Liquidity Risk Management for Portfolios_Joseph Cherian IPARM Asia 2011 Asia Etrading
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Transcript of Liquidity Risk Management for Portfolios_Joseph Cherian IPARM Asia 2011 Asia Etrading
CENTER FOR
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INVESTMENTS
Joseph Cherian
Professor of Finance (Practice)
Director, Centre for Asset Management Research & Investments (CAMRI)
NUS Business School
Scientific Advisory Board
Orissa Group Inc.
Liquidity Risk data kindly provided by Orissa Group, Inc. (OGI, Inc.)
Liquidity Risk Management for Portfolios
IPARM SEA 2011August 17, 2011
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A few opening claims
Liquidity risk is well-studied but still an “elusive concept”
Recent experience suggests that it is central to asset pricing and risk management
Liquidity risk drives security prices away from fundamentals
In other words, markets are not efficient in pricing liquidity risk and hence it presents trading opportunities if exploited properly
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What we wish to achieve today
Establish a practical understanding of liquidity risk
Introduce extant and new empirical metrics to estimate liquidity risk (or scores) using intraday data
Introduce simple equity trading strategies to exploit liquidity risk
Identify liquidity regimes in markets
Compare US versus Asian equity markets
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Understanding Liquidity and Liquidity Risk
Definition
Liquidity is the ease of trading a security
Liquidity Risk is the uncertainty associated with liquidity
Other Definitions
Ease of availability of financing for very short term maturities
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A few observations
Liquidity is not a fixed property
Liquidity can suddenly dry up
Liquidity influences asset returns
Liquidity is a significant source of risk
Size and trading volume are insufficient proxies of liquidity
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How to measure Liquidity and Liquidity Risk?
First Step: Estimate the cost of liquidating positions (or illiquidity)
Measured as the magnitude of price movements (volume-weighted returns) resulting from order size (dollar volume) – Amihud [2002]
Modeled using intraday trading data for stock “i” over intraday time interval “t” and in month “m”, appropriately normalized:
Second Step: Estimate the uncertainty in the cost
Formulate a time-series model of illiquidity
Estimate liquidity risk as the illiquidity shock – Amihud [2002]
𝐼𝐿𝐿𝐼𝑄𝑡 ,𝑚𝑖 =
|| ,
i
mtr
i
mtV ,
×0CPI
CPI t
ILLIQt = a + b* ILLIQt-1 + t
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Properties of illiquid portfolios
Largest 3000 US stocks by market capitalization
Illiquidity
Portfolio
Next month
ret
Log dollar
trade
volume
Log
market
cap
*ILLIQ
COST
Market
Beta
Size
Beta
Valuation
Beta
1 0.96% 20.75 22.64 0.05% 1.03 0.18 -0.06
2 0.95% 19.15 20.97 0.34% 1.15 0.58 0.04
3 1.06% 18.17 20.16 1.01% 1.19 0.83 0.12
4 1.14% 17.23 19.55 2.26% 1.26 0.86 0.23
5 1.15% 16.25 19.11 4.19% 1.27 0.79 0.42
Table 2: Properties of Illiquidity Portfolios. This table reports the properties of 5 portfolios sorted using
*ILLIQ. Portfolio 1 has the lowest illiquidity and Portfolio 5 has the highest illiquidity. The portfolios are
formed at the end of each month from a universe of 3000 largest US stocks by average market
capitalization for the month. Market, HML and SMB beta are computed using contemporaneous monthly
regressions of excess portfolio returns with Fama-French factors for Market (Rm_minus_Rf), Size (SMB)
and Valuation (HML). All values are reported as monthly averages for the period 1993-2009.
