低噪声自动测试及噪声源自动校准系统

本文介绍一个噪声自动测试系统。该系统主要完成两大类功能:测试低噪声器件的噪声温度和校准固态噪声源的超噪比。同时兼有测量被测件的电压驻波比和测量电子部件/器件及接收机的噪声系数等功能。测试/校准软件用于控制仪器的设置和测试流程;计算和补偿插入损耗;计算和修正失配影响;自动生成标准格式的原始记录和证书报告(包括曲线)。该系统为同轴、宽频段、全面开展无线电噪声参数测试/校准的自动测试系统。     

Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models

We present a neural network-based calibration method that performs the calibration task within a few milliseconds for the full implied volatility surface. The framework is consistently applicable throughout a range of volatility models—including second-generation stochastic volatility models and the rough volatility family—and a range of derivative contracts. Neural networks in this work are used in an off-line approximation of complex pricing functions, which are difficult to represent or time-consuming to evaluate by other means. The form in which information from available data is extracted and used influences network performance: The grid-based algorithm used for calibration is inspired by representing the implied volatility and option prices as a collection of pixels. We highlight how this perspective opens new horizons for quantitative modelling. The calibration bottleneck posed by a slow pricing of derivative contracts is lifted, and stochastic volatility models (classical and rough) can be handled in great generality as the framework also allows taking the forward variance curve as an input. We demonstrate the calibration performance both on simulated and historical data, on different derivative contracts and on a number of example models of increasing complexity, and also showcase some of the potentials of this approach towards model recognition. The algorithm and examples are provided in the Github repository GitHub: NN-StochVol-Calibrations.     

Stochastic interest rate modelling using a single or multiple curves: an empirical performance analysis of the Lévy forward price model

In current financial markets negative interest rates have become rather persistent, while in theory it is often common practice to discard such rates as incredible and irrelevant. However, from a risk management perspective, it is crucially important to financial institutions to properly account for this phenomenon in their Asset Liability Management (ALM) studies. In this paper, we develop a coherent framework on how to best incorporate negative interest rates in these studies through a single curve stochastic term structure model and compare it to its multiple curve analogue. It turns out that, from the wide range of available single curve models, especially the Lévy Forward Price model (LFPM) of Eberlein and Özkan [The Lévy LIBOR model. Financ. Stoch., 2005, 9, 327–348] seems appropriate for ALM purposes. This paper describes an optimisation routine for calibrating this LFPM under the risk-neutral measure in both the single and multiple curve framework to the market prices of interest rate caplets with different strike rates, maturities and tenors. In addition, an empirical performance analysis is made of the single and multiple curve LFPM, where we include four deterministic volatility specifications and provide an explicit parametrisation of a piecewise homogeneity restriction with both deterministic and random breakpoints. This comparative analysis indicates that both the single and multiple curve LFPM is best adopted with the Linear-Exponential Volatility (LEV) specification and that deterministic breakpoints should be included, rather than random breakpoints.     

A calibration method with dynamic updates for within-match forecasting of wins in tennis

In-match predictions of player win probabilities for professional tennis matches have a wide range of potential applications, including betting, fan engagement, and performance evaluation. The ideal properties of an in-play prediction method include the ability to incorporate both useful pre-match information and relevant in-match information as the match progresses, in order to update the pre-match expectations. This paper presents an in-play forecasting method that achieves both of these goals by combining a pre-match calibration method with a dynamic empirical Bayes updating rule. We present an optimisation rule for guiding the specifications of the dynamic updates using a large sample of professional tennis matches. We apply the results to data from the 2017 season and show that the dynamic model provides a 28% reduction in the error of in-match serve predictions and improves the win prediction accuracy by four percentage points relative to a constant ability model. The method is applied to two Australian Open men’s matches, and we derive several corollary statistics to highlight key dynamics in the win probabilities during a match.     

Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness

This study assesses systemic risk inherent in credit default swap (CDS) indices using empirical and statistical analyses. We define systemic risk in two perspectives: the possibilities of simultaneous and contagious defaults, and then quantify them separately across benchmark models. To do so, we employ a Marshall-Olkin copula model to measure simultaneous default risk, and an interacting intensity-based model to capture contagious default risk. For an empirical test, we collect daily data for the iTraxx Europe CDS index and its tranche prices in the period from 2005 to 2014, and calibrate model parameters varying across time. In addition, we select forecasting models that have minimal prediction errors for the calibrated time series. Finally, we identify significant changes in each dynamic of systemic risk indicator before and after default and downgrade-related episodes that have occurred in the global financial crisis and European sovereign debt crisis.     

A strategic predictive distribution for tests of probabilistic calibration

Forecasts of probability distributions are needed to support decision making in many applications. The accuracy of predictive distributions should be evaluated by maximising sharpness subject to calibration. Sharpness relates to the concentration of the predictive distributions, while calibration concerns their statistical consistency with the data. This paper focuses on calibration testing. It is important that a calibration test cannot be gamed by forecasts that have been strategically designed to pass the test. The widely used tests of probabilistic calibration for predictive distributions are based on the probability integral transform. Drawing on previous results for quantile prediction, we show that strategic distributional forecasting is a concern for these tests. To address this, we provide a simple extension of one of the tests. We illustrate ideas using simulated data.     

乙酰丙酮分光光度法工作曲线稳定性研究

对乙酰丙酮分光光度法测定纺织品中甲醛含量的工作曲线稳定性进行了研究。实验结果表明,乙酰丙酮分光光度法工作曲线有良好的稳定性,相近环境温度不同贮存时间下所作工作曲线斜率的相对标准偏差（RSD）≤2.04%。     

The Japanese saving rate between 1960 and 2000: productivity,policy changes,and demographics

In this paper, we use an overlapping generations model to study the factors generating the saving rate in Japan between 1960–2000. The model economy allows for observed aging of the population, total factor productivity (TFP), and fiscal policy to affect the national saving rate. Our calibrated general equilibrium setup generates saving rates that are reasonably similar to the data during this period. Our counterfactual experiments indicate that observed TFP growth rates are the main reason for both the secular decline and the two humps in the saving rate during 1960–2000.      

A strategic analysis of global warming: Theory and some numbers

We model the global warming process as a dynamic commons game in which the players are countries, their actions at each date produce emissions of greenhouse gases, and the state variable is the current stock of greenhouse gases. The theoretical analysis is complemented by a calibration exercise. The first set of results establishes theoretically, and then with illustrative numbers, the over-emissions due to a “tragedy of the commons.” The power of simple sanctions to lower emissions and increase welfare is then examined as is the effect of cost asymmetry. Finally, a complete theoretical charactrization is provided for the best equilibrium, and it is shown that it has a very simple structure; it involves a constant emission rate through time.     

原油流量标准检定系统的科学建立

针对目前流量标准检定系统存在的问题,提出了适合我国国情又有符合国际标准、较为科学的流量标准检定系统,从计量管理的角度,阐述了建立系统的重要意义,并提出了实施系统的一些见解。