Questions tagged [estimation]

The calculated approximation of a result which is usable even if input data may be incomplete or uncertain.

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mean reversion model estimation - what method?

how can I estimate this model for mean reversion?
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Model-Free Option Pricing

From Breeden and Litzenberger (1978) and subsequent work, we may find the risk-neutral density $q_{S_T}$ of $S_T$ from European option prices - assuming there are enough traded options (e.g. SPX) via ...
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Tools in R for estimating time-varying copulas?

Are there libraries in R for estimating time-varying joint distributions via copulas? Hedibert Lopes has an excellent paper on the topic here. I know there is an existing packaged called copula but ...
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How is Kalman Filter used to estimate Term structure Models

I am implementing "The Term Structure of Variance Swap Rates and Optimal Variance Swap Investments" . This paper is using kalman filter to estimate the state and the mean variance and a parameters on ...
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Mean-variance portfolio optimization: methods for superior estimates of returns

Leaving aside the aspects related to the estimation of the variance component (all the latest techniques to compute a stable covariance matrix of a given set of assets such as simple shrinkage, Ledoit-...
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How to approximate the Carr-Madan decomposition formula?

I have came across the excellent answer. I'm looking for a dicrete approximation of the Carr-Madan decomposition formula of the function $f(F_T)$ of the terminal futures price by taking a static ...
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Combine EWMA or ARCH model with estimator other than squared returns

Currently I use the EWMA model with the squared logarithmic returns as proxy estimator for the volatility, in order to forecast the volatility one step ahead in an intraday scenario (time frame is a ...
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How are distributions for tail risk measures estimated in practice?

Let's say you want to calculate a VaR for a portfolio of 1000 stocks. You're really only interested in the left tail, so do you use the whole set of returns to estimate mean, variance, skew, and shape ...