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@Yowster laid out the full method in the forum, and the results since then are on the SteadyOptions performance page: nine closed bullish combos, seven winners, and nearly every winner closed at its roughly 10% target. The two losses were AMD at −2.1% and JPM at −14.5%. Figure 1. The nine bullish combos on the SteadyOptions performance page (highlighted), September 18 through October 15. Source: steadyoptions.com/performance. @yowster's write-up uses three EarningsStudy screens to build each trade. The last of them, the GEX page, is the one I want to look at closely here. It has an As Of slider that replays the page on any past date, so we can ask a simple question of every trade: what did the gamma map show on the evening before entry? And did that picture help, mislead, or not matter? Three screens, three questions The method in @yowster's post answers three questions in order, and each one lives on a different screen. Has this setup worked on this stock before? The Daily Screener answers it with an exit rule and a hit count. Set the rule to take profit at +15%, and each cell shows how many prior cycles hit that target from that entry day. The GOOGL example showed 7 of 7, and the same screen on October 19 still shows 7 of 7 on the long-call rows. Figure 2. The Daily Screener for GOOGL with the exit rule set to take profit at +15%, filtered to Call Debit Spread and LongOption. Each cell shows how many prior cycles reached +15% from that entry day. Captured October 19, 2026 (T-7 before the October 28 report). Is the move the trade needs a normal one? The Long Stock Trend chart shows the stock's path into the report for every prior cycle, with the median drawn in black and the macro calendar (CPI, PPI, FOMC) marked on the axis. If the combo needs a 4% rise, you can see at a glance whether that is routine for this name or a stretch. Figure 3. The Long Stock Trend chart for GOOGL. Each colored line is one prior cycle measured from T-8; the black line is the median path; macro events are flagged along the top. How is the trade built? @yowster construction, in brief: a call debit spread with the long strike at or slightly above the money, plus a narrower put debit spread with the long strike a little below the money, roughly two-thirds the width of the call side. All legs use the earnings-week expiration and the trade closes before the report. He keeps the total cost below the width of the put spread, targets about 10%, and expects most losses to stay under 10%. For his GOOGL example, the P&L chart showed that a rise of a little under 4% would reach the 10% target, which is exactly what the trend chart above lets you check. Figure 4. Yowster's GOOGL bullish combo as published in his forum post: +1 335 put / −1 325 put / +1 345 call / −1 360 call, October 30 expiration, $8.70 debit. Reproduced with Yowster's permission. What does the options market's positioning look like right now? That is the GEX page, and it is the subject of the rest of this article. What the GEX page measures Market makers who sell options hedge them with stock, and how they hedge depends on their gamma. Net GEX adds up that gamma exposure across the whole option chain, in dollars per 1% move in the stock. When net GEX is positive, the usual reading is that dealer hedging leans against the move: they buy dips and sell rips. Price tends to be stickier and pullbacks shallower. When net GEX is negative, hedging tends to push in the same direction as the move, so moves extend whichever way they start. The page labels the two regimes "Positive gamma" and "Negative gamma." It also marks the gamma flip, the price where the regime changes, and the call and put walls, the strikes carrying the most call-side and put-side gamma. We read the Net GEX label as a quick sentiment check. Since the combo's main risk is a drop, a backdrop where dips tend to get cushioned is the one you want. Three caveats matter, and the page states them. The data is end-of-day. Open interest reflects positions as of the prior close. And the sign of each contract's gamma is a model assumption about who is short what, because the data carries no trade direction. The page describes the terrain. It does not forecast. Nine trades, replayed For each combo I set the As Of slider to the last close before the entry date, which is what a trader would have had in hand the night before. Here is what the page showed. Figure 5. Each SteadyOptions bullish combo with the GEX page reading from the session before entry. Trade results from the SteadyOptions performance page. Six of the nine trades were entered in positive gamma. Five of those won, and the one loss was AMD's −2.1%. Three were entered in negative gamma. Two of those won, and the third was the biggest loss of the run, JPM's −14.5%. Averaged per trade, the positive-gamma entries returned +8.2% and the negative-gamma entries +1.5%. Two things stand out. Negative