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Overview presentation on market liquidity and market liquidity risk by Sebastian Stange and Prof. Christoph Kaserer. Comments are highly appreciated.
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Sebastian Stange and Prof. Christoph KasererChair of Financial Management and Capital MarketsTechnische Universität MünchenArcisstr. 21D-80290 MünchenTel.: +49 89 / 289 - 25485Mail: [email protected] URL: www.ifm.wi.tum.de
Market Liquidity and Its Risk
An Overview
2Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Presentation aims to convey state of research on market liquidityGoals of this presentation
• Quick introduction to important aspects and developments
• Summary of current state of research
• Starting point for further research
• Practitioners
• Students
• Researchers
• Those interested
for
General financial background required
3Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
This presentation presents an overview on market liquidityAgenda
• Introduction
• Market liquidity
– Definition
– Characteristics
– Measurement
– Empirical facts
• Market liquidity risk
– Introduction
– Models
• Summary and open research questions
4Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity has continuous attention in practicePress clippings
"Credit crisis puts heat on liquidityFinancial market liquidity can take months to build but just seconds to evaporate [...] Credit traders have received a painful reminder of [...] strangled trading liquidity"Financial Times, 30.07.2007
'Panicked Traders Take VW Shares on a Wild Ride - stock soared to as high as 1,005 euros a share ... after last week at 210 euros.... short sellers were forced to act"
NY Times, 28.08.2008
'Some less liquid strategies which also provided genuine portfolio diversification [...] have romped past the S&P 500'Michael Goldman, Global Investor, 04/2007
"Unless you include liquidity in your models, which some small funds don't, then the model may not always work."Euromoney, June 2007
'[Quantitative strategies] rely on their ability to trade with high frequency […] What if the model is built to sell a company at 20, but there is no buyer?'Euromoney, June 2007
Liquidity always a hot topic – especially in crises
• Liquidity always scarce when needed most
Institutional investors engage in illiquid strategies
• Sometimes large, concentrated position to exploit market inefficiencies
• Returns due to liquidity risk compensation?
Trading strategies rely on tradability of assets• Hedging often requires frequent trading
Risk management still needs to account for illiquidity
• Often neglected• Strong recent pressure from regulators
Introduction
5Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity
Liquidity is approached from various research directions
Market micro-structure
Transaction costliterature
Factor in asset pricing Risk
management
Volume / volatilities literature
Anomalyexplanation
Asset management
= Causes
= Effect
Limits toarbitrage
Supply-demandcurve
Introduction
6Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
This presentation focuses on market liquidity only Delimitation of topic area
Monetary liquidityMonetary liquidity
• Liquidity of an economy
Funding liquidityFunding liquidity
• Liquidity of liabilities
• Perspective of a firm (solvency)
• Corporate finance view
Market liquidityMarket liquidity
• Also "asset liquidity"
• Liquidity of assets only
– "Marketability"
– "Ease of trading an asset"
• Perspective of an investor
• Capital market view
Introduction
7Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
This presentation presents an overview on market liquidityAgenda
• Introduction
• Market liquidity
– Definition
– Characteristics
– Measurement
– Empirical facts
• Market liquidity risk
– Introduction
– Models
• Summary and open research questions
8Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity can be defined as the cost of trading an assetLiquidity cost has three components
Market liquidity – Definition
Liquidity
Lt(q)
Direct trading costs
D(q)
Price impact costs
PIt(q)
Delay costs
Dt(q)
=
+
+
• Cost L of trading a quantity q of an asset• Relative to fair value• Fair value often set at mid-price, i.e. mid-point of bid-ask-spread
• Includes exchange fees, commissions, taxes• Deterministic• Small for institutional investors
• Difference between transaction price and mid-price• Depends on order size q and point of time
• Includes search cost, cost due to add. risk during delay
