This paper studies the full equilibrium dynamics of an economy with financial frictions. Due to highly non-linear amplification effects, the economy is prone to instability and occasionally enters volatile episodes. Risk is endogenous and asset price correlations are high in down turns. In an environment of low exogenous risk experts assume higher leverage making the system more prone to systemic volatility spikes- a volatility paradox. Securitization and derivatives contracts leads to better sharing of exogenous risk but to higher endogenous systemic risk. Financial experts may impose a negative externality on each other by not maintaining adequate capital cushion.

In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk neutral dynamics for a general class of multivariate heteroskedastic models, and we provide a feasible way to price options in this framework. Our framework can be used irrespective of the assumed underlying distribution and dynamics, and it nests several important special cases. We provide an application to options on the minimum of two indices. Our results show that not only is correlation important for these options but so is allowing this correlation to be dynamic. Moreover, we show that for the general model exposure to correlation risk carries an important premium, and when this is neglected option prices are estimated with errors. Finally, we show that when neglecting the non-Gaussian features of the data, option prices are also estimated with large errors.

Our objective in this paper is to examine whether one can use option-implied information to improve the selection of portfolios with a large number of stocks, and to document which aspects of option-implied information are most useful for improving their out-of-sample performance. Portfolio performance is measured in terms of four metrics: volatility, Sharpe ratio, certainty-equivalent return, and turnover. Our empirical evidence shows that, while using option-implied volatility and correlation does not improve significantly the portfolio volatility, Sharpe ratio, and certainty-equivalent return, exploiting information contained in the volatility risk premium and option-implied skewness increases substantially both the Sharpe ratio and certainty-equivalent return, although this is accompanied by higher turnover. And, the volatility risk premium and option-implied skewness help improve not just the performance of mean-variance portfolios, but also the performance of parametric portfolios developed in Brandt, Santa-Clara, and Valkanov (2009).

We decompose aggregate market variance into an average correlation component and an average variance component. Only the latter commands a negative price of risk in the cross section of portfolios sorted by idiosyncratic volatility. Portfolios with high (low) idiosyncratic volatility relative to the Fama-French (1993) model have positive (negative) exposures to innovations in average stock variance and therefore lower (higher) expected returns. These two findings explain the idiosyncratic volatility puzzle of Ang et al. (2006, 2009). The factor related to innovations in average variance also reduces the pricing errors of book-to-market and momentum portfolios relative to the Fama-French (1993) model. (JEL G12) In an influential study, Ang, Hodrick, Xing, and Zhang (2006, 2009; AHXZ hereafter) show that stocks with high idiosyncratic risk, defined as the standard deviation of the residuals from the Fama-French (1993) model, have anomalously low future returns.1 This finding is puzzling in light of theories that suggest that idiosyncratic volatility (denoted as IV) should be irrelevant or positively related to expected returns.2 If a factor is missing from the Fama-French model, the sensitivity of stocks to the missing factor times the movement in the missing factor will show up in the residuals of the model. Firms with greater sensitivities to the missing factor We thank Geert Bekaert (editor), two anonymous referees, and seminar participants at the Norwegian Business School (BI) and Texas A&M University for many valuable comments and suggestions. Chen acknowledges financial support from a Nanyang Technological University Start-up Grant. Send correspondence to Ralitsa

∗We are grateful to Mike Chernov, Francisco Gomes and the seminar participants at London Business School for helpful comments. All errors are our responsibility. Dynamic Hedging in Incomplete Markets: A Simple Solution Despite much work on hedging in incomplete markets, the literature still lacks tractable dynamic hedges in plausible environments. In this article, we provide a simple solution to this problem in a general incomplete-market economy in which a hedger, guided by the traditional minimum-variance criterion, aims at reducing the risk of a non-tradable asset. We derive fully analytical optimal hedges and demonstrate that they can easily be computed in various stochastic environments. Our dynamic hedges preserve the simple structure of complete-market perfect hedges and are in terms of generalized “Greeks, ” familiar in risk management applications, as well as retaining the intuitive features of their static counterparts. We obtain our time-consistent hedges by dynamic programming, while the extant literature characterizes either static or myopic hedges, or dynamic ones that minimize the variance criterion at an initial date and from which the hedger may deviate unless she can pre-commit to follow them. We demonstrate that our dynamically optimal hedges typically outperform their static and myopic counterparts under plausible economic environments. We also show that our results can be applied to portfolio management with tracking-error.

Abstract We formally compare two versions of the market variance risk premium (VRP) measured in the equity and option markets. Both VRPs follow common patterns and respond similarly to changes in volatility and economic conditions. However, we reject the null hypothesis that they are identical and …nd that their di¤erence is strongly related to measures of the …nancial standing of intermediaries. These results shed new light on the information content of the VRP, suggest the presence of market frictions between the two markets, and are consistent with the key role played by intermediaries in setting option prices. JEL classi…cation: G12, G13, C58

Meeting of the European Accounting Association, the 8th INFINITI Conference on International Finance, and the XVII Foro de Finanzas, IESE. We are especially grateful for the constructive and helpful comments of Juan Ángel Lafuente and Enrique Sentana, the editor, and two anonymous referees that substantially improved the contents of the paper. We assume full responsibility for any remaining errors. 2

In this paper, we find that FX correlationis a key driverof FX risk premia and carrytrade returns. We show that the correlation risk premium, defined as the difference between the risk-neutral and objective measure correlation is large (15 % per year) and highly time-varying. Sorting currencies according to their exposure with correlation innovations yields portfolios with attractive risk and return characteristics. Moreover, high (low) interest rate currencies have negative (positive) loadings on the correlation risk factor. To addressourempiricalfindings, weconsideramulti-countrygeneralequilibriummodel with time-varying risk aversiongenerated by external habit preferences. In the model, currency risk premia compensate for exposure to global risk aversion, defined as a weighted average of country risk aversions. We show that high global risk aversion is associated with high conditionalexchangeratesecondmoments, so currenciesthat hedgeagainstadverseglobal risk aversion fluctuations can be empirically identified as currencies that appreciate when conditional exchange rate second moments are high. If the precautionary savings motive is sufficiently strong, the model can also address the forward premium puzzle, as high

I would like to thank Dr. Francis Boabang for all his help and guide in accomplishing my research project. I would also like to thank my truly friend Cunzhi Han for giving me advice to deal with the data problem. Finally, I would like to give my deepest thank to my family and friends for their supportiveness, encouragement and inspiration. 1 The impact of fundamental accounting signals on option returns

Abstract We find that option returns are significantly lower over nontrading periods, the vast majority of which are weekends. Our evidence suggests that nontrading returns cannot be explained by risk, but are rather the result of widespread and highly persistent option mispricing driven by the incorrect treatment of stock return variance during periods of market closure. The size of the effect implies that the broad spectrum of finance research involving option prices should account for nontrading effects. Our study further suggests how alternative industry practices could improve the efficiency of option markets in a meaningful way.