Evidence indicates that people fear change and the unknown. We model this behavior as familiarity bias in which individuals focus on adverse scenarios in evaluating defections from the status quo. The model explains portfolio underdiversification, home and local biases. More importantly, equilibrium stock prices reflect an unfamiliarity premium. In an international setting, our model predicts t...

We provide a necessary and a sufficient condition on an individual’s expected utility function under which any zero-mean idiosyncratic risk increases cautiousness (the derivative of the reciprocal of the absolute risk aversion), which is the key determinant for this individual’s demand for options and portfolio insurance. JEL Classification Codes: D51, D58, D81, G11, G12, G13.

We compare capital requirements derived by tail conditional expectation (TCE) with those derived by tail conditional median (TCM) and find that there is no clear-cut relationship between these two measures in empirical data. Our results highlight the relevance of TCM as a robust alternative to TCE, especially for regulatory control. JEL Classification: G10, G11, G23, G29

The idea of representing choice under uncertainty as a trade-off between mean returns and some measure of risk or uncertainty is fundamental to the analysis of investment decisions. In this paper, we show that preferences can be characterized in this way, even in the absence of objective probabilities. We develop a model of uncertainty averse preferences that is based on a mean and a measure of...

Approximate Incremental Value-at-Risk formulae provide an easy-to-use preliminary guideline for risk allocation. Both the cases of risk adding and risk pooling are examined and beta-based formulae achieved. Results highlight how much the conditions for adding new risky positions are stronger than those required for risk pooling. JEL classification: C13; D81; G11; G12.

this paper estimates the determinants of inflation in iran using a linear and non- linear regression model over the period 1959-2008. in the model specification, the conventional variables (liquidity, production and exchange rate) as well as positive and negative oil revenue shocks, monetary disequilibrium, and demand gap are considered. the results show that nonlinear time series regression mo...

Motivated by the growing literature on volatility options and their imminent introduction in major exchanges, this paper proposes a new model that prices option contracts on volatility. To the best of our knowledge, the impact of volatility jumps in the valuation of volatility options has not yet been studied. The objective of this paper is to fill in this gap in the volatility derivatives lite...

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predict...

This paper uses a simple model of mean-variance capital markets equilibrium with proportional transactions costs to analyze the competition of stock markets for investors. We assume that equity trading is costly and endogenize transactions costs as variables strategically influenced by stock exchanges. Among other things, the model predicts that increasing financial market correlation leads to ...

Decision making under uncertainty is a challenge faced by many decision makers. Stochastic programming is a major tool developed to deal with optimization with uncertainties that has found applications in, e.g. finance, such as asset-liability and bond-portfolio management. Computationally however, many models in stochastic programming remain unsolvable because of overwhelming dimensionality. F...