Financing Technological Innovation: Evidence from Patent-Intensive Firms

ABSTRACT

Equityholders of firms with high debt loads have an incentive to underinvest, a distortion that can be most costly for firms with attractive growth options. Using a novel patent-based measure of a firm's growth options, we find that firms issue more equity and shy away from debt financing when they have larger investment opportunities sets. The results are more pronounced among firms in patent-intensive industries. The findings suggest the existence of conflicts of interest between debtholders and equityholders. Our results are consistent with the use of conservative debt policies by technology-intensive firms to mitigate the debt overhang associated with their future growth options.     

Semitractability of optimal stopping problems via a weighted stochastic mesh algorithm

In this paper, we propose a Weighted Stochastic Mesh (WSM) algorithm for approximating the value of discrete‐ and continuous‐time optimal stopping problems. In this context, we consider tractability of such problems via a useful notion of semitractability and the introduction of a tractability index for a particular numerical solution algorithm. It is shown that in the discrete‐time case the WSM algorithm leads to semitractability of the corresponding optimal stopping problem in the sense that its complexity is bounded in order by with being the dimension of the underlying Markov chain. Furthermore, we study the WSM approach in the context of continuous‐time optimal stopping problems and derive the corresponding complexity bounds. Although we cannot prove semitractability in this case, our bounds turn out to be the tightest ones among the complexity bounds known in the literature. We illustrate our theoretical findings by a numerical example.     

A STRUCTURAL RISK‐NEUTRAL MODEL FOR PRICING AND HEDGING POWER DERIVATIVES

We develop a structural risk‐neutral model for energy market modifying along several directions the approach introduced in Aïd et al. In particular, a scarcity function is introduced to allow important deviations of the spot price from the marginal fuel price, producing price spikes. We focus on pricing and hedging electricity derivatives. The hedging instruments are forward contracts on fuels and electricity. The presence of production capacities and electricity demand makes such a market incomplete. We follow a local risk minimization approach to price and hedge energy derivatives. Despite the richness of information included in the spot model, we obtain closed‐form formulae for futures prices and semiexplicit formulae for spread options and European options on electricity forward contracts. An analysis of the electricity price risk premium is provided showing the contribution of demand and capacity to the futures prices. We show that when far from delivery, electricity futures behave like a basket of futures on fuels.     

我国上市公司股票期权激励问题研究

本文首先阐述了股票期权的含义及理论基础;其次,在介绍了我国股票期权实施现状的基础上,系统地分析了我国公司所面临的相关法律法规、外部市场环境及内部治理结构等方面的问题;最后,针对以上存在的各项问题提出了相应的对策建议。     

PRICING ASIAN OPTIONS FOR JUMP DIFFUSION

We construct a sequence of functions that uniformly converge (on compact sets) to the price of an Asian option, which is written on a stock whose dynamics follow a jump diffusion. The convergence is exponentially fast. We show that each element in this sequence is the unique classical solution of a parabolic partial differential equation (not an integro‐differential equation). As a result we obtain a fast numerical approximation scheme whose accuracy versus speed characteristics can be controlled. We analyze the performance of our numerical algorithm on several examples.     

基于期权定价理论的风险投资决策

项目评价的传统方法———净现值(NPV)法在应用于风险投资项目时,由于低估了投资价值,往往会使得投资者失去一些有价值的投资机会。结合风险投资的特性,将期权定价理论应用于风险投资决策中,并建立连续及离散两种状态下的决策模型     

Individual Agents,Firms, and the Real Estate Brokerage Process

This study examines how individual agents affect house selling prices and time on the market while controlling for brokerage firm-specific effects as well as supply and demand conditions that vary by neighborhood. Firm size effects disappear once firm specialization and agent characteristics are taken into account but geographic concentration by firms leads to higher selling prices. For individual agents, neither sex nor selling own listings affects price or selling time, but there are gains from partnering transactions across firms. Agents who specialize in listing properties obtain higher prices for their sellers while those who specialize in selling obtain lower prices for their buyers. Houses nearer to other transactions of an agent sell for higher prices. Finally, greater scale of listing and selling activity by an agent tends to lower selling price or lengthen the time on the market.

Disaggregate Real Exchange Rate Behaviour

In this paper, we re-examine the “PPP Puzzle” using sectoral disaggregated data. Specifically, we first analyse the mean reversion speeds of real exchange rates for a number of different sectors in 11 industrial economies and then focus on relating these rates to variables identified in the literature as key determinants of CPI-based real exchange rates, namely: the trade balance, productivity and the mark up. In particular, we seek to understand to what extent the relationships existing at the aggregate level are borne out at the disaggregate level. We believe that this analysis can help shed light on the PPP puzzle.

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

我国房地产泡沫与银行信贷规模的相关性研究

本文首先从理论上深刻剖析了房地产泡沫与银行信贷规模相互之间的作用与传导机制,在此基础上选取2006年-2018年相关指标的年度数据,对房地产泡沫与银行信贷规模进行了图形拟合与周期性波动规律分析,分析发现二者存在极高的契合度。建立房地产泡沫的函数,构建协整方程实证发现银行信贷规模对房地产泡沫的长期弹性系数为0.51,从长期来看银行信贷规模每增加1%,房地产泡沫也相应增加0.51%,进一步建立VAR模型实证发现房地产泡沫与银行信贷规模互为格兰杰因果关系,二者相互影响、相互促进。通过方差分解实证发现银行信贷规模对房地产泡沫的变动具有重要的影响,另一方面,房地产泡沫是影响银行信贷规模变动最主要的因素。