共查询到20条相似文献，搜索用时 15 毫秒
1.
Gurupdesh S. Pandher 《Journal of forecasting》2007,26(7):475-496
This paper presents a simple empirical approach to modeling and forecasting market option prices using localized option regressions (LOR). LOR projects market option prices over localized regions of their state space and is robust to assumptions regarding the underlying asset dynamics (e.g. log‐normality) and volatility structure. Our empirical study using 3 years of daily S&P500 options shows that LOR yields smaller out‐of‐sample pricing errors (e.g. 32% 1‐day‐out) relative to an efficient benchmark from the literature and produces option prices free of the volatility smile. In addition to being an efficient and robust option‐modeling and valuation tool for large option books, LOR provides a simple‐to‐implement empirical benchmark for evaluating more complex risk‐neutral models. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
2.
This paper proposes a robust multivariate threshold vector autoregressive model with generalized autoregressive conditional heteroskedasticities and dynamic conditional correlations to describe conditional mean, volatility and correlation asymmetries in financial markets. In addition, the threshold variable for regime switching is formulated as a weighted average of endogenous variables to eliminate excessively subjective belief in the threshold variable decision and to serve as the proxy in deciding which market should be the price leader. The estimation is performed using Markov chain Monte Carlo methods. Furthermore, several meaningful criteria are introduced to assess the forecasting performance in the conditional covariance matrix. The proposed methodology is illustrated using daily S&P500 futures and spot prices. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
3.
We propose a simple class of multivariate GARCH models, allowing for time‐varying conditional correlations. Estimates for time‐varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions without resorting to any variance reduction technique. We back‐test the models on a six‐dimensional exchange‐rate time series using different goodness‐of‐fit criteria and statistical tests. We collect empirical evidence of their strong predictive power, also in comparison to alternative benchmark procedures. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
4.
This paper investigates the informational content of unconventional monetary policies and its effect on commodity markets, adopting a nonlinear approach for modeling volatility. The main question addressed is how the Bank of England, Bank of Japan, and European Central Bank's (ECB's) announcements concerning monetary easing affect two major commodities: gold and silver. Our empirical evidence based on daily and high‐frequency data suggests that relevant information causes ambiguous valuation adjustments as well as stabilization or destabilization effects. Specifically, there is strong evidence that the Japanese Central Bank strengthens the precious metal markets by increasing their returns and by causing stabilization effects, in contrast to the ECB, which has opposite results, mainly due to the heterogeneous expectations of investors within these markets. These asymmetries across central banks' effects on gold and silver risk–return profile imply that the ECB unconventional monetary easing informational content opposes its stated mission, adding uncertainty in precious metals markets. 相似文献
5.
Jean‐Thomas Bernard Lynda Khalaf Maral Kichian Sebastien Mcmahon 《Journal of forecasting》2008,27(4):279-291
In examining stochastic models for commodity prices, central questions often revolve around time‐varying trend, stochastic convenience yield and volatility, and mean reversion. This paper seeks to assess and compare alternative approaches to modelling these effects, with focus on forecast performance. Three specifications are considered: (i) random‐walk models with GARCH and normal or Student‐t innovations; (ii) Poisson‐based jump‐diffusion models with GARCH and normal or Student‐t innovations; and (iii) mean‐reverting models that allow for uncertainty in equilibrium price. Our empirical application makes use of aluminium spot and futures price series at daily and weekly frequencies. Results show: (i) models with stochastic convenience yield outperform all other competing models, and for all forecast horizons; (ii) the use of futures prices does not always yield lower forecast error values compared to the use of spot prices; and (iii) within the class of (G)ARCH random‐walk models, no model uniformly dominates the other. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
6.
This paper adopts the backtesting criteria of the Basle Committee to compare the performance of a number of simple Value‐at‐Risk (VaR) models. These criteria provide a new standard on forecasting accuracy. Currently central banks in major money centres, under the auspices of the Basle Committee of the Bank of International settlement, adopt the VaR system to evaluate the market risk of their supervised banks. Banks are required to report VaRs to bank regulators with their internal models. These models must comply with Basle's backtesting criteria. If a bank fails the VaR backtesting, higher capital requirements will be imposed. VaR is a function of volatility forecasts. Past studies mostly conclude that ARCH and GARCH models provide better volatility forecasts. However, this paper finds that ARCH‐ and GARCH‐based VaR models consistently fail to meet Basle's backtesting criteria. These findings suggest that the use of ARCH‐ and GARCH‐based models to forecast their VaRs is not a reliable way to manage a bank's market risk. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
7.
