# Tag Info

### Why is asset volatility easier to estimate than the asset mean if it contains the mean?

Let me add two points to Quantoisseur's answer. Standard Errors The difference between estimating variances and means is that the standard error of the variance estimator depends on the size of the ...
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### What is the preferred GARCH method in practice?

I personally use the simple Garch(1,1) for volatility filtering in the risk management area. In fact in most cases I don't even estimate the parameters, I stick 0.94 for mean reversion, 0.04 for the ...
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### What good papers of short term (<30 seconds) volatility estimation

Very interesting question. I am not an expert on the subject, however, I was able to find a collection of papers on the subject that should get you started. Here is a good and very informative paper ...
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### Estimating implied volatility of an index component with no vanilla options market

There is no standard approach to this problem to the best of my knowledge. Different approaches exist and each has its own pros and cons as usual. To mention a few: Information-based methods: these ...
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### Are asset return means difficult to predict because they have no lower bound?

To answer, the assertion that volatility is easier to predict than expected return requires clarification. The phrase "easier to predict" is particularly ambiguous. To me this means that the ...
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### Why is asset volatility easier to estimate than the asset mean if it contains the mean?

The answer is not statistical. In almost every other area of statistics, estimating the mean is easier (i.e. it can be estimated with higher precision) and estimating higher moments like variance (and ...
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### Unsmoothing of returns

Did you try solving for $w_k$? $$\bar{r}_t = \sum_{k=0}^p w_k r_{t-k}$$ $$\bar R = W R$$ Since you probably have $t>>k$, you can solve for $W$ using OLS $$\bar R = W R +\varepsilon$$ -- ...
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### Bond yield to maturity vs current interest yield

Not really. For infinite maturity bonds we have $Price = coupon/yield$ so your approximation is actually correct. However for short dated bonds it is not a good approximation. For example , a 1 ...
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### Neural Networks for Estimation of Unmarked Private Asset Returns from Market Data

Based on an my updated understanding of your problem you have a portfolio consisting of $N$ illiquid assets. Valuations are not real time and usually lagged, by say, upto 3 months (or slightly longer),...
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### Methods for superior estimates of returns in m.v. portfolio optimization

Expected returns are very difficult to estimate reliably without incurring estimation error as found out by Merton (1980) "On estimating the expected return on the market". This is why estimating ...
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### Arithmetic Brownian Motion in Market Making papers

The time step typically depends on the context. Due to the self-similarity of Brownian motion the mathematics should work similarly on any time scale, although the resultant estimates might vary ...
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### Why is asset volatility easier to estimate than the asset mean if it contains the mean?

A simpler answer is thus. There are known historical values for the past year for the mean. It's simply the end of year value divided by the beginning value. However, we can't improve the estimate ...
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It makes no sense to write $C^h \to e^{\delta C}$ as $T \to \infty$ when $C = I_K +\Lambda/T$ since $e^{\delta C}$ on the right-hand side depends on $T$. What can be confirmed is $(C^h)_{k,k} \to e^{\... • 3,365 3 votes ### GJR-GARCH with$\alpha = 0$as parameter estimate$\alpha=0$does not imply constant volatility. Consider just a simple Garch(1,1): $$\sigma^2_t = \omega + \alpha \eta_t^2 + \beta \sigma^2_{t-1}$$ Note that: $$\sigma^2_t = \omega + (\alpha + \... • 6,810 3 votes ### What is the preferred GARCH method in practice? Interesting question, as All the answers (including mine) could not be generalized unfortunately. As far as I am concerned, I use a univariate EGARCH for risk modelling purposes (Filtered Historical ... • 315 3 votes Accepted ### Streaming update of the GARCH(1,1) model If you estimate your model via Maximum Likelihood method, you are forced to re-estimate the full model. This is due to the fact that estimates are values which maximize the full likelihood, the latter ... • 2,514 3 votes Accepted ### What volatility estimator for continuous data and small time window? First, you should use an exponential moving average, since the amount of state you need to keep is much smaller than for a simple moving average. Second the well known estimator of volatility,$$ \... • 5,628 3 votes ### Why is asset volatility easier to estimate than the asset mean if it contains the mean? The sample variance and standard deviation (volatility) formulas are: If your question is why is volatility easier to predict than returns, the intuitive answer is because the numerator is squared ... • 760 3 votes ### Do EWMA weights remove autocorrelation in asset returns? EWMA (and other sort of moving averages) introduces positive autocorrelation into otherwise uncorrelated returns. The fitted values of EWMA are linear combinations of past returns, and the constituent ... • 1,788 3 votes Accepted ### A simple question about VaR estimation I think there is a mistake in your definition. It should be between "50th and 51st" sorted numbers. 95% VAR means 5% is in the tail. 5% * 1000 = 50. The 95% VAR will be the 50th worst ... • 5,325 3 votes ### Do portfolio mean and portfolio variance have probability distributions? Yes, they can/do. But you have to drink the proverbial Kool-Aid(or taking the blue pill is probably the more relevant metaphor these days ;-), and approach this as a Bayesian inference problem. So ... • 4,926 3 votes ### How does yahoo calculate Growth Estimates 5 year forward estimates comes from Refinitiv IBES (Institutional Broker Estimate System). It will be the mean estimate from all the analyst that cover the stock that report into IBES. It’s used ... 2 votes ### Predicting stock returns - in a panel data specification or by using portfolio formation strategies? Both approaches can be useful. For stocks, sorting into quantiles is popular because it's easy to understand and explain it's a simple matter to build factor portfolios and track or backtest their ... • 876 2 votes ### What is Estimation Risk - VAR Backtest Even in calculating VAR, you have certain assumptions / constants / random numbers being used. Hence, even your VAR calculation is not 100% correct. So, you are estimating VAR and you hedge similar ... • 314 2 votes Accepted ### How to approximate the Carr-Madan decomposition formula? Carr-Madan formula tells you that the European-style payoff$f(F_T)$can be decomposed as:$\$f(F_T)=f(\kappa) + f'(\kappa) [(F_T - \kappa)^+ - (\kappa - F_T)^+] + \int_0^{\kappa} f''(K) (K-F_T)^+ \ d ...
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