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Liquidation cost (Market Illiquidity Level – MIL)
Largest 3000 US stocks by market capitalization
Cost of trading a USD 10 Million position in a day
US Median Liquidation Cost
0%
1%
2%
3%
4%
5%
6%
Jan-9
3
Jan-9
4
Jan-9
5
Jan-9
6
Jan-9
7
Jan-9
8
Jan-9
9
Jan-0
0
Jan-0
1
Jan-0
2
Jan-0
3
Jan-0
4
Jan-0
5
Jan-0
6
Jan-0
7
Jan-0
8
Jan-0
9
Jan-1
0
CreditLTCM
(MIL)
Note: MIL and other acronyms / variables defined in Appendix
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Early warning indicator: liquidity deterioration
Increase in Liquidation Cost (Capital Markets vs. Market Median) Jan-06 - Jun 07: 22% vs. -23%
Jun 07 - Jul 08: 253% vs. 132%
Market Universe: US Largest 3000 stocks by market capitalization
Liquidation Cost: Capital Market vs. Market Average
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
Jan-0
6
Apr-
06
Jul-06
Oct-
06
Jan-0
7
Apr-
07
Jul-07
Oct-
07
Jan-0
8
Apr-
08
Jul-08
Oct-
08
Jan-0
9
Apr-
09
Jul-09
Oct-
09
Jan-1
0
Capital Markets Market Aggregate
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Liquidity premium – Market Illiquidity Factor
Market Illiquidity Factor (MIF) measures how liquidity risk is priced by market participants.
0
20
40
60
80
100
120
140
160
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
Market Illiquidity Factor (MIF)
LTCM Crisis, Aug 1998
Lehman Bros Bankruptcy, Sep 2008
Subprime Crisis,
Cumulative return of illiquid securities relative to liquid securities
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Liquidation regimes - concentrated during crisis
1.0%
1.1%
1.2%
1.3%
1.4%
1.5%
1.6%
90
100
110
120
130
140
150
160A
pr-
2009
Ma
y-2
009
Jun-2
009
Jul-2
009
Aug-2
009
Sep-2
009
MIL
MIF
Benign Liquidity Regime
MIF MIL
1.2%
1.4%
1.6%
1.8%
2.0%
2.2%
2.4%
2.6%
90
92
94
96
98
100
102
104
106
108
110
Apr-
1998
Ma
y-1
998
Jun-1
998
Jul-1
998
Aug-1
998
Sep-1
998
MIL
MIF
Liquidity Crisis Regime
MIF MIL
0.9%
1.0%
1.1%
1.2%
1.3%
1.4%
1.5%
1.6%
90
92
94
96
98
100
102
104
106
108
110
Jul-2
008
Aug-2
008
Sep-2
008
MIL
MIF
De-Leveraging Regime
MIF MIL
1.1%
1.2%
1.3%
1.4%
1.5%
1.6%
1.7%
1.8%
1.9%
2.0%
85
87
89
91
93
95
97
99
De
c-20
08
Jan-2
009
Feb
-2009
MIL
MIF
Liquidity Correction Regime
MIF MIL
(Flight-to-liquidity)
(Fight-for-liquidity)
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US Market Illiquidity FactorTM
(MIF)
125
130
135
140
145
150
155
160
165
170
175
180
185
Se
p-0
7
No
v-0
7
Ja
n-0
8
Ma
r-0
8
Ma
y-0
8
Ju
l-0
8
Se
p-0
8
No
v-0
8
Ja
n-0
9
Ma
r-0
9
Ma
y-0
9
Ju
l-0
9
Se
p-0
9
No
v-0
9
Ja
n-1
0
Iilliq
uid
s O
utp
erf
orm
Liquidity deteriorates
Illiquids outperform
("deleveraging" regime)
Liquidity improves
Illiquids underperform
("liquidity-correction" regime)
Liquidity improves
Illiquids outperform
("benign" regime)
Liquidity deteriorates
Illiquids underperform
("flight-for-liquidity" regime)
US Median Liquidation Cost
0%
1%
2%
3%
4%
5%
6%
Se
p-0
7
No
v-0
7
Ja
n-0
8
Ma
r-0
8
Ma
y-0
