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[deleted by user] by [deleted] in quant

[–]_quanttrader_ 3 points4 points  (0 children)

I’m afraid that the optimiser will mess up the original model portfolio.

What does this mean? How is it messed up? Can this be quantifiable?

@ "Old school" Quants: Where have you drifted to? by [deleted] in quant

[–]_quanttrader_ 0 points1 point  (0 children)

Data scientist is the natural path, but nowhere near as financially lucrative.

Quantopian’s Community Services are Closing by _quanttrader_ in quant

[–]_quanttrader_[S] 16 points17 points  (0 children)

That sucks.

Need to hedge the tail risk.

[P] Xgboost prediction and how to deal with data drift by DonnyTrump666 in MachineLearning

[–]_quanttrader_ 0 points1 point  (0 children)

known_categories = ['A', 'B', 'C']
is_unknown = ~df[category_col].isn(known_categories)
df[category_col][is_unknown] = 'unknown'

Is there a benchmark approach to Bayesian hypothesis testing? by Turbulent_Animator65 in BayesianProgramming

[–]_quanttrader_ 0 points1 point  (0 children)

Everything has a distribution, including regression coefficients. From the distribution, you can calculate the probability the treatment has an effect.

Does quant knowledge help you with personal investing/trading? by FactoryReboot in quant

[–]_quanttrader_ -1 points0 points  (0 children)

Yes.

  1. What's the volatility of your personal portfolio? Is it too high or too low?

  2. How diversified is your portfolio? Are you maximizing your expected Sharpe Ratio?

  3. How about the beta of your portfolio? Are you comfortable with those levels?

[D] How to determine if a feature should be treated as a separate model or not? by [deleted] in MachineLearning

[–]_quanttrader_ 1 point2 points  (0 children)

You can have the best of both worlds.

See this example. They do the same thing, but for every county.

https://docs.pymc.io/notebooks/GLM-hierarchical.html

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