ESTIMATING VOLATILITY FUNCTIONALS WITH MULTIPLE TRANSACTIONS

2016 ◽  
Vol 33 (2) ◽  
pp. 331-365 ◽  
Author(s):  
Bing-Yi Jing ◽  
Zhi Liu ◽  
Xin-Bing Kong
Keyword(s):  
High Frequency ◽  
Ad Hoc ◽  
Asymptotic Properties ◽  
Financial Econometrics ◽  
Future Research ◽  
Simulation Studies ◽  
Recording Time ◽  
Integrated Volatility ◽  
Research Problems ◽  
Real World Problems

The phenomenon of multiple transactions at each recording time is a common occurrence for high-frequency financial data because of the heavy trading of the market and limitation of the recording mechanism. This situation has existed for many years, but has become more common in recent years because of heavier trading. Surprisingly, there have been few studies on this important issue, in spite of some ad hoc approaches to treat multiple transactions. In this paper we investigate how to handle multiple transactions, particularly in the context of estimating the integrated volatility and integrated quarticity, which are of great interest in financial econometrics. Two approaches are proposed for this purpose, and their asymptotic properties are investigated. Their performances are confirmed by simulation studies. The estimators are also applied to some real world problems. The work represents only the first step in this direction, and some future research problems are discussed.

scholarly journals A New Volatility Model: GQARCH-Ito Model

2020 ◽  
Author(s):  
Huiling Yuan ◽  
Yong Zhou ◽  
Lu Xu ◽  
Yulei Sun ◽  
Xiangyu Cui
Keyword(s):  
High Frequency ◽  
Historical Data ◽  
Asymptotic Properties ◽  
Low Frequency ◽  
Simulation Studies ◽  
Finite Sample ◽  
Volatility Model ◽  
Forecasting Performance ◽  
Volatility Asymmetry ◽  
Quasi Maximum Likelihood

Volatility asymmetry is a hot topic in high-frequency financial market. In this paper, we propose a new econometric model, which could describe volatility asymmetry based on high-frequency historical data and low-frequency historical data. After providing the quasi-maximum likelihood estimators for the parameters, we establish their asymptotic properties. We also conduct a series of simulation studies to check the finite sample performance and volatility forecasting performance of the proposed methodologies. And an empirical application is demonstrated that the new model has stronger volatility prediction power than GARCH-It\^{o} model in the literature.

scholarly journals Threshold Estimation for a Spectrally Negative Lévy Process

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Honglong You ◽  
Chuncun Yin
Keyword(s):  
High Frequency ◽  
Lévy Process ◽  
Asymptotic Properties ◽  
Levy Process ◽  
Simulation Studies ◽  
Finite Sample ◽  
Threshold Estimation ◽  
Lévy Measure ◽  
Spectrally Negative Lévy Process ◽  
Unknown Diffusion Coefficient

Consider a spectrally negative Lévy process with unknown diffusion coefficient and Lévy measure and suppose that the high frequency trading data is given. We use the techniques of threshold estimation and regularized Laplace inversion to obtain the estimator of survival probability for a spectrally negative Lévy process. The asymptotic properties are given for the proposed estimator. Simulation studies are also given to show the finite sample performance of our estimator.

High-Frequency Financial Econometrics

2014 ◽  
Author(s):  
Yacine Aït-Sahalia ◽  
Jean Jacod
Keyword(s):  
High Frequency ◽  
Practical Importance ◽  
Financial Econometrics ◽  
Trading Strategies ◽  
Financial Data ◽  
Jump Processes ◽  
High Frequency Trading ◽  
Microstructure Noise ◽  
Econometric Methods ◽  
Mathematical Foundations

High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. The book covers the mathematical foundations of stochastic processes, describes the primary characteristics of high-frequency financial data, and presents the asymptotic concepts that their analysis relies on. It also deals with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As the book demonstrates, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. The book approaches high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.

