Similar Search Results

How Many Observations Should One Use When Calculating Historical Estimators for Expected Returns, Volatilities and Correlations?

Steiner, Andreas - 2022

Deriving estimators from historical data is common practice in applied quantitative finance. The availability of ever larger data sets and easier access to statistical algorithms has also led to an increased usage of historical estimators. In this research note, we illustrate how to assess the...

Persistent link: https://www.econbiz.de/10014236566

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2022 - This version: January 2022

recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the … unconditional correlation matrix. In this paper, we show how performance can be increased further by using open/high/low/close (OHLC …

Persistent link: https://www.econbiz.de/10013040932

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2021 - This version: June 2021

Persistent link: https://www.econbiz.de/10012584099

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2020

. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this …

Persistent link: https://www.econbiz.de/10012253083

Covariance prediction in large portfolio allocation

Trucíos, Carlos; Zevallos, Mauricio; Hotta, Luiz K.; … - In: Econometrics : open access journal 7 (2019) 2/19, pp. 1-24

Many financial decisions, such as portfolio allocation, risk management, option pricing and hedge strategies, are based on forecasts of the conditional variances, covariances and correlations of financial returns. The paper shows an empirical comparison of several methods to predict...

Persistent link: https://www.econbiz.de/10012025822

Estimation of the Long-Memory Stochastic Volatility Model Parameters that is Robust to Level Shifts and Deterministic Trends

McCloskey, Adam - 2012

I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of additive low-frequency contamination in log-squared...

Persistent link: https://www.econbiz.de/10013098304

Estimation of Quarticity with High Frequency Data

Mancino, Maria Elvira - 2013

We propose a new methodology based on Fourier analysis to estimate the fourth power of the volatility function (spot quarticity) and, as a byproduct, the integrated function. We prove the consistency of the proposed estimator of the integrated quarticity. Further, we analyse its efficiency in...

Persistent link: https://www.econbiz.de/10013084252

High-Dimensional Minimum Variance Portfolio Estimation Based on High-Frequency Data

Cai, Tony - 2019

This paper studies the estimation of high-dimensional minimum variance portfolio (MVP) based on the high frequency …

Persistent link: https://www.econbiz.de/10012900204

Efficient Quasi-Bayesian Estimation of Affine Option Pricing Models Using Risk-Neutral Cumulants

Brignone, Riccardo; Gonzato, Luca; Lütkebohmert, Eva - 2022

We propose a general, accurate and fast econometric approach for the estimation of affine option pricing models. The … algorithm belongs to the class of Laplace-Type Estimation (LTE) techniques and exploits Sequential Monte Carlo (SMC) methods. We … estimation by designing a density tempered SMC sampler. We test our algorithm on simulated data by tackling the challenging …

Persistent link: https://www.econbiz.de/10014235890

Conditional Quantile Analysis for Realized GARCH Models

Kim, Donggyu; Oh, Minseog; Wang, Yazhen - 2021

conditional quantile estimation. Specifically, we model the conditional standard deviation as a realized GARCH model and employ … proposed dynamic quantile models. We devise a two-step estimation procedure to estimate the conditional quantile parameters …. The first step applies a quasi-maximum likelihood estimation procedure, with the realized volatility as a proxy for the …

Persistent link: https://www.econbiz.de/10013216324