scholarly journals Realized Semicovariances

Econometrica ◽  
2020 ◽  
Vol 88 (4) ◽  
pp. 1515-1551
Author(s):  
Tim Bollerslev ◽  
Jia Li ◽  
Andrew J. Patton ◽  
Rogier Quaedvlieg
Keyword(s):  
High Frequency ◽  
Asymptotic Properties ◽  
Sampling Interval ◽  
Asymptotic Results ◽  
First Order ◽  
Economic Information ◽  
Stochastic Correlation ◽  
Realized Covariance ◽  
Return Variance ◽  
Portfolio Return

We propose a decomposition of the realized covariance matrix into components based on the signs of the underlying high‐frequency returns, and we derive the asymptotic properties of the resulting realized semicovariance measures as the sampling interval goes to zero. The first‐order asymptotic results highlight how the same‐sign and mixed‐sign components load differently on economic information related to stochastic correlation and jumps. The second‐order asymptotic results reveal the structure underlying the same‐sign semicovariances, as manifested in the form of co‐drifting and dynamic “leverage” effects. In line with this anatomy, we use data on a large cross‐section of individual stocks to empirically document distinct dynamic dependencies in the different realized semicovariance components. We show that the accuracy of portfolio return variance forecasts may be significantly improved by exploiting the information in realized semicovariances.

scholarly journals Forecasting security's volatility using low-frequency historical data, high-frequency historical data and option-implied volatility

2020 ◽  
Author(s):  
Huiling Yuan ◽  
Yong Zhou ◽  
Zhiyuan Zhang ◽  
Xiangyu Cui
Keyword(s):  
High Frequency ◽  
Implied Volatility ◽  
Historical Data ◽  
Simulation Analysis ◽  
Asymptotic Properties ◽  
Low Frequency ◽  
Sampling Interval ◽  
Forecasting Performance ◽  
Quasi Maximum Likelihood ◽  
Iv Model

Low-frequency historical data, high-frequency historical data and option data are three major sources, which can be used to forecast the underlying security's volatility. In this paper, we propose two econometric models, which integrate three information sources. In GARCH-It\^{o}-OI model, we assume that the option-implied volatility can influence the security's future volatility, and the option-implied volatility is treated as an observable exogenous variable. In GARCH-It\^{o}-IV model, we assume that the option-implied volatility can not influence the security's volatility directly, and the relationship between the option-implied volatility and the security's volatility is constructed to extract useful information of the underlying security. After providing the quasi-maximum likelihood estimators for the parameters and establishing their asymptotic properties, we also conduct a series of simulation analysis and empirical analysis to compare the proposed models with other popular models in the literature. We find that when the sampling interval of the high-frequency data is 5 minutes, the GARCH-It\^{o}-OI model and GARCH-It\^{o}-IV model has better forecasting performance than other models.

The Korteweg-de Vries equation and water waves. Solutions of the equation. Part 1

1973 ◽  
Vol 59 (4) ◽  
pp. 721-736 ◽  
Author(s):  
Harvey Segur
Keyword(s):  
Water Waves ◽  
Large Time ◽  
Vries Equation ◽  
Asymptotic Properties ◽  
Series Representation ◽  
Convergent Series ◽  
Asymptotic Results ◽  
De Vries ◽  
Method Of Solution

The method of solution of the Korteweg–de Vries equation outlined by Gardneret al.(1967) is exploited to solve the equation. A convergent series representation of the solution is obtained, and previously known aspects of the solution are related to this general form. Asymptotic properties of the solution, valid for large time, are examined. Several simple methods of obtaining approximate asymptotic results are considered.

scholarly journals Limit Theory for High Frequency Sampled MCARMA Models

2014 ◽  
Vol 46 (3) ◽  
pp. 846-877 ◽  
Author(s):  
Vicky Fasen
Keyword(s):  
Asymptotic Behavior ◽  
High Frequency ◽  
Lévy Process ◽  
Asymptotic Properties ◽  
Domain Of Attraction ◽  
Levy Process ◽  
Sample Variance ◽  
Limit Theory ◽  
Second Moments ◽  
Time Grid