gamma is not the same as bearish. BA and UNH both entered with the stock below the flip, and both made 9–10% within a few days. BA had an RSI of 27.7, it sat right on its 185 put wall, and it bounced hard. Negative gamma amplifies moves in both directions, which is exactly why the outcomes there were so spread out. Two clean wins and one deep loss is what a wider distribution looks like. A positive headline can hide a weak floor. AMD was entered in positive gamma and still lost. That case deserves a closer look. AMD: the cushion was lower than the headline (Screenshots from EarningsStudy) Figure 6. AMD as of October 12. The headline reads positive gamma, but spot had slipped below the 600 put wall and the per-strike bars directly under it are red. The What Changed panel shows the regime four sessions later. On October 12, AMD's headline read +$147.5M, positive gamma, with spot 5% above the flip. But the per-strike profile on the right tells a more detailed story. The positive gamma sat above the stock, around the 620 call wall. The strikes below spot were negative, and spot at 593 had already slipped under the 600 put wall. The positive total came from above the price; underneath it, there was no cushion. The What Changed panel shows how that played out. By October 16, spot had fallen almost $65 and net GEX had swung by −$197M into negative territory. The combo was already closed by then, at −2.1%, because the put spread hedge did its job. As a lesson in reading the page, AMD says to look past the headline sign: check where the stock sits relative to the put wall, and whether the bars directly underneath it are green or red. JPM: below the flip and below the wall (Screenshots from EarningsStudy) Figure 7. JPM as of September 23. Negative gamma, spot sitting on the flip and below the 340 put wall, every per-strike bar beneath the stock red, MACD below its signal line for 27 sessions, and price 4.4% under its 50-day average. All three negative-gamma entries had the stock below the flip. JPM was the only one where it had also broken below its put wall. Net GEX was −$13.6M with spot on the flip line itself, the per-strike bars underneath were all red, and the MACD had been below its signal line for 27 sessions. BA and UNH, by contrast, were each sitting just above their put walls when they bounced. JPM was also held 13 days, the longest of the nine; none of the others ran past four. Steady Options contributor’s own notes flag that risk: losses grow when a trade stays open a long time and RV bleeds out. None of this means the page "called" JPM. Three trades can't establish a pattern, and BA and UNH won from the same regime. What JPM shows is what a weak floor looks like on this page: no positive gamma underneath the stock and no wall holding it. When you see that, it's reasonable for position size or entry timing to reflect it. MSFT: what a clean backdrop looks like (Screenshots from EarningsStudy) Figure 8. MSFT as of October 8: +$1.91B net GEX, spot 22.6% above the flip, holding just above the 520 put wall with mostly green bars underneath, MACD above signal for seven sessions. For contrast, MSFT on October 8 showed the textbook picture: a large positive net GEX, the flip far below at 426, spot sitting just above its put wall with mostly green bars stacked underneath, and momentum confirming. The combo hit its target in four days. How to use this, and what it can't tell you Nine trades is an anecdote. This is not a backtest. It is a replay with hindsight, and two of the three negative-gamma trades won. What the replay supports is narrower and more useful than a filter: the GEX page tells you what kind of ground you are standing on. In positive gamma, losses in this run stayed small. In negative gamma, the outcomes spread out in both directions. If you want to add it to the bullish-combo checklist, here is the order I'd use, following method: History first. On the Daily Screener, check the hit rate for your exit rule at your entry day. Reachability. On the Long Stock Trend chart, check whether the move your P&L chart needs is a normal one for this stock. Backdrop last. On the GEX page, read the regime, then the distance from spot to the flip, then where spot sits relative to the put wall and whether the bars just under it are green or red. Use the As Of slider and the What Changed panel to compare with a few sessions earlier. As AMD showed, a regime can change within days, and a weakening trend reads differently from one that has held steady for weeks. The point of putting these on one platform is that each answers a different question, and none of them is enough alone. A strong hit rate with negative gamma under the stock is a different trade from the same hit rate with a green cushion beneath it. The combo structure Yowster built already limits the damage when the stock drops. These screens help you see when that protection is likely to be tested. Credit where it's due: the bullish combo, its