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Alternative Risk Premia

volatility-tradingLevel 3 — Advanced

Prerequisites

Options Market StructureEdge Identification

What It Is

Identifying and harvesting persistent mispricings across derivatives markets by providing liquidity to end users (pension funds, structured product buyers, corporate hedgers) who transact based on structural needs rather than price optimization. Distinct from pure vol selling — focuses on relative value: simultaneously buying cheap and selling expensive exposures while hedging out directional market risk.

Correct Execution

Practitioner identifies the end user whose structural needs create the mispricing, builds a portfolio of strategy "sleeves" each targeting a specific flow type, and manages the resulting basis risk. Can articulate why each trade exists (whose behavior is creating the dislocation), whether it is structural/persistent or opportunistic/fleeting, and what will cause it to reverse. Sizes each sleeve based on current opportunity relative to historical mean, not fixed allocation.

Progression Levels

Diagnostic Tree

Coaching Cues

  • "What is the end user doing in this part of the market and why? That's your trade." — Benn Eifert; when identifying any vol trade
  • "Bring balance to the force — find the congestion, provide the liquidity." — Benn Eifert; when evaluating new strategy sleeves
  • "The model doesn't know about the xiv rebalancing. Add that knowledge." — Benn Eifert; when model outputs diverge from known structural dynamics
  • "Academic premia, regulatory premia, flow premia — they're all real but have different lives and sizes." — Sandrine Ungari; when classifying new edge sources

Common Errors

  1. Treating all vol strategies as the same thing: Call overwriting (directional exposure, equity beta is dominant risk) ≠ volatility investing (isolates features of return distribution, not direction) → they require different frameworks for edge identification, sizing, and risk management.
  2. Over-relying on factor labels for vol: Value/momentum/carry don't map cleanly to vol strategies → the Star Wars framework (structural end-user needs create opportunity) is more accurate than the factor taxonomy → understand the economic rationale specific to vol markets.
  3. Assuming structural flows are permanent: Pension OWC programs grew, reached peak, may shrink. Buffer funds are growing → track AUM and behavior evolution, not just historical opportunity size.
  4. Trying to fully automate vol relative value: Non-linear payoffs mean model errors have non-linear consequences → human judgment at the "last mile" is not optional. Vol strategies sit ~7-8/10 systematic, not 10/10.
  5. Ignoring short-vol ETP mechanical dynamics: When short-vol ETPs are large, they must buy vix futures on a spike. This is known, predictable, and creates the catastrophic event. Not incorporating this known mechanical risk into position sizing is a structural error.

Edges

⚡ Conventional Wisdom Is Wrong

Vol Investing Is Not Vol Selling

volatility-tradingalternative-risk-premia →

Most practitioners conflate volatility investing (relative value — simultaneously buying cheap and selling expensive exposures, hedging out directional risk) with vol selling (collecting the variance risk premium by selling options). Vol selling is a directional carry trade. Vol investing is liquidity provision to specific end users. They have completely different risk profiles, sizing frameworks, and failure modes.

What most people do
Treat any options strategy that generates positive theta as "volatility investing." Use the same risk framework (VIX level, max notional) for both call overwriting and relative value vol books.
What the best do
Classify every vol position by its economic function: is this directional carry (vol selling, positive theta) or relative value (long one part of the vol surface against another)? Apply entirely different sizing, monitoring, and exit frameworks to each.
Why it's an edge: Prevents treating a directional carry trade as if it has the diversification and self-hedging properties of a relative value position. The Volmageddon failure mode applies to the former, not the latter.
How to exploit: For every options position, document whether it is (a) a directional carry trade capturing the variance risk premium, or (b) a relative value trade capturing a spread between two differently mispriced vol surfaces. Size (a) based on VRP spread; size (b) based on the spread between the two legs.
Benn Eifert, "Volatility Investing," Flirting with Models S2E2, 2021-04-10
🔑 Hidden Causal Lever

Full Automation Fails At The Last Mile In Options

volatility-tradingalternative-risk-premia →

Vol relative value strategies sit at approximately 7-8/10 on the systematic spectrum — not 10/10. Options have non-linear payoffs where model errors have asymmetric consequences. A model calibrated on historical data cannot know that short-vol ETPs must mechanically buy VIX futures on a spike — but a human who tracks market structure can. That human judgment layer is not optional or transitional; it is permanent.

