Predictive Gamma Strategy

Backtest methodology

Reported backtest figures are derived from a daily historical simulation of each strategy over its stated sample period, using historical market data for the instruments traded. Each simulated trading day applies the same signal, sizing, entry, and exit logic used in live operation. Trades are simulated at historical quotes with a conservative fill convention — sales filled at the bid and purchases at the ask — and with transaction costs and exchange/contract fees deducted on every leg; NAV is struck at the close. Position sizes are generated by the same Value-at-Risk-based engine (Strategies 1–3) or fixed NAV-proportional rule (Strategy 4) described above, so simulated exposure scales with the modelled book exactly as it would live.

The simulation does not model real-world frictions that affect live results, including market impact and partial or missed fills, intraday liquidity gaps, quote staleness or data errors, borrowing/financing effects, and the divergence that arises because a client executes independently of the model. Backtested results are hypothetical: they are produced with the benefit of hindsight, do not represent actual trading, and do not reflect the effect of material market or economic factors on real decisions. Past or simulated performance is not a reliable indicator of future results, and live results will differ — potentially materially — from any figure shown here. All figures below are stated gross of any management or performance fees charged by a distributing firm.

Common strategy specification

Instruments and venue

All strategies trade exchange-listed, cash-settled, European-style index options on Cboe: Mini-SPX (XSP) options, which reference the S&P 500 at one-tenth of the standard SPX notional, and VIX (Cboe Volatility Index) options. No over-the-counter instruments are used. Strategies 1–3 are operated as overlays on a core long S&P 500 position; Strategy 4 is standalone.

Evaluation cadence and data

The book is evaluated once per trading day from market data. Signals, sizing, entries, and exits are determined on that daily cycle (Strategy 4 additionally settles intraday — see below).

Execution assumptions

Trades are modelled at prevailing market quotes with transaction costs and fees included, using a deliberately conservative convention (sales at the bid, purchases at the ask). The model evaluates once daily; live runs are struck around the market open. It assumes normally functioning liquid-listed markets. Because clients execute independently, their fills, timing, and costs will differ from the model and may not be achievable in stressed or illiquid conditions. Individual trade failures are skipped rather than forced.

Position sizing — VaR engine (Strategies 1–3)

Sizes are risk-budgeted, not fixed. Each prospective structure is sized so that its modelled loss under a forward-looking adverse scenario equals a pre-set stress-loss budget (a small, fixed fraction of NAV). The per-unit stress loss is the worse of two historical-simulation Value-at-Risk scenarios — (i) S&P 500 down with VIX up, and (ii) S&P 500 up with VIX down — estimated at roughly 99% confidence over a 1-day horizon on a multi-year (~3-year) lookback, and applied to each leg through its delta, gamma, and vega. Sizing is on a net-risk basis: long/hedge legs are credited against short-risk legs. The result is then reduced as VIX rises and clamped between a floor of one unit and a hard, NAV-scaled cap, so exposure scales up as NAV compounds and down as risk rises, always within fixed limits. If the VaR input is unavailable, the engine falls back to conservative flat shock assumptions so the book is never sized on missing data.

Position sizing — Strategy 4

Does not use the VaR engine. It trades a fixed number of straddles proportional to NAV, holding nominal risk roughly constant as the book compounds.

Greeks

Portfolio Greeks (beta-weighted delta and gamma, time-weighted vega, theta, and theta- and delta-to-NAV ratios) are computed and reported daily for monitoring. They are not run to fixed targets or tolerance bands. The binding pre-trade risk control is the VaR stress-loss budget (Strategies 1–3) or the fixed NAV-proportional size (Strategy 4); Greeks are an oversight lens, not a control input.

Defensive Premium Harvest

Investment objective. Enhance the yield and reduce the drawdown of a core S&P 500 holding by systematically harvesting the equity/variance risk premium through short index puts, while carrying a standing long-volatility hedge against left-tail events. Target: a better risk-adjusted outcome than buy-and-hold or a standard buy-write.

Instruments / venue. Short S&P 500 (XSP) puts for income; long VIX calls as a convex hedge. Listed, cash-settled, European-style; not OTC. Run as an overlay.

Expiry selection. Puts in a medium-dated tenor; the VIX-call hedge longer-dated, so it persists across multiple income cycles. Positions are exited as expiry approaches.

Strike selection. Puts low-delta out-of-the-money, balancing premium against assignment risk; VIX calls low-delta OTM. The hedge quantity is set as a fixed fraction of the put premium, so protection scales with the income written.

Position sizing. VaR engine (see Common Framework), with the long VIX-call hedge netted into the budget, so the position reflects true combined net risk rather than gross short-put notional.

Rebalancing triggers. Calendar: a new tranche on a periodic, rules-based schedule, with a volatility-based entry refinement that can bring an entry forward within the window. Event-based: early exit as expiry approaches; a long-horizon moving-average trend filter flattens both the put and the hedge legs when the index breaks below trend and gates new entries while it remains below trend.

Greeks / execution. Per Common Framework.

