Operations Research
http://lists.repec.org/mailman/listinfo/nep-ore
Operations Research2015-02-22Walter FrischOn Flexible Linear Factor Stochastic Volatility Models
http://d.repec.org/n?u=RePEc:pra:mprapa:62216&r=ore
In this thesis I discuss flexible Bayesian treatment of the linear factor stochastic volatility model with latent factors, which proves to be essential in order to preserve parsimony when the number of cross section in the data grows. Based on the Bayesian model selection literature, I introduce a flexible prior specification which allows carrying out restriction search on the mean equation coefficients of the factor model – the loadings matrix. I use this restriction search as a data-based alternative to evaluate the cross sectional restrictions suggested by arbitrage pricing theory. A mixture innovation model is also proposed which generalizes the standard stochastic volatility specification and can also be interpreted as a restriction search in variance equation parameters. I comment on how to use the mixture innovation model to catch both gradual and abrupt changes in the stochastic evolution of the covariance matrix of high-dimensional financial datasets. This approach has the additional advantages of dating when large jumps in volatility have occurred in the data and determining whether these jumps are attributed to any of the factors, the innovation errors, or combinations of those.Malefaki, Valia2015-01Factor model; Bayesian priorNonparametric change-point analysis of volatility
http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2015-008&r=ore
This work develops change-point methods for statistics of high-frequency data. The main interest is the volatility of an Itˆo semi-martingale, which is discretely observed over a fixed time horizon. We construct a minimax-optimal test to discriminate different smoothness classes of the underlying stochastic volatility process. In a high-frequency framework we prove weak convergence of the test statistic under the hypothesis to an extreme value distribution. As a key example, under extremely mild smoothness assumptions on the stochastic volatility we thereby derive a consistent test for volatility jumps. A simulation study demonstrates the practical value in finite-sample applications.Markus Bibinger, Moritz Jirak, Mathias Vetter, 2015-02high-frequency data, nonparametric change-point test, minimax-optimal test, stochastic volatility, volatility jumpsSingle-Step Estimation of a Partially Linear Model
http://d.repec.org/n?u=RePEc:mia:wpaper:2015-01&r=ore
In this paper we propose an asymptotically equivalent single-step alternative to the two-step partially linear model estimator in Robinson (1988). The estimator not only has the potential to decrease computing time dramatically, it shows substantial finite sample gains in Monte Carlo simulations.Daniel J. Henderson, Christopher F. Parmeter2015-01-01Cross-validation, bandwidth, bias, Monte Carlo, Kernel Publication Status: Under ReviewBivariate GARCH models for single asset returns
http://d.repec.org/n?u=RePEc:war:wpaper:2015-03&r=ore
In this paper an alternative approach to modelling and forecasting single asset returns volatility is presented. A new, bivariate, flexible framework, which may be considered as a development of single-equation ARCH-type models, is proposed. This approach focuses on joint distribution of returns and observed volatility, measured by Garman-Klass variance estimator, and it enables to examine simultaneous dependencies between them. Proposed models are compared with benchmark GARCH and range-based GARCH (RGARCH) models in terms of prediction accuracy. All models are estimated with maximum likelihood method, using time series of EUR/PLN spot rate quotations and WIG20 index. Results are very encouraging especially for foreasting Value-at-Risk. Bivariate models achieved lesser rates of VaR exception, as well as lower coverage tests statistics, without being more conservative than its single-equation counterparts, as their forecasts errors measures are rather similar.Tomasz Skoczylas2015bivariate volatility models, joint distribution, range-based volatility estimators, Garman-Klass estimator, observed volatility, volatility modelling, GARCH, leverage, Value-at-Risk, volatility forecastingFinancial frictions and the volatility of monetary policy in a DSGE model
http://d.repec.org/n?u=RePEc:lan:wpaper:75949436&r=ore
The paper investigates the impacts of the volatility of monetary policy on the economy in a DSGE model with financial frictions a la Bernanke, Gertler, and Gilchrist (1999). The model is estimated by the particle filter maximum likelihood estimator for the U.S. economy. Our results first show that a positive monetary volatility shock causes a contraction in economic activity: output, consumption, investment, hours, and real wages fall. Second, we argue that financial frictions amplify the effects of the shock via the financial accelerator mechanism. Third, we document that the size of the effects of the shock is relatively small mostly because of the counteracting response of monetary policy to the shock. Therefore, the impacts would be substantial if monetary policy was restrained to respond to changes in current conditions in the economy.Anh Nguyen2015DSGE models, financial accelerator, Taylor rule, monetary policy, stochastic volatility, particle filter, higher-order approximations, policy uncertaintyMigration feedback effects in networks: an agent-based model
http://d.repec.org/n?u=RePEc:new:wpaper:1307&r=ore
Miriam Rehm, Ali Asjad Naqvi2013-10migration, agent-based modeling, networksA New Class of Bivariate Threshold Cointegration Models
http://d.repec.org/n?u=RePEc:msh:ebswps:2015-1&r=ore