strike rules and its use of these screens are Yowster's work; his GOOGL P&L chart is reproduced with his permission. His original post is in the SteadyOptions forum under "Earnings Bullish Combo Trade Strategy." All trade results are from the SteadyOptions performance page. SO members on the All-services bundle: full core access to EarningsStudy is free through the partnership. Sign in at earningsstudy.com with your SteadyOptions email. EarningsStudy provides educational research and market information only, not investment, financial or trading advice. GEX values are model estimates from end-of-day data, and dealer positioning is inferred, not observed. Options trading involves substantial risk. Past results do not guarantee future results.

The foundation of these strategies is a concept called delta-neutral. This guide explains what delta-neutral means, walks through the core neutral structures traders use around earnings, and shows each one on a real setup using EarningsStudy — with the actual strikes and relative-volatility readings the platform generates. We'll use Micron (MU), Costco (COST), and JPMorgan (JPM) as running examples, all heading into confirmed earnings reports. First, what is delta? Delta measures how much an option's price changes when the underlying stock moves $1. A call has a positive delta between 0 and 1; a put has a negative delta between 0 and -1. Beyond that, delta has a second use that matters most here: it's your directional exposure. Positive total delta means you profit when the stock rises; negative total delta means you profit when it falls. A position is delta-neutral when its legs' deltas add up to approximately zero. At that instant, small moves in the underlying — either direction — have roughly no effect on the position's value. You've removed directional risk and positioned yourself on something else: volatility and time. Once direction is neutralized, your profit and loss is driven by the other Greeks — gamma (how fast delta changes), theta (time decay), and especially vega (sensitivity to implied volatility). That vega exposure is why delta-neutral strategies and earnings go hand in hand. Why go delta-neutral at all — and the one thing that splits these strategies Removing direction sounds like removing opportunity, so it's worth being clear on what you gain. Direction is the hardest thing to forecast — especially around a binary event like earnings, where the stock can gap either way on the same news. A delta-neutral position sidesteps that guess entirely and lets you bet on something more studiable: how far the stock moves, and what happens to implied volatility. You're no longer asking "up or down?" You're asking "big or small?" and "is volatility rich or cheap?" But "delta-neutral" does not mean "indifferent to volatility." This is the single most important idea in the whole article: every neutral structure starts with zero delta, yet they split cleanly into two camps by how they react to two things once the event hits — how far the stock moves (gamma) and which way implied volatility travels (vega). One camp wants a big move and rising IV; the other wants stillness and the IV crush. Getting this backwards is how traders put on exactly the wrong structure for their view. Long-gamma (long-volatility) structures — the straddle, strangle, and double diagonal — want a big move, and they want rising implied volatility. Two forces help them, not one. First, movement: as the stock runs, their delta grows in the direction of the move, so they make money faster the further it goes (that's the long gamma). Second, IV: because these positions are net long options, they're long vega — so if implied volatility on those long legs rises, the options gain value even before the stock moves. A violent earnings reaction into rising IV is their best friend. Their enemy is the opposite pair: a stock that sits still while IV falls, letting the crush and time decay bleed the premium they paid. Short-gamma (short-volatility) structures — the calendar and iron fly — want stillness, and they want falling implied volatility. Again, two forces working together. Because these positions are net short the near-term options, they're short vega on that leg — so when implied volatility collapses in the post-earnings crush, those sold options lose value and the position profits. And because they're short gamma, they also want the stock to stay near where it started so time decay works in their favor. A big move is their enemy: push far enough from the center and the calendar's short leg or the iron fly's short strikes turn against you, and the move can overwhelm the crush and the decay you were counting on. Table 1. The same delta-neutral starting point splits into two opposite bets. Each camp is driven by two forces working together — the direction of the stock's move and the direction implied volatility travels. Long-vol structures want a big move and rising IV; short-vol structures