Pricing caps with HJM models: The benefits of humped volatility

In this paper we compare different multifactor HJM models with humped volatility structures, to each other and to models with strictly decreasing volatility. All the models are estimated on Euribor and swap rates panel data maximizing the quasi-likelihood function obtained from the Kalman filter. We develop the analysis in two steps: first we study the in-sample properties of the estimated models, then we test the pricing performance on caps. We find the humped volatility specification to greatly improve the model estimation and to provide sufficiently accurate cap prices, although the models has been calibrated on interest rates data and not on cap prices. Moreover, we find the two-factor humped volatility model to outperform the three-factor models in pricing caps.     

随机利率下跳-扩散过程的产量保险定价模型

本文研究了农产品价格为一般的跳-扩散模型,随机跳部分为复合Poisson过程,并假设远期利率服从HJM模型,利用测度变换技巧,给出了合同的在此模型下的解析解.     

Pilot-Wave Theory and Financial Option Pricing

This paper tries to argue why pilot-wave theory could be of use in financial economics. We introduce the notion of information wave. We consider a stochastic guidance equation and part of the drift term of that equation makes reference to the phase of the wave. In order to embed information in financial option pricing we could use such a drift. We also briefly argue how we could embed information in the pricing kernel of the option price. PACS: 03, 89.65.Gh.     

Pricing strategies for perishable products: the case of Vienna and the hotel reservation system hrs.com

Consider a retailer who sells perishable products for which there is uncertain demand. Yield management with dynamic pricing is a standard practice that firms use for revenue management. For perishable products, recent analysis has focused on the distribution of flight capacity, referred to as ticket sales. Other non- storable, non-transportable, immaterial hospitality products include hotel capacity. The article discusses the extent to which hotel pricing strategies vary within the internet distribution system hrs.com. This study focuses on the distribution of hotel rooms available for booking on the internet for Vienna and gives an outlook to Euroland capitals. The main research interests are the underlying pricing models and the setting of the end price. Data was taken from hrs.com, which is the most important specialist for hotel room internet distribution in Germany according to recent studies by KMPG and others. The results include the identification of different pricing strategy clusters with regard to hotel category and hotel availability over a 22-day period for Vienna and one city from all Euroland countries (the capitals were studied for all cases except for the Netherlands, for which data was collected for Amsterdam). The study took the arrival days Mondays, Tuesdays, Wednesdays and Thursdays into account, and used data for all these days from the 11th of July, 2005, to the 10th of October, 2005, for Vienna, and the first and the last of these dates as a comparison base for the other Euroland cities.     

Intertemporal service pricing with strategic customers

We study a two-period intertemporal pricing game in a single-server service system with forward-looking strategic customers who make their purchase decision based on current information and anticipated future gains. Subgame perfect Nash equilibrium (SPNE) prices are derived. A comparison between revenue-maximizing equilibrium prices and welfare-maximizing equilibrium prices is conducted and the impact on the system’s performance of misunderstanding customers’ type is evaluated.     

On coordinate transformation and grid stretching for sparse grid pricing of basket options

We evaluate two coordinate transformation techniques in combination with grid stretching for pricing basket options in a sparse grid setting. The sparse grid technique is a basic technique for solving a high-dimensional partial differential equation. By creating a small hypercube sub-grid in the ‘composite’ sparse grid we can also determine hedge parameters accurately. We evaluate these techniques for multi-asset examples with up to five underlying assets in the basket.     

Recovering risk-neutral probability density functions from options prices using cubic splines and ensuring nonnegativity

We present a new approach to estimate the risk-neutral probability density function (pdf) of the future prices of an underlying asset from the prices of options written on the asset. The estimation is carried out in the space of cubic spline functions, yielding appropriate smoothness. The resulting optimization problem, used to invert the data and determine the corresponding density function, is a convex quadratic or semidefinite programming problem, depending on the formulation. Both of these problems can be efficiently solved by numerical optimization software.     

Third-order extensions of Lo’s semiparametric bound for European call options

Computing semiparametric bounds for option prices is a widely studied pricing technique. In contrast to parametric pricing techniques, such as Monte-Carlo simulations, semiparametric pricing techniques do not require strong assumptions about the underlying asset price distribution. We extend classical results in this area. Specifically, we derive closed-form semiparametric bounds for the payoff of a European call option, given up to third-order moment (i.e., mean, variance, and skewness) information on the underlying asset price. We analyze how these bounds tighten the corresponding bounds, when only second-order moment (i.e., mean and variance) information is provided. We describe applications of these results in the context of option pricing; as well as in other areas such as inventory management, and actuarial science.     

Bilevel optimization applied to strategic pricing in competitive electricity markets

In this paper, we present a bilevel programming formulation for the problem of strategic bidding under uncertainty in a wholesale energy market (WEM), where the economic remuneration of each generator depends on the ability of its own management to submit price and quantity bids. The leader of the bilevel problem consists of one among a group of competing generators and the follower is the electric system operator. The capability of the agent represented by the leader to affect the market price is considered by the model. We propose two solution approaches for this non-convex problem. The first one is a heuristic procedure whose efficiency is confirmed through comparisons with the optimal solutions for some instances of the problem. These optimal solutions are obtained by the second approach proposed, which consists of a mixed integer reformulation of the bilevel model. The heuristic proposed is also compared to standard solvers for nonlinearly constrained optimization problems. The application of the procedures is illustrated in case studies with configurations derived from the Brazilian power system.