An objective function for simulation based inference on exchange rate data

Winker, Peter; Gilli, Manfred; Jeleskovic, Vahidin

doi:10.1007/s11403-007-0020-4

Cited by 82 publications

(57 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…201f, or the application of MSM in Franke, 2009, Section 2.2). In this paper, we follow Winker et al (2007) and Franke and Westerhoff (2011) and choose a bootstrap approach to construct from the empirical returns a large number of samples of the moments, from which subsequently the covariances can be derived. The details are given in Appendix A2.…”

Section: The Methods Of Simulated Momentsmentioning

confidence: 99%

“…Defining a (moment-specific) bootstrapped p-value to quantify a model's goodness-of-fit, it turns out that roughly one-third of all simulation runs cannot be directly rejected by the data. On the other hand, the joint MCR amounts to more than 25 per cent, which we think is a fairly respectable order of 3 See Gilli and Winker (2003), Alfarano et al (2005), Manzan and Westerhoff (2007), Winker et al (2007), Boswijk et al (2007), Amilon (2008), Franke (2009), Li et al (2010), Chiarella et al (2011), Franke and Westerhoff (2011). 4 The choice of MSM does not rule out that also other estimation approaches may be tried.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Structural stochastic volatility in asset pricing dynamics: Estimation and model contest

Franke

Westerhoff

2012

Journal of Economic Dynamics and Control

200

184

View full text Add to dashboard Cite

In the framework of small-scale agent-based financial market models, the paper starts out from the concept of structural stochastic volatility, which derives from different noise levels in the demand of fundamentalists and chartists and the time-varying market shares of the two groups. It advances several different specifications of the endogenous switching between the trading strategies and then estimates these models by the method of simulated moments (MSM), where the choice of the moments reflects the basic stylized facts of the daily returns of a stock market index. In addition to the standard version of MSM with a quadratic loss function, we also take into account how often a great number of Monte Carlo simulation runs happen to yield moments that are all contained within their empirical confidence intervals. The model contest along these lines reveals a strong role for a (tamed) herding component. The quantitative performance of the winner model is so good that it may provide a standard for future research.JEL classification: D84; G12; G14; G15.

show abstract

Section: The Methods Of Simulated Momentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structural stochastic volatility in asset pricing dynamics: Estimation and model contest

Franke

Westerhoff

2012

Journal of Economic Dynamics and Control

200

184

View full text Add to dashboard Cite

show abstract

“…21 We therefore choose a bootstrap procedure to construct, from the empirical observations, additional samples and derive the covariances in Σ from them. We nevertheless depart from the block bootstraps that have been used in Winker et al (2007) or Franke and Westerhoff (2011a,b), since the original long-range dependence in the return series is interrupted every time two non-adjacent blocks are pasted. The fact that our estimation is concerned with summary statistics and not the one-period ahead predictions of a time series allows us to sample the single days and, associated with each of them, the history of the past few lags required to calculate the lagged autocorrelations.…”

Section: The Methods Of Simulated Momentsmentioning

confidence: 99%

Why a simple herding model may generate the stylized facts of daily returns: explanation and estimation

Franke

Westerhoff

2014

J Econ Interact Coord

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThe paper proposes an elementary agent-based asset pricing model that, invoking the two trader types of fundamentalists and chartists, comprises four features: (i) price determination by excess demand; (ii) a herding mechanism that gives rise to a macroscopic adjustment equation for the market fractions of the two groups; (iii) a rush towards fundamentalism when the price misalignment becomes too large; and (iv) a stronger noise component in the demand per chartist trader than in the demand per fundamentalist trader, which implies a structural stochastic volatility in the returns. Combining analytical and numerical methods, the interaction between these elements is studied in the phase plane of the price and a majority index. In addition, the model is estimated by the method of simulated moments, where the choice of the moments reflects the basic stylized facts of the daily returns of a stock market index. A (parametric) bootstrap procedure serves to set up an econometric test to evaluate the model's goodness-of-fit, which proves to be highly satisfactory. The bootstrap also makes sure that the estimated structural parameters are well identified.JEL classification: D84; G12; G14; G15.

show abstract

“…In this, we follow the existing literature which approximates the fundamental price by a moving average (Winker et al, 2007;ter Ellen and Zwinkels, 2010;Huisman et al, 2010). For example Winker et al (2007) assume as the proxy for the fundamental price a moving average (MA) over the last 200 observations of the DM/USD exchange rate time series for the period 1991/11/11 to 2000/11/9. ter Ellen and Zwinkels (2010) Long-term and short-term MAs are also commonly used by practitioners in trading to extrapolate divergence from the fundamental value in the technical analysis.…”

Section: Fundamental Price Approximationmentioning

confidence: 99%

Estimation of financial agent-based models with simulated maximum likelihood

Kukačka

Baruník

2017

Journal of Economic Dynamics and Control

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This paper proposes a general computational framework for empirical estimation of financial agent based models, for which criterion functions do not have known analytical form. For this purpose, we adapt a nonparametric simulated maximum likelihood estimation based on kernel methods. Employing one of the most widely analysed heterogeneous agent models in the literature developed by Brock and Hommes (1998), we extensively test properties of the proposed estimator and its ability to recover parameters consistently and efficiently using simulations. Key empirical findings point us to the statistical insignificance of the switching coefficient but markedly significant belief parameters defining heterogeneous trading regimes with superiority of trend-following over contrarian strategies. In addition, we document slight proportional dominance of fundamentalists over trend following chartists in main world markets. Terms of use: Documents in AbstractThis paper proposes a general computational framework for empirical estimation of financial agent based models, for which criterion functions do not have known analytical form. For this purpose, we adapt a nonparametric simulated maximum likelihood estimation based on kernel methods. Employing one of the most widely analysed heterogeneous agent models in the literature developed by Brock and Hommes (1998), we extensively test properties of the proposed estimator and its ability to recover parameters consistently and e ciently using simulations. Key empirical findings point us to the statistical insignificance of the switching coe cient but markedly significant belief parameters defining heterogeneous trading regimes with superiority of trend-following over contrarian strategies. In addition, we document slight proportional dominance of fundamentalists over trend following chartists in main world markets.JEL: C14, C51, C63, D84, G02, G12

show abstract

An objective function for simulation based inference on exchange rate data

Abstract: Indirect estimation, Simulation based estimation, Exchange rate returns, C14, C15, F31,

Cited by 82 publications

References 17 publications

Structural stochastic volatility in asset pricing dynamics: Estimation and model contest

Structural stochastic volatility in asset pricing dynamics: Estimation and model contest

Why a simple herding model may generate the stylized facts of daily returns: explanation and estimation

Estimation of financial agent-based models with simulated maximum likelihood

Contact Info

Product

Resources

About