885 resultados para Implied volatility (VIX)
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Assuming that daily spot exchange rates follow a martingale process, we derive the implied time series process for the vector of 30-day forward rate forecast errors from using weekly data. The conditional second moment matrix of this vector is modelled as a multivariate generalized ARCH process. The estimated model is used to test the hypothesis that the risk premium is a linear function of the conditional variances and covariances as suggested by the standard asset pricing theory literature. Little supportt is found for this theory; instead lagged changes in the forward rate appear to be correlated with the 'risk premium.'. © 1990.
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We use information from the television game show with the highest guaranteed average payoff in the United States, Hoosier Millionaire, to analyze risktaking in a high-stakes experiment. We characterize gambling decisions under alternative assumptions about contestant behavior and preferences, and derive testable restrictions on individual risk attitudes based on this characterization. We then use an extensive sample of gambling decisions to estimate distributions of risk-aversion parameters consistent with the theoretical restrictions and revealed preferences. We find that although most contestants display risk-averse preferences, the extent of the risk aversion implied by our estimates varies substantially with the stakes involved in the different decisions.
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We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.
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In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of maximizing the expected value of a payoff function when the underlying distribution is ambiguous and therefore robustness is relevant. Our primary objective is to develop this framework and relate it to the standard notion of robustness, which deals with only a single guarantee across one uncertainty set. First, we show that our approach connects closely to the theory of convex risk measures. We show that the complexity of this approach is equivalent to that of solving a small number of standard robust problems. We then investigate the conservatism benefits and downside probability guarantees implied by this approach and compare to the standard robust approach. Finally, we illustrate theme thodology on an asset allocation example consisting of historical market data over a 25-year investment horizon and find in every case we explore that relaxing standard robustness with soft robustness yields a seemingly favorable risk-return trade-off: each case results in a higher out-of-sample expected return for a relatively minor degradation of out-of-sample downside performance. © 2010 INFORMS.
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We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis. Time-varying parameters are linked to latent processes that are thresholded to induce zero values adaptively, providing natural mechanisms for dynamic variable inclusion/selection. We discuss Bayesian model specification, analysis and prediction in dynamic regressions, time-varying vector autoregressions, and multivariate volatility models using latent thresholding. Application to a topical macroeconomic time series problem illustrates some of the benefits of the approach in terms of statistical and economic interpretations as well as improved predictions. Supplementary materials for this article are available online. © 2013 Copyright Taylor and Francis Group, LLC.
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Quantity-based regulation with banking allows regulated firms to shift obligations across time in response to periods of unexpectedly high or low marginal costs. Despite its wide prevalence in existing and proposed emission trading programs, banking has received limited attention in past welfare analyses of policy choice under uncertainty. We address this gap with a model of banking behavior that captures two key constraints: uncertainty about the future from the firm's perspective and a limit on negative bank values (e.g. borrowing). We show conditions where banking provisions reduce price volatility and lower expected costs compared to quantity policies without banking. For plausible parameter values related to U.S. climate change policy, we find that bankable quantities produce behavior quite similar to price policies for about two decades and, during this period, improve welfare by about a $1 billion per year over fixed quantities. © 2012 Elsevier B.V.
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This paper describes a knowledge-based temporal representation of state transitions for industrial real-time systems. To allow expression of uncertainty, we shall define fluents as disjuncts of positive/negative time-varying properties. A state of the world is represented as a collection of fluents, which is usually incomplete in the sense that neither the positive form nor the negative form of some properties can be implied from it. The world under consideration is assumed to persist in a given state until an action(s) takes place to effect a transition of it into another state, where actions may either be instantaneous or durative. High-level causal laws are characterized in terms of relationships between actions and the involved world states. An effect completion axiom is imposed on each causal law to guarantee that all the fluents that can be affected by the performance of the corresponding action are governed. This completion requirement is practical for most industrial real-time applications and in fact provides a simple and effective treatment to the so-called frame problem.
