Cloud Asset Pricing Tree (CAPT) Elastic Economic Model for Cloud Service Providers

Cloud providers are incorporating novel techniques to cope with prospective aspects of trading like resource allocation over future demands and its pricing elasticity that was not foreseen before. To leverage the pricing elasticity of upcoming demand and supply, we employ financial option theory (future contracts) as a mechanism to alleviate the risk in resource allocation over future demands. This study introduces a novel Cloud Asset Pricing Tree (CAPT) model that finds the optimal premium price of the Cloud federation options efficiently. Providers will benefit by this model to make decisions when to buy options in advance and when to exercise them to achieve more economies of scale. The CAPT model adapts its structure to address the price elasticity concerns and makes the demand, price inelastic and the supply, price elastic. Our empirical evidences suggest that using the CAPT model, exploits the Cloud market potential as an opportunity for more resource utilization and future capacity planning.

An Exact Subexponential-Time Lattice Algorithm for Asian Options

Abstract Asian options are popular financial derivative securities. Unfortunately, no exact pricing formulas exist for their price under continuous-time models. Asian options can also be priced on the lattice, which is a discretized version of the continuous-time model. But only exponential-time algorithms exist if the options are priced on the lattice without approximations. Although efficient approximation methods are available, they lack accuracy guarantees in general. This paper proposes a novel lattice structure for pricing Asian options. The resulting pricing algorithm is exact (i.e., without approximations), converges to the value under the continuous-time model, and runs in subexponential time. This is the first exact, convergent lattice algorithm to break the long-standing exponential-time barrier

Extremely Accurate and Efficient Algorithms for European-Style Asian Options with Range Bounds

Asian options can be priced on the unrecombining binomial tree.Unfor- tunately,without approximation,the running time is exponential.This pa- per presents e fficient and extremely accurate approximation algorithms for European-style Asian options on the binomial tree.For a European-style Asian option with strike price X on an n -perio binomial tree,our algorithm runs in O (kn 2 )time with a guaranteed error bound of O (X √n/k )for any positive integer k .Parameter k can be adjusted for any esired trade-o ffbetween time and accuracy.This basic algorithm is then mo i fied to give increasingly tighter upper and lower bounds (or range bounds )that bracket the desired option value while maintaining the same computational e fficiency.As the upper and lower bounds are essentially numerically identical in practice,the proposed al- gorithms can be said to price European-style Asian options exactly without combinatorial explosion.Our results also imply for the first time in the lit- erature that the popular Hull-White algorithms are upper-bound algorithms. Extensive computer experiments are conducted to con firm the extreme accu- racy of the algorithms and their competitiveness in comparison with alternative schemes