What are the key takeaways from this All the Credit episode?

Key insights include: **Strategy Selection Bar:** PGIM maintains approximately 20 active systematic trades, adding only 2-4 new strategies annually. Half are always-on positions, half are tactical market timing trades. This high bar prevents false positives from data mining and ensures each trade has strong fundamental thesis backing.; **Data Quality Constraints:** Systematic credit strategies focus on macro-level trades like up-in-quality versus down-in-quality or synthetic versus cash because individual bond price data remains unreliable. ETF growth improves index-level price discovery but actually reduces individual security transparency as fewer bonds trade directly.; **Fixed Income Passive Churn:** Unlike equity index funds, fixed income passive vehicles create systematic opportunities through constant rebalancing. Bonds continuously enter and exit indices, most exiting a year before maturity, creating predictable buying and selling patterns that systematic strategies can exploit ahead of passive flows.

What did Tyler Thorn discuss on All the Credit?

Tyler Thorn explains PGIM's systematic credit investing approach, which combines rules-based strategies with fundamental analysis to exploit macro credit market patterns, focusing on index-level trades rather than individual security selection in fixed income markets. Key topics include: **Strategy Selection Bar:** PGIM maintains approximately 20 active systematic trades, adding only 2-4 new strategies annually. Half are always-on positions, half are tactical market timing trades. This high bar prevents false positives from data mining and ensures each trade has strong fundamental thesis backing.; **Data Quality Constraints:** Systematic credit strategies focus on macro-level trades like up-in-quality versus down-in-quality or synthetic versus cash because individual bond price data remains unreliable. ETF growth improves index-level price discovery but actually reduces individual security transparency as fewer bonds trade directly..

How long is this episode of All the Credit?

This episode is 28 minutes long. SignalCast provides an AI-generated summary so you can get the key insights in about 3 minutes.

All the Credit

Credit Markets in Transition: Systematic Strategies

July 22, 2025

28 min episode · 2 min read

Tyler Thorn

Episode

28 min

Read time

2 min

Topics

Productivity, Investing, Sales & Revenue

AI-Generated Summary

Published Jan 2, 2026

Key Takeaways

✓Strategy Selection Bar: PGIM maintains approximately 20 active systematic trades, adding only 2-4 new strategies annually. Half are always-on positions, half are tactical market timing trades. This high bar prevents false positives from data mining and ensures each trade has strong fundamental thesis backing.
✓Data Quality Constraints: Systematic credit strategies focus on macro-level trades like up-in-quality versus down-in-quality or synthetic versus cash because individual bond price data remains unreliable. ETF growth improves index-level price discovery but actually reduces individual security transparency as fewer bonds trade directly.
✓Fixed Income Passive Churn: Unlike equity index funds, fixed income passive vehicles create systematic opportunities through constant rebalancing. Bonds continuously enter and exit indices, most exiting a year before maturity, creating predictable buying and selling patterns that systematic strategies can exploit ahead of passive flows.
✓Complexity as Opportunity: Fixed income market complexity creates alpha because investors have varied goals. Someone buying 30-year bonds versus one-year bonds has different objectives, causing sector-specific dislocations as large investor groups drive segments rich or cheap, generating exploitable mispricings across the credit curve.

What It Covers

Tyler Thorn explains PGIM's systematic credit investing approach, which combines rules-based strategies with fundamental analysis to exploit macro credit market patterns, focusing on index-level trades rather than individual security selection in fixed income markets.

Key Questions Answered

•Strategy Selection Bar: PGIM maintains approximately 20 active systematic trades, adding only 2-4 new strategies annually. Half are always-on positions, half are tactical market timing trades. This high bar prevents false positives from data mining and ensures each trade has strong fundamental thesis backing.
•Data Quality Constraints: Systematic credit strategies focus on macro-level trades like up-in-quality versus down-in-quality or synthetic versus cash because individual bond price data remains unreliable. ETF growth improves index-level price discovery but actually reduces individual security transparency as fewer bonds trade directly.
•Fixed Income Passive Churn: Unlike equity index funds, fixed income passive vehicles create systematic opportunities through constant rebalancing. Bonds continuously enter and exit indices, most exiting a year before maturity, creating predictable buying and selling patterns that systematic strategies can exploit ahead of passive flows.
•Complexity as Opportunity: Fixed income market complexity creates alpha because investors have varied goals. Someone buying 30-year bonds versus one-year bonds has different objectives, causing sector-specific dislocations as large investor groups drive segments rich or cheap, generating exploitable mispricings across the credit curve.

Notable Moment

Thorn reveals that PGIM deliberately avoids individual bond selection strategies despite having better alpha potential, because the firm already employs an entire floor of fundamental analysts excelling at bottom-up credit work, making macro systematic strategies more additive and orthogonal.

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Episode Transcript

You're listening to All the Credit, a monthly podcast series brought to you by PGIM, an active global investment manager. Welcome to All the Credit. I'm Brian Barnhurst, global head of credit research at Public Fixed Income. Today's episode continues our look at the evolution of credit markets. At first blush, systematic strategies may seem out of place in a largely fundamental investment shop, but the reality is that fundamental insights and analysis are the building blocks of many systematic strategies. To break down the asset class and our approach to systematic investing, I'm fortunate to be joined by Tyler Thorn, portfolio manager on the multi sector team and the lead portfolio manager on our systematic strategies. Tyler, welcome to the podcast. Thanks. Happy to be here. Systematic investing is sort of a catch all buzzword. To level set, help us break down the universe of systematic and programmatic investing. Yes. Systematic investing is definitely becoming a bit of a buzzword. It's almost like the word privates. And it can come to mean almost everything and nothing, but their one unifying thing that's true for all systematic investing is that it's rules based. There are certain criteria that when they happen, you're going to try to buy something or you're gonna try to sell that thing. When thinking about that world, I think that you can really break it down further into two axes. One is what type of investing are you trying to do? All the way from really broad macro, where is the S and P 500 going? Where is ten year treasuries going? All the way down to really micro where are Ford bonds going or even where is five year Ford going versus five year GM. On the other side of that, you also have how frequently you're trading, which is correlated to, and then you also causal with how much of fundamental theory you have in the investments you're making versus how much of a purely black box investing style you have. If you're trading every second, think about high frequency traders, they don't need to have a fundamental thesis about what they're doing. They have a large enough sample size, enough data that they can consume that it's really just getting the smartest, fastest computers all in one place, grabbing the best data you can get, and you create alpha that way. If you have less data available to you, think about fixed income credit where bonds mostly trade over the phone, and you maybe get one good price a month. You wanna be slower in how you're executing, and you also wanna be more fundamental bottom up, understanding the reasons why a trade would work before you put it on. You don't have enough data just to data mine everything and know it's gonna work. You actually need to think, why should this work before you do any study? Traditional equity factors actually fall a little bit more into that world. Value, momentum, …

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