want stillness and the IV crush. So the real question a delta-neutral earnings trader asks is: do I expect this particular stock to move more, or less, than the options are pricing in — and does its history favor the move or the crush? That's not something to guess stock by stock. It's something to measure — which is where EarningsStudy's backtesting and screening come in. Why earnings is a volatility event, not a direction event Before a company reports, implied volatility (IV) swells as traders bid up options in anticipation of a big move. After the report, the uncertainty resolves and IV collapses — the IV crush. This is the central dynamic of earnings trading, and it's why neutralizing direction makes sense: the thing you can actually study and anticipate isn't which way the stock goes, but how its volatility behaves around the event. That's exactly what EarningsStudy is built to measure. Rather than guessing, you can look at how a specific stock's option structures have actually behaved across many past earnings cycles. Let's walk through the neutral strategies one at a time, each on a real setup. The Calendar Spread — Selling Near-Term Volatility A calendar spread sells a near-term option and buys a longer-dated option at the same strike. Around earnings, it leans on the front-month IV being pumped up more than the back month — the near leg you sold crushes harder than the far leg you own. Built at the money, it starts roughly delta-neutral, and — as Table 1 showed — it wants the stock to sit still. Here's a put calendar on Micron (MU) heading into its confirmed 2026-09-30 report, seven days out (T-7). The key panel is the Relative Volatility (RV) reading: the current RV of 1.40% sits against a median of 1.18%, a quick read on whether this calendar is pricier or cheaper than it usually is at this point in the cycle. The same view for Costco (COST), three days out, tells a different story — its RV of 0.78% sits right on its median, so this calendar is priced about where it typically is. The Beta Calendar Matrix — Every Entry/Exit Pair at a Glance This is where the newly released Beta Calendar Matrix earns its place. Instead of a single RV number, it shows the historical median return of the calendar for every combination of entry day and exit day around earnings, color-coded so the profitable regions are obvious. Read it like a heatmap: each cell answers "if I had entered on this day and exited on that day, what did this calendar historically return?" The right-side panel translates today's actual entry into concrete exit options. The Classic / Beta toggle switches between the original view and this new matrix. A crucial caveat, and it applies to every matrix and RV reading in this article: these are historical medians, not predictions. A green cell means the structure tended to work at that timing in the past; it is not a guarantee about the upcoming report. Backtests and calculations may be inaccurate and must be independently verified. The Straddle — the Pure Long-Volatility Bet A long straddle buys a call and a put at the same at-the-money strike. The positive call delta and negative put delta roughly cancel, so you're delta-neutral at entry — you don't care about direction, only that the stock moves enough in either direction to overcome the combined premium. It's long-gamma and long-vega: a big move is exactly what it wants, but it's fighting the post-earnings IV crush. Here's the MU straddle at T-7. Its RV of 10.26% sits below its median of 12.16% — a hint the straddle is relatively cheap versus its own history, which is what a straddle buyer wants. The Strangle — the Same Bet, Wider and Cheaper A strangle is the straddle's cheaper cousin: buy an out-of-the-money call and an out-of-the-money put. Lower cost, but the stock has to move further to pay off. EarningsStudy lets you step the wings out (Base / Wing 1 / Wing 2) to see how the tradeoff shifts. The Iron Fly — the Defined-Risk Short-Volatility Play Now we flip to the short-volatility side. An iron fly sells an at-the-money straddle and buys protective wings above and below, collecting a net credit. It's delta-neutral at entry, short-vega (so it benefits from the IV crush), and — critically — defined-risk, because the long wings cap the loss if the stock gaps. Like the calendar, it wants the stock to stay put. Here's the iron fly on JPMorgan (JPM), heading into its confirmed 2026-10-13 report. Note this is a net credit ($13.78) rather than a debit — you're paid to take the position, and you profit if the IV crush deflates the options faster than the stock moves against you. The Iron Fly Matrix shows every entry/exit timing pair, color-coded by historical median return. The Double Diagonal — Combining Calendar and Directional Structure A double diagonal combines diagonal call and put spreads, selling near-term options and buying longer-dated ones at different strikes. It's a neutral, income-oriented structure that benefits