8
Ju
l-0
8
Se
p-0
8
No
v-0
8
Ja
n-0
9
Ma
r-0
9
Ma
y-0
9
Ju
l-0
9
Se
p-0
9
No
v-0
9
Ja
n-1
0
Liq
uid
ity d
ete
rio
rate
s
12
Liquidity regimes
Liquidity Premium
Liq
uid
ity
Leve
l
Illiquids Underperform
Level Deteriorating
"flight-for-liquidity"
Abnormal
Illiquids Outperform
Level Deteriorating
"deleveraging"
Illiquids Outperform
Level Improving
"benign"
Abnormal
Illiquids Underperform
Level Improving
"liquidity-correction"
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Applications in active portfolio management: Liquidity
analysis presents alpha generation opportunities
When Market Illiquidity Level increases (i.e., as liquidity deteriorates)
Investors favor liquid securities over illiquid securities
US: Russell 2000 (proxy for illiquid securities) underperforms DJ Industrial Average (proxy for liquid securities)
When Market Illiquidity Level decreases (i.e., as liquidity improves)
Market participants favor illiquid securities over liquid securities
US: Russell 2000 outperforms DJ Industrial Average
Analysis period: Jan 1, 1993 through Nov 20, 2009
Trailing Liquidity
# of
weeks
Russell 2000
(RUT) DJIA (DJI)
Russell 2000
(RUT) DJIA (DJI)
Return Return Std Dev Std Dev
Deteriorating 384 -3.6% 7.6% 25.2% 19.8%Improving 484 17.6% 9.0% 17.8% 15.2%
Return Std Dev
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Applications in active portfolio management: Liquidity
Analysis presents alpha generation opportunities
When Market Liquidity deteriorates
Short Russell 2000 (RUT)
Long Dow Jones Industrial Average (DJI)
When Market Liquidity improves
Long Russell 2000 (RUT)
Short Dow Jones Industrial Average (DJI)
Weekly rebalancing 0%
2%
4%
6%
8%
10%
12%
Lo
ng
DJI
Sh
ort
Ru
ssell 2
000
exclu
de
cu
rr w
eek
exclu
de last
2 w
eeks
exclu
de last
3 w
eeks
exclu
de last
4 w
eeks
exclu
de last
5 w
eeks
exclu
de last
6 w
eeks
We
ek
ly R
etu
rn (
An
nu
alize
d) Outperforms
Naïve Long DJI / Short RUT strategy
HFR Equity Market Neutral strategy
The liquidity based trading signal is persistent
Results does not consider transaction costs-100%
-50%
0%
50%
100%
150%
200%
Jan-9
3
Jan-9
4
Jan-9
5
Jan-9
6
Jan-9
7
Jan-9
8
Jan-9
9
Jan-0
0
Jan-0
1
Jan-0
2
Jan-0
3
Jan-0
4
Jan-0
5
Jan-0
6
Jan-0
7
Jan-0
8
Jan-0
9
Cu
mu
lati
ve
Re
turn
%
Trading Strategy Long RUT/Short DJI
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Applications in passive portfolio management:
Determining optimal holding periods
Notes
1. Liquidity Risk is expressed using the Stock Liquidity Rating (SLR) scheme: (AAA, AA, A, BBB, BB, B, CCC, CC, C and D) with AAA having lowest risk and D having highest risk
2. Cumulative Return is the equally weighted return for given SLR portfolio, adjusted for round trip market impact cost. A SLR portfolio is defined as all stocks with a given SLR selected from the universe of largest 3000 U.S. stocks. The average size of a portfolio is $300 million. The portfolio is held constant throughout the holding period.