Backtest methodology

(Sample period: 2023-03-08 – 2026-06-30; hypothetical)

• Average outperformance vs benchmark (S&P 500): + 0.38 % per month, + 1.11 % per quarter, + 3.67 % per year
• Average time in trade (holding duration): 38.9 days
• Average trade frequency: 2.93 per week, 12.75 per month

Diagonal Volatility Carry

Investment objective. Add a non-directional, low-correlation return stream by harvesting the volatility risk premium (implied volatility tending to price richer than subsequently realised), expressed through a net-short VIX call structure, as an overlay.

Instruments / venue. VIX options only (listed, cash-settled, European-style; not OTC).

Structure and key risk characteristic. A net-short VIX call ratio — more nearer-the-money calls sold than further-out-of-the-money calls bought — in a medium-dated tenor, rolled as expiry approaches. Because more calls are sold than bought, the position remains net-short above the long strike and the upside tail is not capped: losses are unbounded if volatility spikes far enough. The long leg softens, but does not bound, the tail. 

Expiry selection. Medium-dated VIX options, rolled systematically as they approach expiry.

Strike selection. Short legs nearer-the-money; long leg further OTM.

Position sizing. VaR engine; the long leg is credited and size is reduced as VIX rises. Sizing mitigates but does not bound the tail, given the net-short structure.

Rebalancing triggers. Calendar / roll: re-established on a continuous roll as each tranche is exited near expiry. Event-based: early exit as expiry approaches. No trend filter is applied.

Greeks / execution. Per Common Framework.

Backtest methodology

(Sample period: 2023-03-08 – 2026-06-30; hypothetical)

• Average outperformance vs benchmark (S&P 500): + 0.20 % per month, + 0.60 % per quarter, + 2.42 % per year
• Average time in trade (holding duration): 30.5 days
• Average trade frequency: 0.91 per week, 3.95 per month

Predictive Gamma Strategy

Investment objective. Extract intraday short-dated premium on the S&P 500 by trading 0DTE straddles only on days the model identifies a high-conviction edge, and standing aside otherwise. The edge claimed is selectivity — when not to trade.

Instruments / venue. 0DTE (same-day expiry) S&P 500 (XSP) options, traded as an at-the-money straddle (call + put at approximately the at-the-money strike), long or short depending on the signal. Listed, cash-settled, European-style; settled at the close.

ML model description (methodological). A gradient-boosted decision-tree classifier trained on a rolling recent window of trading days. Each day the model is re-fit on the most recent window and predicts the probability that selling that day's at-the-money straddle would be profitable; the training label is whether a same-day short straddle would have been profitable historically. Inputs are engineered from the volatility complex and recent price/volatility behaviour and include, but are not limited to, short-dated-versus-standard implied-volatility relationships (for example, a short-horizon VIX measure relative to the standard VIX), VVIX momentum, and realised-versus-implied move spreads. Because it is retrained continuously on rolling data, the model adapts to the recent regime rather than relying on a single static training.

Signal interpretation guide. The model produces one probability per day, mapped to three postures:

• Short straddle — probability of a profitable short above an upper threshold (model anticipates a "volatility crush"/quiet session).
• Long straddle — probability below a lower threshold (model anticipates a "volatility breakout"/large move).
• Flat (no trade) — in the dead-band between the thresholds; low-conviction days are skipped by design.

A signal expresses a probabilistic lean, not a certainty — high-conviction days can still lose, and a 0DTE straddle carries severe intraday risk (see Risk Disclosure, §4.4).

Position sizing. Fixed and NAV-proportional. No other targeting.

Rebalancing triggers. Daily / intraday: a posture is taken (or skipped) each session; positions are 0DTE and expire/settle the same session; the next day's posture is re-evaluated from scratch. There are no multi-day rolls.

Why the benchmark differs. Strategies 1–3 are overlays on a core S&P 500 position, so the meaningful question is whether they improve on owning the index — hence the S&P 500 benchmark. Strategy 4 is a standalone, broadly market-neutral intraday premium program with no core index exposure; benchmarking it against the S&P 500 would compare unlike things. The relevant comparison is the naive alternative that shares its mechanics — selling a 0DTE straddle every session — which isolates the only thing the model claims to add: selecting when to trade and when to stay flat. Outperforming that benchmark does not imply low absolute risk, since the benchmark is itself a high-risk approach.

Greeks / execution. Greeks monitored, not targeted. Execution per Common Framework, with the added caution that same-day settlement and extreme 0DTE gamma make entry timing and fill quality especially consequential.

Backtest methodology

(Sample period: 2024-02-08 – 2026-06-30; hypothetical)

• Average outperformance vs benchmark (0DTE straddle sold every session): + 0.26 % per month, + 0.83 % per quarter, + 2.79 % per year
• Average time in trade (holding duration): 1 day

Systematic Surface Capture

Investment objective. Generate low-correlation income by harvesting structural richness across the S&P 500 volatility surface — both upside skew (overpriced "crash-up" calls) and the term structure (short-dated decay) — as an overlay.

Instruments / venue. S&P 500 (XSP) options (listed, cash-settled, European-style; not OTC), in two blocks.

Structure. (a) Short call strip: deep-OTM short calls capturing upside skew. (b) Put ratio (described in the engine as a "calendar"): a net-short put ratio — more nearer-dated puts sold than longer-dated puts bought — combining front-tenor decay with a longer-dated leg. This block is net-short puts, not a fully hedged calendar, and carries directional downside risk accordingly.

