Removing Maturity Effects of Implied Risk Neutral Densities and Related Statistics

When studying a time series of implied Risk Neutral Densities (RNDs) or other implied statistics, one is faced with the problem of maturity dependence, given that option contracts have a fixed expiry date. Therefore, estimates from consecutive days are not directly comparable. Further, we can only obtain implied RNDs for a limited set of expiration dates. In this paper we introduce two new methods to overcome the time to maturity problem. First, we propose an alternative method for calculating constant time horizon Economic Value at Risk (EVaR), which is much simpler than the method currently being used at the Bank of England. Our method is based on an empirical scaling law for the quantiles in a log-log plot, and thus, we are able to interpolate and extrapolate the EVaR for any time horizon. The second method is based on an RND surface constructed across strikes and maturities, which enables us to obtain RNDs for any time horizon. Removing the maturity dependence of implied RNDs and related statistics is useful in many applications, such as in (i) the construction of implied volatility indices like the VIX, (ii) the assessment of market uncertainty by central banks (iii) time series analysis of EVaR, or (iv) event studies

The Generalized Extreme Value (GEV) Distribution, Implied Tail Index and Option Pricing

Crisis events such as the 1987 stock market crash, the Asian Crisis and the bursting of the Dot-Com bubble have radically changed the view that extreme events in financial markets have negligible probability. This paper argues that the use of the Generalized Extreme Value (GEV) distribution to model the Risk Neutral Density (RND) function provides a flexible framework that captures the negative skewness and excess kurtosis of returns, and also delivers the market implied tail index of asset returns. We obtain an original analytical closed form solution for the Harrison and Pliska (1981) no arbitrage equilibrium price for the European option in the case of GEV asset returns. The GEV based option prices successfully remove the well known pricing bias of the Black-Scholes model. We explain how the implied tail index is efficacious at identifying the fat tailed behaviour of losses and hence the left skewness of the price RND functions, particularly around crisis events

Surface alterations produced in grinding of austempered ductile iron

The technological advances achieved in recent decades have allowed to obtain cast parts of ductile iron with no metallurgical defects and of complex shapes and dimensions very close to the final ones. Heat treatments have enabled to obtain ADI within a wide range of mechanical properties. After properly choosing the processing variables, the most suitable combination of strength and toughness can be attained for each application. When restrictive dimensional or shape accuracy is required, a high precision machining process, such as grinding, is used. This process induces significant temperature gradients and surface plastic deformations which could affect the surface characteristics. The aim of this paper is to analyze the effects of grinding on power consumption, surface characteristics, roughness and distortion on ADI plates grade 2 and 5. The results indicate that it is possible to achieve excellent surface finishes with moderate power consumption and low residual stresses and distortions.Fil: Sosa, Amadeo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigación En Ciencia y Tecnología de Materiales (i); Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; ArgentinaFil: Echeverría, M. D.. Universidad Nacional de Mar del Plata. Facultad de Ingenieria. Departamento de Mecanica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigación en Ciencia y Tecnología de Materiales (i); Argentin

Forecasting Extreme Volatility of FTSE-100 With Model Free VFTSE, Carr-Wu and Generalized Extreme Value (GEV) Option Implied Volatility Indices

Since its introduction in 2003, volatility indices such as the VIX based on the model-free implied volatility (MFIV) have become the industry standard for assessing equity market volatility. MFIV suffers from estimation bias which typically underestimates volatility during extreme market conditions due to sparse data for options traded at very high or very low strike prices, Jiang and Tian (2007). To address this problem, we propose modifications to the CBOE MFIV using Carr and Wu (2009) moneyness based interpolations and extrapolations of implied volatilities and so called GEV-IV derived from the Generalised Extreme Value (GEV) option pricing model of Markose and Alentorn (2011). GEV-IV gives the best forecasting performance when compared to the model-free VFTSE, Black-Scholes IV and the Carr-Wu case, for realised volatility of the FTSE-100, both during normal and extreme market conditions in 2008 when realised volatility peaked at 80%. The success of GEV-IV comes from the explicit modelling of the implied tail shape parameter and the time scaling of volatility in the risk neutral density which can rapidly and flexibly reflect extreme market sentiments present in traded option prices

Dynamic Learning, Herding and Guru Effects in Networks

It has been widely accepted that herding is the consequence of mimetic responses by agents interacting locally on a communication network. In extant models, this communication network linking agents, by and large, has been assumed to be fixed. In this paper we allow it to evolve endogenously by enabling agents to adaptively modify the weights of their links to their neighbours by reinforcing 'good' advisors and breaking away from 'bad' advisors with the latter being replaced randomly from the remaining agents. The resulting network not only allows for herding of agents, but crucially exhibits realistic properties of socio-economic networks that are otherwise difficult to replicate: high clustering, short average path length and a small number of highly connected agents, called 'gurus'. These properties are now well understood to characterize 'small world networks' of Watts and Strogatz (1998)

NDN, CoAP, and MQTT: A Comparative Measurement Study in the IoT

This paper takes a comprehensive view on the protocol stacks that are under debate for a future Internet of Things (IoT). It addresses the holistic question of which solution is beneficial for common IoT use cases. We deploy NDN and the two popular IP-based application protocols, CoAP and MQTT, in its different variants on a large-scale IoT testbed in single- and multi-hop scenarios. We analyze the use cases of scheduled periodic and unscheduled traffic under varying loads. Our findings indicate that (a) NDN admits the most resource-friendly deployment on nodes, and (b) shows superior robustness and resilience in multi-hop scenarios, while (c) the IP protocols operate at less overhead and higher speed in single-hop deployments. Most strikingly we find that NDN-based protocols are in significantly better flow balance than the UDP-based IP protocols and require less corrective actions

Designing large value payment systems: An agent-based approach

The purpose of this paper is to show how agent-based simulations of payment systems can be used to aid central bankers and payment system operators in thinking about the appropriate design of payment settlement systems to minimise risk and increase their efficiency. Banks, which we model as the 'agents', are capable of a degree of autonomy with which to respond to payment system rules and adopt a strategy that determines how much collateral to post with the central bank at the start of the day (equivalently how much liquidity to borrow intraday from the central bank) and when to send payment orders to the central processor. An interbank payment system with costly liquidity requires banks to solve an intraday cash management problem, minimising their liquidity and delay costs subject to their beliefs about what the other banks are doing. Some preliminary results are given on how banks learn to endogenously determine how much liquidity to post in the interbank liquidity management game

Application of approximation theory by nonlinear manifolds in Sturm-Liouville inverse problems

We give here some negative results in Sturm-Liouville inverse theory, meaning that we cannot approach any of the potentials with $m+1$ integrable derivatives on $\mathbb{R}^+$ by an $\omega$-parametric analytic family better than order of $(\omega\ln\omega)^{-(m+1)}$. Next, we prove an estimation of the eigenvalues and characteristic values of a Sturm-Liouville operator and some properties of the solution of a certain integral equation. This allows us to deduce from [Henkin-Novikova] some positive results about the best reconstruction formula by giving an almost optimal formula of order of $\omega^{-m}$.Comment: 40 page

La reunión en Roma de los años 1550-1551 y la elaboración de las Constituciones de la Compañía de Jesús (Primera parte)

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¿Intento de una Congregación General de la Compañía de Jesús en el año 1545?

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