Estimating Switching Costs and Oligopolistic Behavior

We present an empirical model of firm behavior in the presence of switching costs. Customers' transition probabilities, embedded in firms' value maximization, are used in a multi-period model to derive estimable equations of a first order condition, market-share (demand), and supply equations. The novelty of the model is in its ability to extract information on both the magnitude and significance of switching costs, as well as on customers' transition probabilities, from conventionally available highly aggregated data which do not contain customer-specific information. As a matter of illustration, the model is applied to a panel data of banks, to assess the switching costs in the market for bank loans. The point estimate of the average switching cost is 4.1% which is about one third of the market average interest rate on loans. More than a quarter of the customer's added value is attributed to the lock-in phenomenon generated by these switching costs. About a third of the average bank's market share is due to its established bank-borrower relationship.

Theories of choice under risk: Insights from financial markets

To date, the plausibility of theories of choice under risk hinges are mainly on experimental evidence. This paper devises and implements an approach amenable of assessing the performance of three families of models (expected utility, rank-dependent expected utility, and the cumulative prospect theory) using information from financial asset markets. Our findings unequivocally support reference-point dependence, diminishing marginal sensitivity, loss aversion, and nonlinear weighting of (gain and loss) physical probabilities. The empirical observations are found to be robust to, inter alia, the parameterization of the utility and probability weighting functions, "day-of-the-week effects", the choice of a reference point, and the introduction of possible, low-probability market crashes (peso component).Cumulative prospect theory Expected utility Market data Rank-dependent expected utility

Evaluation periods and asset prices: Myopic loss aversion at the financial marketplace

Examining myopic loss aversion (MLA [Benartzi, S., Thaler, R., 1995. Myopic loss aversion and the equity premium puzzle. Quarterly Journal of Economics 110, 73-92]) in real financial markets has several merits: in repeated situations investors may learn from each other, aggregate market prices may eliminate individual violations of expected utility, and individuals may decide differently in real situations than in laboratories. We utilize a special feature at the Tel Aviv stock exchange (TASE): occasional shifts of securities from daily to weekly trading. If investors' decisions are influenced by trading frequency manipulation, then returns should be predictably affected. MLA results in a negative relation between risk aversion and the length of the evaluation period. Thus, the longer the evaluation period is, the lower the expected return is. This intuition also suggests reduced sensitivity to economic events in longer evaluation periods. We find strong support for MLA in the marketplace when testing expected return, as well as return sensitivity.Equity premium Financial markets Loss aversion Mental accounting Myopic loss aversion Prospect theory

Mood impacts on probability weighting functions: "Large-gamble" evidence

This paper integrates considerations of mood into non-expected utility theories and extends the existing literature on how mood influences peoples' decisions and choices. An important element in many non-expected utility theories is the probability weighting function (PWF), that nonlinearly weights physical probabilities. Using US market price data, we attempt to establish an empirical relation between investors' mood and these PWFs. To proxy investors' mood, we rely on an established medical phenomenon, seasonal affective disorder, a source of depression caused by the scarcity of daylight time during fall and winter, as well as on a measure of cloudiness. We find statistical evidence indicating that bad mood causes investors to systematically distort their PWFs.

Overconfident investors and probability misjudgments

This paper explores systematic distortions of subjective probabilities by overconfident investors. In agreement with many non-expected utility theories, our devised setup acknowledges nonlinear weighting of physical probabilities by both rational and overconfident investors. Overconfidence - assumed to be higher after a history of gains and lower after a history of losses - changes these probability transformations. Using US asset price data, overconfident investors are found to be more optimistic than rational investors about future prospects.Market data Overconfidence Probability weighting functions