Expiry selection. Short calls short-dated; the put ratio pairs a nearer-dated front leg with a longer-dated back leg; positions exited as expiry approaches.

Strike selection. Short calls deep OTM; put ratio short legs nearer-the-money, long leg further OTM.

Position sizing. VaR engine, with a single stress-loss budget shared across both blocks (risk-parity); each block is then sized independently against that shared budget.

Rebalancing triggers. Calendar: on a periodic, rules-based schedule, with entry gated by the trend filter (new positions only while the S&P 500 is above its long-horizon moving average). Event-based: early exit as expiry approaches; a trend-filter breach trims the put exposure.

Greeks / execution. Per Common Framework.

Backtest methodology

(Sample period: 2023-03-08 – 2026-06-30; hypothetical)

• Average outperformance vs benchmark (S&P 500): + 0.13 % per month, + 0.39 % per quarter, + 1.26 % per year
• Average time in trade (holding duration): 44.7 days
• Average trade frequency: 2.11 per week, 9.2 per month

Risk disclosure statement

1. Purpose and scope

This Risk Disclosure Statement accompanies the Rivativ product information for each strategy and forms part of the materials provided to professional clients and to firms that license Rivativ research for onward distribution ("you", "the recipient"). It describes the principal risks associated with the Rivativ options strategies in general (Section 3) and the additional risks specific to each individual strategy (Section 4).

It is not exhaustive. It does not describe every risk that may arise, and the risks described may combine or interact in ways that amplify losses.

2. Nature of the relationship

Rivativ provides research, strategy frameworks, and model portfolios only. Rivativ does not manage client capital, does not execute trades, does not hold client assets, and does not provide personalised investment advice. All trading decisions and all execution are made by the recipient or its clients, on their own account and at their own risk.

Model portfolios are illustrative expressions of Rivativ's views. They are not personalised to any recipient's or end-investor's financial situation, objectives, portfolio size, tax position, or risk tolerance, and they are not instructions or recommendations to trade.

Recipient responsibility. Rivativ is established in Germany; the strategies primarily reference US-listed instruments (S&P 500 index options, VIX options). It is the recipient's sole responsibility to determine, under the laws and regulations applicable to it and to any end-investor it serves, (a) whether these strategies and instruments are appropriate and suitable, (b) whether the recipient is permitted to use or distribute them, and (c) to which categories of client they may lawfully be offered. The recipient is responsible for its own client classification, suitability/appropriateness assessments, and regulatory disclosures.

3. General risks applicable to all strategies

Options are complex, high-risk instruments. They are not suitable for all investors. Trading options can result in the total loss of invested capital. For uncovered or short option positions, losses can substantially exceed the amount initially invested or the premium received.

• Market and directional risk. Adverse movements in the S&P 500 or related instruments can cause significant losses, including rapidly and within a single session.
• Volatility risk. Changes in implied volatility can produce losses.
• Leverage and margin risk. Options provide leverage. Positions may require margin; adverse moves can trigger margin calls and the forced liquidation of positions at unfavourable prices, potentially crystallising losses greater than the capital allocated.
• Tail and gap risk. Markets can gap sharply between sessions or move violently intraday on news or macro events. Risk-limiting features (hedges, defined-risk structures, trend filters, position limits) may fail to engage in time, may not perform as modelled, and do not eliminate the risk of severe loss in extreme conditions ("black swan" events).
• Liquidity risk. In stressed markets, bid-ask spreads widen, certain strikes or tenors become illiquid, and it may be impossible to enter, adjust, or exit positions at or near modelled prices.
• Assignment and early-exercise risk. Short option positions may be assigned, including early, requiring delivery or cash settlement at inopportune times.
• Execution and slippage risk. Because you execute independently, your fills, timing, and costs will differ from those assumed in the model. Slippage, latency, and partial fills can materially reduce or eliminate the modelled edge.
• Tracking / divergence risk. Your realised results will differ — potentially significantly — from the published model portfolio, due to differences in execution timing, position sizing, available capital, costs, and market conditions at the moment you act.
• Model and methodology risk. The strategies rely on quantitative assumptions (for example, the persistence of the volatility risk premium, term-structure behaviour, and correlation relationships) that may weaken, disappear, or reverse. Edges identified historically may not persist; market regimes change.
• Risk-model limitations. Value-at-Risk and similar measures are statistical estimates based on historical data and assumptions. They can be exceeded, particularly during discontinuous moves; "hard limits" do not guarantee that losses stay within budget.
• Currency risk. Recipients and end-investors operating in EUR, GBP, or other currencies bear exchange-rate risk on USD-denominated instruments.
• Concentration and correlation risk. The strategies are concentrated in S&P 500 / US volatility exposures. Assumed diversification or hedging relationships can break down precisely when protection is most needed.
• Interest-rate risk. Changes in interest rates affect option pricing and financing costs.
• Counterparty and clearing risk. Exposure exists to brokers, clearing houses, and other counterparties involved in execution and settlement.
• Hypothetical and past performance. Any backtested, simulated, or historical figures are illustrative only and subject to inherent limitations (including hindsight and the absence of real execution). Past performance is not a reliable indicator of future results.
• Conflicts of interest. Rivativ, its management, and its shareholders may hold or trade positions in the same or similar strategies and instruments referenced in the research, and their interests may differ from or conflict with yours.
• No guarantee; no liability. Rivativ gives no guarantee of any outcome or return. To the fullest extent permitted by applicable law, Rivativ accepts no liability for any loss or damage — direct, indirect, or consequential — arising from use of or reliance on its research or model portfolios.

