ET
Energy Transfer LP Common Units
stockNYSE

Correct. Anything that's considered "market sensitive" is posted after 4 pm ET. Source: I post to cms.gov

**BanBet Created** ▲ | **Record:** 0W - 1L | Ticker | Target | Entry | Move | Expires | |:---:|:---:|:---:|:---:|:---:| | **MSTR** | $160.00 (above) | $151.74 | +5.4% | Fri 4:04 PM ET |

**BanBet Created** ▲ | Ticker | Target | Entry | Move | Expires | |:---:|:---:|:---:|:---:|:---:| | **NVDA** | $240.00 (above) | $230.28 | +4.2% | Thu, Oct 22, 3:15 PM ET |

Hi, happy Thursday! It's great that you're thinking ahead to learn the withdrawal process. I see you chatting in the comments and would also like to confirm that you have separate sources within your 403(b) account: Roth, Traditional, and after-tax. When you're logged into Netbenefits.com, follow these steps to look at what you have invested in each source: 1. Select your account from the homepage 2. Scroll down to the "Current Portfolio" box and click the "Sources" tab 3. Select "Sources Details" From here you can see your percentages, securities, and totals for each source. When it comes time to withdraw, if you're looking to take from a specific source, our Workplace Investing team can assist. Call and say you want a source specific withdrawal, and choose your source. Whatever you pick, it will sell the underlying funds in each source proportionally. Our team hours are Mon. - Fri., 8:00 a.m. - midnight ET, although this can vary by plan. [Contact us](https://www.fidelity.com/customer-service/contact-us) Keep us updated if any other questions arise.

Right at 12:58p ET as they were changing shows.

I currently maintain positions in both EPD and WES. I also hold ET and MPLX.

**BanBet Created** ▼ | Ticker | Target | Entry | Move | Expires | |:---:|:---:|:---:|:---:|:---:| | **QQQ** | $700.00 (below) | $745.53 | -6.1% | Thu, Oct 29, 1:24 PM ET |

PAMP ET!!! DAMP ETTT!!! SNIP SNAP SNIP SNAP!! :kek:

I mean a 24bps swing on QQQ from 2pm ET to EOD was still something lol

Hey, thanks for getting back to us. If you haven't already, I'd definitely recommend clearing both your browser's cache & cookies, as this can often resolve similar issues. If you've tried the above step or continue to experience this issue in another browser, please contact our technical support team for further troubleshooting. You can reach them Monday-Friday from 8:30 a.m. to 9:00 p.m. ET. [Contact us](https://www.fidelity.com/customer-service/contact-us) We appreciate you for choosing Fidelity and engaging with us on the sub.

| Ticker | Target | Entry | Current | Move | Expires | |:---:|:---:|:---:|:---:|:---:|:---:| | **SPY** ▲ | $785.00 (above) | $779.22 | $775.00 | +0.7% | Fri 3:54 PM ET | | **Record** | 0W - 2L | 0% | - | - | - |

**BanBet Created** ▲ | **Record:** 0W - 2L | Ticker | Target | Entry | Move | Expires | |:---:|:---:|:---:|:---:|:---:| | **SPY** | $784.00 (above) | $775.29 | +1.1% | Sat 10:00 AM ET |

⏰ Friendly reminder that there's a **$22 billion 30-year bond auction today**. Results will be announced at 1:00 p.m. ET.

MOBX has an investor call at 4pm ET

**BanBet Created** ▲ | **Record:** 1W - 0L | Ticker | Target | Entry | Move | Expires | |:---:|:---:|:---:|:---:|:---:| | **GOOGL** | $355.00 (above) | $351.22 | +1.1% | Fri 9:05 AM ET |

At 5:00 AM ET, the National Hurricane Center reported that Hurricane Isaias had strengthened to 80 mph, with further intensification expected. Approximately 25.08% of U.S. Gulf of Mexico oil production and 16.37% of natural gas production were already shut in as of Wednesday. This represents approximately 512,000 barrels of daily oil production temporarily offline.

I agree. My theory is that the market makers were taking losses and forced ET to ban a pool of profitable traders (anyone involved in too much trading). Their main issue appears to be short-term trading, but they want define what is acceptable. It’s a guessing game that makes trading impossible on ET.

