At a recent conference, over a beer, I was asked, "why should I even bother with bonds anymore?"

There was, of course, some recency bias to the question.

But the main concern, as I teased it out, was about a structural shift in correlations between stocks and bonds. The proposed solution was replacing stocks + bonds with stocks + cash (or a buffered product).

My problem with this solution is that it eliminates a unique return driver from the portfolio.

"But Corey, what if stocks and bonds have perfect correlation going forward?"

The most obvious edge is when you know precisely who your counter-party is and precisely why they have to act in a way – usually constraints – that leads to your profit opportunity.

You can then soften your certainty across both axes (counter-parties and behavior).

https://twitter.com/bennpeifert/status/1961175152357773746

Here's a recent example of something that looks like a reasonably precise edge.

Sycamore Partners just acquired Walgreens Boots Alliance for $11.45 / share and non-transferable divested asset proceed ("DAP") rights.

The DAP rights represent a potential payout of up to $3.00 per share, with 70% of net proceeds from the sale of the VillageMD assets going to DAP right holders, capped at that amount.

If you held $WBA at the time the merger closes, you inherit the DAP rights. The difficult-to-value, illiquid nature of this right makes it unappealing for many funds.

So, it's not terribly surprising that when the official merger close date was announced, $WBA started to sell off as funds shed their exposure.

Someone who was willing to warehouse the DAP right risk could have stepped in to buy it at a meaningful discount – and it even repriced upward meaningfully into the merger close.

the back story here is I was trying to run a strategy on a new crypto exchange.

with 2.5bp taker and 0bp maker fees, i was trying to execute all my trades as limit orders to reduce t-costs, but constantly found myself immediately underwater by 15-20bp. on both entry and exit.

https://twitter.com/choffstein/status/1935686689248157735

the problem is that the exchange does, on average, ~$400/second in BTC volume. the median is likely $0/second.

so, if I put a $10k limit order on the best bid or best ask, the odds of organic taker flow hitting me was unlikely.

Alright, so, I wanted to run some simulations to demonstrate the trade-off between short-term volatility and long-term certainty.

To start, I simulated out completely random* yield curve changes.

Below is an example evolution.

https://twitter.com/choffstein/status/1923061735805587858

Next, I used these random yield curves to price out the return of two portfolios.

First was a portfolio where I just keep rolling over 6-month Treasuries every single month.

Below is the spread of annualized returns over time.

(I'll address the negative drift in a moment.... but ignore it; it's not the point.)

"The reward for accepting lower market liquidity is an increase in diversification benefits, rather than more profitable trends." New research note from Quantica about trend following, capacity, and commodities.

👇
quantica-capital.com/publications/p…

The team at ReSolve is out with some new research on multi-asset carry when applied to Liquid versus Extended trading universes. In September 2021, ReSolve started trading a multi-asset carry strategy with a target volatility of 20%.

The universe includes ~70 markets (bonds, currencies, energies, metals, equities, grains, livestock, and softs).

Over the live period, they've realized a Sharpe of ~0.5

In celebration of another managed futures replication fund being launched today, here's a little insight into a problem that both top-down (returns-based) and bottom-up (process-based) replication face. Both of these approaches use the historical returns of an index.

The return of that index is driven by two factors:

(1) The underlying component weights
(2) The underlying component returns

Replication is trying to figure out (1), but (2) can be a significant problem.

“Levered portfolios are subject to variance drain!"

So are your long-only active stock funds.

Don’t believe me? Read on. Any long-only active stock strategy can be thought of as a combination of two parts:

- 100% exposure to the benchmark
- 100% exposure to a long/short portfolio capturing the over- and under-weight positions of the manager

(It's long/short portfolios all the way down...🐢)

Most folks are accustomed to evaluating investment products based upon their performance.

In the case of capital efficient strategies, I think this misses a huge opportunity. Consider a capital efficient strategy that gives you $1 of exposure to stocks and $1 of exposure to bonds for every $1 invested.

i.e. a 2x levered 50/50.

I would expect most people to look at a long-term graph and pontificate about the trade offs of leverage and diversification

One question I receive all the time is,

If Treasury futures don’t pay coupons, aren’t they just the price return of the bonds?

Let’s debunk it with a quick picture and then explain. The white line is Ultra 10-year US Treasury Note Futures.

