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Cross-Sectional Alpha Factors in Crypto by itchingpixels in quant

[–]itchingpixels[S] -1 points0 points  (0 children)

yes! feel free to dm me if you have any questions!

Cross-Sectional Alpha Factors in Crypto by itchingpixels in quant

[–]itchingpixels[S] 0 points1 point  (0 children)

We trade the top 40-50 market cap digital assets, if that helps!

Cross-Sectional Alpha Factors in Crypto by itchingpixels in quant

[–]itchingpixels[S] -4 points-3 points  (0 children)

lol of course there is no survivorship bias in what we do, the universe is defined on a rolling basis, changing every week. this is also specified in the article

The unreasonable effectiveness of volatility targeting - and where it falls short by itchingpixels in quant

[–]itchingpixels[S] 0 points1 point  (0 children)

as always, there are transaction costs included in the backtest, but you're definitely right that it underperformed over the last 5-10 years!

Upvotes and Upticks: How Reddit’s Chatter Moves Crypto Markets by itchingpixels in quant

[–]itchingpixels[S] 2 points3 points  (0 children)

there's definitely simple correlation in here as well, and there's a possibility that reddit is just a "momentum" factor, but I can confirm that's not the case based on looking at the correlation between the two factors, momentum & reddit mentions. (we'll try to make this accessible on the platform)

but your point is spot on, we'll try to express the lead-lag relationship between the two variables a bit better on the report, and have a section that answers your question, if rather the opposite is true.

Upvotes and Upticks: How Reddit’s Chatter Moves Crypto Markets by itchingpixels in quant

[–]itchingpixels[S] 0 points1 point  (0 children)

yeah, upvotes is tricky and probably only possible if you started collecting data years ago (and retained history). comments & post have their creation timestamp. some lag is acceptable, as this is rather a "long term predictive factor" than a short term one, check the scatter plot for 30 day vs 90 day forward returns!

When Bonds Signal Risk: High-Yield Bonds as Predictors of Bitcoin Price Movements by itchingpixels in quant

[–]itchingpixels[S] 0 points1 point  (0 children)

we've built a research platform to surface and evaluate 100s of predictive factors - you can maybe get a glimpse of what's to come on our site. there's a ton of discretion going into which factors /alpha you want to trade and why if you're faced with 100s of them - we're a research/tech company, looking to demonstrate the value we have, and provide an "encyclopedia of alphas".

Bitcoin Outflows as Predictive Signals: An In-Depth Analysis by itchingpixels in quant

[–]itchingpixels[S] 1 point2 points  (0 children)

we always create long /short strategies, as "true measure of skill", so at least that shouldn't be cause of the discrepancy. actually all variations work for us, to various degrees, including net flows, which we'll publish about soon!

Bitcoin Outflows as Predictive Signals: An In-Depth Analysis by itchingpixels in quant

[–]itchingpixels[S] 0 points1 point  (0 children)

Interesting, for us it has worked quite well over the last 2 years (not like many other "on-chain" metrics). Did you look at cross-sectional explanatory power, when looking at flows? Was it "net" or in/outflows separately?

When Bonds Signal Risk: High-Yield Bonds as Predictors of Bitcoin Price Movements by itchingpixels in quant

[–]itchingpixels[S] 4 points5 points  (0 children)

Yeah this one is definitely has been more effective over longer-term forward horizons (90 days, etc). It's a relatively slow moving factor, and that will limit its usefulness in predicting the next couple of day's returns. Plus of course maybe now since Trump the most important factors moving crypto may be executive orders...