financial time-series volatility estimation
Modelling and Forecasting Tourist Arrivals to Cambodia: An Application of ARIMA-GARCH Approach
... In financial and economic time series estimation and prediction, the most common models which were typically and frequently employed are autoregressive conditional heteroskedasticity or ...
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Natural Cubic Spline Model for Estimating Volatility
... Abstract— Volatility measures the dispersion of returns for a market variable since a reasonable estimation of the volatility is an appropriate starting point for assessing investment risks and ...
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S Transform Based Analysis for Stock Market Volatility Estimation
... volatile financial time series ...The time bound data exhibit the irrational price movement, whose part of a pattern is usually called ...multivariate time series problems are ...
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Applied financial econometric analysis: The dynamics of swap spreads and the estimation of volatility
... the financial crisis subsided at the begin ning of 1999, the instability in swap markets ...the time series properties of spreads will be studied in the next ...
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Using CAViaR models with implied volatility for value-at-risk estimation
... implied volatility outperforms historical volatility as a predictor of the realised volatility in a large majority of 35 futures markets including equity indices, interest rates, currencies, ...
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Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation
... the estimation procedure, namely the dominance of the fundamental- ists and the discrepancy between the values of the parametric estimation as compared to the Hill estimates, are not in harmony with our ...
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Essays on Financial and Time Series Econometrics.
... given time grid, even in the form of equidistant ...frequency financial data is that they are observed at times that are random and not evenly ...is time endogeneity in the price sampling times, as ...
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Volatility and duration models for financial intaday data: formulation, estimation and evaluation
... find time series consisting of count data. Such series record the number of events of a particular type occurring in a given ...each time period is relatively ...
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Bayesian Inference of Stochastic Volatility Models and Applications in Risk Management.
... of financial time series distribution is that it often displays a heavy tail with asymmetry and positive ...stochastic volatility model with Skewed Generalized Error Distribution that ...
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Modeling Exchange Rate Volatility: Application of the GARCH and EGARCH Models
... Financial time series such as, exchange rates, stock returns and other financial series are known to exhibit certain stylized patterns which are crucial for correct model specification, ...
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Spatial modelling and volatility matrix estimation in high dimension statistics with financial applications
... efficient estimation but no complicated parameter space is ...square estimation is applied for the coefficients of linear combinations and ...our time-lagged spatial model causing least square type ...
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Financial Integration, Volatility of Financial Flows and Macroeconomic Volatility
... between financial integration and the volatility of total output and its main components may be summarized as ...between financial integration and the volatility of total ...international ...
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Unit Root Tests in Time Series and Stochastic Volatility Models
... The remainder of the article is organized into seven sections. The next section discusses the application of the standard unit root tests to the volatility process and presents two estimation methods used ...
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A study on the volatility forecast of the US housing market in the 2008 crisis
... In this paper, the in-sample estimation of the real estates related financial data series are compared with the out-of-sample conditional mean and volatility forecast performance of the [r] ...
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Fractal Geometry of Financial Time Series
... Because the correlations play a crucial role in shaping the basic distributions, it seems the more remarkable that the price records analyzed here have such a large degree of distributional self-similarity. It implies ...
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Spurious long range dependence: evidence from Malaysian equity markets
... For KLCI, FIN, IND and PRP indices, the pre-period analysis included the events such as the Asian financial and currency crises. Exceptional, only the PLN index indicated short-range dependence with the value ...
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Volatility Forecasting using Machine Learning and Time Series Techniques
... existing time series data are designed to accommodate simple seasonal patterns with a small integer-valued period (reminiscent of 12 for month-to-month data or 4 for quarterly ...seasonal time ...
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Testing extreme dependence in financial time series
... initial time for a period of 4 weeks are shown in Figure 6, Figure 7, and in Figure 8, with a moving window of 3 years (about 156 data points) and 4 years (about 208 data points), and step of one month (about 4 ...
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Quasi Bayesian estimation of time varying volatility in DSGE models
... model’s volatility estimates are much smoother, as illustrated in Figure 1, while the SV-DSGE delivers more noisy and ragged ...more time variation in the TFP shock’s volatility which a¤ects ...
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Modelling and Analysis on Noisy Financial Time Series
... There are two parameters in AR to be tuned, i.e., the length of prediction (output), and the order p in AR. The order of p is required to be tuned in advance. Also it is not easy to evaluate the quality of the AR model, ...
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