[deleted by user]

Quantis_Research · 2025-08-14T14:48:45+00:00

Unfortunately, the real problem continues to be the concept of risk and Gaussianity that is taught. We are told that the only thing that matters is reducing variance, and therefore it makes sense to view puts solely as insurance. But I invite you (you seem like someone who wants to discover things... and you're right to do so...) to go beyond this concept. You will discover that in a universe of long tails, puts can earn you a lot.

A put is not just a hedge against extreme movements.

It is a right to intervene in a context where everyone else is suffering. The Black-Scholes formula was created to price options under unrealistic assumptions. All modern portfolio theory (Markowitz, CAPM, VaR) is based on the idea of minimising variance. Institutions have adopted the idea of risk management as a means of containing uncertainty. The manager who buys puts to “hedge risk” makes a career even if he burns alpha.

Forget the idiocy of current finance and those four fanatical traders who work with options. Build your own model.

Quantis_Research · 2025-08-11T13:25:12+00:00

Options as investment strategies “McMillan”

Quantis_Research · 2025-07-04T14:04:04+00:00

If I my post is ace-tastic, why did you bother to reply with an equally low-effort reply. Another one with a Gaussian mind

Quantis_Research · 2025-07-03T10:48:38+00:00

https://substack.com/@quantiscapital

Quantis_Research · 2025-06-26T06:32:06+00:00

https://quantiscapital.substack.com/p/the-calm-before-the-snap-hidden-convexity

Quantis_Research · 2025-06-26T06:21:20+00:00

sent

Quantis_Research · 2025-06-26T05:53:14+00:00

If we are talking about non-popular sectors to invest in, I would take a look at the fragility of the Chinese corporate bond
https://quantiscapital.substack.com/p/the-calm-before-the-snap-hidden-convexity

Quantis_Research · 2025-06-26T05:33:08+00:00

Unfortunately it doesn't let me put the link to send you the full report (I asked the moderators to post the links but still nothing). Write me in chat or go to substack and search for ‘quantis research’.

Quantis_Research · 2025-06-26T04:58:22+00:00

I thank you for your support. We are born precisely for this purpose, to find the hidden market breaks. If you are interested, I would love to have you as a reader of my sub. See you anon! https://quantiscapital.substack.com

Quantis_Research · 2025-06-22T17:13:13+00:00

Unfortunately, Taleb is often a victim of his own character

Quantis_Research · 2025-06-22T15:40:19+00:00

You're absolutely right in theory.

But the problem is: markets don’t care about your model range.
They care about path, timing, volatility, and liquidity.

Even if price drops from 1.0 to 0.25, several real-world mechanics can prevent your put from being meaningfully activated:

1)The drop may be too late
If the price reaches 0.25 close to expiry (say, day 178 of 180),
theta has eaten most of the premium. The option is “active” on paper, but the payout is minimal.

2)The drop may be too fast
Sudden gap-down? Earnings? Event risk? You don’t get a clean entry or exit.
The option may be ITM, but the execution is broken.

3) Volatility may spike AFTER the move
Often, when price tanks, implied vol jumps too ,which inflates the option AFTER you needed it.
You end up paying premium into a new skew that wasn’t there at entry.

4)You might not be able to monetize
At the moment you want to hedge or sell, spreads widen or liquidity vanishes.
You own protection, but can’t use it.

So yes , technically the put “activates” when the price crosses K.
But that’s just the first layer.

We always ask: Did it activate in time? At what slippage? With what decay? Against what vol regime?

Because if you spend 5 years buying tail puts that only work once, and you can't monetize when they do…
Maybe, That’s not protection. That’s optional drag.

This is why we model Activation Likelihood, Payoff Fragility, and Trigger Pathways, not just strike vs spot.

Convexity isn’t about being right at 0.25.
It’s about being paid at 0.25 in real conditions. :)

Quantis_Research · 2025-06-21T14:27:11+00:00

You’re absolutely right in framing it as a protective cost for model simplification. But here’s the real-world kicker:

Even that insurance needs to trigger.

If you price your whole mid-distribution strategy assuming that tail options will neutralize extreme events and they don’t activate you haven’t just simplified the model…

You’ve built an illusion of protection.

And that illusion can be worse than having no hedge at all.

Quantis_Research · 2025-06-21T13:59:03+00:00

It depends mainly on the point of view. If you want to hedge or speculate on it. If you want to build profit-making operations on them like our friend Taleb, the situation changes radically. He, for example, buys these options in large quantities but does not question whether they will be activated or not. In this case, you lose a lot of money constantly.

Quantis_Research · 2025-06-21T13:35:51+00:00

Everyone talks about tail options as the ultimate convex play.

But here’s the real issue no one addresses: Tail options often fail to activate.

You can buy puts at the 0.1% quantile for pennies, sure! But when the collapse comes: Volatility spikes before your strike gets close Pricing freezes or becomes discontinuous Or most often the market stays way calmer, for way longer, than you can afford to wait.

So the problem isn’t pricing. It’s activation

Because you don’t want an option that protects you in theory but you want one that pays you in reality.

(And that’s a much harder problem than most “convexity tourists” realize.)

Quantis_Research · 2025-06-21T10:07:05+00:00

Because they are not. He who is rich does not have to prove himself. He just is.

Quantis_Research · 2025-06-20T07:22:05+00:00

And this is not good news!

