A calibration procedure for analyzing stock price dynamics in an agent-based framework

In this paper we introduce a calibration procedure for validating of agent based models. Starting from the well-known financial model of (Brock and Hommes, 1998), we show how an appropriate calibration enables the model to describe price time series. We formulate the calibration problem as a nonlinear constrained optimization that can be solved numerically via a gradient-based method. The calibration results show that the simplest version of the Brock and Hommes model, with two trader types, fundamentalists and trend-followers, replicates nicely the price series of four different markets indices: the S&P 500, the Euro Stoxx 50, the Nikkei 225 and the CSI 300. We show how the parameter values of the calibrated model are important in interpreting the trader behavior in the different markets investigated. These parameters are then used for price forecasting. To further improve the forecasting, we modify our calibration approach by increasing the trader information set. Finally, we show how this new approach improves the model׳s ability to predict market prices.     

A quantitative approach to multinational production

I examine new data on the number and revenues of foreign affiliates of multinational firms across a large number of country pairs. The data shed light on the behavior of the intensive and extensive margins of multinational production (MP). To capture the patterns observed in the data, I build and calibrate a multi-country general-equilibrium model of MP that combines a Lucas (1978) span-of-control with an Eaton and Kortum (2002) type model, and includes both fixed and variable costs of opening affiliates abroad. I use the calibrated model to calculate the gains that a country would experience from liberalizing access to foreign firms. Those calculations suggest that the welfare losses of closing up to foreign firms would be around 4%, while the gains of liberalizing access to foreign firms would be large, particularly if the variable – rather than the fixed – component of MP costs were lowered.     

Calibrating rough volatility models: a convolutional neural network approach

In this paper, we use convolutional neural networks to find the Hölder exponent of simulated sample paths of the rBergomi model, a recently proposed stock price model used in mathematical finance. We contextualise this as a calibration problem, thereby providing a very practical and useful application.     

The effects of experience and task difficulty on accuracy and confidence assessments of auditors

This study extends prior research in psychology and auditing by examining the effects of audit experience and task difficulty on control risk evaluation. It also examines whether the effect of framing is mitigated by the simultaneous presentation of information. Ninety‐eight auditors performed a control risk evaluation task and recorded their judgement and their confidence. We find that judgement confidence increases with audit experience and that judgement confidence decreases as perceived task difficulty increases. However, we find no relation between audit experience and judgement accuracy or between perceived task difficulty and judgement accuracy. In addition, we find a significant negative relation between judgement confidence and judgement accuracy, which indicates that the participants' confidence is not appropriate. As expected, there is no framing effect when information is presented simultaneously.     

Estimating parameters of real business cycle models

The calibration technique is the most common procedure to match the data generated from an equilibrium business cycle model with actual macroeconomic time series. This paper goes a step further and tests and applies a maximum likelihood procedure, in combination with the simulated annealing, to estimate the parameters of a baseline RBC model from U.S. macroeconomic time series data. The procedure is tested on a simulated data set where the parameters are known and then applied to U.S. time series data. This permits us to evaluate the efficiency of the procedure and the extent to which the RBC model is a good representation of macroeconomic data.     

A PDE approach to jump-diffusions

In this paper, we show that the calibration to an implied volatility surface and the pricing of contingent claims can be as simple in a jump-diffusion framework as in a diffusion framework. Indeed, after defining the jump densities as those of diffusions sampled at independent and exponentially distributed random times, we show that the forward and backward Kolmogorov equations can be transformed into partial differential equations. This enables us to (i) derive Dupire-like equations [Risk Mag., 1994, 7(1), 18–20] for coefficients characterizing these jump-diffusions; (ii) describe sufficient conditions for the processes they induce to be calibrated martingales; and (iii) price path-independent claims using backward partial differential equations. This paper also contains an example of calibration to the S&P 500 market.     

测控系统测轨数据的时间校正问题

本文分析了航天测控系统几类测轨数据的时间校正问题及相应的校正计算方法,指出在同一系统时标形成的测轨数据不一定是同一时的目标参数,提出了使各测轨数据同步的一种方案.     

基于组件技术的现场校准系统软件设计与实现

针对ATS系统模块多、校准数据量大及现场校准需求,基于COM组件技术设计和实现了现场校准系统软件。软件采用了基于组件的设计模式,使得本系统具有良好的结构性、扩展性和可维护性。该系统能有效地提高校准工作效率,最大程度地体现了ATS的原位误差情况,保证了校准数据的可靠性和精确性。     

TT＆C站的距离零值标校及其误差分析

本文对采用上行调频、下行调相、多侧音测距体制的TT＆C站的距离零值标校方法、标校设备进行了讨论,并对标校误差进行了分析。     

Hypothetical–actual bid calibration of a multigood auction

Evidence suggests the calibration of hypothetical and actual behavior is good-specific. We examine whether clustering commodities into mutual categories can reduce the burden. While we reject a common calibration across sets of commodities, a sport-specific calibration function cannot be rejected.