Suppose Z t is the square of a time series Y t whose conditional mean is zero. We do not specify a model for Y t , but assume that there exists a p ×1 parameter vector Φ such that the conditional distribution of Z t | Z t ?1 is the same as that of , where Z t ?1=(Z t ?1,…,Z t ?p )T for some lag p ?1. Consequently, the conditional variance of Y t is some function of . To estimate Φ , we propose a robust estimation methodology based on density power divergences (DPD) indexed by a tuning parameter α ∈[0,1], which yields a continuum of estimators, , where α controls the trade‐off between robustness and efficiency of the DPD estimators. For each α , is shown to be strongly consistent. We develop data‐dependent criteria for the selection of optimal α and lag p in practice. We illustrate the usefulness of our DPD methodology via simulation studies for ARCH‐type models, where the errors are drawn from a gross‐error contamination model and the conditional variance is a linear and/or nonlinear function of . Furthermore, we analyze the Chicago Board Options Exchange Dow Jones volatility index data and show that our DPD approach yields viable models for the conditional variance, which are as good as, or superior to, ARCH/GARCH models and two other divergence‐based models in terms of in‐sample and out‐of‐sample forecasts. 相似文献
8.
Accurate modelling of volatility (or risk) is important in finance, particularly as it relates to the modelling and forecasting of value‐at‐risk (VaR) thresholds. As financial applications typically deal with a portfolio of assets and risk, there are several multivariate GARCH models which specify the risk of one asset as depending on its own past as well as the past behaviour of other assets. Multivariate effects, whereby the risk of a given asset depends on the previous risk of any other asset, are termed spillover effects. In this paper we analyse the importance of considering spillover effects when forecasting financial volatility. The forecasting performance of the VARMA‐GARCH model of Ling and McAleer (2003), which includes spillover effects from all assets, the CCC model of Bollerslev (1990), which includes no spillovers, and a new Portfolio Spillover GARCH (PS‐GARCH) model, which accommodates aggregate spillovers parsimoniously and hence avoids the so‐called curse of dimensionality, are compared using a VaR example for a portfolio containing four international stock market indices. The empirical results suggest that spillover effects are statistically significant. However, the VaR threshold forecasts are generally found to be insensitive to the inclusion of spillover effects in any of the multivariate models considered. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
9.
The paper deals with unobserved components in ARIMA models with GARCH errors, in the context of an actual application, namely seasonal adjustment of the monthly Spanish money supply series. The series shows clear evidence of (moderate) non-linearity, which does not disappear with simple outlier correction. The GARCH structure explains reasonably well the non-linearity, and this explanation is robust with respect to the GARCH specification. We look at the time variation of the standard error of the adjusted series estimator and show how it can be measured. Next, we look at the implications this variation has on short-term monetary control. The non-linearity seems to have a small effect in practice. It is further seen that the conditional variance of the GARCH process may, in turn, be decomposed into components. In fact, the conditional variance of the money supply series is the sum of a weak linear trend, a strong non-linear seasonal component, and a moderate non-linear irregular component. This information has policy implications: for example, there are periods in the year when policy can be more assertive because information is more precise. Finally, looking at the non-linear components of the money supply it is seen how linear combinations of non-linear series can produce series that behave linearly. 相似文献
10.
Mohammad Mohammadi 《Journal of forecasting》2017,36(7):859-866
The best prediction of generalized autoregressive conditional heteroskedasticity (GARCH) models with α‐stable innovations, α‐stable power‐GARCH models and autoregressive moving average (ARMA) models with GARCH in mean effects (ARMA‐GARCH‐M) are proposed. We present a sufficient condition for stationarity of α‐stable GARCH models. The prediction methods are easy to implement in practice. The proposed prediction methods are applied for predicting future values of the daily SP500 stock market and wind speed data. 相似文献
11.
In this paper we extend Taub (1979) approach for prediction in the context of the variance components model. The extension obtained is based on the two‐way random‐effect model with heteroskedasticity. Prediction functions are then obtained in three heteroskedasticity cases (heteroskedasticity on the individual term , heteroskedasticity on the composite term ?it, and heteroskedasticity on the temporal term ). Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
12.
Reliable correlation forecasts are of paramount importance in modern risk management systems. A plethora of correlation forecasting models have been proposed in the open literature, yet their impact on the accuracy of value‐at‐risk calculations has not been explicitly investigated. In this paper, traditional and modern correlation forecasting techniques are compared using standard statistical and risk management loss functions. Three portfolios consisting of stocks, bonds and currencies are considered. We find that GARCH models can better account for the correlation's dynamic structure in the stock and bond portfolios. On the other hand, simpler specifications such as the historical mean model or simple moving average models are better suited for the currency portfolio. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
13.