**BanBet Created** ▼ | **Record:** 5W - 8L | Ticker | Target | Entry | Move | Expires | |:---:|:---:|:---:|:---:|:---:| | **NVDA** | $223.02 (below) | $237.51 | -6.1% | Thu, Oct 15, 7:14 AM ET |

**BanBet Created** ▲ | **Record:** 0W - 1L | Ticker | Target | Entry | Move | Expires | |:---:|:---:|:---:|:---:|:---:| | **MU** | $1200.00 (above) | $1086.74 | +10.4% | Sat 3:21 AM ET |

📅 Oct. 30, 2026: Warrants expire at 5 PM ET... And other dates to know.

**📊 Key U.S. Economic Data (ET)** **8:30 AM** | Unemployment Claims | Forecast: 200K | Previous: 197K **4:30 AM** | Fed Speaker: FOMC Member Waller Speaks ⚠️ For informational purposes only. Not financial advice. 📌 #SPY #SPX #UnemploymentClaims #FOMC

Over the past few months I went fairly deep into testing an Opening Range Breakout + Relative Volume strategy based on the paper *A Profitable Day Trading Strategy for the U.S. Equity Market*. I originally expected this to end with a paper-trading/live system. Instead, it turned into an interesting case study in how a strategy can look very strong in a conventional backtest and then collapse once you model how the trades would actually have to be executed. I thought the results might be useful to others here, particularly anyone working on intraday strategies with tight stops. # The basic strategy The main 5-minute version was approximately: * US equities * opening price > $5 * previous 14-day average volume ≥ 1M shares * ATR14 > $0.50 * first opening range = 09:30–09:35 ET * RVOL = today's first-5-minute volume / average first-5-minute volume over the previous 14 sessions * RVOL ≥ 1 * rank Top 20 by RVOL * bullish first candle → only trade long * bearish first candle → only trade short * long stop-entry at OR high / short stop-entry at OR low * initial stop = 0.10 × ATR * no profit target; remaining positions close near EOD I rebuilt the historical universe and signal pipeline, then eventually added SIP trades/quotes and an execution simulator. Data/execution stack was mostly: * Alpaca SIP historical trades/quotes/bars * point-in-time-ish / survivorship-reduced US equity universe * ticker/entity continuity handling * \~310 ms empirical execution latency * NBBO-based marketable execution * IBKR-style commissions * displayed-liquidity constraints in the later tests * SSR handling * partial fills / exit-liquidity handling One limitation: this is not the paper's exact CRSP + IQFeed dataset, and the universe is not truly survivorship-free. # 1. First surprise: I could reproduce the theoretical edge The conventional/bar-style implementation looked good. Approximate D2 theoretical expectancy: **2016–2023: +0.15R/trade** Later 2024–2026 period: **\~+0.14R/trade** On the exact subset that later received executable fills, the theoretical result was about +0.155R and +0.165R respectively. So this wasn't a case where I simply coded the strategy and immediately got garbage. The idealized strategy really did appear to have an edge. **\[Chart 1 here: theoretical vs executable\]** # 2. Then I replaced theoretical fills with SIP/NBBO execution This was the point where everything changed. Instead of assuming: * breakout entry at exactly the OR level * stop exit at exactly the stop price I used historical SIP trades and NBBO quotes. At approximately **310 ms latency**: |Period|Theoretical D2|Executable| |:-|:-|:-| |2016–2023|\+0.155R|**−0.380R**| |2024–2026|\+0.165R|**−0.616R**| Even the **zero-latency executable bound was negative**: * 2016–2023: −0.184R * later period: −0.420R That was the first major warning that this wasn't something a faster VPS or different broker would magically solve. # Why? The 0.10 ATR stop is extremely tight relative to actual market microstructure. Median quoted spread near the stop execution was approximately: * historical: **0.44R** * later period: **0.58R** In other words, if my entire intended loss is 1R, one side of the bid/ask spread alone is already a meaningful fraction of the whole risk budget. And the strategy trades precisely when the market is moving quickly. Entry moves through the breakout level. Then, when the trade fails, the stop is triggered while price is moving against me. The theoretical backtest effectively assumes: >enter at the breakout level → lose exactly 1R if stopped. Reality was more like: >detect breakout → latency → cross spread → fill beyond breakout → anchor stop to actual fill → adverse move → trigger stop → latency → cross spread again. That completely changed the payoff distribution. # 3. I tried to rescue the execution problem I preregistered 18 execution variants before testing them. Variables included: * 0.10 / 0.20 / 0.30 ATR stops * spread filters * market vs collared marketable-limit entries **0/18 qualified.