from front-month IV crush while the longer-dated longs retain value — and, unlike the calendar, it leans long-volatility, so a move toward its wings helps rather than hurts. Four legs across two expirations means execution and commissions matter more, which is exactly why seeing the historical payoff before committing is valuable. Finding the Right Symbol for the Right Strategy Here's the payoff of everything above. Once you understand that each stock has its own volatility personality — some make violent earnings moves, others barely twitch and simply crush — the natural question is: which stocks have historically rewarded which strategy? A name that routinely gaps hard on earnings is a candidate for the long-vol structures (straddle, strangle, double diagonal); a name that reliably sits still while its inflated premium collapses is a candidate for the short-vol structures (calendar, iron fly). Guessing that stock by stock is hopeless. Measuring it is exactly what EarningsStudy's backtesting and screening are for. Two capabilities do the work: Per-strategy backtesting. For any symbol, each strategy page reconstructs how that structure actually performed across the stock's past earnings cycles — the RV reading against its own median, and the Beta return matrix that scores every entry/exit timing pair. A symbol whose calendar matrix is a field of green has a history of the stillness-and-crush that calendars and iron flies want; a symbol whose straddle repeatedly paid has a history of the big moves that straddles and strangles want. You're reading the stock's tendency, not forecasting a single report. Screening across symbols. Rather than checking tickers one at a time, the screener surfaces the names entering their earnings window and flags where a given structure has historically lined up — filtered by the same VIX and confirmation conditions you'd trade under. That turns "which of tonight's reports suits an iron fly?" from a manual hunt into a sorted list. The workflow that ties the whole article together looks like this: Start from the concept: decide whether you're hunting a big-move (long-vol) or a stay-still (short-vol) setup — Table 1 is the map. Screen for candidates entering their earnings window that fit that profile. Backtest each candidate on the specific structure — read the RV vs. its median and the Beta matrix to confirm the stock's history actually favors it. Check the volatility environment: rich IV for this stock favors selling it (calendar, iron fly); cheap IV favors buying it (straddle, strangle). Size and manage with the reminder that all of it is historical tendency, never a guarantee about the next report. Put simply: the concept tells you what kind of setup you're looking for, and the backtesting and screener tell you which symbols have historically delivered it — so you're pairing each stock with the strategy its own earnings history supports, instead of forcing one strategy onto every name. The One Caveat That Governs All of It Delta-neutral is a snapshot, not a permanent state. Each structure is neutral only at the instant you put it on, at one stock price. The moment the stock moves, gamma pushes your delta away from zero and the position takes on direction — helping the long-vol structures and hurting the short-vol ones, exactly as Table 1 lays out. These are positions to understand and monitor, not set and forget. And every number in the tool is a measured history, not a forecast; the market can and does behave differently on any given report. The Bottom Line Delta-neutral strategies free you from the hardest problem in trading — predicting direction — and let you trade something more studiable: how a stock's volatility behaves around its earnings. Long-volatility structures (straddles, strangles, double diagonals) want a big move and cheap IV; short-volatility structures (iron flies, calendars) want stillness and the IV crush. The skill is matching the structure to the stock — and that's a question you answer by studying real history with backtesting and screening, not by guessing. This article is for educational purposes only and is not investment advice. EarningsStudy provides research tools and market information, not personalized recommendations; backtests and calculations may be inaccurate and must be independently verified. Options trading involves substantial risk, and multi-leg and short-volatility strategies in particular can produce large losses. Understand the maximum risk of any position before entering it. Example figures reflect a data snapshot and will not match live prices. A quick note on scope: this article uses US-listed options and standard US options terminology. The concepts apply anywhere options trade, but the examples and any tax references assume a US context.