James Chong 《Journal of forecasting》2004,23(8):603-620
This paper compares daily exchange rate value at risk estimates derived from econometric models with those implied by the prices of traded options. Univariate and multivariate GARCH models are employed in parallel with the simple historical and exponentially weighted moving average methods. Overall, we find that during periods of stability, the implied model tends to overestimate value at risk, hence over‐allocating capital. However, during turbulent periods, it is less responsive than the GARCH‐type models, resulting in an under‐allocation of capital and a greater number of failures. Hence our main conclusion, which has important implications for risk management, is that market expectations of future volatility and correlation, as determined from the prices of traded options, may not be optimal tools for determining value at risk. Therefore, alternative models for estimating volatility should be sought. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
14.
CAO DengQing WANG JinLin & HUANG WenHu School of Astronautics Harbin Institute of Technology PO Box Harbin China 《中国科学:技术科学》2010,(2)
The concept of approximate inertial manifold (AIM) is extended to develop a kind of nonlinear order reduction technique for non-autonomous nonlinear systems in second-order form in this paper. Using the modal transformation, a large nonlinear dynamical system is split into a ‘master’ subsystem, a ‘slave’ subsystem, and a ‘negligible’ subsystem. Accordingly, a novel order reduction method (Method I) is developed to construct a low order subsystem by neglecting the ‘negligible’ subsystem and slaving the ‘slav... 相似文献
15.
陈华宏 《世界科技研究与发展》2012,34(5):857-859
编制了房地产开发企业项目管理层执行力调查问卷,通过对270份有效问卷随机分成的两个均等样本分别采用探索性因子分析和验证性因子分析方法.研究表明:房地产开发企业项目管理层执行力维度结构模型由领悟能力、计划能力、指挥能力、督导能力和创新能力等五维构成. 相似文献
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17.
Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub‐optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out‐of‐sample forecasting performance of various linear and GARCH‐type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decision making. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
18.
The paper derives the scalar special case of the well‐known BEKK multivariate GARCH model using a multivariate extension of the random coefficient autoregressive (RCA) model. This representation establishes the relevant structural and asymptotic properties of the scalar BEKK model using the theoretical results available in the literature for general multivariate GARCH. Sufficient conditions for the (direct) DCC model to be consistent with a scalar BEKK representation are established. Moreover, an indirect DCC model that is consistent with the scalar BEKK representation is obtained, and is compared with the direct DCC model using an empirical example. The paper shows, within an asset allocation and risk measurement framework, that the two models are similar in terms of providing parameter estimates and forecasting value‐at‐risk thresholds for equally weighted and minimum variance portfolios. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
19.
Returns of several US equity exchange‐traded funds on the days of major macroeconomic announcements are examined for the period of January 2009 to July 2013. The ARMA+GARCH model with external linear regression terms that describe announcement events and their surprises is used. It is found that mean daily returns may be notably higher on the announcement days than those for the buy‐and‐hold strategy, though their difference may be not statistically significant. The ISM Manufacturing Reports, Non‐Farm Payrolls, International Trade Balance, Index of Leading Indicators, Housing Starts, and Jobless Claims turn out to be the most statistically significant factors in the model. Three trading strategies that realize daily returns on the various macroeconomic announcement days are compared with the buy‐and‐hold strategy. The choice of announcements with statistically significant regression coefficients yields higher mean daily returns and better Sharpe ratios but possibly lower compound returns. Transaction costs may significantly affect profitability of these trading strategies. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
20.
In this article, we propose a regression model for sparse high‐dimensional data from aggregated store‐level sales data. The modeling procedure includes two sub‐models of topic model and hierarchical factor regressions. These are applied in sequence to accommodate high dimensionality and sparseness and facilitate managerial interpretation. First, the topic model is applied to aggregated data to decompose the daily aggregated sales volume of a product into sub‐sales for several topics by allocating each unit sale (“word” in text analysis) in a day (“document”) into a topic based on joint‐purchase information. This stage reduces the dimensionality of data inside topics because the topic distribution is nonuniform and product sales are mostly allocated into smaller numbers of topics. Next, the market response regression model for the topic is estimated from information about items in the same topic. The hierarchical factor regression model we introduce, based on canonical correlation analysis for original high‐dimensional sample spaces, further reduces the dimensionality within topics. Feature selection is then performed on the basis of the credible interval of the parameters' posterior density. Empirical results show that (i) our model allows managerial implications from topic‐wise market responses according to the particular context, and (ii) it performs better than do conventional category regressions in both in‐sample and out‐of‐sample forecasts. 相似文献