New Economics Papers
on Financial Markets
Issue of 2011‒07‒02
three papers chosen by

  1. Global bond risk premiums By Rebecca Hellerstein
  2. Maximum entropy distribution of stock price fluctuations By Rosario Bartiromo
  3. Optimal High Frequency Trading with limit and market orders By Fabien Guilbaud; Huyen Pham

  1. By: Rebecca Hellerstein
    Abstract: This paper examines time-varying measures of term premiums across ten developed economies. It shows that a single factor accounts for most of the variation in expected excess returns over time, across the maturity spectrum, and across countries. I construct a global return forecasting factor that is a GDP-weighted average of each country’s local return forecasting factor and show that it has information not spanned by the traditional level, slope, curvature factors of the term structure, or by the local return forecasting factors. Including the global forecasting factor in the model produces estimates of spillover effects that are consistent with our conceptual understanding of these flows, both in direction and magnitude. These effects are illustrated for three episodes: the period following the Russian default in 1998, the bond conundrum period from mid-2004 to mid-2006, and the period since the onset of the global financial crisis in 2008.
    Keywords: Bonds ; Risk ; Forecasting
    Date: 2011
  2. By: Rosario Bartiromo
    Abstract: The principle of absence of arbitrage opportunities allows obtaining the distribution of stock price fluctuations by maximizing its information entropy. This leads to a physical description of the underlying dynamics as a random walk characterized by a stochastic diffusion coefficient and constrained to a given value of the expected volatility, taking in this way into account the information provided by the existence of an option market. This model is validated by a comprehensive comparison with observed distributions of both price return and diffusion coefficient. Expected volatility is the only parameter in the model and can be obtained by analysing option prices. We give an analytic formulation of the probability density function for price returns which can be used to extract expected volatility from stock option data. This distribution is of high practical interest since it should be preferred to a Gaussian when dealing with the problem of pricing derivative financial contracts.
    Date: 2011–06
  3. By: Fabien Guilbaud (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - CNRS : UMR7599 - Université Pierre et Marie Curie - Paris VI - Université Paris Diderot - Paris 7); Huyen Pham (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - CNRS : UMR7599 - Université Pierre et Marie Curie - Paris VI - Université Paris Diderot - Paris 7, CREST - Centre de Recherche en Économie et Statistique - INSEE - École Nationale de la Statistique et de l'Administration Économique)
    Abstract: We propose a framework for studying optimal market making policies in a limit order book (LOB). The bid-ask spread of the LOB is modelled by a Markov chain with finite values, multiple of the tick size, and subordinated by the Poisson process of the tick-time clock. We consider a small agent who continuously submits limit buy/sell orders and submits market orders at discrete dates. The objective of the market maker is to maximize her expected utility from revenue over a short term horizon by a tradeoff between limit and market orders, while controlling her inventory position. This is formulated as a mixed regime switching regular/ impulse control problem that we characterize in terms of quasi-variational system by dynamic programming methods. In the case of a mean-variance criterion with martingale reference price or when the asset price follows a Levy process and with exponential utility criterion, the dynamic programming system can be reduced to a system of simple equations involving only the inventory and spread variables. Calibration procedures are derived for estimating the transition matrix and intensity parameters for the spread and for Cox processes modelling the execution of limit orders. Several computational tests are performed both on simulated and real data, and illustrate the impact and profit when considering execution priority in limit orders and market orders
    Keywords: Market making; limit order book; inventory risk; point process; stochastic control
    Date: 2011–06–24

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.