Asset Pricing
Giacomo Morelli
Introduction
2023-2024
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Teacher and Lectures
➢ Giacomo Morelli: morellig@luiss.it
➢ Teaching Assistant (TA):
• Vittoria Di Felice: vdifelice@luiss.it
➢ Lectures:
•
Monday 14.00-15.15 (online, virtual room Webex)
•
Tuesday, 11:00-12.30 (campus, Room Polivalente)
•
Friday, Gr 1, 11.45-12.45 (campus, Room A401)
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Friday, Gr 2, 10:45-11.45 (campus, Room A203)
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Organization
➢ There will be lectures as well as empirical exercises with data from financial markets
➢ Background in Quantitative Methods for Finance is required
➢ You are supposed to work in groups (max 5 students) on weekly problem sets (PS) that
will be subject to evaluation. Solutions to PS will be discussed in class. Students’
participation during lectures is essential
➢ There will be 3 Intermediate Assessments (in groups)
➢ You are supposed to use Python
➢ Final award for the best group
➢ Final exam
➢ Thesis (topics etc…)
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Learning Verification Method
➢ Attending students:
• Class participation 10% (valid only for May-June)
• Intermediate Assessment 60% (valid only for May-June)
• Final exam 30% (valid only for May-June)
➢ Non attending students:
• Final exam 100%
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Study Materials
➢ The main reference textbook:
• Lasse Heje Pedersen. Efficiently Inefficient. How Smart Money are
Invested and Market Prices are Determined. Princeton University Press
➢ Other reference textbooks:
• John C. Hull. Options, Futures and Other Derivatives, Pearson (9th
Edition)
• Bodie, Kane & Marcus – Investments, McGraw Hill (10th Edition)
• Y. Hilpsch, Derivatives Analytics with Python: Data Analysis, Models,
Simulation, O’Reill
➢ I will discuss the required readings at the beginning/end of each lecture
➢ Slides:
• Current trend is learning only through slides. Please, don’t
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Dublin Descriptors
Knowledge and understanding:
By the end of the course, students should be able to:
• understand risk-return relationship, market ef ciency, investment strategies derivatives; fund management,
asset price dynamics;
• collect, analyse, model and critically interpret investments related to business;
• use the software Python for investment analysis.
Applying knowledge and understanding:
Upon completing the study program, students will be able to:
• use asset pricing models;
• use nancial thinking to formalise complex problems and apply analytical tools to solve them;
• develop investment decisions;
• coding.
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Dublin Descriptors II:
Making judgements:
• face complex problems and apply analytical tools in an independent way;
• give original interpretations to the results obtained from the data analysis;
• these are requirements that students develop during the weekly problem sets.
Communications Skills:
• develop the ability to communicate in written form through completing weekly assignments and participating to class
discussions;
Learning skills:
• analyse risk-return, market ef ciency, arbitrage opportunities;
• autonomously understand and interpret new more advanced techniques and adapt them to the speci c reference
context;
• problem solving; and decision making;
• use the acquired knowledge to access to prominent job positions within hedge funds, investment banking,
consulting companies and institutions and/or to access to further advanced learning programs such as PhD or
Master’s in Finance or Management.
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Objectives
➢ Discuss market efficiency and asset price dynamics
➢ Provide insight into the relationship between risk and return to develop investment decisions
➢ Equip students with a solid background in the different investment strategies in:
• Assets market
• Derivatives markets
➢ Collect, analyse, model and critically interpret investments related to business
➢ Focus on fund management
➢ Use the software Python for investment analysis
➢ Use asset pricing models
➢
Use financial thinking to formalise complex problems and apply analytical tools to solve them
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Overview
➢ Market efficiency
➢ Risk-return relationship
➢ Derivation of the Capital Asset Pricing Model (CAPM)
➢ Hedge funds and other smart money
➢ Overview of hedge fund styles and strategies
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Equity Strategies
Arbitrage Strategies
Macro Strategies
Fixed-income arbitrage
Investment styles and factor investment
➢ Derivatives (Options market)
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Market Efficiency
➢ Market efficiency: at the heart of financial economics
➢ Nobel Prize 2013 awarded to Eugene Fama, Lars Hansen, and Robert Shiller
➢ Efficient!
➢ Inefficient!
Efficient Markets?
Markets cannot be fully efficient
1. If they were, there would be little incentive to collect information (GrossmanStiglitz, 1980)
2. Logically impossible that both market for asset management and asset markets fully
efficient
– Asset market efficient !
no one should pay for active management
➢
Failure of the Law of One Price, e.g.
