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Transcript of Marco Lazzarino & Simone Zola See disclaimer at the end of the presentation Quant Strategies &...
Marco Lazzarino&
Simone Zola
See disclaimer at the end of the presentation
Quant Strategies & Structuring:
issues in high volatility markets
Contents
Overview
Quantitative Strategies
Algorithmic Trading
Multi-Factor Portfolio Construction
Bayesian Black-Litterman Models
Operational
Structuring
Funding
Equity
Final Considerations
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MPS Asset ManagementIreland
-
Quantitative Portfolio Management
MPS AM Ireland: Quantitative Portfolio Management
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January 2009
Asset Under Management: 3 bln Euro23 active sub-funds
CASH2 sub-funds
active
BOND5 sub-funds
active
EQUITY11 sub-funds active
FLEXIBLE3 subfunds active
(IRISH SICAV)FX
1 sub-fund
Formulaic1 sub-fund
Discussion aims…
The aim of our presentation is to point out some characteristics of the investment process typical of many quant companies showing how these features
have proved being harmful in extreme market conditions and mainly in relation to volatility
January 2009 5MPS Asset Management Ireland LTD
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Quantitative Strategies
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January 2009
Quantitative Strategies
We will focus on some of the most popular areas of quantitative portfolio management such as
Algorithmic Trading
Stop LossNoise Signals
Multi-Factor Portfolio Construction
Bayesian Black-Litterman Models: views
Operational: Hedging & Program Trades
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January 2009
Algorithmic Trading
Algorithmic Trading refers to automatic trading rules.
They range from Technical Analysis to complex Neural Network strategies.
Their investment horizon can be intraday (high frequency) or longer
Those techniques allow to identify signals according to which
Open a strategy
Close a strategy (Take Profit or Stop Loss)
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January 2009
Algorithmic Trading: Stop Loss
A typical expression for a Stop Loss can be given by
For a given l, the volatility gives the maximum affordable loss.
In case of extreme levels of volatility, for a given l, the value at risk of the strategy can increase dramatically
Enrica Cisana & Gavin Curran, Fixed Income Team
EntryLevelStopLoss *)1(
* Currency Management: Overlay and Alpha Trading, ed. By J. James (2004)
*
Algorithmic Trading: an example from FX
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Recent high Vol affects SL levels
Enrica Cisana - Fixed Income Team & Giulio Maggiori - FX Desk
January 2009
Algorithmic Trading: Noise Signals
High volatility affects technical indicators that are purely trend following increasing the probability of noise signals
January 2009 11MPS Asset Management Ireland LTD
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Enrica Cisana & Gavin Curran, Fixed Income Team
10Y notes Future 7th January 2009 : LONG MACD/SO SIGNAL10Y notes Future 8th January 2009 : SHORT MACD/SO SIGNAL
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January 2009
Multifactor Optimization
Multi-factor models are worldwide used to monitor risk and for portfolio construction. According to them a generic security return can be expressed by
Several versions have been studied and their level of sophistication can be significantly high
They require
identification of the Factors
calibration of exposures
ufxr
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January 2009
Multifactor Optimization
Some of the most widely used software packages based on these models usually update risk exposures monthly. The updated risk exposures are usually available with a time lag…
Portfolio managers tend to rebase their portfolios at the end of the month
Lags between portfolio construction and exposures calibration were sources of inaccurate optimizations
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January 2009
Bayesian Black-Litterman Models: views
Over several years, we have been collecting monthly views from most of the major brokerage firms in a unique database. Their goodness is assessed in several ways. Among them we use an Hit Ratio
31-Jan-2006 21-Jan-2007 11-Jan-2008 31-Dec-2008-2
-1.8
-1.6
-1.4
-1.2
-1
-0.8
-0.6
-0.4
-0.2
Dates
Info
rmat
ion
Rat
io
Total Information Ratios for all brokers views for Europe
31-Jan-2006 21-Jan-2007 11-Jan-2008 31-Dec-2008-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
DatesIn
form
atio
n R
atio
Total Information Ratios for all brokers views for the US
Views performance have been getting steadily worse
Michael Harrington, Research Team
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January 2009
Quantitative Strategies - Operational
Extreme volatility has affected executions of all types: program trades, time orders and hedging.
Among the others, in FX for example, the all time high spread being charged in the actual market was not being reflected in the benchmark
Daily QEUR1M= 07/12/2005 - 29/01/2009 (GMT)
Line, QEUR1M=, Bid(Last)26/01/2009, -9.20Line, QEUR1M=, Ask(Last)26/01/2009, -6.50
Price
USD
.12
-24
-20
-16
-12
-8
-4
0
4
8
12
16
20
24
28
32
36
40
16 02 16 01 16 01 16 03 17 01 16 01 16 03 17 01 16 01 18 02 16 01 16 01 18 01 16 01 16 01 16 02 16 01 16 01 18 02 16 01 16 03 17 01 16 01 16 03 17 01 16 01 18 03 17 01 16 01 16 02 16 01 16 01 18 01 16 01 16 03 17 01 16 01 16
Dec 05 Jan 06 Feb 06 Mar 06 Apr 06 May 06 Jun 06 Jul 06 Aug 06 Sep 06 Oct 06 Nov 06 Dec 06 Jan 07 Feb 07 Mar 07 Apr 07 May 07 Jun 07 Jul 07 Aug 07 Sep 07 Oct 07 Nov 07 Dec 07 Jan 08 Feb 08 Mar 08 Apr 08 May 08 Jun 08 Jul 08 Aug 08 Sep 08 Oct 08 Nov 08 Dec 08 Jan 09
Neil Coughlan, Head of FX Desk
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January 2009
Quantitative Strategies – other…
Difficult currency hedging for currency hedged products
Volatile Program Trades executions
Trading for counterparty risk exposure reduction
Trading for volatility reduction in ALM products
…
Extreme volatility has affected executions of all types: program trades, time orders and hedging.
