drifting with markets

Joined January 2018
I think one could quite confidently call this a stock pickers market since there is more idio dollar spread available than in any non-crisis year since 2002 (see first chart comparing demeaned, windorized ESTU total returns decile ranked in 2019, 2025, 2026 (all through the 1/1-10/12 YTD period). We note the total return spread between top and bottom decile is larger in 2026 than either of the other two sampled years which further supports this thesis. However, a larger proportion of the x-sectional volatility this year has been factor-driven which the next two charts further expand on. The second chart tracks how far apart stocks have drifted from each other in 2026, split into the component explained by factor exposures and the component that is stock-specific. The dashed lines show where each would be if no moves had reversed. From this we note that idio dispersion has compounded steadily all year while factor dispersion ran ahead of its line until June 22, then collapsed through late July. The third chart shows stocks are ranked by how much factor exposure helped or hurt them through June 22. From this we note that the biggest factor winners had gained 47pp, then gave back 25pp by July 29. The biggest losers recovered 11pp. Every decile reversed in order meaning this was a systematic unwind. The takeaway here is that through June, factor tilts created a 79pp spread between stocks and almost half of that reversed in five weeks, whereas the same window in 2025 gave back 1%. So pnl generated by stock-specific returns were relatively more stable, while gains carried by factor exposure largely have not been. This all generally supports the notion that there IS spread to capture in 2026 but that a sloppy approach to this has resulted in underperformance relative to the market given the broad factor return reversal the market has been experiencing in 2H 26'. Methodology: Top 3,000 stocks by market cap in the risk model's US estimation universe, Jan to Oct 12 each year: daily returns are split into factor (total minus specific) and idio (risk model specific), winsorized at the 1st/99th percentile and demeaned across stocks each day to remove the market. They are then summed additively to compare cross-sectional dispersion, decile spreads and the build-up and reversal of factor vs idio returns against 2025 and 2019.
This isn’t a stock picker’s market. If you just sat in the passive market index, you did fine/well. Stock pickers, who spent lots of time analyzing the stocks they picked, are understandably upset that all that analysis was for naught and doing nothing won. Isn’t that efficiency?
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Excited to announce Options 101! It's a site that provides free, no-ads, no-shill education on financial options (calls + puts). The first course is one I'm now teaching this fall at Charles University in Prague. Lecture notes, videos, assignments. options-101.com/
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***BONDISTAN IS NOW ON SALE!*** GET IT WHILE IT'S HOT It has been a journey to get this ready for publishing and I'm proud to finally share this with everyone. It would mean the world if you could spread the word and maybe buy a copy (or few dozen). Your support for my work means everything. ❤️ Available in physical and digital, Bondistan 2nd Edition in all its glory is here. Links to the various formats below. (If you're using your non-US Amazon storefront just search for "tourist guide to bondistan") Hardcover (Physical)📔: amazon.com/dp/B0HGQG3XJP Paperback (Physical)📔: amazon.com/dp/B0HGLDK8RF Kindle e-book (digital)📱: amazon.com/dp/B0H1D4GVQR Gumroad Store (digital - PDF + e-book + Prove-outs)📱: effmkthype.gumroad.com/l/bon…
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Using Astra (checked by fable), I think I have proven and formally verified that in the Black-Scholes model, the exercise boundary of an American put option is log-convex for nonzero dividends. It’s not really earth-shattering, but it’s a legitimate open problem in mathematical finance: it was shown in 2008 that the exercise boundary was convex for the zero-dividend (q=0) case, and in 2013 that it could be non-convex for dividends exceeding the risk-free rate r, but the very practical worlds where 0 < q <= r were unknown (barring a claimed tightening of the bound in 2017). Astra found a relatively intuitive proof that the boundary is log-convex (stronger than convexity) for the full 0 < q <= r domain. — essentially sweeping sets of candidate linear boundaries, to show that the exercise boundary would never intersect that line twice. This result is probably not useful standalone when we already have numerical solutions for pricing American options and have empirically observed for many years that the boundary was convex (not to mention this is in pure Black-Scholes world)… but it’s a doorway to provably reliable pricing approximations and [redacted].
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*BREAKING: Bondistan is opening its borders on 15th September to celebrate Lehman Collapse Day and you're invited to get your visas ready! The Ultimate Guide to Bondistan 2nd Edition is coming to print! Do me a favour and spread the word! More details to follow.
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Tho retweeted
AI has made me too lazy with writing Forcing myself to write more on jaechung.net Will be posting random musings from time to time First piece was on early days of @ManifoldTrading
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Tho retweeted
Exchange tech thread: how we run multiple matching engines and upgrade without downtime
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bro wtf
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Tho retweeted
I've been building an exchange for the better part of the past year. I'll say more in the coming weeks but we have a small, focused, top notch team working in earnest to deliver a high quality venue that treats traders with respect. xitter.cf/pascaldottrade/status/…
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Good morning my loves, happy Saturday. Sorry I've been quiet, obviously been busy, but thought it'd be nice to give you all the details on the multi-strategy absolute return program that experienced the 28% drawdown this year. (1/n)
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slice of life
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Do I have any followers who work at AlphaGrep (either now or in the past) who would be willing to talk to me about it? Trying to figure out some stuff.
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man vs mountain
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The gap between where you are and where you want to be exists only in the space between thinking and doing. Everything you desire already has a path to it. Someone has done it before, or the steps can be broken down and figured out. The real barriers aren't external; they're the stories you tell yourself about why you can't start today, with what you have, from where you are. Your desires aren't random, they're signals pointing toward your authentic self. Trust them, but hold them lightly. As you move toward them, you'll discover that the person you become in pursuit of what you want is often more valuable than getting the thing itself. Start now. Start imperfectly. Start with one small action today. Then another tomorrow. Consistency compounds faster than talent, and action creates clarity faster than planning. Most people wait for permission, perfect conditions, or complete knowledge. You don't need any of these. The universe is incredibly responsive to genuine effort. When you commit and start moving, resources appear, people help, opportunities emerge. But this magic only happens after you begin, never before. Your time is finite and precious. Every day you delay acting on what matters to you is a day you can't get back. Stop researching, stop preparing, stop waiting for the right moment. The right moment is now, and you already have enough to take the first step. Everything else is just details you'll figure out along the way.
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Haute Fihnance 101
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RSVP for a timeslot. No public hours. May 7-10, Caelum Gallery @ W26th.
Through this elevator you will enter Hardo’s Debut Art Show - Haute Fihnance 101 - on May 7-10, 2026
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Mean-variance optimization (MVO) is one of the most foundational ideas in finance. It is also one of the easiest to caricature. You estimate expected returns and a covariance matrix, feed them into an optimizer, and often the result disappoints. So what goes wrong?
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Tho retweeted
Threw together a Wordle-style game for data transformations. You get a chart and guess what was done to the data (winsorize, z-score, gaussian rank, lag, etc). Reply if you want to try it and I'll probably put it out there.
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If I have an obj func like: x*active_risk + y*market_impact + z*linear_cost, is there a neat way to find (x,y,z) analytically or top down rather than a grid search on backtest results? paging the OGs: @__paleologo @macrocephalopod @0xfdf and everyone. Thank you in advance!
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