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ahgt_123


Total Posts: 4
Joined: May 2020
 
Posted: 2020-05-22 20:16
I am testing some mean reversion strategies on intraday data (1 min - 15 min) basically simple time series models (arima ,arima + garch) + some other oscillators as exogenous variables.(my main aim is more to get a decent R2 than making a live strategy).

I read a lot of papers about modelling intraday volatility using fourier transforms and stuff and how it is absolutely required in intraday trading.Theoretically, it also made sense to me and so implemented the model by andersen & bollerslev.It captured the intraday vol curve pretty well on plot.

However ,the performance of the model didn't increase neither in R2 nor profitability and i have tried multiple things.

I wanted to know if this feature is generally used in live trading by real quant traders
in any setting (futures/options) or is it merely a theoretical thing and i should focus on other stuff.


gaj


Total Posts: 88
Joined: Apr 2018
 
Posted: 2020-05-24 09:43
The most important thing in trading is forecasting expected returns. Forecasting volatility can be useful but it is by no means "absolutely required".

I'm curious about what you have tried. Can you provide more details about the model that you're trying to make?

ahgt_123


Total Posts: 4
Joined: May 2020
 
Posted: 2020-05-24 14:10
The models are general arima models with exogenous variables :



where r is the return ,err error term and x1 ,x2 exogenous variables(oscillators).
The intraday adjustment said to write r as:




where s is the seasonality calculated by the fourier regressions.

The paper said to use r_hat for modelling instead of r which i did.
The R2 of the model did not improve, neither the profitability of simple trading strategies( short/long when forecasted r greater/lesser than actual ; short/long with thresholds ; short long with volatility(modeled as garch) based thresholds).



gaj


Total Posts: 88
Joined: Apr 2018
 
Posted: 2020-05-24 15:41
> short/long when forecasted r greater/lesser than actual

This is gambler's fallacy.

ahgt_123


Total Posts: 4
Joined: May 2020
 
Posted: 2020-05-24 16:25
Sorry , i meant the reverse :

forecast > actual ; long
forecast < actual ; short

gaj


Total Posts: 88
Joined: Apr 2018
 
Posted: 2020-05-24 16:36
yes that is exactly the gambler's fallacy.

ahgt_123


Total Posts: 4
Joined: May 2020
 
Posted: 2020-05-24 17:38
How to backtest then ?

P.S. I don't understand how this relates to gambler's fallacy.I dont have any practical experience but i guess most models would be backtested in this format only or may be the reverse for momentum based strategies.

Also, anyone has any idea on intra-day periodicity modelling ,will it help in improving R2 of the model in any form (transformation etc.) .

I dont have any options data so i cant really back-test trading vol ,but i do have vix data.
Will it be equivalent if i fit the model directly on vix index?




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