japan strategy

7/28/2019 Japan Strategy

1/12

MONETARY POLICY AND EXTREME VALUES

LETS TALK ABOUT RISK

01

DATE:JUNE,2013

SUMMARY REPORT

AUTHOR:JEAN MEILHOC

Twitter: jeanmeilhoc

Linkedin: Jean Meilhoc

Scribd: jeanmeilhoc


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SUMMARY

I. JAPAN BOLD MONETARY POLICY: VIRTUOUS

CYCLE OF REFLATION ............................................................. 3

I.IBOLD MONETARY POLICY SUPPORT FROM BANK OF JAPAN AS

KURODA IS INSTALLED ................................................................... 3

I.IIPRO-GROWTH ABE ADMINISTRATION TO PURSUE KOIZUMIS

UNFINISHED BUSINESS..................................................................... 3

I.IIIPOSITIVE CHANGES FOR EQUITY MARKET SUPPLY/DEMAND

AND VALUATION ............................................................................. 3

II. LETS TALK ABOUT RISK ................................................... 5

II.IVARIANCE WITH ONE SOURCE OF RISK..................................... 5

II.IIIVARIANCE WITH TWO SOURCE OF RISK.................................. 5

II.IVVALUE AT RISK...................................................................... 6II.VCOMPUTATION......................................................................... 9

CONCLUSION .............................................................................. 12

KEY WORDS: MACROECONOMICS; MONETARY POLICY; BANK OF

JAPAN (BOJ); QUANTITATIVE EASING (QE); INFLATION; RISK

MANAGEMENT; QUANTITATIVE ANALYSIS; VALUE AT RISK; VAR

ONE;DELTA VAR


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I. JAPAN BOLD MONETARY POLICY: VIRTUOUS CYCLE OF

REFLATION

I.I Bold monetary policy support from Bank of Japan as

Kuroda is installed

Pre-requisite for equity investors nowadays as liquidity drives

markets

Inflation likely to move into positive territory by 2014

New era of weak yen following end of sage have status

I.II Pro-growth Abe administration to pursue Koizumis

unfinished business

Willing to open its market through new trade agreements

Implies accelerating restructuring and improved efficiency at

companies

Aiming to unlock the cash from Japan Incs balance sheet to

restart the economy

I.III Positive changes for equity market supply/demand

and valuation

Domestic investors both retail and institutional set to rethink

their equity allocations

Positive impact of mild inflation on valuations


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Robust Monetary

Policy Through QE

and Asset purchases

Inflation created

through debt

monetization and

through foreign goods

whose real value in

Yen rise

Yen weakening

Higher Corporate

earnings

Changing expectationsof economic agents:

Hoarding cash is no

longer a winning

game and Wealth

effect

Consumer activity

increases as well as

corporate re-leverage

Wages increase and

goods and assets pricesrise

TRUST

Inflation

Trade balancekeeps

deterioratin

Foreign direct

investment

exceeds current

account surplus

Life insurers

will likely

reduce their

currency

hedge ratios

and

generate huge

pressure to sell


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II.LETS TALK ABOUT RISK

Having discussed the various kinds of returns in considerable detail

in a range of research papers, we now turn to measures of riskiness of

Japanese investment. Just like return, there are various kinds of risk.Fluctuation prices could be measurable by statistical distributions.

We will consider the total risk of an asset or a portfolio of assets as

measured by its standard deviation, which is the square root of

variance.

II.I Variance with one source of risk

Variance is a measure of the volatility of returns. It is computedas the average squared deviation from the mean

Higher variance suggests less predictable profitability

The standard deviation of returns of an asset is the square root of

the variance of returns. Written !2

, we have:

!=

(Ri!)2

i=1

n

"

n!1. Y

, with:

o Ri the return for period i, calculated as R =Pt

Pt!1

!1

o P is the price of the asset

o n the total number of periods, assuming that it is the

sample of the population of returns, and

o =

Xi

i=1

n

!

n

o We also annualized !2

by multiplying by the square

root of a Y (252 days). It is usually the case in the

investment world where we only have a sample ofreturns available instead of the population of returns. The

above expression is useful to underestimates the variance.

II.III Variance with two source of risk

Like a portfolios return, we can calculate a portfolios

variance

When computing the variance of portfolio returns, standard

statistical methodology can be used to find the variance of


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the full expression of portfolio return. Although the return of

a portfolio is simply a weighted average of the returns of

each security this is not the case with the standard deviation

of a portfolio unless all securities are perfectly correlated,

with !=1

The standard deviation of a two-asset portfolio is given by

the weighted square root of the portfolios variance:

!p= w

1

2!

1

2+w

2

2!

2

2+2w

1!

1w

2!

2"

1,2. Y

, where

o w1 and w2 is the amount of money invested in the

first and the second asset respectively.