A Survey Study on Attacks in MANET Ad-Hoc Network

2017 ◽  
Vol 7 (7) ◽  
pp. 387
Author(s):  
. Harpal ◽  
Gaurav Tejpal ◽  
Sonal Sharma
Keyword(s):  
Routing Protocol ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Survey Study ◽  
Short Article ◽  
The People ◽  
Distance Vector ◽  
Mobile Ad Hoc ◽  
Real World Problems

In this time of instant units, Mobile Ad-hoc Network(MANET) has become an indivisible part for transmission for mobile devices. Therefore, curiosity about study of Mobile Ad-hoc Network has been growing because last several years. In this report we have mentioned some simple routing protocols in MANET like Destination Sequenced Distance Vector, Active Source Redirecting, Temporally-Ordered Redirecting Algorithm and Ad-hoc On Need Distance Vector. Protection is just a serious problem in MANETs because they are infrastructure-less and autonomous. Principal target of writing this report is to handle some simple problems and security considerations in MANET, operation of wormhole strike and acquiring the well-known routing protocol Ad-hoc On Need Distance Vector. This short article will be a great help for the people performing study on real world problems in MANET security.

scholarly journals An approach to emerging optical and optoelectronic applications based on NiO micro- and nanostructures

Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
María Taeño ◽  
David Maestre ◽  
Ana Cremades
Keyword(s):  
Gas Sensors ◽  
High Frequency ◽  
Future Research ◽  
Electrochromic Devices ◽  
Fuel Cell Electrodes ◽  
Magnetic Devices ◽  
Optical Microresonators ◽  
Optical Limiters ◽  
Recent Developments ◽  
Potential Applicability

Abstract Nickel oxide (NiO) is one of the very few p-type semiconducting oxides, the study of which is gaining increasing attention in recent years due to its potential applicability in many emerging fields of technological research. Actually, a growing number of scientific works focus on NiO-based electrochromic devices, high-frequency spintronics, fuel cell electrodes, supercapacitors, photocatalyst, chemical/gas sensors, or magnetic devices, among others. However, less has been done so far in the development of NiO-based optical devices, a field in which this versatile transition metal oxide still lags in performance despite its potential applicability. This review could contribute with novelty and new forefront insights on NiO micro and nanostructures with promising applicability in optical and optoelectronic devices. As some examples, NiO lighting devices, optical microresonators, waveguides, optical limiters, and neuromorphic applications are reviewed and analyzed in this work. These emerging functionalities, together with some other recent developments based on NiO micro and nanostructures, can open a new field of research based on this p-type material which still remains scarcely explored from an optical perspective, and would pave the way to future research and scientific advances.

scholarly journals Revisiting the CompCars Dataset for Hierarchical Car Classification: New Annotations, Experiments, and Results

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 596
Author(s):  
Marco Buzzelli ◽  
Luca Segantin
Keyword(s):  
Real World ◽  
High Performance ◽  
Ad Hoc ◽  
Future Research ◽  
Levels Of Detail ◽  
Excellent Starting Point ◽  
Starting Point ◽  
Hierarchical Nature ◽  
Multiple Levels ◽  
Entire Dataset

We address the task of classifying car images at multiple levels of detail, ranging from the top-level car type, down to the specific car make, model, and year. We analyze existing datasets for car classification, and identify the CompCars as an excellent starting point for our task. We show that convolutional neural networks achieve an accuracy above 90% on the finest-level classification task. This high performance, however, is scarcely representative of real-world situations, as it is evaluated on a biased training/test split. In this work, we revisit the CompCars dataset by first defining a new training/test split, which better represents real-world scenarios by setting a more realistic baseline at 61% accuracy on the new test set. We also propagate the existing (but limited) type-level annotation to the entire dataset, and we finally provide a car-tight bounding box for each image, automatically defined through an ad hoc car detector. To evaluate this revisited dataset, we design and implement three different approaches to car classification, two of which exploit the hierarchical nature of car annotations. Our experiments show that higher-level classification in terms of car type positively impacts classification at a finer grain, now reaching 70% accuracy. The achieved performance constitutes a baseline benchmark for future research, and our enriched set of annotations is made available for public download.

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.

Sign in / Sign up

Export Citation Format

Share Document