The yellow line is the S&P U.S. Treasury Bond Current 10-Year Index (Total Return) divided by 1-3 Month T-Bills (Total Return)

Staying on trend
Designing an algorithmic trading strategy

Highlighting some new research from SocGen Diversification matters.

“Consider a hypothetical experiment. We construct a series of model portfolios, each containing between 2 and 100 randomly selected trend-following strategies, drawn from a pool of 120 such strategies. For simplicity, we assign the same notional value to each strategy within a portfolio. We then calculate the Sharpe ratio of each portfolio."

cc @investingidiocy

1/ People keep sending me this piece from AQR and asking for my thoughts regarding alternatives, cash rates, and return stacking.

At the risk of inviting the ire of Cliff… I disagree (a little) with the piece.

*ducks*

aqr.com/Insights/Resea… 2/ Actually, that’s probably not fair.

I disagree with the overwhelming interpretation I see people making, which is: higher cash returns imply lower forward asset class returns.

My company, Newfound Research, turned 15 today.

Coming up on this anniversary, I reflected quite a bit on my career.  I’m not sure why, but this milestone feels larger than I would've expected.

So I decided to write something.

15 Ideas, Frameworks, and Lessons from 15 Years This is going to be an obnoxiously long thread, with obnoxiously long posts, so if you'd rather read it as a blog or listen to an audio version, here are the links:

📝

🎙️ Spotify: blog.thinknewfound.com/2023/08/15-ide…
open.spotify.com/episode/0u2tBK…

TIL that the sum of the squared z-scores is always equal to the number of z-score values. Also, the shape of the distribution of z-scores will be the same as the original shape of the distribution of the underlying data.

This one seems more obvious, since you’re just shifting the scaling. But never thought about it before.

1/ A month-or-so ago, @GestaltU penned a piece about replicating the Societe Generale Trend index.

I spent the better part of last week doing a deep dive into the recent performance of these approaches.

investresolve.com/peering-around… 2/ Adam proposes two primary means of replication:

Top Down: Regress recent returns of the SG Trend Index on futures markets to identify the weights that best explain returns.

Bottom Up: Combine an ensemble of trend models selected and weighted to match the SG Trend Index.

pretty explosive recent episode of @TopTradersLive with @andrewdbeer1 and @AuspiceTim…

nobody asked for my opinion, but i’m going to share it anyway.

toptradersunplugged.com/podcast/246-sy… first, kudos to both of these gentlemen for pioneering access to CTAs in an ETF wrapper.

i liked niels's summary: everyone on the podcast can agree that investors should allocate more to the space.

1/ A "quick" summary of my Democratize Quant discussant role for @RA_Insights's paper "Reimagining Index Funds"

(The paper actually seems to have been taken down from Research Affiliates's website... but here's the tweet, I guess

https://twitter.com/RA_Insights/status/1646894358023802880

) 2/ The key contributions of this paper are:

👣 Economic footprint is a more stable measure than market capitalization

📈 Economic footprint avoids "buy high, sell low" behavior

🌊 Economic footprint should be proportional to market cap, retaining liquidity and capacity.

I think one of the best exercises for a young quant is to try to replicate QIS research / indices.

You can learn a ton.

Practically: gather/clean/store data, write non-trivial code, and interpret research.

But more importantly... You get to see how strategies perform out of sample.

Or how they perform with slightly different inputs.

Or how the different steps of the strategy impact the output in non-linear ways.

You develop more intuition for what will have an outsized impact.

What's worse than a twitter thread? A thread of threads.

Here's my 🧵² on Return Stacking™️

(i.e. threads you may have missed) 1/ What is Return Stacking™️?

https://twitter.com/choffstein/status/1437772693764550662?lang=en

On our way...

thinknewfound.com/structural-alp…

https://twitter.com/choffstein/status/1607721358187716610

The models are now available at Altruist, Amplify, Morningstar Model Marketplace, OneDigital, and SmartX.

Huge thank you to our partners at @SimplifyAsstMgt for their continued support in this endeavor.

this was a “fun” real life example of “limits to arbitrage” for me.

the limits I encountered:

1. taxes
2. liquidity
3. laziness

https://twitter.com/0xtuba/status/1639964219847110656

Assuming I timed things perfectly, a repeg would’ve realized a ~14% return.

With a bunch of ETH, I had two choices:

1. Sell ETH to buy USDC
2. Borrow against my ETH