– Asset management: Closed-end fund discount, ETFs
– Stocks: Siamese twin stock spreads
– Bonds: Off-the-run vs. on-the-run bond spreads
– FX: Covered interest-rate parity violations
– Credit: CDS-bond basis
Not subject to “joint hypothesis problem”
➢
Completely
Inefficient
➢
➢
3. Clear evidence against market efficiency
EFFICIENCY-O-METER
Perfectly
Efficient
Inefficient Markets?
Market prices cannot be completely divorced from fundamentals
1. Money managers compete to buy low and sell high
2. Free entry of managers and capital
3. If markets were completely divorced from fundamentals
– Making money should be very easy
– But, professional managers hardly beat the market on average
➢
➢
Completely
Inefficient
➢
➢
Perfectly
Efficient
EFFICIENCY-O-METER
➢
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Efficiently Inefficient Markets
Markets are efficiently inefficient
➢ Markets must be
– inefficient enough that active investors are compensated for their costs
– efficient enough to discourage additional active investing
➢ Investment implications
– some people must be able to beat the market
Efficient market hypothesis
Investment Implications
Passive investing
Inefficient market
Active investing
Efficiently inefficient markets
Active investing by those with
comparative advantage
➢
➢
Completely
Inefficient
➢
Market Efficiency
Efficiently
Inefficient
Perfectly
Efficient
EFFICIENCY-O-METER
➢
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Efficiently Inefficient Markets: Trading Strategies vs. Finance Theory
➢ Finance theory tells you what the price of stocks and bonds “should” be
➢ What if the market price is different?
– Model is wrong or market is wrong?
– What can you do about it?
– How can you tell?
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What is a Hedge Fund: Definition I
“Hedge funds are investment pools that are relatively unconstrained in what they do.
They are relatively unregulated (for now), charge very high fees, will not necessarily
give you your money back when you want it, and will generally not tell you what
they do. They are supposed to make money all the time, and when they fail at this,
their investors redeem and go to someone else who has recently been making money.
Every three or four years they deliver a one-in-a-hundred year flood. They are
generally run for rich people in Geneva, Switzerland, by rich people in Greenwich,
Connecticut.”
— Cliff Asness, Journal of Portfolio Management 2004.
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What is a Hedge Fund: Definition II
➢ Hedge fund:
– investment vehicles pursuing a variety of complex trading strategies to make money
– “hedge” refers to reducing market risk by long/short investing
– “fund” pool of money
➢ Can use sophisticated investment strategies and fee structures:
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Leverage
Short selling
Derivatives
Incentive fees (mutual funds are restricted)
➢ Limited disclosure requirements
➢ To achieve this relative regulatory freedom, hedge funds are
– Restricted in how they can raise capital
– Non solicitation
– Investors must be “accredited investors”
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What is a Hedge Fund: Historical Background
1949
Albert Wislow Jones starts the first U.S. hedge fund
1966
Fortune: “The Jones Nobody Keeps Up With” (written by Carol Loomis) coins
the term “hedge fund” publicizes Jones’s results: Over 10 years, he had outperformed
best mutual fund by 87%
1966-69 Increased hedge fund activity: More than 130 hedge funds started, including
George Soros's Quantum Fund and Michael Steinhardt's Steinhardt Partners
1986
Institutional Investor report that Julian Robertson’s Tiger Fund has averaged
43% per year for 6 years
1990Institutional investors start to embrace hedge funds (including the Yale
endowment model), leading to a rapid growth of the industry
2000
The poor equity market performance fuels hedge fund demand
2008
About 10,000 hedge funds with more than $2 Trillion in AUM, constituting
more than half the trading volume on several major exchanges
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How Do You Beat the Market?
➢ Conceptually, how do you beat the market?
➢ How do you beat the market in practice?
– What do great investors have in common?
How Do You Beat the Market?
➢ Categorization of hedge fund strategies
(There is no standard, the various hedge fund index providers have different categories)
Ainslie
Chanos
Asness
Soros
Harding
Scholes
Griffin
Paulson
Hedge Fund Strategies: Equity Strategies
➢ Equity long/short
– Discretionary trading
– Fundamental analysis and catalysts
– It’s easy to be a contrarian, except when it’s profitable.
– Buy on rumors, sell on news.
➢ Dedicated short bias
– Identifying frauds, forensic accounting
– While equity long/short is more long than short, the reverse is true for short biased funds
➢ Equity market neutral
– Quant
– Value, momentum, pairs trading, statistical arbitrage,
high frequency trading, index arbitrage
– Have a rule. Always follow the rule, but know when to break it.
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Hedge Fund Strategies: Macro Strategies
➢ Global macro
– Carry trades, central bank watching, devaluation, thematic, yield curve, country selection
– Soros: When you have tremendous conviction on a trade, you have to go for the jugular. It
takes courage to be a pig.
