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Summary Advanced Behavioural Finance (FEM11076)
A summary of the lecture slides.
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Summary Lectures Advanced Behavioral FinanceSession 1: Introduction to Behavioral Finance
Traditional vs. behavioral finance
- Rational expectations hypothesis:
o Investors and managers are rational
o efficient market hypothesis asset prices incorporate all available information
- Behavioral finance:
o Some agents aren’t rational
o Asset prices systematically deviate from fundamental values
o Impact on corporate finance decisions, investments and asset prices
Rationality and limits to arbitrage
Rational choice meets 4 criteria
1) Based on agents’ current assets
2) Based on possible consequences of the choice (no effect of framing)
3) Consistent with EU framework
a. Consider different possible outcomes
b. Decide how good/bad each outcome will make him feel
c. Weigh outcomes by probability and sum up
4) When agents receive new information, they update their expectations (Bayes law)
Market efficiency
- An efficient market = prices equal fundamental value
o Prices equal discounted sum of expected future CF’s
o Discount rate is consistent with normatively acceptable
o Prices incorporate all available information
- Forms of market efficiency
o Strong = “prices incorporate” all public and private information
o Semi-strong = “” all public information
o Weak = “” only past public information
- Market efficiency and stock returns
o The arbitrage concept keeps the market efficient: even with some irrational traders
who create mispricing rational traders grab the opportunity and thereby correct it
o Behavioral finance argues that a mispricing isn’t always a riskless profitable arbitrage
opportunity
Behavioral finance
- Some agents are not fully rational:
o Fail to update beliefs/incorporate all available information
o Make normatively unacceptable choices
- Limits to arbitrage:
o Rational agents cannot always correct irrationality of other investors
o Irrationality (mispricing) can have substantial/long impact
- Behavioral biases:
o Irrational decisions aren’t random systematic mispricing
o Belief formation = how agents form expectations
, o Decision-making (preferences) = how agents evaluate risky decisions
Limits to arbitrage strategies to correct mispricing can be both risky and costly unattractive.
Risks & costs allowing mispricing to survive:
1) Fundamental risk
a. Risk asset loses value
b. Finding perfect hedge is usually impossible
2) Noise trader risk
a. Mispricing worsens in the short run
b. Can force arbitrageurs to liquidate positions prematurely worsens further
3) Implementation costs
a. All costs that make it less attractive to exploit mispricing
b. Transaction costs, short sale constrains, information costs
c. Horizon risk
Noise trader risk - sufficient conditions to limit the arbitrage:
- Arbitrageurs are risk averse and have short horizons
o Arbitrageurs cannot afford to be patient
o Creditors and investors evaluate the arbitrageur based on his returns
o Forced closure of a short position
- Noise trader risk is systematic
o Investor sentiment causing assets to be undervalued could also increase mispricing in
the short term
Finding evidence on the limits to arbitrage
1) We need to know the real fundamental value
2) Joint hypothesis problem (bad-model risk)
a. Test of mispricing is a joint test of mispricing and asset pricing
b. Is it mispricing or omitted (miscalculated) risk factor?
3) Few cases of mispricing can be measured without doubt
Twin shares
- Dual listed companies:
o 2 firms function as 1 operating business
o Retain separate stock
o Shares represent claims on exact same underlying CF’s
o Examples: Unilever, Reed Elsevier, Shell etc.
- Limits to arbitrage:
o Fundamental risk = none
o Noise trader risk =?