What happened was the front leg's closing quote: it blew out to $4.70 wide — and dragged the computed mid far enough to nearly double the measured debit, and with it the relative volatility reading: 0.55% became 1.00%. Two trading days later, on Monday, August 10, the close showed the other way a late snapshot drifts. RV always measures whichever strike is at-the-money at the moment of the snapshot — that's by design. In the final minutes the stock moved about half a point, so the closing snapshot's ATM landed one strike higher (275 instead of 270), where the calendar is structurally smaller. Fine so far. But then the closing quotes — more than $4 wide on the front leg — squeezed that calendar's measured value to $0.10, when the pre-close market had priced the same 275 calendar at $0.40. Stack the two effects and the close printed an RV of 0.10% against the pre-close reading of 0.50%. A jumpier anchor, measured through sleepier quotes. None of these numbers was a bug — we reproduced all four from the raw quote records before publishing this. They are what the two snapshots honestly reported. The difference, in every case, was fourteen minutes. Notice what the two distortions have in common besides their timestamp: one direction each way. The close didn't lean bullish or bearish on volatility — once too high, once effectively zero. And the Monday case generalizes: across the symbols we have re-verified so far, on about 1 in 18 entry days (5.6%) the closing snapshot anchored to a different at-the-money strike than the pre-close market did. Once you understand why the final minutes can do that, you understand something important about every backtest, every screener, and every "is this expensive?" judgment you have ever made from end-of-day options data. Note: This feature of “4pm compare” retires from the app after a couple of months. What actually happens at 4:00pm Most of us grew up treating the closing price as the official price — the number the newspaper printed, the mark your broker settles to. For stocks, that is roughly fair: the closing auction concentrates enormous volume into a single, hard-to-manipulate print. Options are different. An option's "price" on an end-of-day file is usually the midpoint between the last bid and the last ask — and the final minutes of the session are precisely when that midpoint is least trustworthy. Market makers carry every open position overnight, through whatever news lands after the bell, so as the close approaches they protect themselves the only way they can: they widen. Quotes that sat a few cents apart at 2pm can be several times wider at 3:59. Attention shifts to the closing auction in the underlying shares. Some quotes go stale; a few cross or collapse to nonsense for a moment. The market is not wrong at 4:00pm — it is simply half-asleep, with one eye on the exit. Measure a relative-volatility ratio, a spread-cost figure, or a backtest fill from that half-asleep market and the noise flows straight into your numbers — twice over. The wide quotes wobble every mid. And because "at the money" is defined by where the underlying sits at the snapshot, a late drift can hand the measurement a different anchor strike — correct by definition, but jumpier in the noisiest minutes of the day. Most of the time the distortion is modest. Sometimes — as our ADBE chart shows — it is enormous. And you cannot tell which kind of day you are looking at from the number alone. This is not a novel observation; it is why professional options-data vendors have long sampled the market before the close rather than at it. The industry's quiet consensus is that a quote captured while market makers are still competing beats a quote captured while they are packing up. When the close lies most: look at the calendar Now look at when our two ADBE distortions happened, because the timing is not random. The August 6 spike was the Thursday close immediately before Friday morning's jobs report. The August 10 crater sat at the Monday close heading into CPI week. Both distortions landed at closes adjacent to major macro releases — which is precisely when you would expect the final minutes to be at their worst. A market maker going home flat-footed into a jobs number or a CPI print has every incentive to quote defensively into that bell; the overnight risk they are pricing is at its maximum. The quotes are widest, the mids wobbliest, exactly on the evenings when an earnings trader most needs a trustworthy reading — because those are also the evenings you are deciding whether tomorrow's setup is cheap. This is why the RV charts draw the macro calendar directly onto the time axis — the JOBS, CPI, PPI, FOMC and PCE flags you see running along the top of every chart. A strange-looking reading next to a macro flag has a candidate explanation you can see at a glance; a strange reading in the middle of a quiet week deserves more suspicion. The pre-close snapshot removes most of the distortion. The macro overlay tells you where to be careful about what remains. The two features were built separately, but they answer the same question from two sides: can I trust this