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Structuring
Structured Products
January 2009 18MPS Asset Management Ireland LTD
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Credit market (liquidity, haircuts…)
Interest rates
Risk models (OAS, CDS…)
Spot levels
Volatility (levels, patterns…)
Correlations (equity, interest rates…)
Interest rates
Structured Products
Funding:Typical haircut on collateral securitiesTrends in corporate bondsVolatility in corporate bondsOpportunities from CDS market
Equity:Volatility patternsVolatility relative valueCorrelationsSpot prices in equities and in optionsOpportunities from exotic derivatives
Opportunities in structured products
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FRN---
Portfolio Swap
Equity Option
Funding: Typical Haircut
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Aprile 2007 Agosto 2008
US Treasuries 0.25 3
Investment-grade bonds 0 - 3 8 – 12
High-yield bonds 10 - 15 25 – 40
Equities 15 20
Investment-grade corporate CDS 1 5
Senior leveraged loans 10 - 12 15 – 20
Mezzanine leveraged loans 18 - 25 35
ABS CDOs:AAA
2 - 4 95
AA 4 - 7 95
A 8 - 15 95
BBB 10 - 20 95
Equity 50 100
AAA CLO 4 10 – 20
Prime MBS 2 - 4 10 – 20
ABS 3 - 5 50 - 60
Source: Global Financial Stability Report, IMF, Oct-08
Changes in the credit market:
Funding: Trends in Corporate Bonds
Negative price returns
Increase in Asset Swap Spread
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ML Global Broad Market Financial
80
85
90
95
100
105
Jan
-07
Ma
r-0
7
Ma
y-0
7
Jul-
07
Se
p-0
7
No
v-0
7
Jan
-08
Ma
r-0
8
Ma
y-0
8
Jul-
08
Se
p-0
8
No
v-0
8
Jan
-09
Pri
ce
0
50
100
150
200
250
300
350
400
450
500
As
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pre
ad
Funding: Volatility in the Bond Market
Radical increase in volatility levelConsequent increase in haircutsCombined with fall in prices
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Loss of value for collateral portfolios
Funding: Opportunities from CDS Market
Asset Swap Spread increased more than CDSNegative basis wider on single name (as much as 800bps)
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Basis
0
50
100
150
200
250
300
Ma
r-0
7
Ma
y-0
7
Jul-
07
Se
p-0
7
No
v-0
7
Jan
-08
Ma
r-0
8
Ma
y-0
8
Jul-
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Se
p-0
8
No
v-0
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Jan
-09
bp
s
Asset Swap Spread iTraxx Europe Corp 5y
Equity: Index Level and Volatility
Spot levels have fallen a long wayVolatility has dramatically increased
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SP 500
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
Jan
-07
Ma
r-0
7
Ma
y-0
7
Jul-
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Se
p-0
7
No
v-0
7
Jan
-08
Ma
r-0
8
Ma
y-0
8
Jul-
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Se
p-0
8
No
v-0
8
Jan
-09
Ind
ex
Le
ve
l
0
10
20
30
40
50
60
IVo
l AT
M 6
0D
SPX Index - Price SPX Index - 6M Imp Vol
Equity: an Uncharted Territory for VolatilitySpread between historical and implied volatilities inverted and widenedThe skew steepenedThe term structure reversedSmirk in Equity Index (DJ EuroStoxx 50)
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SP 500 - Volatility PatternsDJ Euro Stoxx - Smirk
-15
-10
-5
0
5
10
15
20
25
30
35
40
Jan-07Mar-0
7May-0
7Jul-07
Sep-07Nov-07
Jan-08Mar-0
8May-0
8Jul-08
Sep-08Nov-08
Jan-09
Hist - IV ATM Skew 80-120 Term 3M-12M Smirk DJ EuroStoxx
Equity: Consequences on Pricing Models
The Implied Tree of volatility forecasts the observed trends
But the scale is completely different
Difficulty in pricing out-of-the-money options with long maturities
Mispricing in the market:Erratic behaviour of implied volatilities
in quoted options
Anomalies in pricing of OTC derivatives:
The same product gets a participation of 60% from bank A and 35% from bank B
Exotic features results in completely different pricing
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Source: E. Derman 1999, Regimes of Volatility.
Equity: Opportunities
Short correlation:Realized correlation has recently been very high if compared to the years of
bull run
Short volatilty with minimum exposure to Vega:Implied volatility is still very high and more bumps are being given to
volatility since in strenuous times realized volatility is usually greater than implied volatility
Short skew:Hard to hedge skew for underlyings that do not have a liquid option market
Cheap forward volatility:Volatility term structure is inverted due to peaking short term volatilities
But all these structures are considered exotic: need of simplification to sell structured products in these days.
January 2009 27MPS Asset Management Ireland LTD
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Final Considerations
Final Considerations
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January 2009
Disclaimer
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January 2009
This material represents speaker’s personal opinions and not of MPS AM Ireland
Indices mentioned throughout the document are property of respective owners
Views expressed on single stocks or sector are theoretical examples and for presentation purposes only; they are not
intended as solicitation to investment.