Note: Definition similar to Amihud (2006), XXX noch ergänzen
9Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
• Tightness = "cost of turning a position around in a short time"
• Depth = "size of an order flow innovation required to change prices a given amount"
• Resiliency = "speed with which prices recover from a random, uninformative shock"
The cost perspective integrates older, more elusive definitions
Market liquidity – Definition
DefinitionDefinition
• "Ease of trading an asset"• "Marketability"
SourceSource
Longstaff (1995)
CommentComment
• Very general• Cost perspective more
specific
Kyle (1985) • Several dimensions• No unifying perspective
• Immediacy = time between order submission and settlement
Black (1971) • A new dimension• No unifying perspective
• Price• Time
Kempf (1999) • Very general
Backup
10Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Asset type, order size and horizon are major liquidity determinants
Market liquidity – Characteristics
• Liquidity costs decrease with – Trading volume– Value certainty
Type of asset
exog
enou
s
Order size
• Liquidity costs increase with order size• Reasons
• Heterogeneous opinion• Delay probability• Capital restrictions
end
ogen
ous
Liquidation horizon
• Liquidity costs decrease with liquidation horizon• Costs relative to return are small when held over long period• Costs are zero for assets held to maturity
• Hence, liquidity is a characteristic of the trading processend
ogen
ous
11Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity is a continuous characteristicLiquidity degrees and categories
Market liquidity – Characteristics
Costly, continuous trading
Rel
ativ
e liq
uidi
ty c
osts
illiquid
Degree of illiquidity
liquid
Costless trading
Notrading
Costly, interruptedtrading
• All order sizes of the asset can be traded at zero costs
• Cash
• None, no liquidity adjustment necessary
• Order sizes can be traded at a cost
• Price impact cost important
• Limit order book markets of stocks
• Precise liquidity cost adjustment
• Asset are traded from time to time
• Zero trading days occur• Delay cost important
• OTC markets of more exotic bonds
• Liquidity cost and delay adjustment
• No order size of the asset is traded
• Prohibitive Liquidity costs
• Rare art, CDOs?
• Intrinsic value determination because price non-observable
Ca
teg
ory
Ex
.M
ain
is
su
e
12Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Cost can be measured as price impact curveLiquidity costs increase with quantity transacted
Market liquidity – Characteristics
mid price
bid price
Quote depth /Size of best limit orders
Price
Market depthQuantity
transacted
ask price
Size of next-bestbid order
buy price function
sell price function
Bid-ask-spread area = absolute liquidity costs
13Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Optimal trading strategies
• Optimal trading strategies can be applied
– Delaying parts of the transaction reduces order size and hence liquidity costs
– But, uncertain future price and liquidity costs, i.e. delay costs, for delayed parts of the position
– Optimal strategy balances liquidity cost saving against increased delay costs
• Several optimization objectives possible
– Maximize expected liquidation proceeds
– Maximize expected liquidation proceeds with penalty for potential shortfall (proceed variance)
• Corresponds to maximizing proceeds VaR
• Immediate liquidation as benchmark strategy
– No optimization strategy is applied
– Proceeds are certain
Market liquidity – Characteristics
14Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Measurement of market liquidity is still difficultMultitude of direct measures and proxies available
Market liquidity – Measurement
Direct measures
• Fees• Quoted bid-ask-spread (Amihud, Mendelson, JFinEco 86)• Traded bid-ask-spread• Effective bid-ask-spread (Roll, JoF 84)• Relation between price change and order flow (Brennan, Subrahmanyam,
JFinEco, 96)• Price response to turnover (Amihud, JFinMar 02)• Volume related reversal (Pastor, Stambaugh, JPolEco 03)• Weighted spread by order size (Irvine et. al., working paper 00)
Indirect measures
• Depth• Volume• Number of transactions• Turnover rate (Datar et al, JFinMar 98)(1)• Proportion of zero-trading days (Bekaert et al., WP, 03)• Turnover-adjusted zero trading days (Liu, JFinEco 06)
15Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Example: Weighted spread measures precise size-specific liquidity cost
Market liquidity – Measurement
Weigthed spread is precise measure...Weigthed spread is precise measure...
