volatility presentation - u.s. department of the treasury volatility presentation . asset price...

1

Volatility Presentation

Asset price volatility has declined over the past two years both in the United States and globally. At the same time, forward-looking measures of market uncertainty across a range of fixed income, equity, and foreign exchange markets have also declined. What are the Committee’s views on these developments and the factors that have contributed to the current environment of low volatility globally?

2

Current state of volatility

Monthly count of Bloomberg articles that contain the phrase “low volatility”. ? Theirs, unclear, mine, relentless comments

3

Current state of volatility

Credit Suisse Interest Rate Volatility Estimate: yield curve weighted index of normalized implied volatility on a rolling series of constant at-the-money one-month expiry swaptions weighted across benchmark maturities 2yr, 5yr, 10yr and 30yr. ? Theirs, unclear, mine, relentless comments

4

Factors contributing to low volatility

1. Actions by the Fed and ECB have significantly clipped the left tail risk, in terms of both economic outcomes and market outcomes (QE I)

2. As interest rates approached the zero lower bound, rate vol is lower by construction which leads to maturity extensions, lower term premia and declining volatility across other asset classes through a lower and more certain discount rate (QE II)

3. Suppression of yield and vol induces investors to take on more risk (QE III). The market clings to perception of certainty regarding outcomes, despite the Fed shifting commitment modes from time or level-based to data dependent. This stage of policy should eventually lead to increased uncertainty and risk.

? Theirs, unclear, mine, relentless comments

Cross asset volatility through progression of central bank policy

0

50

100

150

200

250

0

10

20

30

40

50

60

Jan-

09

May

-09

Sep-

09

Jan-

10

May

-10

Sep-

10

Jan-

11

May

-11

Sep-

11

Jan-

12

May

-12

Sep-

12

Jan-

13

May

-13

Sep-

13

Jan-

14

May

-14

3m10

y bp

vol

VIX

and

FX lo

g vo

l

VIX index EUR/USD 3mth vol 3m10y vol (RHS)

QE I QE II and Operation Twist QE III

5

Short term price volatility versus long term economic uncertainty

Realized volatility is extremely low, which leads to lower implied volatility in a self-reinforcing loop.

-10%

10%

30%

50%

70%

Jul-1

0

Oct

-10

Jan-

11

Apr-

11

Jul-1

1

Oct

-11

Jan-

12

Apr-

12

Jul-1

2

Oct

-12

Jan-

13

Apr-

13

Jul-1

3

Oct

-13

Jan-

14

Apr-

14

Jul-1

4

Implied and Realized Vols in Equities

VIX Index SPX 1mth realized vol

0

5

10

15

20Implied and Realized Vols in FX

EUR/USD 1mth implied EUR/USD 1mth realized vol

0

50

100

150

200Implied and Realized Vols in 10yr Rate (bpvol)

1m10y implied vol 1m10y realized vol

0%

20%

40%

60%

80%

100%

Jul-1

0

Oct

-10

Jan-

11Ap

r-11

Jul-1

1

Oct

-11

Jan-

12

Apr-

12

Jul-1

2

Oct

-12

Jan-

13Ap

r-13

Jul-1

3

Oct

-13

Jan-

14Ap

r-14

Jul-1

4

IG Implied & Realized Vol

IG CDX 3mth implied vol IG CDX 3mth realized vol

6


Dispersion among Wall Street analyst forecasts for GDP is falling – VIX level on right hand scale – Standard deviation of US GDP forecasts provided to database on left hand scale

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The Global financial Stress Index (GFSI) measures • Risk as indicated by cross-asset measures of volatility, solvency and liquidity • Hedging demand implied by equity and currency option skew • Investor risk appetite gauged by trading volumes and flows into equities and high yield bonds

and out of money markets 33 out of 39 indicators point to vol being too low.

