diegot @gp97pe

Maybe just a little early on semis New Paradigm. This is why I would never short this kind of strength though, being early and right is still wrong. But for those screenshotting gains and celebrating I would have definitely been realizing some gains.

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diegot @gp97pe

4 months ago

@zhengyaojiang How do you envision the final version of this agent? Being able to saturate held out benchmarks?

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diegot @gp97pe

5 months ago

@IncomeSharks @crypto_condom @AltcoinSherpa What about $LAR sir

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diegot @gp97pe

5 months ago

@Vi1SoN @Pentosh1 Hyperliquid

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diegot @gp97pe

6 months ago

@Geiger_Capital $DGXX say it

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diegot @gp97pe

6 months ago

@GoodfireAI @jryio what is your success criteria for 'controlling model by intervening on geometry'?

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diegot @gp97pe

8 months ago

@ivancio4 Gracias por mantener al tanto de la situacion!!!

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diegot @gp97pe

9 months ago

@ThinkingUSD revenue per employee ...

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diegot @gp97pe

10 months ago

#IBelieve

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diegot @gp97pe

11 months ago

@BaijuBhatt Why are companies commiting so much money to earth data centers if space ones sound 100x better?

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Aporia @0xaporia

11 months ago

One last note on the Fear & Greed Index When people encounter the Fear and Greed Index in their feeds, they typically operate under a straightforward assumption: • low index values predict positive future returns • high index values predict negative future returns In other words, the index functions as a mean reversion indicator: when markets are overbought (extreme greed) or oversold (extreme fear), people expect that prices will revert toward the mean from these extremes. This is a hypothesis we can test. We can examine actual returns following extreme index readings. An easy and fast way to do this is to plot returns against index values and visually inspect the relationship. Under our mean reversion hypothesis, we would expect to see: • low index values: data points clustering top left • high index values: data points clustering bottom right The results reveal a lot of noise, but also a pattern, particularly in extreme greed territory: the indicator frequently fails during trending markets. When you trade based on overbought or oversold signals, you're essentially positioning against the prevailing trend. In practical terms, this means buying too early in downtrends and selling too early in uptrends. Instead of confirming our hypothesis, we not only find considerable noise but sometimes even the opposite of what we would expect to happen. Obviously, you can discuss how this approach could be slightly tweaked to improve performance. Criticism is welcome, as always. My point is: this is a metric influencers love to hype, but as the chart shows, it’s mostly just noise :)