28 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 ...
  • 14.1k
16 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.
  • 4,247
12 votes

Choosing the right statistical test for Mutual Fund Performance Evaluation

Define excess return $r^x_{it} = r_{it} - r^f_{t}$ as the return $i$ minus the risk free rate, and $f_{jt}$ similarly denotes the excess return of factor $j$ at time $t$. Let's say we have some factor ...
  • 6,414
11 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 ...
  • 3,480
11 votes

Fama Mac-Beth (1973) vs Fixed effect

A more apples to apples comparison would be between (i) Fama-Macbeth procedure and (2) clustering standard-errors by date. Adding fixed-effects is somewhat different. Problem: cross-sectional ...
  • 6,414
10 votes
Accepted

What is the stambaugh bias? Why is it important for predictability regressions?

The bias comes from the paper Stambaugh (1999) and has nothing to do with small sample bias. It has to do with point (1) below. The argument goes as follows: Typical lagged explanatory variables ...
  • 6,923
8 votes
Accepted

Suppose that we are wrong about the relevant class of distributions for financial economics and econometrics. Now what?

I will be glad to help, but let me first advise you away from working on this topic until you have an academic position. This topic has been poison for me, but I am slogging on anyways. Before you ...
  • 4,123
7 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 ...
  • 13.3k
7 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 ...
  • 27k
7 votes

Predict the behavior of a time series (P&L trading desk)

Without seeing your trading desk's P&L it's impossible to say whether it is predictable or not. But here are a few thoughts - There's no reason to think that it isn't predictable. In general, ...
  • 5,638
7 votes
Accepted

Interpreting the coefficients of Fama-MacBeth regression

No, you cannot interpret the average return for the factor as the risk premium. The second stage regression is equivalent to building a set of portfolios that have no net investment, a unit exposure ...
  • 1,366
6 votes
Accepted

Momentum - skipping the most recent month

The idea of skipping a month was already in Jegadeesh and Titman 1993. The key academic paper in this area. Jegadeesh himself (without Titman) discovered a 1-month return REVERSAL effect in ...
  • 9,656
5 votes

Is a linear combination of GARCH processes also a GARCH process?

No, a sum of two GARCH processes is generally not a GARCH process. (I am not even sure whether there exists a nontrivial special case where the opposite holds.) By GARCH I mean the classic ...
4 votes

Which quantitative tools are actually used for hedging energy price and volume risk?

Just came across this thread...not sure if you already have your answer, but thought I'd give you a shout. In the energy business, we employ a range of models. You'll find the most sophisticated ...
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4 votes

Which quantitative tools are actually used for hedging energy price and volume risk?

I am a professor too and I did work with Siemens Corporate Technology which provides the quantitative technology for their copper and electricity trading (Siemens being one of the biggest players in ...
  • 27k
4 votes

rollapply with Arima model: testing for stability of coefficients

There are a couple of issues with your example. First, for this ticker, there is a problem with the Yahoo price data for the period 2014-11-26 through 2014-12-03 in which the prices drop about 80% ...
  • 404
4 votes
Accepted

Which python packages would you recommend for time series analysis?

The gold standard for time series analysis in Python is pandas. Pandas was originally developed at AQR to support their in-house research and has since been open-sourced. It has very high-performance ...
  • 10.9k
4 votes
Accepted

Quantitative features of asset price bubbles beginning

A nice paper by Sornette, about Dragon Kings here
4 votes
Accepted

What is time-varying risk premium? Forecasting stock returns

Another way of staying "time-varying risk-premium", is saying that the risk-premium is predictable. However, that the fact that the risk-premium is predictable does not means that you can make money ...
  • 6,923
4 votes
Accepted

Question on the use of a limit in a proof

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^{\...
  • 3,480
3 votes

Any package to run VAR-GARCH or VECM-GARCH models in R?

Yes, it exists and it is called ccgarch package. You can install that by simply running in R install.packages("ccgarch") and ...
  • 2,446
3 votes
Accepted

Can you explain me these comments on high frequency data?

1) Spurious autocorrelation of non-synchronous trading data was analyzed in this article: http://www.amazon.com/An-econometric-analysis-nonsynchronous-trading/dp/1245789457 During some time intervals ...
  • 439
3 votes
Accepted

Standard Stochastic Volatility Models VS Moving Average Stochastic Volatility Model

Finally I have found the answer on my own. The problem was related to the trasformation of the dataset. The original code used: ${{y}_{t}}=400*(\log ({{P}_{t}})-\log ({{P}_{t-1}}))$ as dataset. ...
3 votes

How to find relationships between financial data?

I'm not sure what you mean by formal but if you have intuition into why gdp or your education metric should be related to the growth of stocks, then by all means, build a model that tries to find the ...
3 votes
Accepted

Fama and French (market premium) factor

Update I downloaded the return series for WFIVX (a Wilshire 5000 index fund) and I calculate a correlation coefficient of .9991 with the Fama-French market return series from Ken French's website (...
  • 6,414
3 votes

How to compute a Fama-Macbeth R-Squared (R2)?

There's nothing different here. To compute $R^2$, you need the actual values $y_i$ and the fitted (i.e. model predicted) values $\hat{y}_i$. Think of the Fama-Macbeth procedure as just another way to ...
  • 6,414
3 votes

Quantitative features of asset price bubbles beginning

There is a mathematical literature proposing bubbles may be modelled as spot processes which follow a strict local martingale dynamics. See Protter https://link.springer.com/chapter/10.1007/978-3-319-...
  • 1,865
3 votes

Criticise GARCH relative to Realized Volatility

Volatility is an unobservable continuous variable defined over a period of time (formally defined as a stochastic process over an interval) whereas Garch models deal with discrete time observations to ...
  • 2,534
3 votes
Accepted

Calculating the pricing error in Fama-Macbeth Regression for Fama/French 5 Factor model

John Cochrane (in Asset Pricing) p. 244: Sampling error is, after all, about how a statistic would vary from one sample to the next if we repeated the observations. Clarification on linear ...
  • 3,026
3 votes

What's the difference between Statistics and Econometrics?

Econometrics means measurement in economics as per Chris Brook, so in the context of this question econometrics can be viewed as application of statistics to economic data/phenomena. Vast majority of ...

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