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Realized volatility follows the business cycle – high around recessions, falling with recovery, bottoming out mid to late cycle before turning up again

5

10

15

20

25

30

35

5

10

15

20

25

30

35

Jan-

37

Jan-

43

Jan-

49

Jan-

55

Jan-

61

Jan-

67

Jan-

73

Jan-

79

Jan-

85

Jan-

91

Jan-

97

Jan-

03

Jan-

09

Jan-

15

Recession S&P 500 Realized Vol (12m ma, rhs)

1m vol

3m vol

1987 Crash WorldCom Bankruptcy US

Down-grade

Asian Crisis

* Realized vol is the annualized standard deviation of daily log changes in S&P 500 over a 1m window

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Supply / demand factors in the options markets

Tail hedgers have decreased as evidenced by

• Falling prices of downside puts on the S&P

• Shrinking fund size of VIX ETF

0

1

2

3

4

5

6

7

8

9

10

1996

1997

1998

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2003

2004

2005

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2009

2010

2011

2012

2013

2014

S&P 500 3m 90% Put Price (%)

0

500

1,000

1,500

2,000

2,500

3,000

Jan-

09Ap

r-09

Jul-0

9O

ct-0

9Ja

n-10

Apr-

10Ju

l-10

Oct

-10

Jan-

11Ap

r-11

Jul-1

1O

ct-1

1Ja

n-12

Apr-

12Ju

l-12

Oct

-12

Jan-

13Ap

r-13

Jul-1

3O

ct-1

3Ja

n-14

Apr-

14

USD

mill

ions

VIX ETF VXXTotal Fund Size USD millions

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Convexity hedging by mortgage accounts has gone down significantly after the crisis because of lower issuance and the Fed’s QE purchases. QE mortgage purchases remove both duration and convexity from the market, making it one of the most powerful policy tools.

MBS Issuance

0%

5%

10%

15%

20%

25%

30%

35%

40%

Jun-

09Se

p-09

Dec-

09M

ar-1

0Ju

n-10

Sep-

10De

c-10

Mar

-11

Jun-

11Se

p-11

Dec-

11M

ar-1

2Ju

n-12

Sep-

12De

c-12

Mar

-13

Jun-

13Se

p-13

Dec-

13M

ar-1

4Ju

n-14

Fed MBS holdings % outstanding

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QE mortgage purchases remove both duration and convexity from the market, making it one of the most powerful policy tools.

Duration effect of QE

Convexity effect of QE

-

50

100

150

200

250

Oct

-09

Jan-

10

Apr-

10

Jul-1

0

Oct

-10

Jan-

11

Apr-

11

Jul-1

1

Oct

-11

Jan-

12

Apr-

12

Jul-1

2

Oct

-12

Jan-

13

Apr-

13

Jul-1

3

Oct

-13

Jan-

14

Apr-

14

Jul-1

4

Estim

ated

Dol

lar a

mou

nt o

f DV0

1 ad

ded

in a

10

0bps

sello

ff (in

MM

$)

Impact of convexity on Fed DV01 Impact of convexity on Index DV01

0%

10%

20%

30%

40%

50%

60%

0

50

100

150

200

250

Oct

-09

Jan-

10

Apr-

10

Jul-1

0

Oct

-10

Jan-

11

Apr-

11

Jul-1

1

Oct

-11

Jan-

12

Apr-

12

Jul-1

2

Oct

-12

Jan-

13

Apr-

13

Jul-1

3

Oct

-13

Jan-

14

Apr-

14

Jul-1

4

Ratio

Fed

/Ind

ex (i

n %

)

Dolla

r am

ount

of D

V01

(in M

M$)

Ratio of DV01 Fed DV01 (in $MM)

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Market complacency and excessive risk taking

Interest rate volatility can be viewed as a proxy for the corporate bond market and the interest rate at which people and companies borrow money. Shown below is 1y10y interest rate vol with 5yr spreads of the credit default index of investment grade on the left and high yield on the left.

60

80

100

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400

600

800

1000

1200

1400

1600

1800

1y10

y bp

vol

HY C

DX

HY CDX 5yr spread bps (LHS) 1y10y bpvol (RHS)

60

80

100

120

140

160

40

90

140

190

240

290

1y10

y bp

vol

IG C

DX

IG CDX 5yr spread bps (LHS) 1y10y bpvol (RHS)

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Days with a 10% or greater correction in the S&P Days in which SPX is at least 10% lower than the peak of the prior 6 months

0200400600800

100012001400160018002000

Jun-

84

Jun-

86

Jun-

88

Jun-

90

Jun-

92

Jun-

94

Jun-

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Jun-

98

Jun-

00

Jun-

02

Jun-

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Jun-

06

Jun-

08

Jun-

10

Jun-

12

Jun-

14

0

1

Days of 10% Correction SPX

Note the lack of 10% corrections during the past hiking cycles in 2004 and 1994

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Against environment of low vol and low returns, the only way to achieve the same return targets is to take on more risk - Ballooning AUM invested in hedge funds, now $2.7 trillion - VAR-based risk management frameworks and risk-parity investment models in which volatility

is an input that determines the amount of risk to take

2,801

0

500

1,000

1,500

2,000

2,500

3,000

1990

1991

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2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

Q1

2014

Q2

2014

AUM

USD

bill

ions

Hedge fund AUM

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Mostly unchanged target for investment returns from the pension community. Latest data from November 2013 shows the median target shifted to just under 8% in 2012, despite the yield on Moody’s AA index having fallen to 4.2%.