• Discount vs. achievable price in limit order book
• Equals area between limit order curves
• Generalization of bid-ask-spread to rest of the limit order book
• Precise price impact measure L(q)= WS(q) / 2
...under realistic assumptions...under realistic assumptions
• Direct trading costs are zero– Ok for institutional investors
• Asset position continuously tradable• Ok for developed markets and positions
smaller than market depth
• Immediate liquidation• Ok, if optimal trading strategies
neglectable
• Weighted spread data available• Ok in many electronic limit order book
markets
Source: Stange, Kaserer (2008a, b)
16Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity cost quickly rise with order sizeExample: Weighted spread for German stocks (I/III)
Market liquidity – Measurement
146
110
5227
15
214
454
331
0
100
200
300
400
500
vol 10 vol 25 vol 50 vol 75 vol 100 vol 150 vol 250 vol 500 vol 750 vol 1000 vol 2000 vol 3000 vol 4000 vol 5000
DAX
MDAX
SDAX
TECDAX
Volume in k €(not to scale)
Average liquidity cost in bp
Note: Sample = daily data for 160 stocks in four major German stock indices over 5.5 years (II/02-1/08)Source: Stange, Kaserer (2008a)
17Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity cost have strongly declined in 2002-2008Example: Average weighted spread for German stock indices (II/III)
Market liquidity – Measurement
Source: Stange, Kaserer (2008a)
18Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity cost decline evident for all order sizesExample: Weighted spread for German stocks by selected order size, indexed (II/III)
Market liquidity – Measurement
Source: Stange, Kaserer (2008a)
19Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Further empirical facts
• Liquidity costs can be substantial
– Price impact is concave (Hasbrouck 1991, Stange/Kaserer 2008)
– Over 50% of total trading cost from price impact and delay (Kritzman, Myrgren and Page 2006)
• There is strong variation over time
– Flight-to-liquidity asymmetry: Liquid assets become more liquid and less liquid less liquid in crises (Acharya and Pedersen (2005), Longstaff (2004))
• Liquidity measures determine asset prices
– Market liquidity esp. important for pricing – no full diversification possible(Acharya and Pedersen (2005) for stock market; Goyenko (2005) for integration between stock and bond market)
– Further sources: Amihud and Mendelson (1986); Datar, Y. Naik, and Radcliffe (1998); Amihud (2002); Pastor and Stambaugh (2003); Acharya and Pedersen (2005); Ang, Chen, and Xing (2006), Keene and Peterson (2007) and others
• There is strong liquidity commonality
Market liquidity – Empirical facts Backup
20Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
This presentation presents an overview on market liquidityAgenda
• Introduction
• Market liquidity
– Definition
– Characteristics
– Measurement
– Empirical facts
• Market liquidity risk
– Introduction
– Models
• Summary and open research questions
21Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Traditional VaR neglects liquidity effects
Definition classical VaRDefinition classical VaR
• Value-at-Risk (VaR) measures worst loss in α% of the cases over a specific forecast horizon h
– (1-α) is confidence level– Loss is generally the forecasted loss in
market prices
CritiqueCritique
• Assumes that position can be liquidated without significant cost
– Bid-ask-spread neglected– Price impact of position size neglected– Market conditions and liquidation horizon
neglected
• Assumes that position can be liquidated within any given horizon
– No delay costs
• Sometimes ad-hoc adjustments from expert estimates used, but only rough proxy for true liquidity risk
– Flat lengthening of horizon– Artificial increase of volatilities– Flat liquidity cost deduction ("hair cut") by
asset class
Market liquidity risk – Introduction
Future market price distribution at horizon h
22Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Traditional VaR assumes 'mark-to-market'-price by conventionSeveral price definitions can be used
Before transaction pricesBefore transaction prices
Mid-price = mark-to-market price• Middle of bid-ask-spread
Bid- / ask-price• Usually quoted by market maker
– But sometimes best limit order prices if no market maker coverage
• Ex-ante achievable transaction price for buy/sell-transaction
– But for small volume (=bid-ask-depth) only
Achievable price in limit order book• Ex-ante price when transacting larger
orders as market order against limit order book
After transaction pricesAfter transaction prices
Transaction price• Ex-post achieved transaction price• Can be inside bid-ask-spread if market
maker transacts within spread• Usually outside bid-ask-spreads for
larger order sizes
'Mark-to-market' simple, but not most realistic assumption
Market liquidity risk – Introduction
23Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Market liquidity risk is worst loss due to liquidity cost
• Liquidity component usually neglected in standard risk models
– Usual assumption that liquidity cost can be neglected if horizon is long enough
– Partially accounted for via asset-class-specific "hair cuts"
• Expert estimates of liquidity cost deduction
• However, liquidity costs are substantial and strongly vary between securities
– 25-30 % underestimation of total risk in emerging market currencies (Bangia et al. 1999)
– Bid-ask-spread component over 50 % of total risk for illiquid stocks (Le Saout 2002)
– 30 % liquidity contribution to intraday risk in small price stocks (Lai 2007)
