The market price of risk of the variance term structure

In this paper I examine the market price of risk of the variance term structure. To this end, the S&P 500 option implied variance term structure is used as a proxy for aggregate variance risk. Principal component analysis shows that time variation in the variance term structure over the 1996–2012 period can be explained mainly by two factors which capture changes in the level and slope. The market price of risk of each factor is estimated in the cross-section of stock returns. The slope of the variance term structure is the most significant factor in the cross-section of stocks returns and carries a negative risk premium. The slope factor has also some predictive ability over long horizon equity returns.     

Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

The effects of capacity reduction policy under the interest rate peg in China

Capacity reduction has been a recurrent theme in China's economic policy. The central government takes various administrative measures to remove excess capacity, accumulated mainly due to underpriced production factors and distorted incentives. I evaluate the de-capacity policy in a series of models and prove that its effects depend critically on its persistence and monetary policy regime. Under an interest rate peg, a transient policy that changes markup temporarily is ineffective and even expansionary, whereas a persistent policy is effective due to a negative wealth effect. A permanent de-capacity policy can lead to over-reactions in macro variables because the interest rate peg adds positive feedback to the economy. Therefore, the de-capacity policy has greater uncertainty under the interest rate peg. As a policy tool, it easily deviates from its target and brings about excessive volatility. However, long-run price stability and a gradually advanced de-capacity policy are conducive to the achievement of policy targets.     

路基稳定性数值分析

本文通过对常见的路基稳定性分析案例进行强度折减法的数值分析,为进一步研究这一方法在路基稳定性分析中的应用奠定基础。     

Pure meat – Public perceptions of risk reduction strategies in meat production

Experience has shown that both the assessment and implementation of new technologies in food production are challenged by negative assessments of the technologies by the public. This article seeks to deepen our understanding of the concerns that may underlie negative attitudes to various kinds of risk reduction strategy in meat production, with the aim of distinguishing between forms of risk reduction in terms of their acceptability. The paper reports the result of a focus-group study. Six focus groups with Danish citizens (N: 5–9) were conducted during May 2006. The design of the groups took a bottom-up approach and included elements of meat quality, meat safety and risk reduction strategies. The study shows the dilemma risk reduction presents to members of the public. On the one hand, people want safe meat; on the other, the study showed that with the exception of hygiene practices, people generally have an aversion to risk reduction strategies. Some variation was found, however, in the rejection of the strategies. Thus, more acceptable strategies are characterised by a low degree of technological interference, and by being close to the consumer’s experience in everyday life and/or familiar to the participants’ picture of meat production. It is also important that the strategy does not alter the quality of the end-product (meat) in an unfavourable way. The implications of the results and the inherent dilemma for meat safety policy formation are discussed.     

Auction winning,social dynamics and non-compliance in a payment for ecosystem services scheme in Indonesia

Conservation auctions for payment for ecosystem services (PES) are useful to identify the levels of incentives that will cover the opportunity costs of farmers supplying ecosystem services. Although auctions are increasingly used for allocation in PES schemes, the factors that lead to their successful implementation and eventual environmental outcomes are poorly understood in developing countries. We investigated the socio-economic and institutional contexts that led to smallholders' auction winning and eventual compliance using linear mixed-effects models, and post-auction and post-contract surveys. We employed a case study of a conservation contract preceded by a sealed-bid, multiple round, uniform price auction for watershed services from coffee farmers in Lampung, Indonesia. The auction participants presented low education levels, low asset endowments and small plot sizes. The study obtained evidence that farmers with larger plot areas were more likely to win the contracts, suggesting economies of scale. Most farmers considered the auction a fair self-selection mechanism to allocate contracts where allocation was not influenced by power or social rank. Non-compliance was associated with labor availability constraints, short duration of land ownership and existence of previous conservation applications, suggesting lax of capability to invest in applying conservation agriculture. Final bids were however not good predictors of compliance, among other factors, calling into question the potential of auctions to elicit the actual incentive from the farmers. Ensuring that farmers understand the purposes of auctions for effective contract allocation beyond a mere game and identifying farmers that might encounter difficulties fulfilling the contract could increase the likelihood that such a PES scheme would be successful.     

CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.     

Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

This paper contributes to the nascent literature on nowcasting and forecasting GDP in emerging market economies using big data methods. This is done by analyzing the usefulness of various dimension-reduction, machine learning and shrinkage methods, including sparse principal component analysis (SPCA), the elastic net, the least absolute shrinkage operator, and least angle regression when constructing predictions using latent global macroeconomic and financial factors (diffusion indexes) in a dynamic factor model (DFM). We also utilize a judgmental dimension-reduction method called the Bloomberg Relevance Index (BRI), which is an index that assigns a measure of importance to each variable in a dataset depending on the variable’s usage by market participants. Our empirical analysis shows that, when specified using dimension-reduction methods (particularly BRI and SPCA), DFMs yield superior predictions relative to both benchmark linear econometric models and simple DFMs. Moreover, global financial and macroeconomic (business cycle) diffusion indexes constructed using targeted predictors are found to be important in four of the five emerging market economies that we study (Brazil, Mexico, South Africa, and Turkey). These findings point to the importance of spillover effects across emerging market economies, and underscore the significance of characterizing such linkages parsimoniously when utilizing high-dimensional global datasets.     

Unrelated question model with two decks of cards

In this paper, we propose a new unrelated question model for estimating the prevalence of a sensitive characteristic within a population by utilizing two decks of cards. The resultant estimator is then compared to its competitors as to efficiency and as to protection of respondents. A real data application analyzing e-cigarette use among college students is considered.     

不完备信息系统辐射源威胁等级判定

针对不完备信息系统条件下的辐射源威胁等级判定问题，提出了一种基于改进容差关系粗糙集（ITR-RS）的不完备信息系统辐射源威胁等级判定方法。该方法将粗糙集中的不完备信息系统理论引入辐射源威胁等级判定中，并构建一套完备的决策规则提取模型。此外，利用辨识矩阵实现对属性的约简，在降低系统所需处理数据量的同时，提高了算法的实时性；在容差关系粗糙集的基础上，提出一种改进的容差关系，在属性主、客权重相结合的基础上引入阈值来划分加权阈值容差类，得到更为合理、准确的决策规则。仿真试验及分析表明，与经典RS算法相比，所提算法的威胁等级判定正确率提高了23%，可用于信息系统不完备条件下的辐射源威胁等级判定。