3.03.54.04.55.05.56.06.57.07.58.0

Moody's Corporate AA Index

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Financial market indicators of excessive risk taking

This represents the extra yield of owning pass-thru mortgage securities from the option value without embedded prepayment assumptions.

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-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

Feb-

98

Feb-

99

Feb-

00

Feb-

01

Feb-

02

Feb-

03

Feb-

04

Feb-

05

Feb-

06

Feb-

07

Feb-

08

Feb-

09

Feb-

10

Feb-

11

Feb-

12

Feb-

13

Feb-

14

S&P 500 implied vol term slope (% of 1m vol, 1m ma)

3m minus 1m 6m minus 3m

Equity vol term structure has held up against complacency in the market place.

-5%

0%

5%

10%

15%

-5%

-3%

-1%

1%

3%

5%

7%

9%

11%

13%

15%

Aug-

09

Nov

-09

Feb-

10

May

-10

Aug-

10

Nov

-10

Feb-

11

May

-11

Aug-

11

Nov

-11

Feb-

12

May

-12

Aug-

12

Nov

-12

Feb-

13

May

-13

Aug-

13

Nov

-13

Feb-

14

May

-14

Aug-

14

FX implied vol term slope (% of 1m vol, 1m ma)


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FX vol term structure is also near the steepest level in the last 5 years.

19


-15%

-10%

-5%

0%

5%

10%

15%

-15%

-10%

-5%

0%

5%

10%

15%

Jun-

96

Jun-

97

Jun-

98

Jun-

99

Jun-

00

Jun-

01

Jun-

02

Jun-

03

Jun-

04

Jun-

05

Jun-

06

Jun-

07

Jun-

08

Jun-

09

Jun-

10

Jun-

11

Jun-

12

Jun-

13

Jun-

14

10y bond implied vol term slope (% of 1m vol, 1m ma)


Rate vol term structure is off the highs despite the Fed being closer to tightening than at any other point in the last 5 years.

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Equity volatility term structures

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Interest rate volatility term structures

25

45

65

85

105

125

145

165

185

205

225Au

g-04

Feb-

05Se

p-05

Mar

-06

Oct

-06

Apr-

07N

ov-0

7Ju

n-08

Dec-

08Ju

l-09

Jan-

10Au

g-10

Feb-

11Se

p-11

Apr-

12O

ct-1

2M

ay-1

3N

ov-1

3Ju

n-14

Dec-

14Ju

l-15

Jan-

16Au

g-16

Mar

-17

Sep-

17Ap

r-18

bpvo

l

10yr rate vol term structures

2005 2006 2007 2008 20092010 2011 2012 2013 2014

Warning sign

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Liquidity providers Less warehouses for risk = higher storage costs

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Conclusions

Monetary policy and regulatory changes have contributed to the decline in volatility.

Less demand for volatility across asset classes naturally lowers the price for such insurance.

VAR-based analysis leads to self-reinforcing loops as low volatility causes models to recommend scaling up risk.

The term structure of volatility is a powerful indicator; flatter vol curves would suggest excessive complacency and presage increasing risk.

Volatility tends to rise mid-to-late stage of the business cycle as expansive endeavors increase through the system.

An unexpected increase in volatility might come from broad-based selling of assets wanting to de-risk in front of a turn in policy.

With liquidity providers having declined in number and capacity, the system is less able to deal with such episodes of higher volatility. Institutions which deliver absolute returns or provide liquidity to the system would be most at risk.

24

Reference

P6: Consensus Economics, UBS

P7: Bank of America Merrill Lynch

P8: Haver, Deutsche Bank

P11: Citibank

P14: HFR Global Hedge Fund Industry Report

P15: Public Fund Survey

P17: Deutsche Bank

P18: Deutsche Bank. FX vol is computed on the currencies that make up the Deutsche Bank Currency Volatility Index.

P19: Deutsche Bank

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