nep-ets New Economics Papers
on Econometric Time Series
Issue of 2010‒08‒06
nine papers chosen by
Yong Yin
SUNY at Buffalo

  1. Numerical distribution functions of fractional unit root and cointegration tests By James G. MacKinnon; Morten Ørregaard Nielsen
  2. Modelling structural changes in the volatility process By Tibor Neugebauer; Juan A. Lacomba; Francisco Lagos
  3. An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application By Theodore Panagiotidis
  4. Spectral Decomposition of Option Prices in Fast Mean-Reverting Stochastic Volatility Models By Jean-Pierre Fouque; Sebastian Jaimungal; Matthew Lorig
  5. Volatilities That Change with Time: The Temporal Behavior of the Distribution of Stock-Market Prices By Achilles D. Speliotopoulos
  6. Asymptotic equivalence in Lee's moment formulas for the implied volatility and Piterbarg's conjecture By Archil Gulisashvili
  7. A Fast Mean-Reverting Correction to Heston's Stochastic Volatility Model By Jean-Pierre Fouque; Matthew Lorig
  8. Optimization of Financial Instrument Parcels in Stochastic Wavelet Model By A. M. Avdeenko
  9. Seasonal decomposition with a modified Hodrick-Prescott filter By Buss, Ginters

  1. By: James G. MacKinnon (Queen`s University); Morten Ørregaard Nielsen (Queen`s University and CREATES)
    Abstract: We calculate numerically the asymptotic distribution functions of likelihood ratio tests for fractional unit roots and cointegration rank. Because these distributions depend on a real-valued parameter, b, which must be estimated, simple tabulation is not feasible. Partly due to the presence of this parameter, the choice of model specification for the response surface regressions used to obtain the numerical distribution functions is more involved than is usually the case. We deal with model uncertainty by model averaging rather than by model selection. We make available a computer program which, given the dimension of the problem, q, and a value of b, provides either a set of critical values or the asymptotic P value for any value of the likelihood ratio statistic. The use of this program is illustrated by means of an empirical example involving opinion poll data.
    Keywords: cofractional process, fractional unit root, fractional cointegration, response surface regression, cointegration rank, numerical distribution function, model averaging
    JEL: C12 C16 C22 C32
    Date: 2010–07
  2. By: Tibor Neugebauer (Luxembourg School of Finance, University of Luxembourg); Juan A. Lacomba (University of Granada, Department of Economics); Francisco Lagos (University of Granada, Department of Economics)
    Abstract: The tension between cooperation and competition that characterizes many business relationships is experimentally studied in a “pie”-creation game; value is created and increased through cooperation in a repeated prisoner’s dilemma game. At the end, the player with the greater stake in the joint pie decides on the division of the pie. Three treatments of the pie-creation game are considered: in the first treatment, rivals create the pie; in the second, non-rivals create the pie; finally, in the third, the pie is created by subjects who do not know about the future pie-division. The data show that the competition for the right to split the pie biases behaviors towards defection when subjects play with their rival.
    Keywords: Competition, cooperation, co-opetition, ambiguously repeated prisoner’s dilemma, experimental economics.
    Date: 2010
  3. By: Theodore Panagiotidis (Department Of Economics, University Of Macedonia, Thessaloniki, Greece; The Rimini Centre for Economic Analysis (RCEA), Italy)
    Abstract: This paper employs a local information, nearest neighbour forecasting methodology to test for evidence of nonlinearity in financial time series. Evidence from well-known data generating process are provided and compared with returns from the Athens stock exchange given the in-sample evidence of nonlinear dynamics that has appeared in the literature. Nearest neighbour forecasts fail to produce more accurate forecasts from a simple AR model. This does not substantiate the presence of in-sample nonlinearity in the series.
    Keywords: nearest neighbour, nonlinearity
    JEL: C22 C53 G10
    Date: 2010–01
  4. By: Jean-Pierre Fouque; Sebastian Jaimungal; Matthew Lorig
    Abstract: Using spectral decomposition techniques and singular perturbation theory, we develop a systematic method to approximate the prices of a variety of options in a fast mean-reverting stochastic volatility setting. Four examples are provided in order to demonstrate the versatility of our method. These include: European options, up-and-out options, double-barrier knock-out options, and options which pay a rebate upon hitting a boundary. For European options, our method is shown to produce option price approximations which are equivalent to those developed in [5]. [5] Jean-Pierre Fouque, George Papanicolaou, and Sircar Ronnie. Derivatives in Financial Markets with Stochas- tic Volatility. Cambridge University Press, 2000.
    Date: 2010–07
  5. By: Achilles D. Speliotopoulos
    Abstract: While the use of volatilities is pervasive throughout finance, our ability to determine the instantaneous volatility of stocks is nascent. Here, we present a method for measuring the temporal behavior of stocks, and show that stock prices for 24 DJIA stocks follow a stochastic process that describes an efficiently priced stock while using a volatility that changes deterministically with time. We find that the often observed, abnormally large kurtoses are due to temporal variations in the volatility. Our method can resolve changes in volatility and drift of the stocks as fast as a single day using daily close prices.
    Date: 2010–07
  6. By: Archil Gulisashvili
    Abstract: The asymptotic behavior of the implied volatility associated with a general call pricing function has been extensively studied in the last decade. The main topics discussed in this paper are Lee's moment formulas for the implied volatility, and Piterbarg's conjecture, describing how the implied volatility behaves in the case where all the moments of the stock price are finite. We find various conditions guaranteeing the existence of the limit in Lee's moment formulas. We also prove a modified version of Piterbarg's conjecture and provide a non-restrictive sufficient condition for the validity of this conjecture in its original form. The asymptotic formulas obtained in the paper are applied to the implied volatility in the CEV model and in the Heston model perturbed by a compound Poisson process with double exponential law for jump sizes.
    Date: 2010–07
  7. By: Jean-Pierre Fouque; Matthew Lorig
    Abstract: We propose a multi-scale stochastic volatility model in which a fast mean-reverting factor of volatility is built on top of the Heston stochastic volatility model. A singular pertubative expansion is then used to obtain an approximation for European option prices. The resulting pricing formulas are semi-analytic, in the sense that they can be expressed as integrals. Difficulties associated with the numerical evaluation of these integrals are discussed, and techniques for avoiding these difficulties are provided. Overall, it is shown that computational complexity for our model is comparable to the case of a pure Heston model, but our correction brings significant flexibility in terms of fitting to the implied volatility surface. This is illustrated numerically and with option data.
    Date: 2010–07
  8. By: A. M. Avdeenko
    Abstract: To define oscillatory movements of securities market, we put in the non-local extension of Ito- equation for wavelet-images of random processes. It is proposed an algorithm of creation of evolutionary equation and a model of prediction of the most probable price movement path. It is carried out experimental validation of findings.
    Date: 2010–07
  9. By: Buss, Ginters
    Abstract: I describe preliminary results for seasonal decomposition procedure using a modified Hodrick-Prescott (Leser) filter. The procedure is simpler to implement compared to two currently most popular seasonal decomposition procedures - X-11 filters developed by the U.S. Census Bureau and SEATS developed by the Bank of Spain. A case study for Latvia's quarterly gross domestic product shows the procedure is able to extract a stable seasonal component, yet allowing for structural changes in seasonality.
    Keywords: seasonal decomposition; Hodrick-Prescott filter; quarterly GDP
    JEL: C13 C14 C22
    Date: 2010–07–28

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