Why VannaForge exists
Cash-secured puts and covered calls are accessible because they fit ordinary Level 2 brokerage accounts, clear capital rules, and self-directed execution. The problem is not access. The problem is decision quality, especially once volatility, execution friction, and portfolio fit are taken seriously.
VannaForge starts from a stricter premise. Premium matters only if the contract still looks sensible after downside context, liquidity, and position sizing are taken seriously. The system is not meant to replace the brokerage relationship. It is meant to improve the decision before the order ticket.
Research roots
VannaForge is not built around one indicator or one model family. The research layer is rooted in published work on volatility, options pricing, execution, and portfolio construction, then translated into a workflow that is readable for serious retail traders.
In public terms, that means the shortlist can be informed by multi-DTE term structure, volatility risk premium, IV or rank context, realized volatility and HAR-RV style measures, regime features, skew and smile shape, risk-neutral tail or expected-shortfall style signals, execution confidence and slippage, portfolio-fit diagnostics, rank stability, rationale strings, and shadow-model metadata where available.
Volatility context
Multi-DTE term structure, VRP, and IV or rank context help frame whether premium is being offered for a sensible backdrop or a stressed one.
Realized risk
Realized volatility, HAR-RV style measures, and regime features help distinguish stable carry from unstable premium.
Shape and tails
Skew, smile, and risk-neutral tail or expected-shortfall style signals help keep rich-looking contracts from being treated too casually.
Execution realism
Execution confidence, slippage, and fill quality matter because paper edge and realized edge are not the same thing.
Portfolio fit
Candidate quality still has to survive cash usage, assignment budget, and concentration constraints at the account level.
Stability checks
Rank stability, rationale strings, and shadow-model metadata help test whether the shortlist is consistent enough to trust.
Where it improves research quality, the private stack can use Python libraries such as XGBoost, PyTorch, and CUDA-accelerated computation. Publicly, that shows up as better ranking, better simulation, and clearer rationale — not as exposed formulas or training recipes.
From yield hunt to underwriting
A typical wheel screener is built to locate premium. VannaForge is built to decide whether that premium deserves to be underwritten. That difference is small in wording and large in practice.
For a self-directed trader, that means a contract does not rise simply because it looks rich on annualized yield. The workflow first asks whether the distance is adequate, whether the backdrop is supportive, whether the contract is tradable in the real world, and whether the position belongs in the account at all.
Typical premium hunt
Start with the richest-looking contract and work backward from the yield table.
- High IV or eye-catching annualized premium
- Quick check of strike distance
- Trade idea promoted fast
VannaForge framework
Start with the underwriting question and let the yield earn its place.
- Is the premium rich enough for the distance?
- Is the backdrop helping or hurting?
- Can the contract actually be entered and managed?
- Does the position fit the trader's cash and assignment budget?
A staged workflow, not a raw list
VannaForge does not try to do the entire job in one pass. It screens wide, narrows hard, and spends deeper analysis only on the contracts that still look worth the attention. Good selection is mostly about disciplined refusal.
In plain English, the workflow starts with a broad universe of liquid names, removes weak or messy contracts quickly, then studies the survivors more carefully before producing a ranked lineup. The point is to do the hard filtering before the user reaches a broker ticket.
Broad screen
Review a liquid universe and remove obvious non-starters quickly.
Deep review
Spend more attention only on the shortlist where premium, context, and tradeability still line up.
Ranked lineup
Present a smaller set of candidates with metrics and a concise trader-facing note.
What the public site is designed to show
The public site is built to show the user, the problem, the workflow, the target audience, and why VannaForge matters to self-directed traders and partner channels. It explains the research lens at a level that is useful to readers while leaving the private implementation off the page.
Who it serves
Self-directed options traders using cash-secured puts and covered calls inside real brokerage accounts, plus publishers and partner teams evaluating a more serious retail workflow.
What problem it solves
Most retail tools surface raw premium tables but leave selection quality, execution realism, and portfolio fit to the user. VannaForge is meant to narrow that gap.
How the workflow works
The public note shows the broad screen, deeper review, and ranked lineup so readers understand the process without needing the internal recipe.
Where partnership fits
The product maps naturally to broker-review, educator, affiliate, and platform ecosystems where the broker keeps the account and VannaForge improves the pre-trade research layer.
What shapes the lineup
The daily lineup is not built around one number. It balances several categories at once so a contract is judged more like a real trade idea and less like a spreadsheet cell. The public view compresses that evidence map into four trader-facing pillars.
Premium quality still matters, but it is interpreted alongside market backdrop, tradeability, and position fit. Those pillars are simple enough to communicate publicly while still reflecting a broader evidence base behind the scenes.
Premium quality
Distance, time, and compensation need to make sense together, not just look attractive in isolation.
Market backdrop
Volatility and regime context matter because premium can be high for the wrong reason.
Tradeability
Spread, fill quality, and execution friction are treated as part of the trade, not as an afterthought.
Position fit
Even a strong candidate can be wrong if it does not fit the trader's cash, assignment, and concentration limits.
The private engine can use a deeper factor set and research stack. The public note keeps the factor families visible and the exact score private.
Why the process can improve with use
Most retail tools are generic by design. They show the same table to everyone and let each trader improvise the rest. VannaForge is meant to become more useful as the workflow gathers real experience: what was filled, what turned out to be optimistic, what was skipped, and which setups proved more stable in practice.
That does not require exposing the internal mechanics on the public site. It simply means the private research layer can learn from execution, rank stability, and workflow history instead of pretending that displayed premium and realized premium are the same thing. For retail traders, that is often the difference between a clever screen and a genuinely useful process.
Generic screener
- Same table for everyone
- Little memory of what proved tradable
- Execution friction left to the user
VannaForge research loop
- Selection logic informed by observed workflow
- More realistic view of tradeability over time
- Public output stays simple while the internal process learns privately
What the trader actually sees
The trader does not need to interact with the internal model stack. The useful public-facing output is much simpler: a smaller ranked lineup, DTE, effective basis, a relative daily rank, an absolute underwriting view, bucket tags, and concise notes on why a trade survived the selection process.
That matters for serious retail users because a better workflow is not about being shown more columns. It is about seeing a shortlist that already respects tradeability, capital fit, downside context, and execution realism before the final decision is made. For broker or publisher partners, that makes the workflow additive rather than competitive.
Screen
Start with a smaller pool of names and contracts that already clear basic quality gates.
Review
Look at premium, distance, execution quality, and the short note explaining the setup.
Decide
Use the lineup as a disciplined shortlist rather than a mechanical trading signal.
Manage
Carry the same emphasis on assignment, execution, and position fit after entry.
Bottom line
VannaForge is not trying to reinvent CSPs or covered calls. It is trying to make them more selective, more disciplined, and more explainable for retail traders who want something above a generic wheel screener.
The public framework is built around the user, the problem, the workflow, and the trader-facing shortlist. That positioning is naturally relevant to self-directed broker ecosystems, active-trader publishers, and affiliate channels that want better-informed options traders instead of generic traffic.
Interested in the pilot?
Request access to the current lineup or open a partner conversation.
The public note shows the framework. Pilot access is how you see the current workflow.