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Short-term forecasting with mixed-frequency data: A MIDASSO approach

Siliverstovs, Boriss - KOF Swiss Economic Institute, Department of Management, … - 2015

-Sampling approach (U-MIDAS) (see Foroni et al., 2015; Castle et al., 2009; Bec and Mogliani, 2013), and the LASSO-type penalised …

Persistent link: https://www.econbiz.de/10011196718

Dissecting the Purchasing Managers’ Index: Are all relevant components included? Are all included components relevant?

Siliverstovs, Boriss - KOF Swiss Economic Institute, Department of Management, … - 2015

We apply the novel approach of Siliverstovs (2015) to modelling data sampled at different frequencies in order to scrutinise the composition of one of the most influential economic indicators in Switzerland. The Purchasing Managers' Index consists of eight sub-indices out of which only five...

Persistent link: https://www.econbiz.de/10011203043

Predicting quarterly aggregates with monthly indicators

Winkelried, Diego - Banco Central de Reserva del Perú - 2012

the so-called Mixed Data Sampling (MIDAS) approach that directly exploits the information content of monthly indicators to … smoothness priors in a distributed lag model, that weakens the restrictions the traditional MIDAS approach imposes on the data to …-nested specifications. It is found that the MIDAS approach is able to timely identify, from monthly information, important signals of the …

Persistent link: https://www.econbiz.de/10010819837

Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach

Girardin, Eric; Joyeux, Roselyne - In: Economic Modelling 34 (2013) C, pp. 59-68

In order to shed new light on the influence of volume and economic fundamentals on the long-run volatility of the Chinese stock market we follow the methodology introduced by Engle et al. (2009) and Engle and Rangel (2008) to account for the effects of macro fundamentals, and augment it with...

Persistent link: https://www.econbiz.de/10010709340

Evaluating Value-at-Risk Measures in Presence of Long Memory Conditional Volatility

Caporin, Massimiliano - 2008

We compare the value-at-risk (VaR) bounds obtained from several models fitted to simulated long memory conditional variance processes. We show that most VaR comparison tests and loss functions may lead to the choice of a misspecified model that produces incorrect risk conditional coverage. The...

Persistent link: https://www.econbiz.de/10012768126

Volatility Forecasts for the Mexican Peso - U.S. Dollar Exchange Rate : An Empirical Analysis of GARCH, Option Implied and Composite Forecast Models

Benavides, Guillermo - 2008

The volatility accuracy of several volatility forecast models is examined for the case of daily spot returns for the Mexican peso - US Dollar exchange rate. The models applied are univariate GARCH, a multi-variate GARCH (BEKK model), option implied volatilities, and a composite forecast model....

Persistent link: https://www.econbiz.de/10012768229

Predictive Accuracy of Futures Options Implied Volatility : The Case of the Exchange Rate Futures Mexican Peso-U.S. Dollar

Benavides, Guillermo - 2008

There has been substantial research effort aimed to forecast futures price return volatilities of financial assets. A significant part of the literature shows that volatility forecast accuracy is not easy to estimate regardless of the forecasting model applied. This paper examines the volatility...

Persistent link: https://www.econbiz.de/10012727671

Autoregressive Conditional Tail Behavior and Results on Government Bond Yield Spreads

Wagner, Niklas - 2005

Previous evidence in empirical finance indicates the potential usefulness of modeling time-variation particularly in the tails of speculative return distributions. Based on results from extreme value theory, the present paper proposes a fixed changepoint Pareto-type autoregressive conditional...

Persistent link: https://www.econbiz.de/10012737381

Risk Management of Hedge Funds Using Fuzzy Neural- and Genetic Algorithms

Glaffig, Clemens - 2004

The article investigates the use of adaptive learning algorithms in constructing dynamic portfolios replicating the return characteristics of a given hedge fund. The emphasis is on out of sample conditional predictive capabilites as necessary to serve as a valuable risk management tool, rather...

Persistent link: https://www.econbiz.de/10012737991

A Simple Two-Component Model for the Distribution of Intra-Day Returns

Coroneo, Laura - 2011

We model the conditional distribution of high frequency financial returns by means of a two-component quantile regression model. Using three years of 30-minute returns, we show that the conditional distribution depends on past returns and on the time of the day. Two practical applications...

Persistent link: https://www.econbiz.de/10012714534

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