3. Period analyzed: Jan 1993 – Jun 2008
Cumulative Return by Liquidity Risk (SLR)
-5%
0%
5%
10%
15%
20%
25%
1 2 3 4 8
Holding Period (Quarters)
Cu
mu
lati
ve
Re
turn
AAA
A
BB
CCC
C
The U.S. evidence suggests
for shorter holding periods (less than 3 quarters) liquid securities provide a higher return on investments
for longer holding periods (more than 3 quarters) illiquid securities provide a higher return on investments
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Applications in Asia: Hong Kong equities versus
US equities
Period Analyzed: Jan – Dec 2007
Hong Kong Equity market has significantly more liquidity risk as indicated by two liquidity metrics
Liquidity VaR: This is the cost incurred for liquidating an (equal-weighted) market portfolio. Higher liquidity VaR indicates more liquidity risk.
Turnover: A lower turnover number (as % of market capitalization) indicates higher liquidity risk
Equity Market
# of
securities
Total Market Cap
(Millions)
Monthly Turnover
(Millions)
Avg Daily Turnover as
% of Total Market Cap
Liquidity VaR
(bps)
Hong Kong (Main Board) 1021 17218587 HK$ 1355482 HK$ 0.38% 766
NYSE 2698 15644242 USD 2757078 USD 0.77% 185
Hong Kong equity market has four times more liquidity risk, and half the average daily turnover, compared to U.S. equity market
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Applications in Asia: Hong Kong equities more
vulnerable to liquidity crisis
The Market Illiquidity Level (MIL) is the barometer of liquidity conditions for an Equities Market. An increase in this level indicates deteriorating liquidity conditions.
US equities’ illiquidity peaked during the last week of November 2007. However, Hong Kong equities illiquidity peaked during the last week of January 2008
OGI's Market Illiquidity Level (MIL)
0
50
100
150
200
250
300
350
11/2
6/2
006
1/2
6/2
007
3/2
6/2
007
5/2
6/2
007
7/2
6/2
007
9/2
6/2
007
11/2
6/2
007
1/2
6/2
008
3/2
6/2
008
MIL (HK Equities)
MIL (U.S. Equities)
Incre
asin
g Liq
uid
ity R
isk
c
Source: OGI, Inc.
Hong Kong equities’ illiquidity deteriorated considerably more compared to US Equities
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OGI Composite India Fund Sample Performance Report
(Source: OGI, Inc.)
Applications in Asia: India
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Applications in Asia: India (Cont’d)
OGI Composite India Fund – Top Vs. Bottom
(Source: OGI, Inc.)
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Summary
Liquidity Risk an important source of risk and still being understood
We introduced empirical metrics to estimate liquidity risk using intraday data that have predictive ability, both in US and Asian markets
Introduce practical applications to manage and exploit liquidity risk
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Appendix: Definitions
Market Illiquidity Level (MIL) is the median illiquidity level for stocks, as captured by the Stock Illiquidity Level (SIL), for the entire market of stocks selected from a universe of 3000 largest public U.S. equities by market capitalization, as determined at the beginning of the quarter. The weekly SIL for each stock is determined using intra-day trading data (ILLIQt). The median SIL across the universe is denoted as MIL. The. The MIL is based on an initial value of 100 registered on Jan 8, 1993. An increase in MIL indicates deteriorating liquidity conditions. When MIL declines, illiquid securities can be expected to outperform liquid securities. When MIL increases, illiquid securities can be expected to underperform liquid securities.
Stock Liquidity Rating (SLR) measures a stock's liquidity risk, given by the uncertainty associated with the cost of liquidating a position (εt). SLR categorizes a stock into one of ten liquidity risk buckets (AAA, AA, A, BBB, BB, B, CCC, CC, C, D), with AAA having the least risk and D the greatest risk
Market Illiquidity Factor (MIF) measures how liquidity risk is priced by market participants. It measures the cumulative return of illiquid securities relative to liquid securities as ranked by the stock-level liquidity rating system (SLR). The MIF for the U.S Equities Market is created through analysis of the 3,000 largest U.S. stocks. The MIF is based on an initial value of 100 registered on April 1, 1993.