II.IV Value at Risk

In evaluating investments using expected return and variance,

risk managers make two important assumptions.

o First, they assume that the returns are normally

distributed because a normal distribution can be fully

characterized by its mean and variance first and second

moment respectively

o Second, they assume that markets are not only

informationally efficient but that they are also

operationally efficient.

Returns, however, are not normally distributed; deviations from

normality occur both because the returns are:

o skewed, which means they are not symmetric around the

mean and

o the probability of extreme events is significantly greater

than what a normal distribution would suggest referred

to as kurtosis or fat tails in a return distribution. High-

risk profile among the mean could be observed.

In financial mathematics and financial risk management, Value at

Risk is a risk measure of the risk of loss on a specific portfolio of

financial assets It is defined by risk exposure at a given probability level at a

specified time horizon

Mathematically, we have: VaR(q) = Ptwt.!NA.T.S

!1(q)

where:

o Pis the price of the asset in time t

o w the amount invested in the asset

o !N

Athe volatility calculated above regarding one or two

source of risks

o Tthe square root of the time horizon divided by Yand

o the distribution assumption S!1(q) . The latest

characterizes the inverse Student-t distribution On


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Excel: =-TDIST(1-q; DF), with DF, the degree of

freedom. This distribution take into account the fat tails

explained in section II.I. or mathematically:

!1

k!

"k+1

2

#

$

%&

'

(

"k

2

#

$%

&

'(

1+t2

k

#

$%&

'(

t+1

2

)

*

+

+++

,

-

.

..

.

!1

-3

-2

-1

0

1

2

3

0% 25% 50% 75% 100%

Inverse cumulated normal [N(x)] & Student-t [F(x)]

distribution

-N-1(x) -F-1(X)


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x0.1

%

1%

2%

5%

10%

20%

30%

40%

50%

60%

70%

80%

90%

95%

99%

99.9

%

-N-1(x)

-3.1

-2.3

-2.1

-1.6

-1.3

-0.8

-0.5

-0.3

0.0

0.3

0.5

0.8

1.3

1.6

2.3

3.1

-F-1(X)

-22.3

-7.0

-4.8

-2.9

-1.9

-1.1

-0.6

-0.3

0.0

0.3

0.6

1.1

1.9

2.9

7.0

22.3


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II.V Computation

By importing data from Bloomberg

PX_LAST

NKY Index

EURJPY Curncy From 6/14/10 to 6/13/13

we calculated Value at Risk shown below:

Global parameters: VaR NKY Index

Confidence Interval (q) 95.0%

Time 1

DF 2

Time horizon (year) 0.063

Student -F-1(1-q) 2.9

Date 13/06/13

Price () 12445

EURJPY 126

Nb stocks 1

Volatility 22%

Position 12445

Price Std Dev () 174

Position Std Dev () 174

VaR(q) (in )..................... 507

VaR (q) (in %)................... 4.1%

Value at Risk

Global parameters:

Confidence Interval (q)

Time

DF

Time horizon (year)

Student -F-1(1-q)

Date

Price ()

EURJPY

Nb stocks

Volatility

Position

Price Std Dev ()

Position Std Dev ()

VaR(q) (in ).....................

VaR (q) (in %)...................

Value at Risk

VaR EURJPY

95.0%

1

2

0.063

2.9

13/06/13

12445

126

1

13%

126

1

1

3

2.4%


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Global parameters:

Confidence Interval (q)

TimeDF

Time horizon (year)

Student -F-1(1-q)

Date

Price ()

EURJPY

Nb stocks

Volatility

Position

Price Std Dev ()Position Std Dev ()

VaR(q) (in ).....................

VaR (q) (in %)...................

Value at Risk

Delta VaR

95.0%

12

0.063

2.9

13/06/13

12445

126

1

27%

12445

213213

622

5.0%


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0

50

100

150

200

250

6/14/10 6/14/11 6/14/12

Delta VaR B(100)NKY IndexEURJPYPoly. (Delta VaR B(100))

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

Delta VaR NKY Index EURJPY


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CONCLUSION

As a conclusion:

Inflation created through debt monetization and through foreign

goods whose real value in Yen rise

Changes expectations of investors Capital expenditure and acquisitions as well as consumer

activities boost micro and macro economics

Snowball effect Good opportunity to invest in Japan

Risks need to be determine through Japanese investments as well

as Yen currency

Value at Risk threshold is computed thanks Student distribution

to catch skewness and kurtosis uncertainty

NKY Index crossed Delta VaR threshold: it means risk is higher

than expected return opportunities. Investors have to buy a put orsell a call, or short the market. However, it becomes to go down.

Investors have to be prepared to change their positions slightly to

avoid liquidity risk

Delta VaR can easily be adaptable in CPPI or OBPI strategies

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