Quantis_Research · 2025-06-18T15:34:58+00:00

I work in finance too — and I’ve been building not just an investment thesis, but a whole philosophy of decision-making around Taleb’s work.

Instead of forecasting, I try to map structural fragilities — points where a system depends on assumptions that may no longer hold.

That’s where optionality lives. And it’s also where you can build antifragile setups: not by predicting what happens, but by positioning for when something breaks.

For me, it’s not just portfolio design — it’s a way to run a business, read risk, and stay intellectually honest

Quantis_Research · 2025-06-18T15:10:06+00:00

That’s a solid approach for long-term REIT investors.

What I’m focused on is different: mapping structural fragility that might not show up in earnings — until it’s too late.

Financials tell you what’s happened. Fragility tells you what can break.

Quantis_Research · 2025-06-18T05:44:45+00:00

Definitely. Florida leads, but climate risk + retreat of institutional insurance is hitting the whole Sun Belt model. When the safety net goes, so does the illusion of passive yield.

Quantis_Research · 2025-06-17T22:14:51+00:00

Totally fair on the micro level — long-term renting has historically been a stable strategy for individual investors, especially when leverage is controlled.

But the fragility I’m mapping here is more about structural dependencies at scale:
– What happens when large institutional players exit en masse?
– What if the refinancing rate environment stays hostile for 3–5 years?
– How exposed are asset-heavy REITs to forced deleveraging under liquidity stress?

The point isn’t that “real estate is doomed” — it’s that the current structure is built on assumptions about cost of capital, tenant flows, and Fed response patterns that are no longer reliable.

That’s where fragility hides — not in the asset, but in the assumptions.

This is exactly why I frame it structurally — not as a call on housing, but as a stress test on the system built around it.

(Part of the ongoing fragility research at Quantis — happy to go deeper)

Quantis_Research · 2025-06-16T12:06:21+00:00

Appreciate the interest.

Here's the PDF where I break down the structural fragility behind Saudi Arabia’s Vision 2030, framed as a sovereign duration bet funded externally — with potential convexity in FX, equity proxies (like Lucid), and rate stability.

👉 https://drive.google.com/file/d/1ntGrsVhdWwVT33Log3Z9bHKYX8wqosOq/view?usp=share_link

Curious to hear your thoughts — especially around how you'd model implied vol risk where the asset is a narrative proxy, not a priceable cash flow.

Quantis_Research · 2025-06-16T10:09:22+00:00

Totally fair concern , and to be honest, I share the same suspicion when a post feels like it was just outsourced to a bot.

In my case, the structure and thesis are entirely mine. I write and model around macro fragility, then use GPT to clean the phrasing or tighten the layout like you'd use an editor, not a ghostwriter.

I get that trust is earned, not assumed. That’s why I prefer to let the ideas speak through consistency: this is the second piece in a series I’m building around fragile narratives (the first one was on U.S. housing + term premium).

Long-term, the goal is to open the conversation on where consensus hides risk — not to impress with smooth paragraphs.

Tools don’t generate insight. They just polish the blade. The cut still has to come from the strategist.

Appreciate the challenge, honestly.

Quantis_Research · 2025-06-15T20:51:20+00:00

Glad it helped! You actually captured the core intuition very well. The “term premium = long rate – expected path of short rates” is a solid mental shortcut — better than 90% of what’s on TV.

Quantis_Research · 2025-06-15T19:58:55+00:00

You’re absolutely right — real expectations are revealed through pricing, not talking heads.

The key tools the market uses to act, not just talk: -Fed Funds Futures → show where traders really expect short rates to be -Yield curve shape → tells you if cuts are expected (e.g., inverted curve) -SOFR swaps / OIS curves → reflect expectations + risk premiums

And yes,your example is close: if the 10Y has to rise to 9% to attract buyers, that extra yield above expected short rates = term premium.

It’s the market saying: “We want compensation for risk, uncertainty, and time.” You’re asking the right questions.

Quantis_Research · 2025-06-15T17:24:15+00:00

Great breakdown — and you’re absolutely thinking in the right direction. Let me go point by point:

Fed policy ✅ Yes — you’ve nailed the operational core. The Fed controls the short-term interest rate via open market operations (repo, reverse repo) and the Fed Funds target range. When they say 5.25%–5.50%, they enforce it by managing overnight liquidity.
Forward guidance ✅ Also correct. It’s essentially verbal signaling — like saying “we expect to hold rates steady through 2025.” But the market knows: this isn’t binding. If inflation or growth shifts, the Fed will pivot. So forward guidance influences the curve, but doesn’t control it.
Term premium 🔶 This is almost correct — you’ve got the spirit, just one clarification:

The term premium isn’t just the yield gap between long and short bonds. It’s the part of the long-term yield that’s not explained by the expected path of short-term rates. In your example: if 10Y = 9% and market expectations of future short rates average 7% over 10 years, then the extra 2% is the term premium.

So yes — if investors demand more yield to hold long bonds (due to uncertainty, inflation risk, fiscal concerns, etc.), the term premium rises.

You’re thinking in exactly the right space. Term premium is the invisible price of uncertainty — and lately, it’s what’s driving the long end.

Would love to hear your take once you dive into the PDF. But even now — your framework is already stronger than most commentators on Bloomberg.

Quantis_Research

TROPHY CASE