Operational, business-continuity and service-availability risks:

Delivery of Rivativ research and model portfolios depends on Rivativ as a business and on a chain of technology and third-party providers. Any disruption to that chain can mean that signals or updated portfolios are delayed, incomplete, incorrect, or not delivered at all — leaving positions un-rebalanced, un-rolled, or unhedged at times when timely action would have mattered. Specific risks include:

• Discontinuation of the service. Rivativ may cease to provide research and model portfolios at any time, including permanently — for example if Rivativ ceases trading, becomes insolvent, is wound up, or otherwise no longer exists. In that event no further updates, signals, rolls, or adjustments will be issued, and any open positions held by you or your end-investors will be left without ongoing strategy support. You should not assume the service will remain available, and you should maintain your own plan for managing or unwinding positions if it stops.
• Service interruption / inability to deliver updates. Technical failures may prevent Rivativ from calculating or transmitting updated portfolios on schedule or at all. Signals may be missed, late, or only partially delivered.
• Software, code and model-engine defects. Rivativ's strategy engine and supporting code may contain bugs, logic errors, or implementation faults. These may cause incorrect, inconsistent, or missing signals and portfolio outputs, and such defects may not be detected immediately.
• Data-provider dependency and outages. The strategies rely on third-party market-data providers. Outages, delays, gaps, or errors in that data can prevent Rivativ from calculating the strategies, or can cause calculations to be based on faulty inputs, producing erroneous or absent signals.
• Cloud infrastructure dependency. Rivativ's systems run on third-party cloud infrastructure (including Amazon Web Services). Any outage, degradation, or failure affecting that infrastructure or its own upstream providers can prevent Rivativ from generating or delivering updated portfolios, regardless of fault on Rivativ's part.
• Broader third-party dependency. Rivativ relies on additional external services (connectivity, hosting, communications, and other vendors). A failure or discontinuation by any of these providers can interrupt or degrade the service.
• Cybersecurity risk. Systems and communications may be subject to cyberattack, unauthorised access, data corruption, or interception, which could disrupt delivery or compromise the integrity of signals.
• Delivery and communication failure. Even when a signal is generated correctly, the channel used to deliver it may fail, and you may not receive it in time to act.
• No guarantee of availability, timeliness, or continuity. Rivativ does not warrant uninterrupted, error-free, or continuous availability of its research or model portfolios. You are responsible for having your own contingency arrangements for monitoring and managing positions during any interruption or discontinuation, and Rivativ accepts no liability for losses arising from any delay, error, interruption, or cessation of the service, to the fullest extent permitted by applicable law.

4. Strategy-specific risks

These risks are in addition to the general risks in Section 3.

4.1 Defensive Premium Harvest

This strategy writes S&P 500 index puts, holds long VIX calls as a hedge, and applies a trend filter, run as an overlay on a core index holding.

• Short-put downside exposure. Writing index puts creates substantial exposure to falling markets. In a sharp or sustained sell-off, losses on the short puts can be large and accumulate quickly.
• Hedge basis risk. The long VIX-call hedge is an imperfect offset to short-put losses. VIX and the S&P 500 are correlated but not perfectly; in a slow grind lower the hedge may contribute little while the short puts lose value, so the realised offset can fall short of the modelled net-risk profile.
• Hedge carry drag. The long VIX calls bleed value (theta/carry) in calm markets, a persistent cost that reduces returns when no shock occurs.
• Trend-filter whipsaw. The trend discipline may flatten the book near a low and re-enter higher, locking in losses or missing a rebound, and it cannot protect against gaps that occur before it triggers.
• Overlay leverage. Because the strategy sits on top of a core index position, total exposure can exceed the nominal capital; a severe decline affects both the core holding and the short puts simultaneously.

4.2 Diagonal Volatility Carry

This strategy expresses short-volatility carry through a VIX call ratio structure (net-short — i.e. more VIX calls sold than bought, with long further-out-of-the-money VIX calls held as partial cover).

• Short-volatility / vol-spike risk. The position is net-short volatility. A sharp rise in volatility causes losses, and those losses accelerate and continue to grow the further and faster VIX rises — there is no level at which the loss stops increasing.
• Unbounded loss potential. Because the structure is net-short VIX calls (more calls sold than bought), the position has no upper cap on losses. As volatility rises beyond the short strikes the uncovered short calls lose value without limit, so a sharp or extreme volatility spike can cause losses far exceeding the carry collected and the capital allocated — potentially many multiples of many months' accumulated premium.
• VIX-specific dynamics. VIX options are priced off VIX futures, not spot VIX. Movements in the futures term structure and in the volatility of volatility (VVIX) can produce losses even when spot VIX appears contained.
• Roll risk. Systematic rolling near expiry exposes the position to adverse term-structure shifts and additional execution cost.
• Negatively skewed return profile. The strategy tends to produce frequent small gains punctuated by occasional larger losses, which can be demanding to hold through.