** There was one interesting pocket: * 0.10 ATR stop * tight spread filter * marketable-limit entry The short side looked substantially better than the long side. That led to one separate short-only hypothesis. # 4. The short-only version was the most promising result I found This version produced: **2016–2026: +0.244R/trade** with roughly: * 1,666 fills * 19% win rate * PF \~1.26 * 7/11 positive years DEV 2016–2020: **+0.303R** 2021–2023: **+0.120R** 2024–2026: **+0.308R** For a moment this looked like the thing that might survive. But there were serious implementation problems. The two hard failures were: **1. Sample size** Only 1,666 fills versus the preregistered 2,500 threshold. **2. Actual displayed liquidity** Median displayed coverage was only: * **46% at entry** * **25% at stop exit** 63.9% of entries wanted more shares than were displayed at the bid, and 79.6% of stop exits wanted more shares than were displayed at the offer. There was also no reliable historical HTB/borrow dataset, which matters a lot for a short strategy selecting volatile, high-RVOL stocks. The return distribution was very right-skewed: * top 10 trades ≈ 66% of total net R I don't consider concentration by itself a reason to reject a positively skewed strategy — tail strategies naturally depend on large winners. But combined with the limited sample, depth problem and borrow uncertainty, it wasn't enough evidence to deploy. # 5. Then I searched the ORB/RVOL design space systematically Instead of continuing to manually tweak things, I built a preregistered search with realistic execution from the start. It tested **20,009 configurations**. Controls included: * capacity-aware NBBO execution * \~310 ms latency * commissions * SSR * frozen search space * no manual “try this after seeing the result” * walk-forward testing * parameter-neighbourhood / plateau testing * Deflated Sharpe * PBO * White Reality Check * Hansen SPA * locked validation/holdout periods Only **one configuration** passed the initial DEV gates. It had approximately: * \+0.071R DEV * \+0.049R OOF * PF \~1.11 * \~1,645 trades But immediate neighbouring parameter settings fell toward zero or negative. It looked like a **parameter spike rather than a stable plateau**. Result: **0 robust candidates out of 20,009 configurations.** Among large-sample configurations, roughly **99.3% lost money OOF**. White Reality Check p-value was approximately 1.0 and Hansen SPA approximately 0.92. At that point I was no longer convinced there was a hidden ORB parameter combination waiting to be discovered. # 6. Was the tight stop the real problem? This became an important question. Maybe the entry was actually good, but the 0.10 ATR stop was destroying it. So I removed the stop entirely. Same canonical ORB/RVOL entry. No target. Enter and simply hold until an executable 15:58 ET exit. 18,169 trades, 2016–2020. Result: **Gross before costs: −3.49 bps/trade** **Net: −11.58 bps/trade** Session-clustered t: **−3.05** 95% bootstrap CI: **−18.8 to −3.8 bps** And: **0/5 years positive.** Longs and shorts were both negative. That changed my interpretation significantly. The tight stop absolutely makes execution worse. But the stop was **not the whole problem**. The canonical ORB/RVOL entry itself did not show robust positive entry→EOD directional alpha in my executable data. # 7. Final experiment: maybe five minutes is simply too early The original paper also tested a published **15-minute opening range**. So instead of inventing another parameter after seeing the failures, I tested that externally specified variant. 