Biqing Cai, Jiti Gao, Dag Tjøstheim2015Î²-null recurrent, cointegration, Markov chain, threshold VAR models <i>T</i><sup>1/2</sup>, while the convergence rate for the estimators for the coefficients in the middle regime is <i>T</i>. Also, we show that the convergence rate of the cointegrating coefficient is <i>T</i><sup>1/2</sup>, which is same as linear cointegration model. The Monte Carlo simulation results suggest that the estimators perform reasonably well in finite samples. Applying the proposed model to study the dynamic relationship between Federal funds rate and 3-month Treasury bill rate, we find that cointegrating coefficients are the same for the two regimes while the short run loading coefficients are different.Decomposing Risk in Dynamic Stochastic General Equilibrium
http://d.repec.org/n?u=RePEc:zbw:vfsc14:100523&r=ore
We analyze the theoretical moments of a nonlinear approximation to real business cycle model with stochastic volatility and recursive preferences. We nd that the conditional heteroskedasticity of stochastic volatility operationalizes a time-varying risk adjustment channel that induces variability in conditional asset pricing measures and assigns a substantial portion of the variance of macroeconomic variables to variations in precautionary behavior, both while leaving its ability to match key macroeconomic and asset pricing facts untouched. We calculate the theoretical moments directly and decomposes these moments into contributions from shifts in the distribution of future shocks (i.e., risk) and from realized shocks and differing orders of approximation, enabling us to identify the common channel through which stochastic volatility in isolation operates and through which conditional asset pricing measures vary over time. Under frictional investment and varying capital utilization, output drops in response to an increase in risk, but the contributions to the variance of macroeconomic variables from risk becomes negligible.Lan, Hong, Meyer-Gohde, Alexander2014Markov Perfect Equilibria in Differential Games with Regime Switching Strategies
http://d.repec.org/n?u=RePEc:eus:ce3swp:0314&r=ore
We propose a new methodology exploring Markov perfect equilibrium strategies in differential games with regime switching. We develop a general game with two players. Players choose an action that inuences the evolution of a state variable, and decide on the switching time from one regime to another. Compared to the optimal control problem with regime switching, necessary optimality conditions are modifed for the first-mover. When choosing her optimal switching strategy, this player considers the impact of her choice on the other player's actions and consequently on her own payoffs. In order to determine the equilibrium timing of regime changes, we derive conditions that help eliminate candidate equilibrium strategies that do not survive deviations in switching strategies. We then apply this new methodology to an exhaustible resource extraction game.Ngo Van Long, Fabien Prieur, Klarizze Puzon, Mabel Tidball2014-12-31differential games, regime switching strategies, technology adoption, non-renewable resourcesIdentification of the Timing-of-Events Model with Multiple Competing Exit Risks from Single-Spell Data
http://d.repec.org/n?u=RePEc:iza:izadps:dp8839&r=ore
This note describes how the (single-spell) identification result of the timing-of-events model by Abbring and Van den Berg (2003b) can be extended to a model that accommodates several competing exit risks. The extended model can be used for example to distinguish between the different effects of a benefit sanction on several competing exit risks out of unemployment such as 'finding work' vs. 'exiting the labor force'. By allowing for a flexible dependence structure between competing exit risks and the duration until entry into treatment, the model can take account of selection into treatment and dependencies between competing exit risks by way of unobservables.Drepper, Bettina, Effraimidis, Georgios2015-02competing risks, treatment effects, multivariate duration analysis, mixed proportional hazard, timing-of-eventsStochastic Volatility in Peruvian Stock Market and Exchange Rate Returns: a Bayesian Approximation
http://d.repec.org/n?u=RePEc:pcp:pucwps:wp00392&r=ore
This study is one of the …rst to utilize the SV model to model Peruvian …nancial series, as well as estimating and comparing with GARCH models with normal and t-student errors. The analysis in this study corresponds to Perus stock market and exchange rate returns. The importance of this methodology is that the adjustment of the data is better than the GARCH models using the assumptions of normality in both models. In the case of the SV model, three Bayesian algorithms have been employed where we evaluate their respective ine¢ ciencies in the estimation of the models parameters being the most e¢ cient the Integration sampler. The estimated parameters in the SV model under the various algorithms are consistent, as they display little ine¢ ciency. The Figures of the correlations of the iterations suggest that there are no problems at the time of Markov chaining in all estimations. We …nd that the volatilities in exchange rate and stock market volatilities follow similar patterns over time. That is, when economic turbulence caused by the economic circumstances occurs, for example, the Asian crisis and the recent crisis in the United States, considerable volatility was generated in both markets. JEL Classification-JEL: C22Willy Alanya, Gabriel Rodríguez2014Modelo de Volatilidad Estocástica, Estimación Bayesiana, Gibbs Sampler, Mixture Sampler, Integration Sampler, Mercado Bursátil, Mercado Cambiario, Modelos GARCH, Perú.Stochastic Complementarity
http://d.repec.org/n?u=RePEc:cie:wpaper:1501&r=ore
Classical deÖnitions of complementarity are based on cross price elasticities, and so they do not apply, for example, when goods are free. This context includes many relevant cases such as online newspapers and public attractions. We look for a complementarity notion that does not rely on price variation and that is: behavioural (based only on observable choice data); and model-free (valid whether the agent is rational or not). We uncover a conáict between properties that complementarity should intuitively possess. We discuss three ways out of the impossibility.Paola Manzini, Marco Mariotti, Levent Ülkü2015Complements and substitutes; Correlation; Stochastic choice