ARBITRAGE BOUNDS FOR PRICES OF WEIGHTED VARIANCE SWAPS

We develop a theory of robust pricing and hedging of a weighted variance swap given market prices for a finite number of co‐maturing put options. We assume the put option prices do not admit arbitrage and deduce no‐arbitrage bounds on the weighted variance swap along with super‐ and sub‐replicating strategies that enforce them. We find that market quotes for variance swaps are surprisingly close to the model‐free lower bounds we determine. We solve the problem by transforming it into an analogous question for a European option with a convex payoff. The lower bound becomes a problem in semi‐infinite linear programming which we solve in detail. The upper bound is explicit. We work in a model‐independent and probability‐free setup. In particular, we use and extend Föllmer's pathwise stochastic calculus. Appropriate notions of arbitrage and admissibility are introduced. This allows us to establish the usual hedging relation between the variance swap and the “log contract” and similar connections for weighted variance swaps. Our results take the form of a FTAP: we show that the absence of (weak) arbitrage is equivalent to the existence of a classical model which reproduces the observed prices via risk‐neutral expectations of discounted payoffs.     

一种适用于机场场面监视MLAT系统的状态模型

根据直角坐标系的目标运动模型和无源多点时差定位系统(MLAT)的特点,推导出了一种到达时间差（TDOA)状态模型方程,并基于该模型方程,设计了一种TDOA跟踪滤波器。与传统TDOA状态模型方程相比,所推导出的状态模型方程和滤波器不但能提高TDOA的估计精度,还可更有效地消除非视距（NLOS）成分。仿真和实测数据证实了所推导状态模型方程和所设计跟踪滤波器的有效性。     

Turbo码的Taylor-Log_MAP译码算法

以Turbo码基本理论和算法为基础,依据无线信息传输的实际要求和Taylor级数的基 本原理,提出了一种Turbo码的Taylor-Log-MAP高效译码算法。该算法对基本的Log-MAP 算法中K运算利用Taylor级数进行展开,针对实际的信道需求对展开式进行截断,实现了Tur bo码 的最佳译码。与传统的对数域最大后验概率译码算法相比,该算法基本保持了优良的译码 性能,同时避免了复杂的对数运算,减小了运算量。仿真结果表明,与现 有的RS码性能相比,使用Turbo码可以获取5 dB的信噪比增益。     

协同通信系统中差分调制在Rayleigh衰落信道中的误码性能分析

根据源-中继-目的节点链路的等效信噪比模型,推导了检测传送和选择检测传送两种 协议下目的节点瞬时信噪比的概率密度函数和特征函数,基于此推导了协同DMPSK调制近似 误符号率的闭合表达式。推导结果不含积分表达式,方便计算,为系统设计和功率分配提供 了理论基础。最后通过仿真验证了推导结果的正确性。     

Dynamics of Urban Residential Property Prices— A Case Study of the Manhattan Market

In a multivariate vector autoregression framework, this paper investigates the weak efficiency of the urban residential real estate market and the cause of weak efficiency. An error correction model is used to estimate long-term relationships among apartment prices and adjustment speed from disequilibrium to equilibrium. Based on a unique dataset of the Manhattan market, the efficiency of this market, seasonal stationarity of property prices, and the weak exogeneity of leading sub-markets are studied. Our results indicate that, in a market of less heterogeneity and higher transaction volumes, the weak efficiency hypothesis is rejected as in previous studies. This result implies that heterogeneity and lack of transaction information may not be the direct source of market inefficiency. Meanwhile, it is found that there are stable long-term relations among prices of different sub-markets. Interestingly, the price of one-bedroom co-operatives (co-op) is weakly exogenous. This implies that the starting co-op for most home buyers in urban areas is a leading indicator of the entire market, which contradicts the claim that high-end luxury co-op leads the market.     

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.     

Hedging derivative securities with genetic programming

One of the most recent applications of GP to finance is to use genetic programming to derive option pricing formulas. Earlier studies take the Black–Scholes model as the true model and use the artificial data generated by it to train and to test GP. The aim of this paper is to provide some initial evidence of the empirical relevance of GP to option pricing. By using the real data from S&P 500 index options, we train and test our GP by distinguishing the case in-the-money from the case out-of-the-money. Unlike most empirical studies, we do not evaluate the performance of GP in terms of its pricing accuracy. Instead, the derived GP tree is compared with the Black–Scholes model in its capability to hedge. To do so, a notion of tracking error is taken as the performance measure. Based on the post-sample performance, it is found that in approximately 20% of the 97 test paths GP has a lower tracking error than the Black–Scholes formula. We further compare our result with the ones obtained by radial basis functions and multilayer perceptrons and one-stage GP. Copyright © 1999 John Wiley & Sons, Ltd.     

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.     

时变步长自适应均衡算法的设计与仿真

研究了自适应均衡算法中步长因子对算法性能的影响。步长因子大,算法收敛速度和跟踪速度快,但收敛后稳态剩余误差大;步长小,算法收敛速度和跟踪速度慢,收敛后稳态剩余误差小。因此,采用固定步长时,算法在收敛速度和收敛精度方面对步长的要求是相互矛盾的。因此本文采用均方误差的Sigmoid函数和误差信号的非线性函数作为步长控制因子,得到了几种改进算法,经计算机仿真表明,改进算法收敛速度加快,稳态剩余误差减小。     

中国技术进步对能源效率影响的空间计量分析

利用探索性空间数据方法,运用空间滞后模型和空间误差模型对全域能源效率的影响因素进行估计,运用地理加权回归模型对局域能源效率的影响因素进行估计。结果表明:中国省域能源效率存在显著的空间相关性,全域层面的人力资本投入和外资技术溢出是促进能源效率提高的主要因素;从局域层面看,东北经济区的人力资本投入和产业结构调整对能源效率提高的贡献较大,而广东等南部地区省份的外商投资带来的技术溢出对能源效率提高的贡献最大。