Are USDA reports still news to changing crop markets?

This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market “surprise,” is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.     

Covariance breakdowns and connectedness of crude oil futures markets with non-synchronous data

ABSTRACT

This article identifies the breakdowns in the covariance of three benchmark crude oil futures markets (WTI, Brent and Dubai) and investigates the changes of market connectedness across the breakdown periods. As the crude oil futures are traded in different regions, this article eliminates the non-synchronous trading data by employing the Vector Moving Average structure and the Bayesian data augmentation approach, which keeps the integrity of original data without changing its properties. The results show that there are significant breaks in the covariance structure of crude oil futures markets. The breakdown periods are consistent with the periods when the market volatilities are at high level and the returns are volatile. The changes of market connectedness are independent of the covariance states, which supports the globalization hypothesis for the crude oil market. The results also suggest that there is more information flow out of the WTI than to the WTI during the sample period, particularly during the breakdown periods in 2008–2009.     

VIX term structure and VIX futures pricing with realized volatility

Using an extended LHARG model proposed by Majewski et al. (2015, J Econ, 187, 521–531), we derive the closed-form pricing formulas for both the Chicago Board Options Exchange VIX term structure and VIX futures with different maturities. Our empirical results suggest that the quarterly and yearly components of lagged realized volatility should be added into the model to capture the long-term volatility dynamics. By using the realized volatility based on high-frequency data, the proposed model provides superior pricing performance compared with the classic Heston–Nandi GARCH model under a variance-dependent pricing kernel, both in-sample and out-of-sample. The improvement is more pronounced during high volatility periods.     

关于编写期货投资分析实验教材的思考

该文主要介绍了期货投资分析实验教材编写的意义、框架和思路,以及该实验教材在编就后所体现出的特点,和我们在编写过程中的一些思考。     

论法律不完备性与政府介入期货市场

在期货市场上，法律不完备性问题表现得较为突出，法律对于侵害行为的阻吓作用非常有限、期货市场法律的不完备性，主要取决于期货市场的特点和性质。政府采取相关的监管方式管理期货市场非常必要，监管的介入需要满足标准化和损害（外部性）足够高的条件。政府管理期货市场立法和法院执法的作用不可或缺，但更主要的是采用监管的方式。     

Are Fundamentals Priced in the Bond Market?*

To date, the discussion of the Lev and Thiagarajan 1993 fundamentals in the prior literature has been exclusively in the context of the stock market. Our study is the first to examine the value‐relevance of these fundamentals for default risk. By focusing on the market for new bond issues, we examine the value‐relevance of the fundamental score using expected rather than realized returns. Also, by focusing on the bond market we provide a different perspective than that brought by prior studies relying solely on stock prices. We find the fundamentals to be priced in the market for new bond issues as indicators of expected future earnings and to be value‐relevant in enabling the market to discern differences in bond credit quality over and above the published bond ratings.     

Pre-Harvest Price Expectations for Corn: The Information Content of USDA Reports and New Crop Futures

This article examines the puzzle of why futures prices continue to react to USDA crop reports despite the fact that reports appear to be no longer "newsworthy," that is, provide no better production estimates than private forecasts. The information value of reports is measured in terms of their influence on rational agents' harvest-time corn price expectations, which are uncovered using a Hamilton-type modeling approach. Results show that reports are still "newsworthy," as they would contribute to agents' price expectations if released a day early. Thus futures price reactions, which closely reflect price expectations, are rational and consistent with efficient markets hypothesis.     

International interest rates and US monetary policy announcements: Evidence from Hong Kong and Singapore

This paper investigates the responses of market interest rates to US monetary policy announcements for the US and two emerging economies, Hong Kong and Singapore which are similar on many respects but have experienced opposite exchange rate regimes in the last twenty years. Our results, based on market expectations extracted from federal fund futures rates, document that FOMC announcements significantly affect the term structure of interest rate in the US and both Asian countries. Further, international interest rate differentials around FOMC meeting dates tend to be negative for short maturities with the impact gradually dissipating as bond maturity increases. Finally, for the case of Singapore, we find that domestic interest rates react to both external and domestic monetary policy announcements with a magnitude that is larger over the full bond maturity spectrum for domestic announcements. These results are robust to time-varying futures risk premia and alternative measures of interest rates expectations.     

Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.