Choosing Models for Six-Month Index Investment Decisions

Summary

The document frames an investment decision as a binary choice: invest in a stock index or stay out, using macroeconomic variables such as volatility measures, currency exchange rates, and Treasury yields. It proposes a classification approach, with nearest-neighbor methods as one possibility, and asks whether that is preferable to a standard econometric model. The prediction target is index performance over a six-month horizon.

The text provides a problem setup rather than a solution, empirical comparison, or supporting results. It does not specify how “invest” should be labeled from returns, what data frequency or sample to use, or how a model would be evaluated. It therefore offers no basis for selecting classification over econometrics. Any practical treatment would need to define the decision threshold and assess predictions in a time-ordered design, with attention to overlapping horizons and the limited number of independent six-month outcomes.

Key ideas

• The proposed task maps macroeconomic features to a binary index investment decision.
• The stated forecast horizon is six months.
• Nearest-neighbor classification is raised as one candidate alongside econometric models.
• The document gives no model recommendation, empirical evidence, or precise rule for assigning labels.

Tags

# Modeling investment decisions with ML / Econometrics


# Modeling investment decisions with ML / Econometrics












I was given the task to decide whether it is a good time to invest into a certain stock index (e.g. S&P 500) or not given a 6 months Investment horizon. The goal is to get one of the following answers: "invest" or "don't invest"

Explanatory variables should be macroeconomic ones such as VIX, EURUSD,10y Treasury yield etc. Apart from that, I am quite free to choose a model.

I was wondering what would be the best approach to tackle the problem. I was considering using some a classificstion algorithm like K nearest neighbors where the features are the above mentioned data (VIX etc) and the label is the performance of the index 6 months from now.

Do you think that's possible or would it make more sense to use a standard econometric model?

Do you have some references where something similar has been done? I am currently a little lost where to start.

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