– Bulls get rich, bears get rich, but pigs get slaughtered.
➢ Managed futures
– Trading in trends and countertrends
– Equity, fixed-income, and commodity futures, currency forwards
– The trend is your friend.
– Show me the charts, I’ll tell you the news.
– Cut losses and let your profits run.
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Hedge Fund Strategies: Arbitrage Strategies
➢ Event driven
– Merger arbitrage (risk arbitrage), distressed, carve outs, spinoffs, splitoffs, when-issued,
IPOs, SEOs, other corporate events, special situations
➢ Convertible bond arbitrage
– long converts, hedge with equity, credit, fixed income
– Gamma, busted, high-money
➢ Fixed income arbitrage
– swap spread, yield curve, butterfly, mortgage, CDS-bond basis, on-the-run/off-the-run
– Keynes: The markets can remain irrational longer than you can remain solvent.
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What do Great Investors Have in Common? Investment Styles
INVESTMENT STYLES
RETURN DRIVERS
Ubiquitous methods used across trading strategies and asset
classes
The reason that these methods work in an efficiently
inefficient market
Value Investing
Risk premia and overreaction
Trend-Following Investing
(momentum and time series momentum)
Initial underreaction and delayed overreaction
Liquidity Provision
Liquidity risk premium
Carry Trading
Risk premiums and frictions
Low-Risk Investing
(betting against beta)
Leverage constraints
Quality Investing
Slow adjustment
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Understanding Hedge Funds: Objectives and Fees
➢ Objective:
– To make money in any environment
– Absolute return benchmark (cf. relative return)
➢ Fees
– Management fees
– Performance fees
– Classic fee structure: two-and-twenty
➢ Other fee characteristics
– Hurdle rate
– High water mark
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Understanding Hedge Funds: Fees
➢ Distribution of management and incentive fees. Fung-Hsieh Table 2
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Understanding Hedge Funds: Performance
➢ Past returns have been reasonably good (esp. before fees) and diversifying
➢ Beware of biases:
– Backfill bias
– Survivorship bias
➢ And risks:
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Negative skewness
Excess kurtosis
Low persistence, i.e. winners do not remain winners
High attrition
Liquidity risk
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Understanding Hedge Funds: Performance
➢ Performance statistics, 1995–2003. Malkiel-Saha Table 1.
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Understanding Hedge Funds: Backfill Bias in Returns
➢ Malkiel-Saha Table 2, 1994-2003.
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Understanding Hedge Funds: Attrition
➢ Malkiel-Saha Table 7, 1994–2003
➢ Of 331 HFs reporting in 1996, 58 were still in existence in 2004, i.e. 18%.
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Performance of Active Investors
➢ “Old consensus” in the academic literature:
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Active investors as represented by mutual funds have no skill: Jensen (1968), Fama (1970), Carhart (1997)
➢ “New consensus” in the academic literature
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The average mutual fund underperforms slightly after fees, not before fees, but the average hides significant
cross-sectional variation across good/bad managers
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Skill exists among mutual funds and can be predicted: Kacperczyk, Sialm, and Zheng (2008), Fama and French
(2010), Kosowski, Timmermann, Wermers, White (2006):
“we find that a sizable minority of managers pick stocks well enough to more than cover their
Moreover, the superior alphas of these managers persist”
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costs.
Skill exists among hedge funds: Fung, Hsieh, Naik, and Ramadorai (2008), Jagannathan, Malakhov, and Novikov
(2010), Kosowski, Naik, and Teo (2007):
“top hedge fund performance cannot be explained by luck, and hedge fund performance persists at
annual horizons… Our results are robust and relevant to investors as they are neither confined to
small funds,
nor driven by incubation bias, backfill bias, or serial correlation.”
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Skill exists in private equity and VC: Kaplan and Schoar (2005)
“we document substantial persistence in LBO and VC fund performance”
➢ Consistent with efficiently inefficient markets
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For details see “Efficiently Inefficient Markets for Assets and Asset Management,” Garleanu and Pedersen (2015)
Understanding Hedge Funds: Organization and the Master-Feeder Structure
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Understanding Hedge Funds: Role in the Economy
➢ Hedge funds are useful:
➢ Make markets more efficient
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Collect information
Trading impounds information into prices
Monitors managers of companies
This could improve real outcomes, e.g.,
• CEO decisions
• real investment
• capital allocation
➢ Provide liquidity
– To investors who need to buy or sell (consumption smoothing)
– To investors who need to hedge
– To companies who need to issue securities
➢ Provide insurance against event risk to other investors
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