– Up to 25-30 % liquidity impact on price risk at 10-day horizons (Stange/Kaserer 2008a)
• More than doubles at daily horizons
• Large variance between stocks and position sizes
Market liquidity risk – Introduction
24Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
We will survey eight different liquidity risk modelsModel overview
Market liquidity risk – Models
Model categoriesModel categories
• Available data
• Type of liquidity measurement
• Assumptions on the structure of liquidity
ModelsModels
1. Bangia et al. (1999): Add-on model with bid-ask-spread
2. Ernst et al. (2008): Modified add-on model with bid-ask-spread
3. Berkowitz (2000): Transaction regression model
4. Cosandey (2001): Volume based price impact
5. Angelidis, Benos (2006): Structurally implied spread
6. Francois-Heude, Wynendaele (2001): Limit order model
7. Giot, Gramming (2008): T-distributed net return model with weighted spread
8. Stange, Kaserer (2008): Empirical net-return model with weighted spread
Note: Untraceable models excluded from overview.
25Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
A simple model deducts worst bid-ask-spreadBangia et al. (1999): Add-on model with bid-ask-spread
Market liquidity risk – Models
Liquidity Measure
Liquidity Risk Measurement
Advantages and Disadvantages
• Data available in many markets• Simple add-on, hence quickly implementable
– Assumes that position can be traded at bid-ask-spread
• However, liquidity costs can quickly rise beyond bid-ask-spread when trading positions larger than bid-ask-depth
• Tends to underestimate risk– Assumes perfect liquidity – price correlation
• Worst spread and worst price occur simultaneously
• Tends to overestimate risk– Logically inconsistent because worst spread
deducted from current, not worst prices• Easily correctable• Tends to overestimate risk
– Historical spread distribution might poorly proxy for future distribution
• Bid-ask-spread
• Worst spread added as cost to worst price
• Empirical distribution ( ) used for worst spread estimation
• Normal distribution used for price risk
1
26Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Non-normality of liquidity can be explicitly taken into accountErnst et al. (2008): Modified add-on model with bid-ask-spread (I/II)
Market liquidity risk – Models
Liquidity Measure Advantages and Disadvantages
• Similar to Bangia et al. (1999), but specifically accounting for non-normality via Cornish-Fisher approximation
• Provides empirically more precise results than Bangia et al. (1999)
• See Ernst et al. (2008)• Can be applied to other liquidity cost
measures as well• See Ernst et al. (2009)
– Skewness and kurtosis need to be additionally estimated
• Bid-ask-spread• Other liquidity measures can be used
analogously
• Worst cost added to worst price
• Cornish-Fisher approximated percentiles, which take skewness ( ) and excess-kurtosis ( ) into account
Liquidity Risk Measurement
2
27Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Modified risk model performs better than Bangia et al. (1999)Ernst et al. (2008): Modified add-on model with bid-ask-spread (II/II)
Market liquidity risk – Models
Note: "Risk correctly estimated" is determined via standard Kupiec (1995)-statistic; Sample = 160 stocks in four major German stock indices over 5.5 yearsSource: Ernst, Stange, Kaserer (2008)
2
28Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Price impact of order size distilled from transaction dataBerkowitz (2000): Transaction regression model
Market liquidity risk – Models
Liquidity Measure Advantages and Disadvantages
• Integrates price impact of order size
– High data requirements– Liquidity measure highly approximate
• Measurement very noisy– Assumption of zero price-liquidity correlation
• Independence between price risk and liquidity impact
• Abs. liquidity cost per share ( ) derived from linear regression of transaction prices when controlling for other risk factor changes (x)
• Not explicitly defined
Liquidity Risk Measurement
3
29Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Simple price impact approximation via relative traded shares Cosandey (2001): Price impact derived from volume
Market liquidity risk – Models
Liquidity Measure Advantages and Disadvantages
• Market volume data available• Accounts for price impact of order size via
simple theoretical assumption
– No time variation of liquidity (here measured with traded share volume)
– Price impact linear to relative traded shares• Concavity of price impact function
neglected
• Worst price risk adjusted for relative increase of traded shares
Liquidity Risk Measurement
• Relative increase of traded shares by position
• Assumes that position increases number of shares but total traded value
4
30Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Liquidity cost derived from theoretical driversAngelidis, Benos (2006): Structurally-implied spread
Market liquidity risk – Models
Liquidity Measure Advantages and Disadvantages
• Partially accounts for price impact of order size via increased volume percentile
– Unclear if structural model is correct– Complicated estimation of parameters in
intraday data required– Possible overestimation because liquidity-
return correlation assumed perfect
• Structurally-implied spread added to price risk• Calculated with top-percentile of volume• Assumes that individual position size
dissipates in market
Liquidity Risk Measurement
• Spread model estimated from intraday data• Model derived from theoretical ideas on
liquidity drivers• Traded shares N, degree of info assym.
