
Portfolio Weights
Ws
Wb
0.0
1.0
0.1
0.9
0.2
0.8
0.3
0.7
0.4
0.6
0.5
0.5
0.6
0.4
0.7
0.3
0.8
0.2
0.9
0.1
1.0
0.0
18.7256%
81.2744%
E(r) Vs Std Dev with 0 correlation
12.00
Stocks 18.73%
Bonds 81.27%
Exp Return
E(rp) %
6.00
6.40
6.80
7.20
7.60
8.00
8.40
8.80
9.20
9.60
10.00
Std Dev.
σp %
12.00
11.09
10.82
11.26
12.32
13.87
15.75
17.87
20.14
22.53
25.00
8.00
E (r)
Parameters
E (rs) =
E (rb) =
σs =
σb=
Psb =
100% Bonds
6.00
4.00
2.00
0.00
0.00
5.00
Ws=(σb^2 - σb σs p) / (σs^2 + σb^2 - 2*σb σs p)
W
b
=
1
-
W
s
10.00
15.00
Std Dev
20.00
25.00
30.00
WHAT ARE THE IMPLICATIONS OF PERFECT POSITIVE CORRELATION
BETWEEN BONDS & STOCKS??
• Let’s say the correlation is 1 or Pbs = 1 (so far we used 0 correlation)
σp^2 = Wb^2 σb ^2 + Ws^2 σs^2 + 2 Wb*σb Ws*σs * 1 = Wb*σb + Ws*σs
15
WHAT ARE THE IMPLICATIONS OF PERFECT POSITIVE CORRELATION
BETWEEN BONDS & STOCKS??
• Let’s say the correlation is 1 or Pbs = - 1
σp^2 = (Wb*σb – Ws*σs)^2
16
WHAT ARE THE IMPLICATIONS OF PERFECT POSITIVE CORRELATION
BETWEEN BONDS & STOCKS??
THE OPTIMAL RISKY PORTFOLIO W/ A RISK-FREE ASSET
• Let’s add Risk Free in our portfolio (bringing what we discussed before regarding CAL line)
17
Comparing Volatility to the Market: BETA COEFFICIENT
First Step: understanding CAPM:
E(rs) = rf + b * p + e
The model that predicts the relationship between the risk and equilibrium expected returns on risky
assets
Second Step: Defining Beta
18
Comparing Volatility to the Market: BETA COEFFICIENT
Defining Beta
19
Comparing Volatility to the Market: BETA COEFFICIENT
Defining Beta
20
Valuation Methods – Private Company

DCF Analysis
–
Transaction Sources & Uses

Capital markets
–
–


–
Initial Valuation – purchase price / Cost of investment
WACC / CAPM concepts
Debt Schedule Payments