4.3 Systematic Surface Capture

This strategy writes short-dated out-of-the-money S&P 500 calls (monetising upside skew) and runs calendar spreads (short front-month, long back-month), with a trend filter and VaR-based sizing, as an overlay.

• Upside / "crash-up" risk. Writing OTM calls caps upside participation and exposes the position to losses in a sharp rally or melt-up (for example a squeeze or a gap higher). Losses on short calls in a strong advance can be substantial.
• Term-structure and vega risk on the calendars. The short-front / long-back structure is sensitive to shifts in the volatility term structure and in implied volatility; an unfavourable change (front-month IV spiking or back-month IV collapsing) can cause losses.
• Gamma risk. The short front-month leg carries high gamma near expiry, so small moves in the underlying can produce large, rapid P&L swings.
• Skew-regime change. The structural overpricing of upside skew that the strategy harvests may compress or reverse, eroding or eliminating the edge.
• Trend-filter whipsaw and overlay leverage / capped participation, as described above.

4.4 Predictive Gamma Strategy

This is a higher-frequency, standalone strategy that uses a proprietary machine-learning classifier to filter 0DTE S&P 500 straddle entries, issuing a daily Long, Short, or Flat signal.

• Model / machine-learning risk. The strategy depends entirely on a proprietary ML classifier. The model may be affected by overfitting, feature drift, and regime change; its performance can degrade, and "high-conviction" signals can be wrong.
• 0DTE gamma risk. Zero-days-to-expiry options carry extreme gamma. An adverse intraday move can cause rapid, large losses with little time to react, and short straddle positions have very large loss potential on a significant intraday move.
• Intraday short-volatility exposure. A single large intraday move (for example on unexpected news or a macro surprise) can produce a loss that exceeds the gains of many prior sessions.
• High execution sensitivity. Higher trading frequency increases transaction costs and slippage and makes results highly dependent on execution quality. Because you execute independently, your daily timing and fills will diverge meaningfully from the model.
• Benchmark is itself high-risk. The strategy is measured against selling a 0DTE straddle every session — itself a high-risk approach. Outperforming that benchmark does not imply low absolute risk.

5. Acknowledgement

By using Rivativ research or model portfolios, the recipient confirms that it has read and understood this Risk Disclosure Statement, that it is acting on its own account and responsibility, that it has made its own assessment of suitability, appropriateness, and regulatory permissibility, and that Rivativ provides no investment advice and accepts no liability for trading decisions or their outcomes.

Suitability framework

Status and purpose of this framework

Rivativ provides research and model portfolios on a non-advisory basis and does not assess suitability or appropriateness for any client or end-investor. This framework is provided only to assist the recipient firm in designing and operating its own assessment process. It is not legal advice, not a substitute for the recipient's own obligations, and not exhaustive.

The recipient is solely responsible for determining which assessment obligations apply to it under the law and regulation governing its activities and its clients, and for applying them. The criteria set out below are examples of the factors a recipient would typically consider; where any additional or different criteria apply under applicable law (including national transpositions of MiFID II and any local rules of the recipient's or the end-investor's jurisdiction), the recipient must apply those as well.

A note on the applicable test: Rivativ's offering is non-advised. Where the recipient or its client uses the research on a purely non-advised, execution-only basis, the relevant MiFID II test may be appropriateness (knowledge and experience only). Where the recipient provides investment advice or portfolio management to its own clients, the fuller suitability test applies. This framework is written around the fuller suitability test so that it also covers the lighter case; the recipient must apply whichever test the law requires for its specific service model.

Manufacturer's target market (MiFID II product governance)

For the purposes of MiFID II product-governance expectations (and the equivalent provisions of the German Wertpapierhandelsgesetz, "WpHG"), Rivativ identifies the following target market for its strategies. The recipient, acting as distributor, must form and document its own target-market assessment and may not rely on Rivativ's.

Positive target market — the strategies are intended for:

• Client type: professional clients and eligible counterparties (per se or elective) as defined under MiFID II / WpHG. The strategies are not manufactured for the general retail market.
• Knowledge and experience: investors with proven knowledge and practical experience of derivatives, in particular listed options on equity indices and volatility products, and of leveraged, short-option and short-volatility strategies.
• Financial situation and ability to bear losses: investors able to bear losses up to and, for the uncovered/net-short strategies, in excess of the capital allocated, without that loss materially impairing their overall financial position.
• Risk tolerance and objectives: investors with a high risk tolerance pursuing return-generation or volatility-premium objectives, who understand and accept negatively skewed and potentially open-ended loss profiles.
• Investment horizon: investors for whom an exposure that may require active management, margin maintenance, and tolerance of sharp drawdowns is consistent with their objectives.

Negative target market — the strategies are not intended for:

• Retail clients without substantial, demonstrable derivatives knowledge and experience;
• Investors seeking capital protection, guaranteed returns, or income with low risk;
• Investors unable or unwilling to bear a total loss of capital, or losses exceeding capital on the uncovered/net-short strategies;
• Investors with a low or medium risk tolerance, or a short loss-bearing horizon;
• Investors who cannot meet margin obligations or actively monitor and manage open positions.