theta, price elasticity to volume kappa, liquidity fixed cost Phi
5
31Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Using more limit order book data increases measure precisenessFrancois-Heude and Wynendaele (2001): Price impact from best limit orders
Market liquidity risk – Models
Liquidity Measure Advantages and Disadvantages
• Accounts for price impact of order size• Price impact more precise because directly
measured in limit order book
– Only applicable in electronic limit order book markets
– Time variation of liquidity neglected– Assumes perfect correlation between liquidity
and price– Five best limit orders need to be available– Intraday only– Liquidity cost only extrapolated for medium to
large order sizes– Somewhat arbitrary spread adjustment– Provides empirically imprecise results than
other models using limit order data• See Ernst et al. (2008)
• Normal price risk adjusted for average price impact
• Correction term for difference between average and stock-specific price impact
Liquidity Risk Measurement
• Price impact curve estimated from best five limit orders
• Available from Paris Bourse• Extrapolated for larger sizes
6
32Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Precise price impact measurement with limit order book dataGiot, Gramming (2005): T-distributed net-return model with weighted spread
Market liquidity risk – Models
Liquidity Measure Advantages and Disadvantages
• Accounts for price impact of order size in very precise way
• Correctly accounts for liquidity-return correlation
– Only applicable in electronic limit order book markets
– Intraday data required if lower frequencies not provided by exchange
– Possible overestimation if instant liquidation assumption is suboptimal
– Possible distortion through assumption of t-distributed net-returns
Liquidity Risk Measurement
• Size-specific liquidity cost extracted as weighted spread from limit order book
• at(n) and bt(n) are weighted ask and bid-prices for trading n = q/Pmid shares
• T-distribution percentile of historical net return distribution
• Net return is mid-price return net of weighted spread liquidity costs
7
33Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Precise empirical price impact measurement with limit order book dataStange and Kaserer (2008): Price impact measured with weighted spread
Market liquidity risk – Models
Liquidity Measure Advantages and Disadvantages
• Accounts for price impact of order size in very precise way
• Correctly accounts for liquidity-return correlation
– Only applicable in electronic limit order book markets
– Intraday data required if lower frequencies not provided by exchange
– Possible overestimation if instant liquidation assumption is suboptimal
• Empirical percentile of historical net return distribution
• Net return is mid-price return net of weighted spread liquidity costs
Liquidity Risk Measurement
• Size-specific liquidity cost extracted as weighted spread from limit order book
• at(n) and bt(n) are weighted ask and bid-prices for trading n = q/Pmid shares
8
Source: Stange, Kaserer (2008b)
34Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Model overview
Market liquidity risk – Models
Source: Stange, Kaserer (2009)
35Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Limit order data models with superior performance in stocksModel performance
Market liquidity risk – Models
Note: "Acceptance rate" is fraction of stocks where Kupiec (1995)-statistic could not reject deviation between realized and predicted loss frequency; ; Sample = 160 stocks in four major German stock indices over 5.5 yearsSource: Ernst, Stange, Kaserer (2009)
However, models including delay costs not developed yet
36Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
This presentation presents an overview on market liquidityAgenda
• Introduction
• Market liquidity
– Definition
– Characteristics
– Measurement
– Empirical facts
• Market liquidity risk
– Introduction
– Models
• Summary and open research questions
37Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Summary Market Liquidity