Principal & Interest
–
–
21
Debt (Loans. Mezzanine and Corporate Bonds)
Equity (Private & Public)
Floating Rate
Fixed Rate
DCF Analysis – Transaction Sources & Uses
TRANSACTION SOURCES & USES
Sources:
Bank Loan
Mezzanine Note
Total Debt
Equity
Total Sources
Uses:
Purchase Price (EV - including Debt)
Transaction Fees & Expenses
Total Uses
22
Debt
Capacity
(EBITDA x)
2.5x
4.0x
1st Year's
EBITDA
Multiple
6.0x
3.0%
Amount
50,000,000
30,000,000
80,000,000
43,600,000
123,600,000
% Capital
40.5%
24.3%
64.7%
35.3%
100.0%
120,000,000
% of
Total
Uses
97.1%
3,600,000
123,600,000
2.9%
100.0%
Amount
Expected
Return
Expected
Return
(After Tax)
5.364%
9.000%
3.433%
5.760%
20.00%
20.00%
WACC
(After Tax)
EBITDA
Multiple
1.39%
1.40%
2.79%
7.05%
9.84%
2.5x
1.5x
4.0x
2.2x
6.2x
WACD = 4.305%
Tax Rate=
36.0%
DCF Analysis – Applying CAPM :
E (re) = rf - β . Pe + ε
COST OF DEBT AND EQUITY
CALCULATIONS
COST OF BANK DEBT CALCULATION
(Floaring Rate)
3M-LIBOR
Assumptions
0.30%
Loan
Spread
4.00%
Equity Risk Premiums (1926-2006)
(CAPM Model)
Initial All -In
Decile
4.30%
1
524,351
7.03%
2
10,344
8.05%
3
4,144
8.47%
4
2,177
8.75%
5
1,328
9.03%
COST OF MEZZANINE NOTE CALCULATION
9.00%
COST OF EQUITY CALCULATION
E (re) = rf - β . Pe + e
Risk Prem.
6-year Treasury Note [ rf ]
1.95%
6
840
9.18%
Beta for Publicly Traded Hotel [ β ]
1.633x
7
538
9.58%
11.05%
8
333
9.91%
0.0%
9
193
10.43%
20.00%
10
85
11.05%
Equity Premium [ Pe ]
23
Mkt Cap $MM
Firm Specific Risk Premium [e]
Cost of Equity
DCF Analysis – Debt Schedules
Debt Money Terms:
• Amount
• Interest Rate (Floating – LIBOR Rate and Fixed Rate)
• Maturity
• Amortization
DEBT ASSUMPTIONS & RETURN ANALYSIS
Bank Loan Information
Amount Outstanding (End of Year)
Schedule Principal Payments
Interest Payment (Calc based on last Year's Outs)
Total Financing Payment
LIBOR RATE
LIBOR Rate Increase Assumptions
Corporate Bond Information
Amount Outstanding
Schedule Principal Payments
Interest Payment (Calc based on last Year's Outs)
Total Financing Payment
Total Financing
Total Debt Outstanding
24
Debt IRR
5.364%
9.000%
Terms
50,000,000
7 years
5.36%
(50,000,000)
0.30%
2010
47,000,000
3,000,000
2,150,000
5,150,000
0.30%
0.00%
2011
42,000,000
5,000,000
2,256,000
7,256,000
0.80%
0.50%
2012
37,000,000
5,000,000
2,226,000
7,226,000
1.30%
0.50%
2013
31,000,000
6,000,000
2,331,000
8,331,000
2.30%
1.00%
2014
24,000,000
7,000,000
1,953,000
8,953,000
2.30%
0.00%
2015
15,000,000
9,000,000
1,512,000
10,512,000
2.30%
0.00%
2016
30,000,000
10 Years
9.00%
(30,000,000)
30,000,000
2,700,000
2,700,000
30,000,000
2,700,000
2,700,000
30,000,000
2,700,000
2,700,000
30,000,000
2,700,000
2,700,000
30,000,000
2,700,000
2,700,000
30,000,000
2,700,000
2,700,000
30,000,000
2,700,000
2,700,000
7,850,000
77,000,000
9,956,000
72,000,000
9,926,000
67,000,000
11,031,000
61,000,000
11,653,000
54,000,000
13,212,000
45,000,000
18,645,000
30,000,000
15,000,000
945,000
15,945,000
2.30%
0.00%
DCF Analysis – Building up the Projections
CASH FLOW & EQUITY RETURN ANALYSIS
Company Projections
Operating
Assump.
5.00%
35.0%
15.0%
50.0%
3.00%
7
Revenues
Cost of Revenues
Operating Costs
EBITDA
Less Depreciation
Less Amortization of Fees
EBIT
Less Interest (Unlevered for DCF Analysis)
EBT
Less Taxes (adj out Interest Exp)
Plus Depreciation & Amortization
Less Working Capital
Less Capex
Cash Flow Before Financing (CFBF)
Entry Year
2009
growth
% of Revenue
% of Revenue
% of Revenue
years
36.0% % of EBT
1.00% % of Revenue
3.00% % of Revenue
Less Financing ( P + I )
Equity Cash Flows
Terminal Value
EBITDA Multiple Method (initial purchase multiple)
Perpetuity Method (using WACC + growth)
Year 1
2010
40,000,000
(14,000,000)
(6,000,000)
20,000,000
(1,200,000)
(514,286)
18,285,714
18,285,714
(6,582,857)
1,714,286
(400,000)
(1,200,000)
11,817,143
Year 2
2011
42,000,000
(14,700,000)
(6,300,000)
21,000,000
(1,260,000)
(514,286)
19,225,714
19,225,714
(6,921,257)
1,774,286
(420,000)
(1,260,000)
12,398,743
Year 3
Year 4
2012
2013
44,100,000 46,305,000
(15,435,000) (16,206,750)
(6,615,000) (6,945,750)
22,050,000 23,152,500
(1,323,000) (1,389,150)
(514,286)
(514,286)
20,212,714 21,249,064
20,212,714 21,249,064
(7,276,577) (7,649,663)
1,837,286
1,903,436
(441,000)
(463,050)
(1,323,000) (1,389,150)
13,009,423 13,650,637
Year 5
2014
48,620,250
(17,017,088)
(7,293,038)
24,310,125
(1,458,608)
(514,286)
22,337,232
22,337,232
(8,041,403)
1,972,893
(486,203)
(1,458,608)
14,323,912
Exit Year
2015
2016
51,051,263
53,603,826
(17,867,942) (18,761,339)
(7,657,689)
(8,040,574)
25,525,631
26,801,913
(1,531,538)
(1,608,115)
(514,286)
23,479,808
25,193,798
23,479,808
25,193,798
(8,452,731)
(9,069,767)
2,045,824
1,608,115
(510,513)
(536,038)
(1,531,538)
(1,608,115)
15,030,850
15,587,992
(7,850,000)
3,967,143
(9,956,000)
2,442,743
(9,926,000) (11,031,000)
3,083,423
2,619,637
(11,653,000)
2,670,912
(13,212,000) (18,645,000)
1,818,850
(3,057,008)
Growth
6.0x
153,153,788
3.50%
9.84%
245,812,934
Average Terminal Value
Debt Outstanding
Equity Value (TV - Debt)
199,483,361
45,000,000
154,483,361
Equity Cash Flows
25
(43,600,000)
$ 1 PV Table (Expected Equity Rate)
PV Table (Expected Equity Rate)
20.00%
61,471,300
Initial Investment
NPV=
(43,600,000)
17,871,300
IRR=
27.9%
3,967,143
x
0.8333398
3,305,978
2,442,743
x
0.6944552
1,696,376
3,083,423
x
0.5787172
1,784,430
2,619,637
x
0.4822680
1,263,367
2,670,912
x
0.4018931
1,073,421
156,302,211
x
0.3349135
52,347,728
Equity Return Scenarios Given Different EBITDA Multiples
5.5x
6.0x
6.5x
7.0x
36.4%
27.9%
22.1%
17.9%
Based on Next Y
Reviewing Financial Risk Management

