Currency downside risk and macroeconomic variables
Some currencies persistently move together with the stock market and crash in periods of market downturns or high volatility, while others serve as a “safe haven”. In this paper, I study whether or not countries’ macroeconomic characteristics are systematically related to the market risk of their currencies. I find that the market risk is not random, especially on the downside, and it can be predicted by macroeconomic variables. Moreover, the market risk has increased significantly since the 2000s, and its predictability also increased. The real interest rate has the highest explanatory power in accounting for the cross-section of currency market risk. Currencies of countries with high local real interest rates have high market betas, especially downside betas, while low real interest rate currencies are immune to stock market changes. Nominal interest rates also have some explanatory power, but only to the extent to which they correlate with the real interest rates. Other variables considered seem to be irrelevant.
Carry trades consistently generate high excess returns with high Sharp ratios, but are subject to crash risk. I take a closer look at the link between the carry trade returns and the stock market to understand the risks involved and to determine when and why currency crashes happen. Every period, I sort currencies of developed and emerging economies by their interest rates and form portfolios to diversify the idiosyncratic risk. First, I find a strong negative relationship between portfolio returns and skewness of exchange rate changes. In fact, skewness and coskewness with the stock market have a much greater explanatory power in the cross-section of excess returns than consumption and stock market betas. But separating the market beta into upside and downside betas improves the validity of the CAPM significantly. Downside beta has a much greater explanatory power than upside beta, and it correlates with coskewness almost perfectly. This means that carry trades crash exactly in the worst states of the world, when the stock market goes down. After controlling for country risk, the downside beta premium in the currency market is comparable to that in the stock market and equals 2-4 percentage points p.a. I also find that country risk proxies well for the downside beta and skewness. This suggests that there is unwinding of carry trades and a “flight to quality” when the stock market plunges, and that lower interest rate currencies serve as a “safe haven”. Finally, I estimate even higher downside betas of the top portfolios and I find an even greater explanatory power of the downside beta in the early 2000s. The growing volume of carry activities might have contributed to the closer link between the currency and the stock markets.
World fi nancial crisis and increased volatility of major economic indicators raised attention to the problem of fi nancial risk management in corporations, and to the possibilities of fi nancial derivatives usage for hedging. In perfect markets hedging by means of derivatives allows corporations to mitigate fi nancial risks allowing for minimum costs. Current paper examines factors that restrict usage of derivatives for hedging currency risks by corporations on Russian fi nancial market. It is concluded that on Russian market it is reasonable to use internal facilities as basic method of currency risk management: asset/liability management, regulation of debt
currency structure, diversifi cation, etc. Derivatives should be used in addition to these facilities in very limited volumes for hedging the most predictable sources of risk.
I propose a new factor – the global downside market factor – to explain high returns to carry trades. I show that carry trades have high downside market risk, i.e. they crash systematically in the worst states of the world when the global stock market plunges or when a disaster occurs. The downside market factor explains the returns to currency portfolios sorted by the forward discount better than other factors previously proposed in the literature. GMM estimates of the downside beta premium are similar in the currency and stock markets, statistically significant and close to their theoretical value. High returns to carry trades are fair compensation for their high downside market risk.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.