Stochastic models for telecom commodity prices

Abstract Bandwidth is becoming commoditized and markets are starting to appear. Potential behaviors of these markets are not yet understood because these markets are still in the early stages of development. This is reflected in the lack of current research on the structure and dynamics of network commodity market prices. We present a method for constructing telecom commodity spot price processes as a first step for understanding these developing markets. Bandwidth, like electricity, is not storable so we draw inspiration from electricity prices and models. However, unique network features of telecommunications require specific inclusion. These are geographical substitution (arbitrage), quality of service (QoS), and the continuing pace of technological development. Developing liquidity acts as a further complication. Thus we model price development as a combination of link price processes modified by prices for equivalent QoS routes. We demonstrate our method on a simple triangular network topology and characterize a network contract graph derived from more than 10 major carrier backbones and new entrant networks. Our results cover the existence and value of arbitrage opportunities together with their effect on price development and network value (NPV). Application of this work ranges from network design to infrastructure valuation and construction of real options.

[1]  Giorgos Cheliotis,et al.  Bandwidth Trading in the Real World: Findings and Implications for Commodities Brokerage , 2001 .

[2]  Nicos Christofides,et al.  An efficient implementation of an algorithm for finding K shortest simple paths , 1999, Networks.

[3]  D. J. Songhurst.  Charging communication networks: from theory to practice , 1999 .

[4]  William F. Sharpe,et al.  Financial Economics: Essays in Honor of Paul Cootner , 1988 .

[5]  Eduardo S. Schwartz.  The stochastic behavior of commodity prices: Implications for valuation and hedging , 1997 .

[6]  Toshihide Ibaraki,et al.  An efficient algorithm for K shortest simple paths , 1982, Networks.

[7]  John N. Tsitsiklis,et al.  Congestion-dependent pricing of network services , 2000, TNET.

[8]  Peter H. Ritchken,et al.  Option pricing under regime switching , 2002 .

[9]  Stephen Gray,et al.  Regime switching in foreign exchange rates : Evidence from currency option prices , 2000 .

[10]  Marco Antonio Guimarães Dias,et al.  Petroleum Concessions with Extendible Options: Investment Timing and Value Using Mean Reversion and Jump Processes for Oil Prices , 1999 .

[11]  D. Pilipović,et al.  Energy Risk: Valuing and Managing Energy Derivatives , 1997 .

[12]  Blake Johnson,et al.  Exotic electricity options and the valuation of electricity generation and transmission assets , 2001, Decis. Support Syst..

[13]  David D. Clark,et al.  A Model for Cost Allocation and Pricing in the Internet , 1995 .

[14]  H. Varian.  Market Structure in the Network Age , 1999 .

[15]  R. C. Merton,et al.  Option pricing when underlying stock returns are discontinuous , 1976 .

[16]  N. Economides.  The Economics of Networks , 1995 .

[17]  John N. Tsitsiklis,et al.  Introduction to linear optimization , 1997, Athena scientific optimization and computation series.

[18]  Eduardo S. Schwartz,et al.  Short-Term Variations and Long-Term Dynamics in Commodity Prices , 2000 .

[19]  Henrik Andersson,et al.  The stochastic behaviour of commodity prices , 2003 .

[20]  L. McKnight,et al.  Internet economics , 1997 .

[21]  Nicos Christofides,et al.  An efficient implementation of an algorithm for finding K shortest simple paths , 1999, Networks.

[22]  M. Manoliu,et al.  Energy futures prices: term structure models with Kalman filter estimation , 2002 .

[23]  S. Deng,et al.  Stochastic Models of Energy Commodity Prices and Their Applications : Mean-reversion with Jumps and Spikes , 1998 .

[24]  Deborah Estrin,et al.  Pricing in Computer Networks: Reshaping the Research Agenda , 2020, The Internet and Telecommunications Policy.

[25]  P S Dial.  Boom or bust. , 1999, Texas medicine.

[26]  Antônio Guimarães Dias,et al.  “ PETROLEUM CONCESSIONS WITH EXTENDIBLE OPTIONS USING MEAN REVERSION WITH JUMPS TO MODEL OIL PRICES ” Marco , 1999 .

[27]  Qiong Wang,et al.  Optimal planning for optical transport networks , 2000, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.