Rare Disasters and Exchange Rates--论文代写范文精选

极端灾害可能是资产市场风险溢价的重要决定因素，这也使得预测汇率和货币期权之间的联系,总体而言,该模型解释了经典汇率之间的联系,汇率和股票市场波动。下面的paper代写范文进行阐述。

Abstract 
We propose a new model of exchange rates, based on the hypothesis that the possibility of rare but extreme disasters is an important determinant of risk premia in asset markets. The probability of world disasters as well as each country’s exposure to these events is time-varying. This creates joint fluctuations in exchange rates, interest rates, options, and stock markets. The model accounts for a series of major puzzles in exchange rates: excess volatility and exchange rate disconnect, forward premium puzzle and large excess returns of the carry trade, and comovements between stocks and exchange rates. It also makes empirically successful signature predictions regarding the link between exchange rates and telltale signs of disaster risk in currency options.

Introduction 
We propose a new model of exchange rates, based on the hypothesis of Rietz (1988) and Barro (2006) that the possibility of rare but extreme disasters is an important determinant of risk premia in asset markets. The model accounts for a series of major puzzles in exchange rates. It also makes signature predictions about the link between exchange rates and currency options, which are broadly supported empirically. Overall, the model explains classic exchange rate puzzles and more novel links between options, exchange rates and stock market movements. In the model, at any point in time, a world disaster might occur. 

Disasters correspond to bad times – they therefore matter disproportionately for asset prices despite the fact that they occur with a low probability. Countries differ by their riskiness, that is by how much their exchange rate would depreciate if a world disaster were to occur (something that we endogenize in the paper). Because the exchange rate is an asset price whose risk affects its value, relatively riskier countries have more depreciated exchange rates. The probability of world disaster as well as each country’s exposure to these events is timevarying. This creates large fluctuations in exchange rates, which rationalize their apparent “excess volatility”. 

To the extent that perceptions of disaster risk are not perfectly correlated with conventional macroeconomic fundamentals, our disaster economy exhibits an “exchange rate disconnect” (Meese and Rogoff 1983). Relatively risky countries also feature high interest rates, because investors need to be compensated for the risk of exchange rate depreciation in a potential world disaster. This allows the model to account for the forward premium puzzle.1 Indeed, suppose that a country is temporarily risky: it has high interest rates, and its exchange rate is depreciated. As its riskiness reverts to the mean, its exchange rate appreciates. Therefore, the currencies of high interest rate countries appreciate on average. The disaster hypothesis also makes specific predictions about option prices. This paper works them out, and finds that those signature predictions are reasonably well borne out in the data. We view this as encouraging support for the disaster view. 

The starting point is that, in our theory, the exchange rate of a risky country commands high put premia in option markets — as measured by high “risk reversals” (which are the difference in implied volatility between an out-of-the-money put and a symmetric out-of-the-money call). Indeed, investors are willing to pay a high premium to insure themselves against the risk that this exchange rate depreciates in the event of a world disaster. A country’s risk reversal is therefore a reflection of its riskiness. 

Accordingly, the model makes four predictions regarding these put premia (“risk reversals”). First, investing in countries with high risk reversals should have high returns on average. Second, countries with high risk reversals should have high interest rates. Third, when the risk reversal of a country goes up, its currency contemporaneously depreciates. These predictions, and a fourth one detailed below, are broadly consistent with the data.2 The model is very tractable, and we obtain simple and intuitive closed form expressions for the major objects of interest, such as exchange rates, interest rates, carry trade returns, yield curves, forward premium puzzle coefficients, option prices, and stocks.3 To achieve this, we build on the closed-economy model with stochastic intensity of disasters proposed in Gabaix (2012) (Rietz 1988 and Barro 2006 assume a constant intensity of disasters), and use the “linearitygenerating” processes developed in Gabaix (2009). Our framework is also very flexible. 

We show that it is easy to extend the basic model to incorporate several factors and inflation. We calibrate a version of the model and obtain quantitatively realistic values for the quantities of interest, such as the volatility of the exchange rate, the interest rate, the forward premium puzzle, the return of the carry trade, as well as the size and volatility of risk reversals and their link with exchange rate movements and interest rates. The underlying disaster numbers largely rely on Barro and Ursua (2008)’s empirical numbers which imply that rare disasters matter five times as much as they would if agents were risk neutral. As a result, changes in beliefs about disasters translate into meaningful volatility. 

This is why the model yields a sizable volatility which is difficult to obtain with more traditional models (e.g. Obstfeld and Rogoff 1995). In addition, our calibration matches the somewhat puzzling link between stock returns and exchange rate returns. Empirically, there is no correlation between movements in the stock market and the currency of a country. However, the most risky currencies have a positive correlation with world stock returns, while the least risky currencies have a negative correlation. Our calibration replicates these facts. The economics is as follows: when world resilience improves, stock markets have positive returns, and the most risky currencies appreciate vis-avis the least risky currencies. Finally, recent research (Lustig, Roussanov and Verdelhan (2011)) has documented a onefactor structure of currency returns (they call this new factor ). Our proposed calibration matches this pattern. In addition, our model delivers the new prediction that risk reversals of the most risky countries (respectively least risky) should covary negatively (respectively positively) with this common factor. This prediction holds empirically. To sum up, our model delivers the following patterns.(paper代写)

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