financial time series forecasts
Robust volatility forecasts and model selection in financial time series
... a series of fits of subsets of increasing size which treat the observations which are outside the subsets as ...in financial time series all the data are always available and the problem of ...
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Essays on Forecasting Financial and Economic Time Series
... tural change. It is not surprising that forecasting an i.i.d. process, as illus- trated in panel (a) of Figure 4.B.3, would require accounting for long past and the benchmark sample mean should perform the best. ...
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Combinations of time series forecasts: when and why are they beneficial?.
... individual forecasts and similar to the linear ...individual forecasts are combined with a one layered neural network with four nodes, using a data set of one and a half years of financial data ...
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Predicting financial volatility: High-frequency time -series forecasts vis-à-vis implied volatility
... time of the closing prices of the option and underlying asset may differ 3 . Second, Fleming et al. (1995) point out that an index lags its true value, since some of the quotes of the stocks underlying the index ...
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Evolution of Energy Strategies in Turkey: Forecasts by Time Series
... The time series, partial autocorrelation function (PACF) and autocorrelation function (ACF) graphs help for determining whether the datasets are stationary or ...the series. For the non- stationary ...
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A Hybrid Approach for Modeling Financial Time Series
... forecasting time series in financial ...for time series forecasting based on a hybrid combination of ARMA and Gene Expression Programming (GEP) induced ...models. Time ...
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Using CAViaR models with implied volatility for value-at-risk estimation
... as series of financial returns tend to exhibit volatility ...alternative time series modelling approaches have been presented, including the use of GARCH volatility models, extreme value ...
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Essays in Financial Time Series
... In the third chapter, a Monte Carlo experiment is conducted to investigate the relative out- of-sample predictive ability of a class of parsimonious conditional variance models when either a structural break or long-run ...
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Neural Networks For Financial Time Series
... Forecasting the future situations in a business environment determines many critical business decisions like procurement of supplies and equipment, inventory control, product demand estimation, cash requirement ...
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Essays on Financial and Time Series Econometrics.
... estimating the bias allows taking advantage of the informational content of time endogeneity, which leads to an efficiency gain and narrower confidence bounds. The finite sample properties of the Laplace estimator ...
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Escalation of Forecasting Accuracy through Linear Combiners of Predictive Models
... in financial time series is a challenging and complex task as it is highly associated with uncertainties, nonlinearity, etc and talks to the current economical as well as political ...multiple ...
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A Neuro-wavelet Method for the Forecasting of Financial Time Series
... on forecasts that fell under the domain of intra-day ...a time interval, given in minutes, that can capture intra-day price changes, [128, 256] ...log-return time series to account for the ...
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Cointegration Analysis of Financial Time Series Data
... a time span of two ...cointegrated series’ found and was traded until cointegration ...lookback time can be chosen arbitrary it generally seems to hold that the longer the lookback is the more stable ...
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Modelling and Analysis on Noisy Financial Time Series
... of time series has at- tracted much attention from statistical and machine learning perspectives [1,2], with a variety of applications in different fields ...analyzing financial time ...
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Nonlinear time series analysis in financial applications
... The estimated nominal term premia, defined in equation (V.20), are depicted in Figure V-17 and Figure V-18 for yields with 5-year and 10-year maturities. Notice the dotted lines represent the difference between the ...
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Testing extreme dependence in financial time series
... In this section, simulations under different scenarios are given. We compare the performance of our method with those of Censored Likelihood Method (CLM) of Ledford and Tawn (1996), Extremogram of Davis and Mikosch ...
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Frontiers in Time Series and Financial Econometrics: An Overview
... are time series and financial ...to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series ...in Time Series and ...
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Performance evaluation of series and parallel strategies for financial time series forecasting
... in financial time series forecasting is ...on time series forecasting and modeling widely use a combination of different models and metaheuristic optimization ...on time ...
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