o Implementation costs = small
Other examples of limits to arbitrage
1) Index inclusions of stock (S&P500, Russell 1000)
a. When stock is added to index it jumps even though the fundamental value doesn’t
change
b. Fundamental risk and noise trader risk
2) Closed-end funds
a. Mutual funds that issue a fixed nr. of shares
, b. Fund share prices differs from net asset value
c. Mainly noise trader risk
d. Lee, Shleifer and Thaler (1991)
3) Bubbles
a. Limited short-selling (implementation costs) during DotCom bubble
b. Housing bubble = short-selling not directly possible
c. Griffin, Harris, Shu and Topaloglu (2011)
4) Equity carve-outs
a. Lamont and Thaler (2003)
Tech stock carve-outs (Lamont and Thaler, 2003)
Equity carve-outs
- Equity carve-out (partial public offering) = IPO for shares, usually minority stake, in a
subsidiary company; partial divestiture of a business unit
- Spinoff = parent firm gives remaining shares in subsidiary to parents’ shareholders; parent
distributes entire ownership interest in subsidiary as stock dividend to existing shareholders
- Sample selection in the paper:
o Carve-outs where parent retains ≥80% of subsidiary
- 3Com and Palm example:
o Carve-out: On 02-03-2000, 3Com sold 5% of its stake in Palm
o Spinoff: 3Com shareholders will receive 1.525 shares of Palm for every share
o The price of 3Com must be at least 1.525 times the price of Palm
Negative stub calculation
- Stub = residual security that is left over after removing the carve-outed subsidiary from the
parent security
- Constructing stubs
- 3Com and Palm example on IPO day:
o Subsidiary Palm closed at $95.06
o Parent 3Com closed at $81.81
- Mispricing: the initial negative stub was
77% of the 3Com value
- The stub was negative for 48 trading days
- Investors worth $2.5 billion decided to own Palm instead of 3Com
- The announcement of IRS approval and distribution date cause the stub to go from negative
to positive
Risk and return from investing in stubs investment strategy: long in parent &
short in subsidiary
- Parents had 30/33 percent higher returns than subsidiary (of six cases in slides)
- The strategy delivers an alpha of 10% per month
- The Sharpe ratio of this strategy is around 0.7 p.m.
- The strategy can benefit from additional risks (cancelled spin-off, takeover)
The role of short-sale constraints
- With irrational traders, short-sale constraints can cause stocks to be overpriced
- Short sales constraints = costs & risks that make it less attractive for pessimistic investors to
short stocks sufficiently and exploit mispricing
1) Shorting process:
, a. To go short, one must first borrow the stock
b. The security lenders receive a fee
c. Rebate rate = interest rate paid to the deposit placed by the borrower
d. Stocks held primarily by individual investors are difficult to short
2) Short interest: total nr. of shares sold short relative to total nr. of shares outstanding
- Someone has to own the shares issued by the firm: the nr. of shares not lent out must equal
the nr. of shares outstanding
Increase over time in short interest for subsidiaries is delayed it may take a while for investors to
become aware of the mispricing short-sale market works sluggishly
Creating synthetic short position with
options
- Put-call parity for options
- Synthetic short: use options to simulate the
payoff of a short stock position
o Buy at-the-money puts
o Sell at-the-money calls
o Borrow the present value of the strike price
Palm option prices
- Substantial violations of put-call parity
- Prices consistent with vary high shorting costs
- The options and equity market are segmented; investors choose to hold the stock even
though there exists a portfolio that provides higher return
Mispricing cause – investor characteristics
- Subsidiaries have higher turnover and lower institutional ownership
- Liquidity cannot explain differences, as similar bid-ask spreads
- Some investors are riding the bubble (greater fool theory)
Conclusion
1) Negative stubs are blatant mispricing’s and gross violations of the law of one price
2) They don’t present exploitable arbitrage opportunities because of the costs of shorting the
subsidiary
3) Arbitrage doesn’t always enforce rational pricing
4) Limits of arbitrage can create market segmentation
5) Systematic irrationality among a subset of investors can cause the prices to deviate from
fundamental value for a longer period of time
Behavioral biases (representativeness)
Decisions of irrational agents aren’t random and can create mispricing’s
1) Beliefs = how agents form expectations
a. Representativeness
b. Overconfidence and overoptimism (wishful thinking)
c. Belief perseverance and confirmation bias
d. Anchoring
e. Availability bias
2) Decision-making (preferences) = how agents evaluate risky decisions
a. Prospect theory
b. Ambiguity aversion
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