Testing and finding the generating functions of an option pricing mechanism through market data

We study dynamic pricing mechanisms of financial derivatives. A typical model of such pricing mechanism is the so-called g-expectation defined by solutions of a backward stochastic differential equation with g as its generating function. Black-Scholes pricing model is a special linear case of this pricing mechanism. We are mainly concerned with two types of pricing mechanisms in an option market: the market pricing mechanism through which the market prices of options are produced, and the ask-bid pricing mechanism operated through the system of market makers. The later one is a typical nonlinear pricing mechanism. Data of prices produced by these two pricing mechanisms are usually quoted in an option market. We introduce a criteria to test if a dynamic pricing mechanism under investigation is a g-pricing mechanism. This domination condition was statistically tested using CME data documents. The result of test is significantly positive. We also provide some useful characterizations of a pricing mechanism by its generating function

PRICE DISCOVERY MECHANISMS AND ALTERNATIVES FOR CANADIAN AGRICULTURE; Part I: A Review of Pricing Mechanisms in Agriculture

The purpose of this section is to review pricing mechanisms in agriculture and food. We started by constructing a taxonomy and system of classification for pricing mechanisms that is rooted in economic theory. This framework was applied to 26 pricing mechanisms observed from the following product categories: · Beef · Hogs · Grains and oilseeds · Dairy · Poultry and Eggs · Processed Food and HorticultureDemand and Price Analysis,

The Design of Arbitrage-Free Data Pricing Schemes

Motivated by a growing market that involves buying and selling data over the web, we study pricing schemes that assign value to queries issued over a database. Previous work studied pricing mechanisms that compute the price of a query by extending a data seller's explicit prices on certain queries, or investigated the properties that a pricing function should exhibit without detailing a generic construction. In this work, we present a formal framework for pricing queries over data that allows the construction of general families of pricing functions, with the main goal of avoiding arbitrage. We consider two types of pricing schemes: instance-independent schemes, where the price depends only on the structure of the query, and answer-dependent schemes, where the price also depends on the query output. Our main result is a complete characterization of the structure of pricing functions in both settings, by relating it to properties of a function over a lattice. We use our characterization, together with information-theoretic methods, to construct a variety of arbitrage-free pricing functions. Finally, we discuss various tradeoffs in the design space and present techniques for efficient computation of the proposed pricing functions.Comment: full pape

Minimizing regret when dissolving a partnership

We study the problem of dissolving an equal-entitlement partnership when the objective is to minimize maximum regret. We initially focus on the family of linear-pricing mechanisms and derive regret-optimizing strategies. We also demonstrate that there exist linear-pricing mechanisms satisfying ex-post efficiency. Next, we analyze a binary-search mechanism which is ex-post individually rational. We discuss connections with the standard Bayesian-Nash framework for both linear and binary-search mechanisms. On a more general level, we show that if entitlements are unequal, ex-post efficiency and ex-post individual rationality impose significant restrictions on permissible mechanisms. In particular, they rule out both linear and binary-search mechanisms.Partnership dissolution; minimax regret; fair division; allocative efficiency

Electricity Transmission Pricing and Performance-Based Regulation

Performance-based regulation (PBR) is influenced by the Bayesian and non-Bayesian incentive mechanisms. While Bayesian incentives are impractical, the insights from their properties can be combined with practical non-Bayesian mechanisms for application to transmission pricing. This combination suggests an approach based on the distinction between ultra-short, short and long periods. Ultra-short periods are marked by real-time pricing of point-to-point transmission services. Pricing in short periods involves fixed fees and adjustments via price-cap formulas or profit sharing. Productivity-enhancing incentives have to be tempered by long-term commitment considerations, so that profit sharing may dominate pure price caps. Investment incentives require long-term adjustments based on rate-of-return regulation with a “used and useful” criterion.

Examining the Attitudes, Pro-Social Value Orientations and Social Norms of Older People to Road Pricing

This study is set to investigate the relationship between older age and the acceptability of road pricing. Specifically, it examines the attitudes of the people aged 60 and over to road pricing in comparison with the attitudes of younger people using relevant literature review findings, secondary data analysis and the results of a questionnaire and three group discussions. Moreover, this research examines whether older people’s support for what is positively valued for society affects these attitudes. Older people are more likely to express positive or negative opinions about road pricing depending on whether they believe it would be good or bad for others, or society. The influence that family, friends or others in general may have on people’s beliefs about road pricing is another subject that is examined. By looking into these issues this work highlights some of the potential opportunities and problems in the present context of the acceptability of road pricing. This will hopefully help policy-makers to decide on actual design criteria and consultation mechanisms that could assist in promoting and communicating better road pricing to older people, making it publicly and therefore politically more acceptable

Extending Demand Response to Tenants in Cloud Data Centers via Non-intrusive Workload Flexibility Pricing

Participating in demand response programs is a promising tool for reducing energy costs in data centers by modulating energy consumption. Towards this end, data centers can employ a rich set of resource management knobs, such as workload shifting and dynamic server provisioning. Nonetheless, these knobs may not be readily available in a cloud data center (CDC) that serves cloud tenants/users, because workloads in CDCs are managed by tenants themselves who are typically charged based on a usage-based or flat-rate pricing and often have no incentive to cooperate with the CDC operator for demand response and cost saving. Towards breaking such "split incentive" hurdle, a few recent studies have tried market-based mechanisms, such as dynamic pricing, inside CDCs. However, such mechanisms often rely on complex designs that are hard to implement and difficult to cope with by tenants. To address this limitation, we propose a novel incentive mechanism that is not dynamic, i.e., it keeps pricing for cloud resources unchanged for a long period. While it charges tenants based on a Usage-based Pricing (UP) as used by today's major cloud operators, it rewards tenants proportionally based on the time length that tenants set as deadlines for completing their workloads. This new mechanism is called Usage-based Pricing with Monetary Reward (UPMR). We demonstrate the effectiveness of UPMR both analytically and empirically. We show that UPMR can reduce the CDC operator's energy cost by 12.9% while increasing its profit by 4.9%, compared to the state-of-the-art approaches used by today's CDC operators to charge their tenants