A policy-definition language and prototype implementation library for policy-based autonomic systems
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This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics, and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing, and is used to demonstrate the simple and efficient use of the tools. The second example demonstrates more-advanced functionality, in the context of an envisioned multi-policy stock trading scheme which is sensitive to environmental volatility
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This paper presents a policy definition language which forms part of a generic policy toolkit for autonomic computing systems in which the policies themselves can be modified dynamically and automatically. Targeted enhancements to the current state of practice include: policy self-adaptation where the policy itself is dynamically modified to match environmental conditions; improved support for non autonomics-expert developers; and facilitating easy deployment of adaptive policies into legacy code. The policy definition language permits powerful expression of self-managing behaviours and facilitates a diverse policy behaviour space. Features include support for multiple versions of a given policy type, multiple configuration templates, and meta policies to dynamically select between policy instances. An example deployment scenario illustrates advanced functionality in the context of a multi policy stock trading system which is sensitive to environmental volatility.
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Financial modelling in the area of option pricing involves the understanding of the correlations between asset and movements of buy/sell in order to reduce risk in investment. Such activities depend on financial analysis tools being available to the trader with which he can make rapid and systematic evaluation of buy/sell contracts. In turn, analysis tools rely on fast numerical algorithms for the solution of financial mathematical models. There are many different financial activities apart from shares buy/sell activities. The main aim of this chapter is to discuss a distributed algorithm for the numerical solution of a European option. Both linear and non-linear cases are considered. The algorithm is based on the concept of the Laplace transform and its numerical inverse. The scalability of the algorithm is examined. Numerical tests are used to demonstrate the effectiveness of the algorithm for financial analysis. Time dependent functions for volatility and interest rates are also discussed. Applications of the algorithm to non-linear Black-Scholes equation where the volatility and the interest rate are functions of the option value are included. Some qualitative results of the convergence behaviour of the algorithm is examined. This chapter also examines the various computational issues of the Laplace transformation method in terms of distributed computing. The idea of using a two-level temporal mesh in order to achieve distributed computation along the temporal axis is introduced. Finally, the chapter ends with some conclusions.
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This study estimates default probabilities of 124 emerging countries from 1981 to 2002 as a function of a set of macroeconomic and political variables. The estimated probabilities are then compared with the default rates implied by sovereign credit ratings of three major international credit rating agencies (CRAs) – Moody's Investor's Service, Standard & Poor's and Fitch Ratings. Sovereign debt default probabilities are used by investors in pricing sovereign bonds and loans as well as in determining country risk exposure. The study finds that CRAs usually underestimate the risk of sovereign debt as the sovereign credit ratings from rating agencies are usually too optimistic.
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Purpose: This paper seeks to investigate the factors influencing the business performance of estate agency in England and Wales. Design/methodology/approach: The paper investigates the effect of housing market, company size and pricing policy on business performance in the estate agency sector in England and Wales. The analysis uses the survey data of Woolwich Cost of Moving Survey (a survey of transactions costs sponsored by the Woolwich/Barclays Bank) from 2003 to 2005 to test the hypothesis that the business performance of estate agency is affected by industry characteristics and firm factors. Findings: The empirical analysis indicates that the business performance of estate agency is subject to market environment volatility such as market uncertainty, housing market liquidity and house price changes. The firm factors such as firm size and the level of agency fee have no explanatory power in explaining business performance. The level of agency fee is positively associated with firm size, market environment and liquidity. Research limitations/implications: The research is limited to the data received and is based on a research project on transaction costs designed prior to this analysis. Originality/value: There is little other research that investigates the factors determining the business performance of estate agency, using consecutive data of three years across England and Wales. The findings are useful for practitioners and/or managers to allocate resources and adjust their business strategy to enhance business performance in the estate agency sector.
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Geochemical evidence invokes anoxic deep oceans until the terminal Neoproterozoic similar to 0.55 Ma, despite oxygenation of Earth's atmosphere nearly 2 Gyr earlier. Marine sediments from the intervening period suggest predominantly ferruginous (anoxic Fe(II)-rich) waters, interspersed with euxinia (anoxic H2S-rich conditions) along productive continental margins. Today, sustained biotic H2S production requires NO3- depletion because denitrifiers outcompete sulphate reducers. Thus, euxinia is rare, only occurring concurrently with (steady state) organic carbon availability when N-2-fixers dominate the production in the photic zone. Here we use a simple box model of a generic Proterozoic coastal upwelling zone to show how these feedbacks caused the mid-Proterozoic ocean to exhibit a spatial/temporal separation between two states: photic zone NO3- with denitrification in lower anoxic waters, and N-2-fixation- driven production overlying euxinia. Interchange between these states likely explains the varying H2S concentration implied by existing data, which persisted until the Neoproterozoic oxygenation event gave rise to modern marine biogeochemistry.
