Target price forecasts: The roles of the 52-week high price and recent investor sentiment

This paper reveals that in addition to fundamental factors, the 52-week high price and recent investor sentiment play an important role in analysts’ target price formation. Analysts’ forecasts of short-term earnings and long-term earnings growth are shown to be important explanatory variables for target prices; equally, the 52-week high price and recent investor sentiment are also shown to explain target price levels and especially target price biases. Our analysis additionally reveals that analysts place greater weight on these two non-fundamental factors in settings with greater task complexity and to some extent in those with greater resource constraints. Conversely, on balance, the results suggest that this increased reliance does not translate into an increased impact per unit of each non-fundamental factor on forecast bias. Finally, our results show that target prices are useful in predicting future stock returns beyond earnings forecasts and commonly used risk proxies. However, in an internally consistent fashion, the informativeness of target prices for future returns is significantly reduced when greater weight is placed on either the 52-week high or recent investor sentiment in the target price formation process.     

Is heterogeneous capital depreciation important for estimating firm-level productivity? Evidence from Chinese manufacturing firms

This paper contributes to the existing literature on estimating firm-level production functions. Using Chinese manufacturing survey data, we employ the firm-level heterogeneous capital depreciation rate to measure firms’ investment and assess its role using Olley and Pakes (1996) (OP) production function estimation technique. Although there is some ongoing debate on the econometric soundness of the OP technique, we argue quantitatively that the heterogeneous depreciation rate muffles the measurement error associated with the key input demand investment. In our sample, it significantly narrows the gap of total factor productivity (TFP) estimates between the OP technique and a state-of-the-art estimation method that works without investment. We further reveal that the improved performance primarily originates from the dynamic evolution in the distribution of the capital depreciation rate.     

Does global liquidity drive commodity prices?

This paper tackles the question of whether a cross-sectional perspective on monetary policy is capable of explaining movements in global commodity prices. In this vein, we contribute to the rich literature on global liquidity in two different ways: on the one hand, to achieve a global series in terms of common monetary policy shocks, we propose a distinction between common and idiosyncratic factors across economies, as proposed by Bai and Ng (2004). Our second innovation stems from the consideration of a Markov-switching vector error correction model when analyzing time-varying short-run dynamics. Having identified the long-run structure which includes a proportional relationship between commodity prices and global liquidity in the first step, our results indeed show that the impact of a global liquidity measure on different commodity prices is significant and varies over time. One regime approximately accounts for times where commodity prices significantly adjust to disequilibria, while the second regime is characterized by either a weak or no commodity price adjustment. The fact that global liquidity also reacts to disequilibria in a specific regime demonstrates the two-way causality between monetary policy and commodity prices.     

冻结造孔防斜保直实践与应用

冻结造孔施工过程中,控制井斜靶域半径问题是冻结造孔的关键点。以陕西麟北煤业开发有限责任公司园子沟煤矿冻结造孔施工为例,本文着重分析冻结造孔施工中靶域半径控制及钻孔防斜保直、测斜、定向技术实践应用。     

Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting

This paper compares the forecast performance of automatic leading indicators (ALIs) and macroeconometric structural models (MESMs) commonly used by non-academic macroeconomists. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and the Philippines. ALIs are found to outperform MESMs for one-period-ahead forecasts, but this superiority disappears as the forecast horizon increases. It is also found that ALIs involve greater uncertainty in choosing indicators, mixing data frequencies and utilizing unrestricted VARs. Two ways of reducing the uncertainty are explored: (i) give theory priority in choosing indicators, and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the VARs by means of the general-to-specific modeling procedure.     

如何解决传媒人才短缺难题

当前,传媒业的激烈竞争实质上是人才的竞争。人才是传媒成败的“牛耳”。解决人才短缺问题是着眼向外,还是着手向内？不排除向外,但主要应下力激活内部人力资源。这样做,可以防止造成新的人才浪费,可以避免爆发恶性人才大战,从而有利于传媒业的和谐发展。那种过份“引进”、忽视“挖潜”的做法是不可取的。     

Bartlett correction to the likelihood ratio test for MCAR with two‐step monotone sample

Assuming that two‐step monotone missing data is drawn from a multivariate normal population, this paper derives the Bartlett‐type correction to the likelihood ratio test for missing completely at random (MCAR), which plays an important role in the statistical analysis of incomplete datasets. The advantages of our approach are confirmed in Monte Carlo simulations. Our correction drastically improved the accuracy of the type I error in Little's (1988, Journal of the American Statistical Association, 83 , 1198–1202) test for MCAR and performed well even on moderate sample sizes.     

Does Integrated Reporting Matter to the Capital Market?

Integrated reporting (<IR>) is an emerging international corporate reporting initiative to address limitations to extant corporate reporting approaches, which are commonly criticized for being both voluminous and disjointed. While <IR> is gaining in popularity, current momentum has been limited due to a lack of clear evidence of its benefits. Utilizing the most suitable setting currently available, being discretionary disclosures made by listed companies on the Johannesburg Stock Exchange, this study provides evidence that analyst forecast error reduces as a company's level of alignment with the <IR> framework increases. Further, the improved alignment is associated with a subsequent reduction in the cost of equity capital for certain reporting companies. The results are obtained after controlling for factors relating to financial transparency and the issuance of standalone non‐financial reports, which suggests that <IR> is providing incrementally useful information to the capital market over and above existing reporting mechanisms.     

Hedging of Asian options under exponential Lévy models: computation and performance

In this paper we consider the problem of hedging an arithmetic Asian option with discrete monitoring in an exponential Lévy model by deriving backward recursive integrals for the price sensitivities of the option. The procedure is applied to the analysis of the performance of the delta and delta–gamma hedges in an incomplete market; particular attention is paid to the hedging error and the impact of model error on the quality of the chosen hedging strategy. The numerical analysis shows the impact of jump risk on the hedging error of the option position, and the importance of including traded options in the hedging portfolio for the reduction of this risk.     

Stable Asymptotics for M‐estimators

We review some first‐order and higher‐order asymptotic techniques for M‐estimators, and we study their stability in the presence of data contaminations. We show that the estimating function (ψ) and its derivative with respect to the parameter play a central role. We discuss in detail the first‐order Gaussian density approximation, saddlepoint density approximation, saddlepoint test, tail area approximation via the Lugannani–Rice formula and empirical saddlepoint density approximation (a technique related to the empirical likelihood method). For all these asymptotics, we show that a bounded ψ (in the Euclidean norm) and a bounded (e.g. in the Frobenius norm) yield stable inference in the presence of data contamination. We motivate and illustrate our findings by theoretical and numerical examples about the benchmark case of one‐dimensional location model.