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This article makes a contribution towards understanding the impact of temperature fluctuations on the economy and financial markets. We present a long-run risks model with temperature related natural disasters. The model simultaneously matches observed temperature and consumption growth dynamics, and key features of financial markets data. We use this model to evaluate the role of temperature in determining asset prices, and to compute utility-based welfare costs as well as dollar costs of insuring against temperature fluctuations. We find that the temperature related utility-costs are about 0.78% of consumption, and the total dollar costs of completely insuring against temperature variation are 2.46% of world GDP. If we allow for temperature-triggered natural disasters to impact growth, insuring against temperature variation raise to 5.47% of world GDP. We show that the same features, long-run risks and recursive-preferences, that account for the risk-free rate and the equity premium puzzles also imply that temperature-related economic costs are important. Our model implies that a rise in global temperature lowers equity valuations and raises risk premiums.

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The paper develops a theory for equity premium around macroeconomic announcements. Stock returns realized around pre-scheduled macroeconomic announcements, such as the employment report and the FOMC statements, account for 55% of the market equity premium during the 1961-2014 period, and virtually 100% of it during the later period of 1997-2014, where more announcement data are available. We provide a characterization theorem for the set of intertemporal preferences that generate a positive announcement premium. Our theory establishes that the announcement premium identifies a significant deviation from expected utility and constitutes an asset market based evidence for a large class of non-expected models that features aversion to "Knightian uncertainty", for example, Gilboa and Schmeidler [30]. We also present a dynamic model to account for the evolution of equity premium around macroeconomic announcements.

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We show that bond risk-premia rise with uncertainty about expected inflation and fall with uncertainty about expected growth; the magnitude of return predictability using these two uncertainty measures is similar to that by multiple yields. Motivated by this evidence, we develop and estimate a long-run risks model with time-varying volatilities of expected growth and inflation. The model simultaneously accounts for bond return predictability and violations of uncovered interest parity in currency markets. We find that preference for early resolution of uncertainty, time-varying volatilities, and non-neutral effects of inflation on growth are important to account for these aspects of asset markets.

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In this paper we show that measures of economic uncertainty (conditional volatility of consumption) predict and are predicted by valuation ratios at long horizons. Further we document that asset valuations drop as economic uncertainty rises that is, financial markets dislike economic uncertainty. Moreover, future earnings growth rates are sharply predicted by current price-earnings ratios. It seems that much of the variation in asset prices can be attributed to fluctuations in economic uncertainty and expected cash-flow growth. This empirical evidence is consistent with the implications of existing parametric general equilibrium models. Hence, the channels of fluctuating economic uncertainty and expected growth seem important for interpreting asset markets.

Capital market --- Financial crises.

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The paper estimates and examines the empirical plausibiltiy of asset pricing models that attempt to explain features of financial markets such as the size of the equity premium and the volatility of the stock market. In one model, the long run risks model of Bansal and Yaron (2004), low frequency movements and time varying uncertainty in aggregate consumption growth are the key channels for understanding asset prices. In another, as typified by Campbell and Cochrane (1999), habit formation, which generates time-varying risk-aversion and consequently time-variation in risk-premia, is the key channel. These models are fitted to data using simulation estimators. Both models are found to fit the data equally well at conventional significance levels, and they can track quite closely a new measure of realized annual volatility. Further scrutiny using a rich array of diagnostics suggests that the long run risk model is preferred.