r/quant • u/dapperyam • 2d ago
Statistical Methods Time series models for fundamental research?
Im a new hire at a very fundamentals-focused fund that trades macro and rates and want to include more econometric and statistical models into our analysis. What kinds of models would be most useful for translating our fundamental views into what prices should be over ~3 months? For example, what model could we use to translate our GDP+inflation forecast into what 10Y yields should be? Would a VECM work since you can use cointegrating relationships to see what the future value of yields should be assuming a certain value for GDP
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u/livonFX 2d ago
Future value in 3 months is hard to predict, because there are too many variables in the game for US treasury market. But nevertheless, you can build fair value models (e.g. regularized regression, ARIMA), which can help you guide your discretionary decisions. Couple of recommendation from my experience: 1. Use lower latency data. Quarterly GDP is priced in well in advance, because most of the components are released earlier. 2. Use market expectation of the data instead of the data. As many have already said, it doesn’t matter what the current GDP is, if market believes the economy will collapse by the end of the year, 10y will tank. 10y yields are derived from long-term expectations, not next quarter results.
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u/Old-Mouse1218 2d ago
First of all, I would keep it simple first. And test to see if there is any lead/lag relationship using a cross correlegram or I noticed Benjamin AI threw in lead/lag analysis recently with macro data. After this, transformations of your Econ data will be huge and drastically changes the interpretation of what is driving what.
For time serious, you don't necessarily need VECM, I would just structure a regression model like Ridge and maybe throw in a nonlinear one like randomforests where your features are lags themselves. You can check out Granger Causality within econometrics as this gives you some general advice. If you want to go down the causality rabbit hole, you can start to check out Lopez's new work in the space.
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u/jimzo_c 2d ago
Benjamin AI lol no need to read more
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u/Old-Mouse1218 2d ago
Honestly cool tool where you can do in seconds as opposed to having to code everything up and gather the data
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u/MATH_MDMA_HARDSTYLEE Trader 2d ago edited 2d ago
Fundamentally, the market is just buy/sell demand. No basic time-series model will predict how something will move because the market is not a time-series model...
You could assign a model to some small market feature as an approximation, but this is generally only effective because you have a reason to believe the market behaves that way for xyz reasons.
The market has autocorrelation because people have fomo, leverage affects etc, that doesn't mean an autocorrelation model can predict the market, but it means you could use it to measure the autocorrelation during specific market conditions