The recipient remains responsible for defining the distribution strategy and for ensuring the product reaches only clients within an appropriate target market under the rules applicable to it.

Recipient (distributor) responsibility

If the recipient determines — at its own discretion and on its own legal responsibility — to make the strategies available to clients outside Rivativ's stated professional/ECP target market (for example to retail clients via a white-label arrangement), the recipient is solely responsible for establishing that this is lawful and appropriate, for applying the correct (and stricter) retail protections, suitability/appropriateness tests, disclosures, and product-governance steps, and for any consequences of doing so. Rivativ does not authorise, assess, or assume responsibility for such distribution.

Suitability assessment criteria

The recipient should assess at least the following in respect of each client, applying any further criteria required by applicable law.

Knowledge. Whether the client understands: how listed index and volatility options work; the meaning and consequences of writing (selling) options; leverage, margin, and assignment; the mechanics of the specific strategy (e.g. net-short ratio structures, calendar spreads, 0DTE exposure); and that risk-limiting features do not prevent severe or, in some cases, unlimited loss.

Experience. The client's prior dealing in derivatives — instrument types, volume, frequency, and the period over which the client has traded them — and whether that experience is relevant to short-option and short-volatility strategies specifically, not merely to options in general.

Financial situation and capacity for loss. The client's income, assets (liquid and total), and existing liabilities; the proportion of the client's portfolio that would be exposed; and the client's ability to absorb losses up to total capital, and beyond capital for uncovered/net-short positions, without material detriment. As a matter of prudent practice, exposure to a single strategy of this risk class would typically be limited to a small percentage of the client's overall investable assets; Rivativ does not set this figure, and the recipient must determine an appropriate limit.

Investment objectives. Whether the client's objectives, return expectations, and intended holding period are consistent with a high-risk, actively managed derivatives strategy that can experience sudden and severe drawdowns.

Risk tolerance. Whether the client's stated and demonstrated tolerance for risk genuinely matches the strategy's risk-reward profile — including frequent small gains punctuated by occasional large losses, and (for the net-short strategies) unbounded loss potential.

Client classification thresholds

Unlike the suitability factors above — for which EU/German law sets the criteria but no fixed numbers — client classification under MiFID II / §67 WpHG does use defined thresholds, which the recipient applies when categorising a client:

• Per se professional ("large undertaking"): an undertaking qualifies if it meets at least two of three size criteria — a balance sheet total of EUR 20 000 000, net turnover of EUR 40 000 000, or own funds of EUR 2 000 000.
• Elective professional (client treated as professional on request): at least two of three criteria must be met — the client has carried out transactions of significant size on the relevant market at an average frequency of 10 per quarter over the previous four quarters; the client's financial instrument portfolio, including cash deposits, exceeds EUR 500 000; or the client has worked in the financial sector for at least one year in a professional position requiring knowledge of the transactions or services envisaged.
• The recipient must also follow the prescribed procedure for an elective professional waiver: the client must request professional treatment in writing, the firm must give a clear written warning of the protections that may be lost, and the client must confirm in writing, in a separate document, that it understands the consequences.
• Even where a client meets these thresholds, such clients are not presumed to have market knowledge and experience comparable to per se professionals, and the firm must still satisfy itself that the client is capable of making its own investment decisions and understanding the risks involved.

Ongoing assessment and records

The recipient should reassess classification and suitability where circumstances change, should keep clients' categorisation current, and should maintain adequate written records of its assessments and of the target-market determination, as required under applicable law.

Predictive Gamma Strategy: June 2026 performance

The Predictive Gamma Strategy returned –1.70% in June, outperforming its benchmark — the daily short 0DTE straddle — by +1.18% as the ML classifier successfully identified and avoided the high-uncertainty sessions that made June particularly costly for undiscriminating short-volatility approaches. The result is a direct demonstration of the strategy's core edge: not the return earned on days it traded, but the losses avoided on the days it chose not to.

June was a loss-making month for the Predictive Gamma Strategy, returning –1.70%, but that figure requires context: the strategy's benchmark — selling a 0DTE S&P 500 straddle every session without discretion — lost –2.88% over the same period, leaving the strategy +1.18% ahead of the naïve alternative. That gap is precisely where the strategy's value proposition lives. The ML classifier, which ingests over 30 live features including VIX/VIX1D ratios, VVIX momentum, and realised-versus-implied move spreads, issues a daily Long, Short, or Flat signal — and June's environment generated exactly the kind of sessions where standing aside is the correct trade.

The hawkish FOMC meeting on 17 June was a textbook example: a policy surprise that drove an outsized intraday move in the S&P 500 would have delivered a sharp loss to any undiscriminating straddle seller that day, while the model's filters are specifically designed to identify elevated-uncertainty sessions and issue a Flat signal rather than commit capital. The VIX averaging 16.41 and finishing near 17–18 describes a month with pockets of genuine intraday dislocation rather than the steady, low-realised-volatility grind in which the strategy earns most cleanly. The –1.70% loss reflects the real cost of those dislocation days where the model did engage; the +1.18% of outperformance reflects how many of the worst sessions it successfully avoided.

