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Found 618 results for '"Realized variance"', showing 1-10
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  1. Hiroyuki Kawakatsu (2022): Modeling Realized Variance with Realized Quarticity
    This paper proposes a model for realized variance that exploits information in realized quarticity. The realized variance and quarticity measures are both highly persistent and highly correlated with each other. The proposed model incorporates information from the observed realized quarticity process via autoregressive conditional variance dynamics.
    RePEc:gam:jstats:v:5:y:2022:i:3:p:50-880:d:909009  Save to MyIDEAS
  2. Rangan Gupta & Christian Pierdzioch (2021): Uncertainty, Spillovers, and Forecasts of the Realized Variance of Gold Returns
    Using data for the group of G7 countries and China for the sample period 1996Q1 to 2020Q4, we study the role of uncertainty and spillovers for the out-of-sample forecasting of the realized variance of gold returns and its upside (good) and downside (bad) counterparts.
    RePEc:pre:wpaper:202137  Save to MyIDEAS
  3. Asger Lunde & Peter Reinhard Hansen (2004): Realized Variance and IID Market Microstructure Noise
    We analyze the properties of a bias-corrected realized variance (RV) in the presence of iid market microstructure noise.
    RePEc:ecm:nasm04:526  Save to MyIDEAS
  4. MEDDAHI, Nour (2002): ARMA Representation of Integrated and Realized Variances
    This paper derives the ARMA representation of integrated and realized variances when the spot variance depends linearly on two autoregressive factors, i.e., SR SARV(2) models. ... We also study the leverage effect case, the relationship between weak GARCH representation of returns and the ARMA representation of realized variances. ... Hence, the positiveness of the expected values of integrated or realized variances is not guaranteed. We also find that for some frequencies of observations, the continuous time model parameters may be weakly or not identified through the ARMA representation of realized variances.
    RePEc:mtl:montde:2002-20  Save to MyIDEAS
  5. Nour MEDDAHI (2002): Arma Representation Of Integrated And Realized Variances
    This paper derives the ARMA representation of integrated and realized variances when the spot variance depends linearly on two autoregressive factors, i.e., SR-SARV(2) models. ... We also study the leverage effect case, the relationship between weak GARCH representation of returns and the ARMA representation of realized variances. ... Hence, the positiveness of the expected values of integrated or realized variances is not guaranteed. We also find that for some frequencies of observations, the continuous time model parameters may be weakly or not identified through the ARMA representation of realized variances.
    RePEc:mtl:montec:20-2002  Save to MyIDEAS
  6. Christian Pierdzioch & Sebastian Rohloff & Roland von Campe (2023): The stance of U.S. monetary policy and the realized variance of gold-price returns
    We use a quantile-regression model to study the association between the stance of U.S. monetary policy and the realized variance of gold-price. ... During a hawkish policy regime, tighter monetary policy is associated with a lower realized variance at the upper quantiles its conditional distribution. During the recent dovish policy regime, in contrast, the link between tighter monetary policy and the realized variance of gold price returns at the upper quantiles of its conditional distributionis positive.
    RePEc:ebl:ecbull:eb-22-00723  Save to MyIDEAS
  7. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian (2021): Do oil-price shocks predict the realized variance of U.S.
    We examine, using aggregate and sectoral U.S. data for the period 2008–2020, the predictive power of disentangled oil-price shocks for Real Estate Investment Trusts (REITs) realized market variance via the heterogeneous auto-regressive realized variance (HAR-RV) model. In-sample tests show that demand and financial-market-risk shocks contribute to a larger extent to the overall fit of the model than supply shocks, where the in-sample transmission of the impact of the shocks mainly operates through their significant effects on realized upward (“good”) variance. Out-of-sample tests corroborate the significant predictive value of demand and financial-market-risk shocks for realized variance and its upward counterpart at a short, medium, and long forecast horizon, for various recursive-estimation windows, for realized volatility (that is, the square root of realized variance), for a shorter sub-sample period that excludes the recent phase of exceptionally intense oil-market turbulence, and for an extended benchmark model that features realized higher-order moments, realized jumps, and a leverage effect as control variables. We also study a quantiles-based extension of the HAR-RV model, and we analyze the economic benefits of using shocks for realized-variance forecasting.
    RePEc:eee:eneeco:v:104:y:2021:i:c:s0140988321005429  Save to MyIDEAS
  8. Matteo Bonato & Rangan Gupta & Christian Pierdzioch (2020): Do Oil-Price Shocks Predict the Realized Variance of U.S.
    We examine, using aggregate and sectoral U.S. data for the period 2008-2020, the predictive power of disentangled oil-price shocks for Real Estate Investment Trusts (REITs) realized market variance via the heterogeneous auto-regressive realized variance (HAR-RV) model. In-sample tests show that demand and financial-market risk shocks contribute to a larger extent to the overall fit of the model than supply shocks, where the in-sample transmission of the impact of the shocks mainly operates through their significant effects on realized upward (good) variance. Out-of-sample tests corroborate the significant predictive value of demand and risk shocks for realized variance and its upward counterpart at a short, medium, and long forecast horizon, for various recursive-estimation windows, for realized volatility (that is, the square root of realized variance), for a shorter sub-sample period that excludes the recent phase of exceptionally intense oil-market turbulence, and for an extended benchmark model that features realized higher-order moments, realized jumps, and a leverage effect as control variables.
    RePEc:pre:wpaper:2020100  Save to MyIDEAS
  9. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias (2023): Improving variance forecasts: The role of Realized Variance features
    In this paper, we effectively extend the Realized-EGARCH (R-EGARCH) framework by allowing the conditional variance process to incorporate exogenous variates related to different observable features of Realized Variance (RV). ... These specifications incorporate realized semi-variances, heterogeneous long-memory effects of RV, and jump variation. ... This can better filter the true distribution of the return innovations, and thus can more accurately estimate their effects on the variance process.
    RePEc:eee:intfor:v:39:y:2023:i:3:p:1221-1237  Save to MyIDEAS
  10. Anne Opschoor & André Lucas (2019): Observation-driven Models for Realized Variances and Overnight Returns
    Applying our new model to 100 stocks of the S&P 500 during the period 2001-2014 and evaluating (in-sample and out-of-sample) in terms of Value-at-Risk and Expected Shortfall, we find our model outperforms alternatives like the HEAVY model that uses close-to-close returns and realized variances, and models treating close-to-open en open-to-close returns as separate processes.
    RePEc:tin:wpaper:20190052  Save to MyIDEAS
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