Numerous psychological studies show that weather conditions affect people's mood and that mood states are correlated with people's subjective evaluation of future probabilities. In this paper, a new approach is developed and asset market data are employed to test the mood-subjective probability relation. Cloud cover and precipitation volume serve as two mood proxies. Our statistical analysis suggests that bad mood states are characterized by investors placing higher probabilities on adverse events.

Using asset market data, as well as theoretical relations between investors’ preferences, option-implied, risk-neutral, probability distribution functions (PDFs,) and index-implied, actual, PDFs, this paper extracts a time-series of investors’ relative risk aversion (RRA) functions. Based on results recently derived by Benninga and Mayshar (2000), these functions are used to recover the evolution of risk preferences heterogeneity. Applying non-parametric estimation on European call options written on the S & P500 index, we find that: (i) the RRA functions are decreasing; and (ii) the constructed risk preferences heterogeneity series is positively correlated in a static, as well as a dynamic, setup with a prevalent proxy for investors heterogeneity, namely, the spread between auction- and market-yields of Treasury bills.

We test whether bond ratings contain pricing‐relevant information by examining security price reactions to Moody's refinement of its rating system, which was not accompanied by any fundamental change in issuers' risks, was not preceded by any announcement, and was carried simultaneously for all bonds. We find that rating information does not affect firm value, but that debt value increases (decreases) and equity value falls (rises) when Moody's announces better‐ (worse‐) than‐expected ratings. We also find that when Moody's announces better‐ (worse‐) than‐expected ratings, the volatilities implied by prices of options on the fine‐rated issuers' shares decline (rise).

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 multiperiod 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%, 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.

The disposition effect [Shefrin, H., Statman M., 1985, The disposition to sell winners too early and ride losers too long. Journal of Finance, 40, 777–790], investors’ tendency to sell gaining assets and hold on to loosing assets, relies on the notion of a reference point distinguishing between losses and gains. While literature using aggregated market data documented the existence of such a reference point affecting investors’ decisions, it had not pinpointed it. The main goal of our work is to shed light on the mechanism of reference point formation. We hypothesize that salient events taking place during a stock’s holding period influence investors’ perceptions and make them update the stock’s reference point. Using analysts’ earnings forecasts, stock price data, and firms’ quarterly earnings announcements, we document that company-specific events indeed affect the reference points. We discover that the earnings announcements played a role in reference point formation when they were not anticipated, i.e., when (i) analysts’ earnings forecasts failed to provide accurate predictions; and (ii) the earnings announcements were followed by market price reactions. Moreover, the reference points were affected more profoundly for low market capitalization, high beta firms, pointing that the reference point updating process is more reactive to events when information flow is low and prices are sensitive to market fluctuations. Our results also corroborate the attention hypothesis, i.e., the observation that agents facing numerous alternatives may consider primarily those that have caught their attention.

The presented research tests cumulative prospect theory (CPT, [Kahneman, D., Tversky, A., 1979. Prospect theory: An analysis of decision under risk. Econometrica 47, 263–291; Tversky, A., Kahneman, D., 1981. The framing of decisions and the psychology of choice. Science 211, 453–480]) in the financial market, using US stock option data. Option prices possess information about actual investors’ preferences in such a way that an exploitation of conventional option analysis, along with theoretical relationships, makes it possible to elicit investor preferences. The option data in this study serve for estimating the two essential elements of the CPT, namely, the value function and the probability weighting function. The main part of the work focuses on the functions’ simultaneous estimation under CPT original parametric specification. The shape of the estimated functions is found to be in line with theory. Comparing to results of laboratory experiments, the estimated functions are closer to linearity and loss aversion is less pronounced.