Fundamental Analysis
–
–

Financial Ratio Analysis
DCF Valuation Analysis
Technical Analysis
–
Portfolio Analysis Approach


26
Historical Returns / Standard Deviation / Correlations
Behavioral Analysis
Behavioral Analysis Concepts
ARE MARKETS EFFICIENT? EMH Concept
Looking for behavioral motivations for buying/selling:
• High Exposure
• Risk Appetite
• Tax motivation
• Resource allocation
Behavioral Finance - People are people and they make decisions differently
“Irrational Exuberance” – Greenspan 12/2006 – affected the stock markets around the
world after he mention that word (Tokyo was down 3.0%, Hong Kong was down 2.0%,
UK down 3.0%, U.S. down 2.0%)
27
Behavioral Analysis Concepts
ARE MARKETS EFFICIENT? EMH Concept
INFORMATION PROCESSING
• Forecasting Errors – High multiples
• Overconfidence – “Irrational Exuberance”
• Conservatism – the article of banks – in Leverage Cycle
BEHAVIORAL BIASES
• Bluffing – Game theory – “All-in” has nothing, betting slow could have a good hand.
• Mental Accounting – managing other people’s money versus your own
• Regret Avoidance – unconventional choices Vs. acceptable choices when wrong
• Prospect theory - as wealth increases more risk averse.
28