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n this paper we analyze an economy with two heterogeneous investors who both exhibit misspecified filtering models for the unobservable expected growth rate of the aggregated dividend. A key result of our analysis with respect to long-run investor survival is that there are degrees of model misspecification on the part of one investor for which there is no compensation by the other investor's deficiency. The main finding with respect to the asset pricing properties of our model is that the two dimensions of asset pricing and survival are basically independent. In scenarios when the investors are more similar with respect to their expected consumption shares, return volatilities can nevertheless be higher than in cases when they are very different.
We propose a long-run risk model with stochastic volatility, a time-varying mean reversion level of volatility, and jumps in the state variables. The special feature of our model is that the jump intensity is not affine in the conditional variance but driven by a separate process. We show that this separation of jump risk from volatility risk is needed to match the empirically weak link between the level and the slope of the implied volatility smile for S&P 500 options.
This paper analyzes the equilibrium pricing implications of contagion risk in a Lucas-tree economy with recursive preferences and jumps. We introduce a new economic channel allowing for the possibility that endowment shocks simultaneously trigger a regime shift to a bad economic state. We document that these contagious jumps have far-reaching asset pricing implications. The risk premium for such shocks is superadditive, i.e. it is 2.5\% larger than the sum of the risk premia for pure endowment shocks and regime switches. Moreover, contagion risk reduces the risk-free rate by around 0.5\%. We also derive semiclosed-form solutions for the wealth-consumption ratio and the price-dividend ratios in an economy with two Lucas trees and analyze cross-sectional effects of contagion risk qualitatively. We find that heterogeneity among the assets with respect to contagion risk can increase risk premia disproportionately. In particular, big assets with a large exposure to contagious shocks carry significantly higher risk premia.
There has been a considerable debate about whether disaster models can rationalize the equity premium puzzle. This is because empirically disasters are not single extreme events, but long-lasting periods in which moderate negative consumption growth realizations cluster. Our paper proposes a novel way to explain this stylized fact. By allowing for consumption drops that can spark an economic crisis, we introduce a new economic channel that combines long-run and short-run risk. First, we document that our model can match consumption data of several countries. Second, it generates a large equity risk premium even if consumption drops are of moderate size.
We study the effects of market incompleteness on speculation, investor survival, and asset pricing moments, when investors disagree about the likelihood of jumps and have recursive preferences. We consider two models. In a model with jumps in aggregate consumption, incompleteness barely matters, since the consumption claim resembles an insurance product against jump risk and effectively reproduces approximate spanning. In a long-run risk model with jumps in the long-run growth rate, market incompleteness affects speculation, and investor survival. Jump and diffusive risks are more balanced regarding their importance and, therefore, the consumption claim cannot reproduce approximate spanning.
We analyze the implications of the structure of a network for asset prices in a general equilibrium model. Networks are represented via self- and mutually exciting jump processes, and the representative agent has Epstein-Zin preferences. Our approach provides a exible and tractable unifying foundation for asset pricing in networks. The model endogenously generates results in accordance with, e.g., the robust-yetfragile feature of financial networks shown in Acemoglu, Ozdaglar, and Tahbaz-Salehi (2014) and the positive centrality premium documented in Ahern (2013). We also show that models with simpler preference assumptions cannot generate all these findings simultaneously.
The term 'financialization' describes the phenomenon that commodity contracts are traded for purely financial reasons and not for motives rooted in the real economy. Recently, financialization has been made responsible for causing adverse welfare effects especially for low-income and low-wealth agents, who have to spend a large share of their income for commodity consumption and cannot participate in financial markets. In this paper we study the effect of financial speculation on commodity prices in a heterogeneous agent production economy with an agricultural and an industrial producer, a financial speculator, and a commodity consumer. While access to financial markets is always beneficial for the participating agents, since it allows them to reduce their consumption volatility, it has a decisive effect with respect to overall welfare effects who can trade with whom (but not so much what types of instruments can be traded).
We analyze the equilibrium in a two-tree (sector) economy with two regimes. The output of each tree is driven by a jump-diffusion process, and a downward jump in one sector of the economy can (but need not) trigger a shift to a regime where the likelihood of future jumps is generally higher. Furthermore, the true regime is unobservable, so that the representative Epstein-Zin investor has to extract the probability of being in a certain regime from the data. These two channels help us to match the stylized facts of countercyclical and excessive return volatilities and correlations between sectors. Moreover, the model reproduces the predictability of stock returns in the data without generating consumption growth predictability. The uncertainty about the state also reduces the slope of the term structure of equity. We document that heterogeneity between the two sectors with respect to shock propagation risk can lead to highly persistent aggregate price-dividend ratios. Finally, the possibility of jumps in one sector triggering higher overall jump probabilities boosts jump risk premia while uncertainty about the regime is the reason for sizeable diffusive risk premia.
We consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on quantities known only in the true model. We apply our method to a calibrated affine model. Our findings are threefold: Jumps matter more, i.e. our approximation is less accurate, if (i) the expected jump size or (ii) the jump intensity is large. Fixing the average impact of jumps, we find that (iii) rare, but severe jumps matter more than frequent, but small jumps.
We consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on results from the true model. We apply our method to a calibrated affine model and fine that relative wealth equivalent losses are below 1.16% if the jump size is stochastic and below 1% if the jump size is constant and γ ≥ 5. We perform robustness checks for various levels of risk-aversion, expected jump size, and jump intensity.