Are Probabilities Used in Markets?

Working in a complete-markets setting, a property of asset demands in identified that is inconsistent with the investor's preference being based on probabilities. In this way, a market counterpart of the Ellsberg Paradox is provided.FINANCIAL MARKET ; SECURITIES ; DEMAND ; INVESTMENTS

Estimating Subjective Probabilities

Subjective probabilities play a role in many economic decisions. There is a large theoretical literature on the elicitation of subjective probabilities, and an equally large empirical literature. However, there is a gulf between the two. The theoretical literature proposes a range of procedures that can be used to recover subjective probabilities, but stresses the need to make strong auxiliary assumptions or "calibrating adjustments" to elicited reports in order to recover the latent probability. With some notable exceptions, the empirical literature seems intent on either making those strong assumptions or ignoring the need for calibration. We illustrate how the joint estimation of risk attitudes and subjective probabilities using structural maximum likelihood methods can provide the calibration adjustments that theory calls for. This allows the observer to make inferences about the latent subjective probability, calibrating for virtually any well-specified model of choice under uncertainty. We demonstrate our procedures with experiments in which we elicit subjective probabilities. We calibrate the estimates of subjective beliefs assuming that choices are made consistently with expected utility theory or rank-dependent utility theory. Inferred subjective probabilities are significantly different when calibrated according to either theory, thus showing the importance of undertaking such exercises. Our findings also have implications for the interpretation of probabilities inferred from prediction markets.

Market integration for agricultural output markets in Peru: the role of public infrastructure

This paper shows the impact that investment in infrastructure may have on the efficiency of agricultural products markets. Using daily price series for the most important agricultural crop in Peru (potato), in 10 cities from 1995 to 2001, we show that there is enough evidence to conclude that agricultural markets are spatially integrated. However we also show that there is short term disequilibria that affect the efficiency with which price information is transmitted across markets. A Threshold Cointegration Model is used to asses the speed of adjustment towards the equilibrium, the presence of transaction costs and the probabilities of successful and failed arbitrage between spatially distributed markets. As was expected, the paper shows that distance and geographic differences are important factors affecting spatial integration and efficiency between markets. However, other elements susceptible of government intervention, such as availability of information (access to local media and telecommunications facilities), road density or access to wholesale markets, are key factors for the reduction of transaction costs and the improvement of spatial integration between markets.Infrastructure, Investment, Rural, Peru

From Default Probabilities To Credit Spreads: Credit Risk Models Do Explain Market Prices

Credit risk models like Moody’s KMV are now well established in the market and give bond managers reliable estimates of default probabilities for individual firms. Until now it has been hard to relate those probabilities to the actual credit spreads observed on the market for corporate bonds. Inspired by the existence of scaling laws in financial markets by Dacorogna et al. (2001) and Di Matteo et al. (2005) deviating from the Gaussian behavior, we develop a model that quantitatively links those default probabilities to credit spreads (market prices). The main input quantities to this study are merely industry yield data of different times to maturity and expected default frequencies (EDFs) of Moody’s KMV. The empirical results of this paper clearly indicate that the model can be used to calculate approximate credit spreads (market prices) from EDFs, independent of the time to maturity and the industry sector under consideration. Moreover, the model is effective in an out-of-sample setting, it produces consistent results on the European bond market where data are scarce and can be adequately used to approximate credit spreads on the corporate level.

Bosnia and Herzegovina 2001-2004 : enterprise restructuring, labor market transitions and poverty

This paper takes stock of labor market developments in Bosnia and Herzegovina over the period 2001-2004, using the panel Living Standards Measurement Study/Living in Bosnia and Herzegovina survey. The analysis estimates a multinomial logit model of labor market transitions by state of origin (employment, unemployment, and inactivity) following the specification of widely used models of transition probabilities, and analyzes the impact of standard covariates. The results provide strong evidence that there are indeed significant differences in labor market transitions by gender, age, education, and geographic location. Using the panel structure of the multi-topic survey data, the authors find that these transitions are related to welfare dynamics, with welfare levels evolving differently for various groups depending on their labor market trajectories. The findings show that current labor market trends reflecting women's movement out of labor markets and laid-off male workers accepting informal sector jobs characterized by low productivity will lead to adverse social outcomes. These outcomes could be averted if the planned enterprise reform program creates a more favorable business environment and leads to faster restructuring and growth of firms.Labor Markets,Labor Policies,Population Policies,,Banks&Banking Reform

A Stylised Model for Extreme Shocks: Four Moments of the Apocalypse

We present a method for calculating the extreme tail quantiles, over arbitrary holding periods, of a continuous-time stochastic volatility model of the form proposed by Scott (1987) with correlation between the processes for volatility and price. The fat tails of this model enable a consistent, tuneable, stylised representation of non-normality in extreme moves of prices across diering markets. Because the model is analytically intractable, four moments are derived by numeric integration and matched to a one-period version of the model, whose quantiles are then found by further numeric integration. We also present a novel Monte-Carlo simulation scheme, which we have used to confirm the accuracy of the moment-matching approximation for quantiles as extreme as one-millionth. Two methods for calibrating the model to market data are also proposed. The model is used in production stress testing at nabCapital to define consistent real-world probabilities for extreme shocks over heterogeneous holding periods.