What determines the long-term correlation between oil prices and exchange rates?

In this study, we obtain the long-term correlation between oil prices and exchange rates by employing the dynamic conditional correlation-mixed data sampling (DCC-MIDAS) model. We then identify the factors that influence the long-term correlation using panel data analysis. We find that the long-run correlations between oil prices and exchange rates are negative for all oil-exchange rate markets except Japan. We also find that both inflation and term spread have negative effects, while the risk-free interest rate has a positive effect on the long-term correlation between oil prices and exchange rates. Importantly, the empirical results show that an increase in inflation will significantly damage the real value of the currency itself.     

Comprehensive Protection,Winners and Losers: A Sectoral Analysis of the Mexican Economy 1970–87

Sectors that have the highest effective protection index should have a greater advantage within an economy than those that have lower index values, and should be the likely winners over a period of years. However, this proposition may not hold, as a result of limitations in the indexes' construction, namely, not considering imperfect structures, the inclusion of non-tradables and intersectoral simultaneity. To overcome these limita-tions, a comprehensive protection (CP) index is proposed. It is based on the Leontief model to calculate market prices and uses a class of equilibrium price models developed on labor value theories. The CP index is then used in a sectoral analysis of the Mexican economy to estimate which sectors are likely to have been winners and which losers. The results of the analysis showed consistency with the instrumentation of the Mexican economic policy. The study concludes that the index formulated here is both theoretically and empirically superior to alternative protection indexes.     

Dynamic interaction of risk–return trade-offs between oil market and China’s stock market: An analysis from the risk preferences perspective

The risk–return trade-off refers to the compensation required by investors for bearing risks, which can be viewed as the risk preference of investors in a market. The current study investigates the dynamic interdependence of risk–return trade-offs between China’s stock market and the crude oil market from the perspective of risk preference of investors, which is designed to explore the transmission process of investors’ risk preference in both markets. Specifically, this study applies the time-varying parameter GARCH-M model, namely TVP-GARCH-M model, to characterize the time-dependent risk–return trade-offs (investors’ risk preferences) in the crude oil and China’s stock markets, then examines their relationship through Granger causality tests. Results show that a variation in risk preferences of the oil market investors can dramatically cause a variation in risk preferences of the Chinese stock market investors, while the risk preference of investors in the Chinese stock market does not lead to that in the crude oil market, which is in accordance with expectations. The dynamic effect of investors’ risk appetite in the crude oil market is further examined by the TVP-VAR model. The findings of this work suggest that there generally exists a positive impact of investors’ risk preference in the oil market and that the effect is time-varying to a greater degree during the short and medium term. Moreover, responses of the Chinese stock market investors’ risk preference were more significant during the 2008 financial crisis. Additionally, the empirical results remain robust when applying alternative crude oil prices and China’s stock prices.     

PICKING WINNERS? A SURVEY OF THE MEAN REVERSION AND OVERREACTION OF STOCK PRICES LITERATURE

Abstract. This paper surveys, and suggests a possible synthesis of, two growing literatures concerning stock market anomalies. The first concentrates on identifying contrarian trading rules, capable of generating profits, when securities are segregated on the basis of past earnings, or share price performance. The other simply examines the time-series properties of security prices to find evidence of low-frequency negative autocorrelation, or 'meanreversion'. We seek to articulate the points of interdependence between the two strands of research and the problems of joint hypothesis testing implied by the close relation between 'Overreaction'and 'mean-reversion'tests.     

The stock–bond comovements and cross-market trading

We propose an asset pricing model with heterogeneous agents allocating capital to the stock and bond markets to optimize their portfolios, utilizing the dynamic interaction between the two markets. While some agents focus on the stock market and have more expertise in it, the others specialize in the bond market. Based on their comparative advantages in a particular market, heterogeneous agents constantly revise their investment portfolios by taking into account the time-varying stock–bond return comovements and the changing market conditions. Agents׳ collective investment behavior shapes the stock–bond interlinkage, which feedbacks on their subsequent capital allocations. Using monthly US stock and bond data from January 1990 to June 2014, we estimate the vector autoregression model with threshold and Markov switching mechanisms. We find evidence in support of flight-to-quality and show that it is mainly driven by the technical traders who actively sell stocks and buy bonds during periods of high market uncertainty.     

The impact of individual and institutional investor sentiment on the market price of risk

We examine the effect of individual and institutional investor sentiment on the market price of risk derived from DJIA and S&P500 index returns. Consistent with behavioral asset pricing models, we find significant positive response of rational sentiment suggesting greater incentive for rational investors to engage in arbitrage when the compensation for taking risk is greater. Further, an increase in irrational optimism leads to a significant downward movement, but an increase in rational sentiment does not lead to a significant change market price of risk. These results are robust for both market indexes, DJIA and S&P500 and for both individual and institutional investor sentiment.     

汇率预期、外汇供给与外汇储备

基于货币资产组合思想和外汇储备供求理论,本文综合运用理论和实证的研究方法分析了汇率预期、外汇供给和外汇储备三者之间的关系。理论研究发现:直接标价法表示的汇率预期波动对非国际货币发行国的外汇供给具有反向影响,而且这种反向影响随着预期汇率大小的不同具有分段特征;为了维持汇率的相对稳定,外汇供给增加的冲击会导致非国际货币发行国的外汇储备增加,但即期汇率的变化方向并不确定;总体而言,预期汇率波动对非国际货币发行国外汇储备具有反向影响。基于中国数据的实证研究很好地支持了理论分析的结论。     

Pricing behavior of exchange traded funds

We attempt to determine whether characteristics found to be effective indicators of individual stock price performance are effective indicators of exchange traded fund (ETF) price performance. Specifically, we test the performance of investing strategies based on separately categorizing ETFs into deciles according to size, trading volume, and momentum. When analyzing the entire sample, we find that the indicators can effectively signal differences in future performance. However, the indicators appear to be indirect proxies for the types of ETFs (broad-based, sector, or international). When we isolate each type of ETF, the indicators are not as effective. The indicators are not as useful for signaling unusual stock price performance of ETFs as they have been for individual stocks. We attribute the distinctly different results found here for ETFs to the unusual characteristics of ETFs that distinguish them from individual stocks. Investing strategies that rely on these indicators for selecting individual stocks may be indirectly driven by stock-specific fundamentals. However, fundamentals are not as meaningful for stock indexes (represented by ETFs) as for individual stocks.