Market liquidity is cost of trading an asset• Components: Direct trading costs, price impact costs, delay costs• Determinants: type of asset, order size, liquidation horizon• Continuous liquidity degrees – different treatment required• Optimal trading strategies developed to minimize sum of cost components
– Balance increased delay cost against reduced price impact– Less relevant for risk management
• Several liquidity measures available– Direct liquidity measure promise increased precise liquidity measurement
Several models can be chosen to measure market liquidity risk• Market liquidity risk is substantial, but often neglected• Models based on limit order data perform better in backtests• Modified risk model (Ernst et al. 2008) consistently outperforms
38Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Interesting open research topics1. Can the superiority of the model of Ernst et al. (2008) be improved via better moment estimation techniques?**2. Estimation and validity of optimal trading strategies (OTS)*
– How can parameters of theoretical models with optimal trading strategies be estimated?– In which situations are optimal trading strategies beneficial compared with instant liquidation - in normal times or also
in crises?3. In which situations are liquidity costs efficient?
• How should arbitrage strategies be constructed?• What drives the efficiency of markets?
4. Are total liquidation costs per stock an asset pricing factor?– Total liquidation costs can be estimated via weighted spread times traded size distribution
5. Can the price impact curve be described via theoretical processes?– Similar to interest rate curve– Arbitrage conditions also apply if liquidity price are efficient– Can be helpful when describing unobservable / hidden liquidity
6. Is it possible to construct liquidity options – in analogy to volatility options?7. How high are liquidity cost / risk levels between different asset classes?8. Can the stability of liquidity cost for relative order size be used in liquidity risk measurement?
– Liquidity costs are relatively constant for order size in relation to volume and market value in the cross section (Stange, Kaserer 2008)
– Is this helpful in implementing an asset class, not asset specific liquidity risk approach?9. How should liquidity risk be integrated into portfolios?
– What is the role of liquidity commonality in the covariance matrix?
Source: Stange, Kaserer (2009)
Backup
39Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Further references
• Bervas (2006) "Market Liquidity and its Incorporation Into Risk Management", Banque de France technical report, http://www.gloriamundi.org
• Ernst, C., S. Stange. and C. Kaserer (2008a) "Accounting for Non-normality in Liquidity Risk", CEFS working paper 2008 No. 14, www.cefs.de
• Ernst, C., S. Stange. and C. Kaserer (2008b) "Empirical evaluation of market liquidity risk models", CEFS working paper 2009 No. 1, www.cefs.de
• Erzegovesi (2002) "VaR and Liquidity Risk. Impact on Market Behaviour and Measurement Issues", Alea Technical Reports Nr. 14, http://eprints.biblio.unitn.it
• Jorion (2007) "Value at risk: the new benchmark for managing Financial risk", 2. Ed., McGraw-Hill, New York
• Loebnitz (2006) "Market Liquidity Risk: Elusive no more - Defining and quantifying market liquidity risk", diploma thesis, University of Twente, http://purl.org/utwente/e582
• Mahadevan, A. (2001) "Incorporating Liquidity Risk in VAR estimation", ICICI Working paper, http://www.gloriamundi.org
• Stange, S. and C. Kaserer (2008a): "The Impact of Order Size on Stock Liquidity - A Representative Study", CEFS working paper, www.cefs.de
• Stange, S. and C. Kaserer (2008b) "Why and How to Measure Liquidity Risk", CEFS working paper, www.cefs.de
• Stange, S. and C. Kaserer (2009) "Market Liquidity Risk – An Overview", CEFS working paper, www.cefs.de
Backup
40Sebastian Stange and Christoph Kaserer, Chair of Financial Management and Capital Markets
Market liquidity v090127b.ppt
Thank you for your attention!
Comments are warmly welcome.
SebastianStange
Prof. ChristophKaserer