number, tonight? Why this matters more for earnings traders than anyone else Earnings trades live and die on small edges measured over short windows. When we ask "is this straddle cheap against its own history?", we are comparing today's price to a median built from dozens of past snapshots. If a meaningful fraction of those snapshots were taken from a distorted market, the median itself is polluted — and a setup can look cheap or rich for no reason except closing-quote noise on a handful of historical days. It also matters at the moment of action. Members who use the Daily Screener know the workflow: the screener surfaces the day's candidates, you pick your structure, and then you have to actually get filled. Under 4:00pm data, there was always an honest gap between the reference price on the screen and the market you would meet the next morning — the printed mid sat inside a spread you knew had been artificially wide. In practice, many of us (myself included) compensated by scaling in: several limit orders at different prices, using the fills themselves to discover where the real market was. That works, but it is a workaround — you are burning patience and partial fills to rediscover information that a better measurement would have given you upfront. A snapshot taken fourteen minutes earlier, while the quote competition is still alive, closes much of that gap. The reference mid is nearer to a price someone would actually trade with you. Spread-cost readings reflect the market you can participate in rather than the market's closing yawn. And the historical medians your judgment leans on are built from cleaner raw material, cycle after cycle. To be precise about what this does not do: it does not make any strategy win more often, and it does not turn a mediocre setup into a good one. It makes the measurements honest. What you do with honest measurements is still up to you. What we changed, and how you can audit it Starting this cycle, EarningsStudy computes relative volatility from a 3:46pm pre-close snapshot instead of the 4:00pm close. The migration is deliberately gradual — current-cycle symbols with earnings in the next 30 days first, earlier years following after verification — because when you change the ruler, you re-measure everything carefully before you trust it. And rather than swapping numbers quietly, we built the audit into the product. On the Calendar and Straddle pages you will find a 4:00pm compare checkbox: solid lines show the new pre-close data, dashed lines show the legacy close-based data for the same symbol, strategy, and cycle. On most names, most days, the two hug each other — reassurance that the history you have been using was broadly sound. And then there are days like ADBE's August 6 and August 10, where the dashed line spikes to a peak, then falls off a cliff, that the pre-close market never showed. Every one of those divergences is a day the old ruler would have misled you — and every one is now inspectable, down to the raw quotes, because we keep both snapshots until the verification is done. One honest caveat while the migration runs: until the historical backfill completes, some today-versus-history comparisons mix a 3:46pm present with a 4:00pm past. The differences are usually small, but they are not zero — which is exactly why the compare view exists and the legacy snapshot is preserved until every cycle is re-verified. If you find a divergence that looks strange, the Ask button inside the app sends it straight to me with the page attached; several members' reports have already sharpened the verification. The part I care most about This upgrade exists because a member insisted on it. @Bhavan1986 made the case that the closing snapshot wasn't good enough — and he was right. When I brought it to the contributors, @Kim, @Yowster and @TrustyJules backed it without hesitation. The better data roughly doubles what we pay for market data, and we are absorbing that rather than passing it on: nothing changes about any member's current rate. That is what the SteadyOptions–EarningsStudy partnership is for — the tools this community trades with should keep getting more honest, not just bigger. It sits in a line with the spread-cost column, the confirmed-date badge, and the per-cycle detail behind every median: the platform's job is to show you numbers you could actually have acted on, not numbers that flatter a backtest. Measuring the market while it is still awake is one more step in that direction. SO members on the All-services bundle: full core access to EarningsStudy is free through the partnership — sign up at earningsstudy.com with your SteadyOptions email. The rest can subscribe at an incredible introductory price of $39.99. EarningsStudy provides educational research and market information only — not investment, financial, or trading advice. Options trading involves substantial risk. Backtests and calculations may contain errors and should be independently verified.