Talking points

• The strategy's core discipline — knowing when not to trade — delivered its clearest benefit in June. A month punctuated by a major policy surprise from the Federal Reserve produced exactly the kind of sharp, unpredictable intraday moves that destroy returns for mechanical straddle sellers. By standing aside on the days its model flagged as high-uncertainty, the strategy avoided the worst of that damage and outperformed the benchmark of selling every day by over one percentage point.
• Clients should understand that the benchmark here is not the S&P 500 index — it is the far more demanding standard of selling a 0DTE straddle every single session. That brute-force approach lost –2.88% in June, a reminder of the tail risk embedded in undiscriminating short-volatility strategies. The strategy's –1.70% loss, while real, reflects selective engagement: capital was only committed on days where the model identified a statistically elevated edge, not indiscriminately across every session.
• A loss month that still outperforms benchmark by +1.18% is the intended behaviour of a disciplined, signal-driven strategy in a noisy environment. The goal is not to win every month — some months, like June, will produce losses when intraday volatility is elevated and unpredictable. The goal is to win meaningfully more than the alternative over time, and the June result is consistent with that objective: the model filtered out enough losing sessions to deliver a materially better outcome than the default approach.

Systematic Surface Capture: June 2026 performance

The Systematic Surface Capture strategy held up strongly in June, returning –0.28% against a –1.28% benchmark decline and delivering +1.00% of outperformance as premium collected across both the skew and term structure of the volatility surface cushioned the impact of a rate-repricing shock. The result reflects the strategy's dual-axis design at work: two independent sources of income, neither dependent on market direction, combining to deliver a materially smoother outcome than the index.

June proved a relatively constructive month for the Systematic Surface Capture strategy, with a loss of just –0.28% against a benchmark decline of –1.28%, delivering +1.00% of outperformance. The strategy harvests two distinct inefficiencies across the S&P 500 volatility surface — the structural overpricing of upside call protection and the accelerated decay of short-dated put premium — and June's environment proved broadly supportive of both. The VIX, averaging 16.41 and finishing near 17–18, sat in a range that kept implied volatility elevated enough to provide meaningful premium on the calls written, while the S&P 500's modest 1–2% decline meant the index drifted lower without the kind of sharp, sustained sell-off that would stress the net-short put ratio leg.

The hawkish FOMC surprise on 17 June did inject intraday volatility, and the trend discipline that trims exposure as the market weakens would have reduced the book's directional footprint around that event — containing the downside at the cost of some premium left on the table. The collapse in crude and gold was largely orthogonal to the strategy's mechanics, but softer commodity prices reinforced the absence of the inflationary breakout scenario that would drive the sharp equity rally the short-call leg is most exposed to. The outcome — outperforming the index by a full percentage point while remaining net-short — is a clean demonstration of the dual-axis VRP capture working across both skew and term structure simultaneously.

Talking points

• The strategy significantly cushioned investors against a difficult month for equities, losing just a fraction of what the S&P 500 index lost. By generating income from two independent sources — overpriced upside protection and the faster decay of short-dated put premium — the strategy did not rely on the market going up to deliver that outcome. The +1.00% of outperformance against the index came from the mathematical passage of time working in the strategy's favour, not from a directional call on markets.
• The month's sharp macro surprise — a hawkish Fed pivot on 17 June — was absorbed without meaningful damage, illustrating how the strategy's trend discipline works in practice. When equity markets came under pressure following the FOMC meeting, the book's exposure was automatically trimmed, reducing the net-short put position that would otherwise carry the most downside in a falling market. That dynamic adjustment is a core feature of the strategy, not a one-off decision.
• Clients should be aware that this strategy carries genuine downside risk in two specific scenarios: a sharp, sustained equity rally, and a violent volatility regime shift. The short upside call leg loses money if the S&P 500 surges strongly, and the net-short put ratio is not fully hedged against a severe drawdown. June avoided both of those conditions, which is a key reason the strategy outperformed — but understanding those tail scenarios is essential context for the strong month-on-month result.

Diagonal Volatility Carry: June 2026 Performance

The Diagonal Volatility Carry strategy posted a –0.85% return in June, outperforming the S&P 500 by +0.43% as the book's dynamic risk engine scaled down exposure in response to the month's hawkish policy surprise and resulting volatility uptick. The result demonstrates the strategy's risk discipline in action: when conditions turn hostile for short-volatility positions, the sizing mechanism limits damage rather than compounding it.

June delivered a genuinely challenging environment for the Diagonal Volatility Carry strategy, and a loss of –0.85% on the month reflects that honestly. The strategy is structurally net-short volatility via a VIX call ratio — collecting premium as implied volatility decays toward realised levels — and the hawkish FOMC meeting on 17 June was a textbook headwind for this posture. Warsh's first decision as Fed Chair, a hold accompanied by a dot plot tilting toward a December hike and a materially higher PCE forecast, injected genuine policy uncertainty and pushed the VIX from subdued mid-month levels to finish the month near 17–18. That directional move in the VIX compressed, though did not eliminate, the premium decay the structure depends on.

