# Tag Info

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### How to estimate real-world probabilities

The risk-neutral measure $\mathbb{Q}$ is a mathematical construct which stems from the law of one price, also known as the principle of no riskless arbitrage and which you may already have heard of in ...
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### Why aren't econometric models used more in Quant Finance?

It's an interesting question. I particularly agree with the $\mathbb{Q}-\mathbb{P}$ dichotomy mentioned by many. I would add to the other answers that, come to think of it, the Black-Scholes ...

### Why aren't econometric models used more in Quant Finance?

I think you need to differentiate between Q-quants vs P-quants. The former might not use Econometrics, but P-quants use them a lot.

### Why quants think that the risk-neutral measure should not be used for financial forecasting?

There is a deeper issue. Frequentist distributions are not probability distributions because they are designed to be minimax distributions rather than actual distributions. This ignores all of the ...

### Why aren't econometric models used more in Quant Finance?

Traditional econometric (time series) models are of little or no value in forecasting market prices for purposes of "making money", i.e, generating excess return over a benchmark in an asset ...
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### Can someone explain rigorously Taleb's criticism of Nate Silver's election forecasting?

hope I am not too late to the party. tl;dr Taleb's paper draws incorrect conclusions from a set of wrong assumptions. In practice, the movements of the forecast at 538 are very much in line with what ...

### Why quants think that the risk-neutral measure should not be used for financial forecasting?

In their book "Counterparty Credit Risk, Collateral and Funding" D. Brigo, M. Morini and A. Pallavicini start with a dialogue between a Physics PhD graduate and an experienced practitioner of ...

### What is the difference between squared returns and variance?

Usually the formula for the sample variance of a stock is given by: \begin{equation} Var(R_{i}) = E (R_t - E(R_t))^2 \end{equation} If you are using daily data to compute the variance then the ...

### What is the purpose of short rate models?

Short rate models were first used in the 1970s and 1980s to try to fit and explain the term structure of interest rates - they went beyond simple parametric shapes (polynomials and exponential forms). ...
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### Is there a HAR that deals with the leverage effect?

There exists a modification of the HAR model that accounts for leverage effect (á la GJR-GARCH) in a high-frequency setting. The semi-variance HAR model, termed the SHAR model of Patton and Sheppard (...

### Why aren't econometric models used more in Quant Finance?

My answer is very much in the spirit of Kiwiakos' answer. E.g. in this paper (where I am one of the coauthors) we use VMA (vector moving average) models (in the multivariate case) and AR models in ...

### Why aren't econometric models used more in Quant Finance?

Having thought about this I think the following reason is also important and wasn't mentioned so far: When you look at the inner working of this whole class of econometric models it all boils down to ...

### Why quants think that the risk-neutral measure should not be used for financial forecasting?

Perhaps a case of views based upon theoretical possibilities rather than empirical realities? In theory, $P$ and $Q$ can be extremely different $P$ is the real world, actual probability measure. $Q$ ...

### Can someone explain rigorously Taleb's criticism of Nate Silver's election forecasting?

Taleb argues that under uncertainty, election forecasts should be seen as a Binary option. A similar thought is presented by De Finetti's principle that probability should be treated like a two-way "...
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### Why is volatility said to be persistent?

Two theoretical explanations regarding the long memory are given by: The mixture of distributions hypothesis of Tauchen and Pitts (1983). Essentially this hypothesis states that trading volume and ...
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### Modelling and forecasting mixed frequency financial data

MIDAS is useful when you have a low frequency series and you want to include high frequency data in the regression. So for instance, if you want to forecast quarterly GDP data and want to include ...
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### Why are stock index futures not used to forecast how much the stock market will rise, given that interest rates futures are used for this purpose?

Interest rate futures enable you to build an interest rate projection curve which you can think of as representing the risk neutral expectation of rates in the future, therefore providing you with a "...

### Why are stock index futures not used to forecast how much the stock market will rise, given that interest rates futures are used for this purpose?

I would put it slightly differently. For Stock index futures , the 2019 contract has the same underlying stocks as the spot index. Therefore the futures price can be simply calculated as spot price ...

### How would you forecast volatility without using any programming languages or machine learning or anything of that sort?

Basically, you have to choose whether to use a forward-looking or a backward-looking method of forecasting volatility. Let's start with the VIX. The VIX is an implied volatility index. Option pricing ...

### Why quants think that the risk-neutral measure should not be used for financial forecasting?

The risk neutral density is a mathematical trick to allow pricing of options. As it has little bearing on reality, it makes little sense to simulate from it for the purposes of forecasting real ...

### Why are stock index futures not used to forecast how much the stock market will rise, given that interest rates futures are used for this purpose?

The main reason is that with interest rate futures interest rates are entering the pricing formula because they are not hedged while with stock index futures the indices are being hedged (while ...

### Why are stock index futures not used to forecast how much the stock market will rise, given that interest rates futures are used for this purpose?

People are all kinda dancing around the straighforward answer, which is that you can trade the underlying for a stock index future but not for an interest rate future. When you can trade the ...

### What is the purpose of short rate models?

I might get down-voted for this, but in my opinion, short-rate models are not very useful for any practical pricing problems in today's finance. Even for simple vanilla rate derivatives (i.e. Caplet ...

### Filling a few missing data in time series?

I would personally delete those days so you dont change the data distribution. If you really need to fill those blanks, random sample imputation would be the way to go.

### Any research on how natural language processing can be used to forecast stocks?

Recent research A recent article by Frank Zhao is interesting to get started: Natural Language Processing - Part I: Primer. You will find more papers on this repo (too long to copy all here): ...
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### Density forecast of a GARCH model

EDIT : I read more about it and I get some help with someone else, here is the correct answer : The density forecast is the predictive likelihood value of the process estimated at the realized ...

### Why is volatility said to be persistent?

Check out the book of Teyssière & Kirman (2007) entitled "Long Memory in Economics". For instance, the model of Gaunersdorfer & Hommes features heterogeneous agents: fundamentalists believe ...
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### Why does computing correlation between index levels vs. percentage changes yield completely different results?

The linked to answer does explain it all, but in brief because one set are stationary processes and the others are not. Correlation as a measures gives us the normalized degree of co-movement ...
I think that what you want is to convert an annually compounded interest rate to a monthly compounded interest rate, right? $$\left(1+\frac{r_{monthly}}{12}\right)^{12} = (1 + r_{annual})$$ r_{...
It just needs the power series(Maclaurin) expansion: $e^{x}=1+x+\frac{x^2}{2!}+\frac{x^3}{3!}+\dots$ Take the Linex function: \$L\left(y,\overset{\wedge}{y}\right)=\frac{2}{a^2}\left[e^{a\left(y-\...