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32 votes
Accepted

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 ...
Quantuple's user avatar
  • 14.7k
17 votes

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.
Kiwiakos's user avatar
  • 4,337
12 votes

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 ...
RRL's user avatar
  • 3,700
8 votes

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 ...
Richi Wa's user avatar
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8 votes

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 ...
vonjd's user avatar
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8 votes
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Preferred Option pricing model

General Comment: In industry, you're effectively an engineer/mechanic. You choose the best tool for the job, and there is no 1 tool that works with everything because they all have different benefits ...
THATS MY QUANT MY QUANTITATIVE's user avatar
7 votes
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Reconciling Two Claims About Volatility Under Fat Tails

I don't think the claim that "Lévy alpha-stable distributions are better descriptors of returns" is universally accepted. While Mandelbrot (and others before him) has correctly identified ...
Adam N.'s user avatar
  • 233
6 votes
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Model to Predict the Change in IV of an Option

One approach that I have seen being used is to try to model the (joint) dynamics of the forward at-the-money volatility as well as its first one or two derivatives. The idea is to find a ...
LocalVolatility's user avatar
5 votes
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GARCH volatility modeling, squared returns, and convergence

Assume that your stationary time series (here a daily close-to-close log-returns' series) is modelled as follows $\forall t \in \mathcal{T}=\{1,...,N\}$ \begin{align} r_t &= E_{t-1}[r_t] + \...
Quantuple's user avatar
  • 14.7k
5 votes
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Model reference price of Limit order book

This reference price is also sometimes called intrinsic price. One of the simplest ways to improve it in regards to the mid-price (assuming you have the depth data) is the following: define a ...
Serg's user avatar
  • 1,022
5 votes
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how are financial data with sparse and asynchronous features imputed in predictive modeling?

There is large literature on MIDAS (mixed-frequency data sampling) models, the leading scholars being Eric Ghysels and Rossen Valkanov — google their research for references. However, the ...
Igor Pozdeev's user avatar
5 votes
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Why do we not use copula for forward starting options?

One is exploring forward volatility of a price of a single asset (joint distributions from within a process), the other explores correlation of two prices at the same time for two different ...
ir7's user avatar
  • 5,043
4 votes

Why do we usually use normal distribution and not Laplace distribution to generate stochastic process?

If you're willing to drop the requirement to have continuous paths, or rather, if you're willing to relax it, it is possible to have a bigger class of stochastic processes called Lévy processes. The ...
Raskolnikov's user avatar
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4 votes

Is there a way to meaningfully generate daily returns from monthly?

This is a commonly seen problem, and also relates to situations in which one is dealing with some less-liquid underlyings. I will describe a method that you could think of as "stochastic backfilling" ...
RiskyScientist's user avatar
4 votes

Model to Predict the Change in IV of an Option

I would say that Derman's 99 paper on "Regimes of Volatility" (also called volatility "stickiness assumptions" by some practitioners) is an excellent place to start your investigations. Here is the ...
Quantuple's user avatar
  • 14.7k
4 votes

Accrual in Default Derivation of Credit CDS Curve

The accrual on default is like the accrued interest on a bond. A credit default swap can be looked as a synthetic bond. As such, with each passing day, interest is earned to the seller of protection ...
AlRacoon's user avatar
  • 6,632
4 votes
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why calibrate volatility and fix the mean reversion

Fixing the mean reversion, and parameterizing the volatility as a step function or as a piecewise linear function, the volatility can be bootstrapped exactly to a set of vanilla options sorted by ...
Antoine Conze's user avatar
4 votes

Pros and cons of mean equation equal to zero in a GARCH model

When you model log-returns $(Y_t)$ by $Y_t=\varepsilon_t$ where $\varepsilon_t|\mathcal{F}_{t-1}\sim N(0,\sigma^2_t)$ and a standard GARCH($p,q$) model with $$\sigma_t^2=\omega+\sum_{i=1}^p \alpha_{i}\...
Kevin's user avatar
  • 16k
4 votes
Accepted

Do different prices under different models admit arbitrage?

This phenomenon is not limited to interest rate derivatives. Any time a product is priced to model - be it equity derivatives, commodity derivatives, simple cash products whose price is not observable ...
Dimitri Vulis's user avatar
4 votes
Accepted

Understanding out-of-sample performance metrics for Realized Volatility

You can compare the losses against each model and determine the "best" model to be the one with the smallest losses. In many cases for larger studies, the results might be ambiguous where ...
Pleb's user avatar
  • 4,386
3 votes

Is there a way to meaningfully generate daily returns from monthly?

Kalman filter (or similar methods) are quite well suited to deal with observations that are of different sampling frequencies and/or asynchronous.
Kiwiakos's user avatar
  • 4,337
3 votes

Geometric brownian motion vs. Ornstein Uhlenbeck

A more abstract yet simple way of looking at this may help. Consider a generic diffusion $dY = (a_t - b_t Y_t) dt + \sigma_t dW_t$, where $Y_t$ is either the modelled quantity itself or $Y_t = \log{...
achirikhin's user avatar
3 votes

Mean and standard deviation of price series with Kalman

I would suggest check out the Wikipedia page first and use more stylized notations. In your update equation mean(t) = mean(t-1) + K(t) * ( price(t) - mean(t-1) ) ...
Will Gu's user avatar
  • 712
3 votes

Model to Predict the Change in IV of an Option

You may be interested in these papers by Dumas et al. (1998) and Goncalves and Guidolin (2006). Here the abstracts: -Dumas et al (1998): Black and Scholes (1973) implied volatilities tend to be ...
fni's user avatar
  • 1,896
3 votes
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Accrual in Default Derivation of Credit CDS Curve

The formula for the accrual on default $$ S_n \sum_{i=1}^n \frac{\Delta_i}{2}(Ps(i-1)-Ps(i))DF_i $$ is just an approximation that says conditional on default occurring within period $i$ (probability ...
Antoine Conze's user avatar
3 votes
Accepted

Lattice pricing of derivatives under multi curve framework (OIS and LIBOR)

There are many resources describing how to build a trinomial tree for the Hull & White model (for instance http://www-2.rotman.utoronto.ca/~hull/downloadablepublications/TreeBuilding.pdf), and ...
Antoine Conze's user avatar
3 votes
Accepted

Market Making Strategies Found by Hamilton-Jacobi-Bellman Equation

At the terminal time $T$, the terminal condition is $g(T, q) = -\alpha q^2$, this implies, $$ \begin{aligned} g(T, q) &= \frac{1}{\kappa} \log{\omega(T, q)} = -\alpha q^2\\ \Rightarrow \omega(T,q)...
Danny's user avatar
  • 514
3 votes
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Is this the correct way to forecast stock price volatility using GARCH

I have solved this problem by performing a rolling forecast the following way. I am unsure (1) if this rolling forecast is correct, and (2) how to then perform a rolling forecast 30 days into the ...
KOB's user avatar
  • 193
3 votes
Accepted

Mathematical models for personal finance decisions

I assume you mean individual economic decisions such as saving, pension, purchasing, and risk taking etc. and all the underlying rational and irrational behaviours. These fall under the behavioural ...
Magic is in the chain's user avatar
3 votes

Why do Factor Models set up their factors differently from regression?

Thanks for editing your original post to show that betas are in front of the factors. In factor models, $\beta$ are factor loadings (regression coefficients) while $X$ are factor exposures (...
develarist's user avatar
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