We consider a multivariate continuous-time ARMA (MCARMA) process sampled at a high-frequency time grid {hn, 2hn,…, nhn}, where hn ↓ 0 and nhn → ∞ as n → ∞, or at a constant time grid where hn = h. For this model, we present the asymptotic behavior of the properly normalized partial sum to a multivariate stable or a multivariate normal random vector depending on the domain of attraction of the driving Lévy process. Furthermore, we derive the asymptotic behavior of the sample variance. In the case of finite second moments of the driving Lévy process the sample variance is a consistent estimator. Moreover, we embed the MCARMA process in a cointegrated model. For this model, we propose a parameter estimator and derive its asymptotic behavior. The results are given for more general processes than MCARMA processes and contain some asymptotic properties of stochastic integrals.

scholarly journals Detecting gas leakage using high-frequency signals generated by air-gun arrays

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. A7-A12 ◽  
Author(s):  
Martin Landrø ◽  
Fredrik Hansteen ◽  
Lasse Amundsen
Keyword(s):  
High Frequency ◽  
Field Experiments ◽  
Water Layer ◽  
Sampling Interval ◽  
Acoustic Energy ◽  
Storage Site ◽  
High Frequency Signal ◽  
Gas Leakage ◽  
Temporal Sampling ◽  
Air Gun

Recent field experiments have demonstrated that marine air-gun arrays create acoustic energy greater than 1 kHz. We have suggested to use the high-frequency signal as a source to look for gas leakage at, for instance, a producing hydrocarbon field, or a [Formula: see text] storage site in which the field is covered by permanent acoustic sensors at the seabed, often referred to as a permanent reservoir monitoring field. The only needed modification is that the temporal sampling interval for the receivers is decreased to 0.1 ms (in contrast to the normal sampling interval of 1 or 2 ms), to ensure that the system is capable of recording signals up to 5 kHz. We suggest using numerous fixed receivers at the seabed to detect a gas chimney by simple high-pass filtering and subsequent transmission type analysis of the recorded signals. We think this method might serve as an elegant, precise, and very cost-effective way to detect gas leakage into the water layer.

scholarly journals Realized Multi-Power Variation Process for Jump Detection in the Nigerian All Share Index

2021 ◽  
Vol 52 (3) ◽  
pp. 397-412
Author(s):  
Mabel Adeosun ◽  
Olabisi Ugbebor
Keyword(s):  
Stochastic Volatility ◽  
Stochastic Models ◽  
Asymptotic Properties ◽  
Higher Order ◽  
Asymptotic Results ◽  
Jump Detection ◽  
Limit Distributions ◽  
Price Process ◽  
Variation Process ◽  
Asymptotic Variances

In this paper, we studied the particular cases of higher-order realized multipower variation process, their asymptotic properties comprising the probability limits and limit distributions were highlighted. The respective asymptotic variances of the limit distributions were obtained and jump detection models were developed from the asymptotic results. The models were obtained from the particular cases of the higher-order of the realized multipower variation process, in a class of continuous stochastic volatility semimartingale process. These are extensions of the method of jump detection by Barndorff-Nielsen and Shephard (2006), for large discrete data. An Empirical Application of the models to the Nigerian All Share Index (NASI) data shows that the models are robust to jumps and suggest that stochastic models with added jump components will give a better representation of the NASI price process.

scholarly journals Sorting using complete subintervals and the maximum number of runs in a randomly evolving sequence: Extended abstract.

2007 ◽  
Vol DMTCS Proceedings vol. AH,... (Proceedings) ◽  
Author(s):  
Svante Janson
Keyword(s):  
Order Term ◽  
Combinatorial Problem ◽  
Random Order ◽  
Priority Queues ◽  
Sorting Algorithm ◽  
Asymptotic Results ◽  
First Order ◽  
Asymptotically Normal ◽  
International Audience ◽  
Space Requirements

International audience We study the space requirements of a sorting algorithm where only items that at the end will be adjacent are kept together. This is equivalent to the following combinatorial problem: Consider a string of fixed length n that starts as a string of 0's, and then evolves by changing each 0 to 1, with the n changes done in random order. What is the maximal number of runs of 1's? We give asymptotic results for the distribution and mean. It turns out that, as in many problems involving a maximum, the maximum is asymptotically normal, with fluctuations of order $n^{1/2}$, and to the first order well approximated by the number of runs at the instance when the expectation is maximized, in this case when half the elements have changed to 1; there is also a second order term of order $n^{1/3}$. We also treat some variations, including priority queues and sock-sorting.

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