What most people do
Treat increasing automation as an unambiguous improvement goal. Assume that adding more systematic rules reduces risk. Target full automation as the endpoint.
What the best do
Deliberately maintain human judgment at the "last mile" of options portfolio construction and risk management — specifically for identifying when known structural fragilities (e.g., crowded mechanical ETPs) are not captured in the historical model.
Why it's an edge: The fully automated vol fund is systematically blind to known market structure dynamics. The partially systematic fund that retains the human structural knowledge layer has an informational advantage in tail scenarios.
How to exploit: Maintain a live "model blind spots" log — structural dynamics (ETP mechanics, dealer hedging regimes, flow crowding) that are known but not in the model. Review this log weekly alongside model output. When the log flags a known risk, override the model.
Benn Eifert, "Volatility Investing," Flirting with Models S2E2, 2021-04-10
🔑 Hidden Causal Lever

VVIX Was The Volmageddon Warning That Everyone Ignored

volatility-tradingalternative-risk-premia →

Before Volmageddon (February 2018), VVIX (implied volatility of VIX — the vol of vol) was elevated, signaling that the market was cheaply pricing the crash scenario for short-vol ETPs despite the known mechanical rebalancing dynamics. The signal existed; it was not read. Short-vol ETP AUM had also grown through retained profits (not just inflows), creating structural leverage that most AUM-watchers missed.

What most people do
Monitor VIX level and short-vol ETP inflows as crowding indicators. Treat stable VIX as a signal that the short-vol trade is safe.
What the best do
Monitor VVIX (vol of vol) as the primary signal for when the market is cheaply pricing a vol spike. Simultaneously track short-vol ETP AUM growth through retained P&L (not just net inflows) to identify hidden leverage accumulation.
Why it's an edge: Two signals that most practitioners don't watch — VVIX and P&L-retained ETP leverage — combine to identify the structural fragility before the event.
How to exploit: Add VVIX to the standard regime monitoring dashboard alongside VIX. When VVIX is elevated relative to VIX (vol surface is in backwardation or steep), treat short-vol positions as fragile regardless of VIX level. Track ETP AUM net of losses to identify leverage buildup.
Benn Eifert, "Volatility Investing," Flirting with Models S2E2, 2021-04-10
🔑 Hidden Causal Lever

Short-Vol ETP AUM Grows Through Retained P&L, Not Just Inflows

volatility-tradingalternative-risk-premia →

Standard AUM-watching underestimates leverage buildup in short-vol ETPs because their AUM grows through retained profits rather than new investor inflows. This hidden leverage accumulation was the structural driver of Volmageddon — the products got bigger through their own profits, not through monitored inflow channels.

What most people do
Monitor inflow data to assess short-vol crowding. Assume AUM growth = new investors = measurable crowding.
What the best do
Track retained P&L as a separate AUM growth driver. Recognize that products compounding through their own profits build leverage invisibly — inflow monitors show nothing. The risk metric is total AUM relative to underlying market depth, regardless of growth source.
Why it's an edge: Retained-P&L-driven growth is invisible to standard crowding monitors. The practitioner who tracks it sees leverage building before traditional flow watchers do — providing early warning of the next structural short-vol blowup.
How to exploit: For any short-vol ETP, calculate: (total AUM - cumulative net inflows since inception) / total AUM. This gives the % of AUM attributable to retained profits. If this exceeds 50%, the product has doubled in size without a single monitored inflow.
From Level 4 and Edge 3 detail — Volmageddon structural analysis

Sources

  • Benn Eifert, "Volatility Investing," Flirting with Models S2E2 (2021-04-10) — vol relative value, Star Wars framework, end-user taxonomy, Volmageddon mechanics, systematic vs. discretionary spectrum
  • Sandrine Ungari, "Alternative Risk Premia," Flirting with Models S3E10 (2021-04-10) — ARP taxonomy (academic/regulatory/flow premia), factor construction evolution, long-vol tail hedge requirement