Critically, the book's risk engine performed its intended role: as the volatility environment turned more hostile, sizing was scaled down, containing the loss to a level that compared favourably against the S&P 500's own decline of –1.28%. The cross-asset backdrop — crude's near-20% collapse, gold's 11% drawdown, and EUR/USD compression — was largely orthogonal to the strategy's mechanics, but it reinforced the equity uncertainty that supported the VIX's elevated close. The +0.43% of outperformance against benchmark is a modest but meaningful read on the risk discipline: the strategy did what it should when conditions soured, limiting damage rather than compounding it.

Talking Points

• The strategy delivered its intended defensive behaviour in a difficult month. June's unexpected hawkish turn from the Federal Reserve pushed volatility higher and compressed the premium income the strategy collects — an environment squarely in the "unfavourable" column. Despite that, the strategy's dynamic risk engine reduced position sizes as conditions deteriorated, and the result was a loss materially smaller than the broader S&P 500 index.
• Outperforming the index by 0.43% during a policy shock is the clearest evidence that active risk management adds real value. A passive index holding bore the full brunt of rate-hike repricing and dollar strength in June; this strategy did not. The sizing discipline — which steps down exposure automatically when the volatility environment turns hostile — is precisely the mechanism that produced that gap.
• Clients should understand that the strategy carries an uncapped tail in extreme volatility events, and June was a reminder of why that risk must be sized carefully. The VIX move this month was meaningful but not extreme; in a sharper spike, the net-short structure would face greater pressure. The risk framework is designed to manage that exposure actively, not eliminate it — and June is a clean example of it working as described.

Market update: June 2026

The dominant cross-asset driver of June 2026 was the hawkish pivot delivered at the June 17 FOMC meeting — Kevin Warsh's first as Fed Chair — where a unanimous hold at 3.50–3.75% was accompanied by a dot plot showing nine of 18 officials projecting at least one rate hike before year-end and a PCE inflation forecast revised sharply higher to 3.6%, pushing fed-funds futures to price roughly a 77% probability of a December hike versus around 24% a month earlier.

That repricing intersected with a near-20% monthly collapse in Brent crude to around $73 per barrel — the worst quarter for oil since 2020 — as US-Iran peace talks and a partial reopening of the Strait of Hormuz unwound the conflict premium, creating a sharp cross-asset divergence.

Gold fell approximately 11% to close near $4,020, its weakest since November 2025, as the dollar rallied to a one-year high and the rate-cut narrative supporting bullion through the spring fully reversed. Equities split along geographic lines: the S&P 500 lost 1-2%, with rate-hike risk and dollar strength offsetting the energy tailwind, while the Euro Stoxx 50 rose approximately 3% to close near 6,300, as lower energy costs and softer eurozone inflation prints led markets to price out further ECB tightening.

The VIX averaged 16.41, finishing near 17–18; EUR/USD compressed roughly two figures from 1.16 to close near 1.143, a clean expression of the widening US rate premium.

Defensive Premium Harvest: June 2026

The Defensive Premium Harvest strategy navigated a challenging June with discipline, returning -1.21% against a weaker S&P 500 and delivering +0.83% of outperformance as systematic put premium harvesting more than compensated for index losses in a hawkish, rate-repricing environment. The result is a clean illustration of the strategy's core promise: a smoother ride than buy-and-hold when markets fall, with no reliance on market timing or directional bets.

The Defensive Premium Harvest strategy returned -1.21% in June, outperforming its S&P 500 benchmark by +0.83% in a month defined by sharp and conflicting cross-asset moves. The dominant macro event — the hawkish pivot from the June 17 FOMC under incoming Fed Chair Kevin Warsh, with the dot plot signalling a high probability of a December rate hike — weighed on U.S. equities and drove a meaningful repricing of rate expectations.

The benchmark lost c. 2% against this backdrop, while realised volatility remained relatively contained (VIX averaging ~16.4), which is precisely the environment this strategy is built to exploit. The Variance Risk Premium contracted during the month (closing at -2.6 points), a headwind for short-vol premium collection, yet the strategy's systematic short-put book continued to harvest theta decay across the medium-dated tenor while the VIX call hedge — sized against net risk — remained an efficient but modest cost in a month where volatility did not spike materially.

The outperformance is consistent with the strategy's core design thesis: in a moderate down-market with contained realised vol, the premium collected from systematically writing index puts more than compensates for index losses, delivering a smoother return path than buy-and-hold. No trend-filter intervention was triggered, indicating the index held above key levels throughout the period.

Talking points

• The strategy did what it was designed to do. In a month where the S&P 500 declined on hawkish Fed repricing, the Defensive Premium Harvest outperformed by +0.83% — capturing steady option premium in a contained-volatility environment while the index fell. This is the core value proposition in action: a smoother ride than buy-and-hold across moderate down-markets.
• Volatility was the friend, not the enemy. Despite a negative Variance Risk Premium reading in June (-2.6 points), the strategy remained disciplined — the short-put book continued to collect theta systematically, and the VIX call hedge held its ground without becoming a significant drag. This illustrates how the strategy's net-risk sizing keeps both legs working together, not against each other.
• Risk controls held firm. The trend filter did not trigger, meaning the strategy stayed fully invested and continued harvesting premium throughout the month — no whipsaw, no premature de-risking. The outperformance was earned through systematic execution, not tactical bets.