Even though according to Prospect theory the individualistically function is concave in the gains region, implying that they are risk averse, its shape changes to convex for very small probabilities. Usually people treat the outcomes based on a reference point, usually their current wealth, from which they evaluate gains and losses. For that reason a certain gain of $1 0 is not perceived as bringing any significant utility to let’s say average middle-class individual, while the possibility, even though small, of winning SIS 000 would actually bring a quite significant change to his wealth.
The opposite goes for the perceived utilities and the utility function, when in the loss region. Even a small probability of losing a significant amount ($10 000), which will severely affect the wealth of the individuals is misperceived as relatively high and undesirable as opposed to the certain, but small loss of $10, which will not affect the wealth of the person around his reference point.
Some real life analogues of the conducted experiment might be buying a lottery ticket, where the individual even gets a small, but negative payoff, on average, or establishing a start-up business, where an entrepreneur invests capital with the hope Of receiving higher return in time, instead of investing the money in a bond or a bank deposit at a risk-free rate. Examples for certain small losses might be a person buying insurance policies and paying a small premium, but avoiding the risk of theft, road accident etc. Q.
The distribution is not normal, but rather positively skewed, with higher percentage of positive earnings surprise than negative. There is also bunching at the O value, inferring a high probability that the average of analysts’ forecasts coincides with the actual earnings reported. This distribution of recast errors actually implies that analysts have a downward bias when producing their estimations. A reason for this might be that analysts have asymmetric loss function, implying that they can be more harshly punished for under-prediction than for over-prediction.
This is due to reactions of investors who, in most cases, have prospect theory utility functions, rather than conventional expected utility functions I. E. Their losses hurt more than gains of the same magna etude increase utility. In terms of the earnings surprise this means that when the actual earnings miss analysts’ projections, he negative returns on stocks in the following days are much more pronounced due to investors unwilling to hold the stock and selling with larger volumes.
In the opposite case of a positive surprise, investors’ utility function is less steep in the gains region and the magnitude of increased purchases of the stock is less pronounced. Boon and Woman (2002) estimate at least six reasons for the analysts’ downward bias when producing forecasts: internal pressures for earning higher brokerage commissions, pressure from management of companies that analysts cover, herding behavior to follow other analysts’ projections, pressure from large institutional investors that analysts work with, conflicts with analysts’ personal investments or unintentional cognitive biases of the analysts.
Other plausible reference points in terms of expected earnings might be results from past quarters + some premium/discount, depending on how the company performed in the most recent quarter, or the earnings reported by companies, operating in the same industry I. E. Competitors. Investor A If the stock goes up, he would be keener to sell in order to realize his gains. The Prospect Theory utility function, which is concave in the region of gains, wows us there will be a point where an increase in his profit will bring very low marginal utility, so at this point the investor would be keen to sell.
If we assume that the investor bought when , the more the stock rises and moves into more concave regions, , until it reaches the point of sell: If the stock goes down, he will hold the stock because he won ‘t accept his loss and try to hold it until the price of the stock returns to the price where he bought the stock (his reference point). He would be more concerned with the potential value of losses and gains than the total wealth outcome, so he would be more inclined to sell when the stock was in the gain-making region, and less likely to sell and more likely to hold at the loss-making region.
This is an observation of the disposition effect, tested by Dean (1998). Investor B If the stock goes up he will like to buy more shares. As an optimistic investor, he would trade more because of the profits that he is making, and the belief that he has information that others don t and that if the stock its going up, the momentum is likely to continue. If the stock goes down, he will like to sell because for him the market it’s telling him that this stock its not worth holding anymore.
The most important thing for him in order to make a decision for buy or sell is to receive a signal from the market and as an overconfident investor he would think that he has information that the market doses ;t and could benefit from that In other words he will consider the pure noise from the stock price movement as a signal and overweight it () The two investors could trade when the price of the stock rises, relative to their reference point because in that point investor A is more willing to sell and realize the gain and investor B is more willing to buy, because of the overestimated weight on the signal.
Also they could trade when the price goes down and reaches a certain point when investor A no longer can hold the position (has sustained huge losses) and investor B could get a signal from the market, that the stock is already undervalued. A) 1 . Overstatement – empirical data show that there are cases when Coos truly believe that certain investment policies are creating value for the company. However, their beliefs are quite often in discrepancy with the broad view of market participants, which is reflected in the stock value.
These investment incentives are more pronounced in companies, that are cash rich, nice Coos will not be constrained by lack of funds and allocate the available cash according to their overconfident beliefs. 2. Corporate Financing – instead of opting for the more rational choice of choosing sustainable mix of debt and equity financing, combined with the use of the company’s outstanding cash, overconfident Coos tend to use larger percentage of financing with cash or debt, since they consider equity financing excessively costly and believe that the market is undervaluing their company. . Overbidding in acquisitions – scholarly research has found evidence that overconfident Coos overestimate their ability to generate returns for their company. This is why such Coos have a tendency to overpay for target companies and undertake mergers that actually bring lower than expected value. A proof for this might be found in market reactions after announcement, where the negative return after the announcement is more pronounced for companies, whose managers are considered as overconfident by investors.
In the last two decades U. S firms spent more than $ 3. 4 trillion on mergers, and if CEO ;s were thinking only about the interests f their shareholders probably they would have acted in a different way, because their actions caused losses amounting to roughly $220 billion (Maintained, Tate 2007). B) CEO overconfidence does not necessarily have to be a bad thing, since this aspect is quite closely con nested with affinity to taking higher risk.
Higher risk, in turn, might lead either to more pronounced negative or positive outcome for the company, and thus also allowing for a beneficial outcome to shareholder interests. Also, such individuals, for reasons connected with their genetics or upbringing, are among the most successful and influential people n society. As discussed in the paper “CEO overconfidence and innovation” by Galas, Simoom (2011 more confident Coos tend to disregard the risk of failure and thus more eagerly indulge in R&D and innovation strategies, which eventually bring higher value to shareholders.
Real life examples of such Coos might be Steve Jobs (Apple Inc. ), Leon Musk (Tests Motors). Question 5 In the presented case, an overoptimistic person will tend to have higher anticipatory utility during his youth, but eventually as time progresses the actual realization will with a high probability be less than his anticipations, so e will get lower realization utility. The total utility he gets will depend on the weights he puts on those two utilities.
If you educate your child to be overoptimistic, in the future for example when he receives his pension fund he will expect certain amount of money, let’s say $1,000 per month, but instead if he actually receives $900 he will feel as if he lost $100, regardless if that amount of money represents a good income for him or not. On the other hand if he receives $1 r 1 00 he won ‘t feel the satisfaction of having more money. The feeling when you lose is deeper than when you win.
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