Results 11 to 20 of about 14,389 (211)

Cointegration and Adjustment in the CVAR(∞) Representation of Some Partially Observed CVAR(1) Models [PDF]

open access: yesEconometrics, 2019
A multivariate CVAR(1) model for some observed variables and some unobserved variables is analysed using its infinite order CVAR representation of the observations.
Søren Johansen
doaj   +5 more sources

RM-CVaR: Regularized Multiple $\beta$-CVaR Portfolio [PDF]

open access: yesProceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
The problem of finding the optimal portfolio for investors is called the portfolio optimization problem. Such problem mainly concerns the expectation and variability of return (i.e., mean and variance). Although the variance would be the most fundamental
Abe, Masaya, Nakagawa, Kei, Noma, Shuhei
core   +2 more sources

CVaR Hedging under Stochastic Interest Rate [PDF]

open access: yesFrontiers in Applied Mathematics and Statistics, 2015
In this paper we assess the partial hedging problems by formulating hedging strategies that minimize conditional value-at-risk (CVaR) of the portfolio loss under stochastic interest rate environment.
Angela eTsao   +2 more
doaj   +2 more sources

Optimizing the CVaR via Sampling [PDF]

open access: yesProceedings of the AAAI Conference on Artificial Intelligence, 2014
Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form of a conditional expectation.
Glassner, Yonatan   +2 more
core   +2 more sources

Optimal Dynamic Portfolio with Mean-CVaR Criterion [PDF]

open access: yesRisks, 2013
Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of a Neyman–Pearson type binary solution.
Mingxin Xu, Jing Li
doaj   +6 more sources

Testing the CVAR in the Fractional CVAR Model [PDF]

open access: yesSSRN Electronic Journal, 2017
We consider the fractional cointegrated vector autoregressive (CVAR) model of Johansen and Nielsen (2012a) and show that the likelihood ratio test statistic for the usual CVAR model is asymptotically chi‐squared‐distributed. Because the usual CVAR model lies on the boundary of the parameter space for the fractional CVAR in Johansen and Nielsen (2012a),
Johansen, Søren   +1 more
openaire   +6 more sources

CVaR Robust Mean-CVaR Portfolio Optimization [PDF]

open access: yesISRN Applied Mathematics, 2013
One of the most important problems faced by every investor is asset allocation. An investor during making investment decisions has to search for equilibrium between risk and returns. Risk and return are uncertain parameters in the suggested portfolio optimization models and should be estimated to solve the problem. However, the estimation might lead to
Maziar Salahi   +2 more
openaire   +1 more source

ESTIMASI CVAR PADA PORTOFOLIO SAHAM MENGGUNAKAN METODE GJR-EVT DENGAN PENDEKATAN D-VINE COPULA

open access: yesE-Jurnal Matematika, 2022
Risk measure using Conditional Value at Risk can be calculate if values that exceeds the p-quantile is known in VaR. The models used to accommodate characteristics of the stock portfolio in this research are EVT-GARCH-D-vine copula and EVT-GJR-D-vine ...
DERY MAULANA   +2 more
doaj   +1 more source

Optimal Frontier-Based Autonomous Exploration in Unconstructed Environment Using RGB-D Sensor

open access: yesSensors, 2020
Aerial robots are widely used in search and rescue applications because of their small size and high maneuvering. However, designing an autonomous exploration algorithm is still a challenging and open task, because of the limited payload and computing ...
Liang Lu, Carlos Redondo, Pascual Campoy
doaj   +1 more source

A Robust and Fast Collision-Avoidance Approach for Micro Aerial Vehicles Using a Depth Sensor

open access: yesRemote Sensing, 2021
Collision-avoidance is a crucial research topic in robotics. Designing a collision-avoidance algorithm is still a challenging and open task, because of the requirements for navigating in unstructured and dynamic environments using limited payload and ...
Liang Lu   +3 more
doaj   +1 more source

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