Behavioral Finance

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probabilistic alternatives that involve risk where the probabilities of outcomes are known. In short, each prospect is a gamble and it shows how people make decisions under uncertainty. It states that people make decisions based on the potential value of losses and gains rather than the final outcome.

In essence, the theory explains the apparent regularity in human behaviors when assessing risk under uncertainty. That is, human beings are not consistently risk-averse; rather they are risk-averse in gains but risk-takers in losses. According to Tversky and Kanheman, people place much more weight on the outcomes that are perceived more certain than that are considered mere probable, a feature known as the “certainty effect”. Peoples choice are also affected by ‘framing effect’. Framing refers to the way a problem is posed to the decision maker and their ‘mental accounting’ of that problem

Hence, prospect theory concludes that :

a) Investors pay attention to change in each transaction than the total value.

b) People look at chances in terms of potential gains and losses in relation to specific reference point.

c) The reference point is psychological and is measured in terms of today’s wealth.

d) Decision makers analyze gains and losses differently.

e) People have more pain for losses and less happiness for gains.

f) Hence, the value function for gains is concave and convex for losses.

EXAMPLES OF PROSPECT THEORY:

CASE I: A person is presented with Rs 30,000 ( Initial endowment ) and two options :

a) A sure gain of Rs.10,000

b) 50% chance to gain Rs.20,000 and 50% chance of gaining Rs.0

CASE II: A person is presented with Rs50,000 and two options :

a) A sure loss of Rs.10,000

b) 50% chance to lose Rs.20,000 and 50% chance to lose Rs.0

The behavior pattern of people was tested in this survey and the results are as follows:

CASE I: 72% chose option a, 28% chose option b

Since the options were framed as gains, investors chose to be risk – averse. They chose a sure probability of gain of a lesser amount over a lesser probability of gain of a larger amount.

CASE II: 36% chose option 1, 64% chose option 2.

Since the options were framed as losses, investors chose to be risk- seeking.

CHAPTER-4

LIMITS TO ARBITRAGE

The textbook definition of “arbitrage” involves a costless investment that generates riskless profits, by taking advantage of mispricings across different instruments representing the same security. Arbitrage is critical to the maintenance of efficient markets, since it is through the arbitrage process that fundamental values are kept aligned with market prices. In practice, arbitrage entails costs as well as the assumption of risk, and for these reasons there are limits to the effectiveness of arbitrage in eliminating certain security mispricings. There is ample evidence for such limits to arbitrage.

Many of these limits are explored in a ground-breaking 1997 paper called, appropriately, “The Limits of Arbitrage,” by Shleifer and Vishny. Below we consider a few limits to arbitrage, and finally some that may apply to our situation as value investors in the stock market.

Fundamental Risk. Arbitrageurs may identify a mispricing of a security that does not have a close substitute that enables riskless arbitrage. If a piece of bad news affects the substitute security involved in hedging, the arbitrageur may be subject to unanticipated losses.

EXAMPLE: here is a pairs trading strategy, which employs two nearly identical securities in the arbitrage process. Say Coke and Pepsi traditionally trade at a similar valuation, a P/E of 10, yet for some reason Coke has become very expensive at 20X earnings, while Pepsi remains at a 10X multiple. The arbitrageur would go long Pepsi, and short Coke. When the multiples converge to historical equality, at some point in the future, the arbitrageur would realize gains. But what if Pepsi declined to a 5X multiple and Coke increased to a 30X multiple for the next 5 years? The arbitrageur is exposed to the fundamental risks of each security

Noise Trader Risk. Noise traders limit arbitrage. Once a position is taken, noise traders may drive prices farther from fundamental value, and the arbitrageur may be forced to invest additional capital, which may not be available, forcing an early liquidation of the position.

Complicating Noise Trader Risk is the structure of many arbitrage markets. Shleifer and Vishny point out that “millions of little traders” don’t have access to the same information that professional, specialized arbitrageurs do. These professional arbitrageurs, who thus do the bulk of the market’s arbitrage work, will go out and raise capital from third parties to ply their trade. If an arbitrage spread widens, however, these third parties may disrupt the arbitrage process by pulling their capital, just when it is most needed to keep an arbitrage trade on.

EXAMPLE: The 2011 bankruptcy of MF Global. MF Global was fundamentally pursuing an arbitrage trade. The firm bought discounted European bonds (that were guaranteed by the European Stability Facility), and then used them as collateral for new loans, which they used to buy yet more bonds. So the bonds were guaranteed, and MF Global only had to repay the loans when the bonds matured at par – in an amount greater that what was owed. It was the perfect arbitrage trade! The ultimate outcome, however, clearly demonstrates the limits to arbitrage: noisy traders pushed bond spreads wider, and MF Global got hit with a margin call that bankrupted the firm.

Implementation Costs. Short selling is often used in the arbitrage process, although it can be expensive due to the “short rebate,” representing the costs to borrow the stock to be sold short. In some cases, such borrowing costs may exceed potential profits. If short rebate fees are 10% or 20%, then arbitrage

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