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The assimilation and regeneration of dissolved inorganic nitrogen, and the concentration of N2O, was investigated at stations located in the NW European shelf sea during June/July 2011. These observational measurements within the photic zone demonstrated the simultaneous regeneration and assimilation of NH4+, NO2− and NO3−. NH4+ was assimilated at 1.82–49.12 nmol N L−1 h−1 and regenerated at 3.46–14.60 nmol N L−1 h−1; NO2− was assimilated at 0–2.08 nmol N L−1 h−1 and regenerated at 0.01–1.85 nmol N L−1 h−1; NO3− was assimilated at 0.67–18.75 nmol N L−1 h−1 and regenerated at 0.05–28.97 nmol N L−1 h−1. Observations implied that these processes were closely coupled at the regional scale and nitrogen recycling played an important role in sustaining phytoplankton growth during the summer. The [N2O], measured in water column profiles, was 10.13 ± 1.11 nmol L−1 and did not strongly diverge from atmospheric equilibrium indicating that sampled marine regions where neither a strong source nor sink of N2O to the atmosphere. Multivariate analysis of data describing water column biogeochemistry and its links to N-cycling activity failed to explain the observed variance in rates of N-regeneration and N-assimilation, possibly due to the limited number of process rate observations. In the surface waters of 5 further stations, Ocean Acidification (OA) bioassay experiments were conducted to investigate the response of NH4+ oxidising and regenerating organisms to simulated OA conditions, including the implications for [N2O]. Multivariate analysis was undertaken which considered the complete bioassay dataset of measured variables describing changes in N-regeneration rate, [N2O] and the biogeochemical composition of seawater. While anticipating biogeochemical differences between locations, we aimed to test the hypothesis that the underlying mechanism through which pelagic N-regeneration responded to simulated OA conditions was independent of location and that a mechanistic understanding of how NH4+ oxidation, NH4+ regeneration and N2O production responded to OA could be developed. Results indicated that N-regeneration process responses to OA treatments were location specific; no mechanistic understanding of how N-regeneration processes respond to OA in the surface ocean of the NW European shelf sea could be developed.
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The assimilation and regeneration of dissolved inorganic nitrogen, and the concentration of N2O, was investigated at stations located in the NW European shelf sea during June/July 2011. These observational measurements within the photic zone demonstrated the simultaneous regeneration and assimilation of NH4+, NO2− and NO3−. NH4+ was assimilated at 1.82–49.12 nmol N L−1 h−1 and regenerated at 3.46–14.60 nmol N L−1 h−1; NO2− was assimilated at 0–2.08 nmol N L−1 h−1 and regenerated at 0.01–1.85 nmol N L−1 h−1; NO3− was assimilated at 0.67–18.75 nmol N L−1 h−1 and regenerated at 0.05–28.97 nmol N L−1 h−1. Observations implied that these processes were closely coupled at the regional scale and nitrogen recycling played an important role in sustaining phytoplankton growth during the summer. The [N2O], measured in water column profiles, was 10.13 ± 1.11 nmol L−1 and did not strongly diverge from atmospheric equilibrium indicating that sampled marine regions where neither a strong source nor sink of N2O to the atmosphere. Multivariate analysis of data describing water column biogeochemistry and its links to N-cycling activity failed to explain the observed variance in rates of N-regeneration and N-assimilation, possibly due to the limited number of process rate observations. In the surface waters of 5 further stations, Ocean Acidification (OA) bioassay experiments were conducted to investigate the response of NH4+ oxidising and regenerating organisms to simulated OA conditions, including the implications for [N2O]. Multivariate analysis was undertaken which considered the complete bioassay dataset of measured variables describing changes in N-regeneration rate, [N2O] and the biogeochemical composition of seawater. While anticipating biogeochemical differences between locations, we aimed to test the hypothesis that the underlying mechanism through which pelagic N-regeneration responded to simulated OA conditions was independent of location and that a mechanistic understanding of how NH4+ oxidation, NH4+ regeneration and N2O production responded to OA could be developed. Results indicated that N-regeneration process responses to OA treatments were location specific; no mechanistic understanding of how N-regeneration processes respond to OA in the surface ocean of the NW European shelf sea could be developed.