09:30–09:45 OR. RVOL recalculated using the first 15 minutes. Everything else kept fixed. This was interesting because waiting until 09:45 genuinely improved market microstructure. # 5-minute vs 15-minute Median spread/R: **0.40 → 0.27** Entry slippage: **0.45R → 0.31R** Entry fill vs OR level: **0.30R → 0.19R** Stop exit cost: **0.39R → 0.27R** Same-minute stops: **27.5% → 15.9%** Gap-through stops: **30.5% → 22.5%** So waiting until 09:45 did almost exactly what I hoped. **\[Chart 3 and Chart 4 here\]** But the actual returns were: |Layer|5-minute|15-minute| |:-|:-|:-| |Paper/bar model|\+0.135R|\+0.073R| |Optimistic executable|−0.415R|−0.327R| |Realistic executable|−0.645R|−0.515R| |Stress|−1.274R|−0.960R| **\[Chart 2 here\]** So the 15-minute version reduced execution damage materially. It just didn't reduce it enough. The signal only had \~+0.07R of theoretical expectancy available to pay for \~0.4–0.6R of executable friction. Stop-hit rate also remained about **87%**. # What I think actually happened My current decomposition is roughly: **Paper/bar backtest** Signal alpha − simplified/absent spread costs − simplified stop fills − simplified queue/depth = attractive result **Executable model** small underlying signal − entry spread − breakout slippage − fill anchoring − stop spread/slippage − fixed commissions − capacity constraints = negative expectancy And after the no-stop test, I would add another issue: >The canonical ORB direction signal itself seems much weaker than the headline backtest suggests. The strategy is extremely positively skewed: lots of losses and rare very large winners. That structure is real. But the average executable loser becomes too expensive relative to the small theoretical edge. # Things I learned the hard way **1. A stop can be tiny statistically but huge microstructurally.** 0.10 ATR sounds reasonable until the spread is 0.4–0.6 of the entire stop distance. **2. “Slippage = 1 tick” is not enough for strategies like this.** The timing of the signal, quote, spread, latency, actual fill and subsequent stop matters. **3. A profitable theoretical signal doesn't guarantee there is enough alpha to pay execution costs.** \+0.15R looked substantial until the real execution waterfall was measured. **4. Backtesting the stop can hide problems in the entry signal.** Removing the stop and holding to EOD was probably one of the most useful diagnostics I ran. **5. Parameter search can find something that looks profitable very easily.** 20,009 configurations produced one interesting spike. Neighbourhood robustness killed it. **6. Displayed liquidity matters even at surprisingly small account sizes.** A $25k account with 1% risk can still ask for thousands of shares when the stop is only 0.10 ATR. **7. A better execution environment cannot manufacture signal alpha.** The 15-minute test is the cleanest example: spreads and stop execution improved substantially, but expectancy remained negative. # Caveats I'm **not claiming the paper is “wrong.”** There are meaningful differences: * paper used CRSP + IQFeed * mine used Alpaca SIP * my universe is survivorship-reduced, not perfectly survivorship-free * there are unavoidable implementation ambiguities around same-bar sequencing * historical borrow availability isn't fully observable * my execution simulator is still a model, not actual historical broker fills Also, after repeated ORB research, I no longer consider the later 2024–2026 data pristine OOS for newly generated hypotheses. What I am comfortable saying is narrower: >Under my data, universe and increasingly realistic SIP/NBBO execution assumptions, I could reproduce the theoretical ORB/RVOL effect, but I could not find robust evidence that the edge was executable. At this point I've closed the ORB/RVOL research track rather than continue parameter mining. The infrastructure is staying — SIP data ingestion, point-in-time mapping, execution simulator, IBKR integration, research framework, etc. — but I'll use it on different signal families. I'd be interested in feedback from anyone who has independently tested this paper or another tight-stop intraday strategy using tick/NBBO data. In particular: * Did you see a similar theory → execution collapse? * How do you model stops when the spread itself is a large fraction of R? * Has anyone replicated this with IQFeed or another consolidated-feed dataset using executable quotes? * Do you see a flaw in the execution assumptions above? Happy to share more methodology/results if useful.

Since this arrives at 11pm ET, I never know if this is meant to be about the previous day or the coming trading day. Today was a good day to take profits on CCs and to place new CSPs. I hope tomorrow is the opposite!

IMO, when you use the term 'lying', that implies an intentional deception. Personally, I seriously doubt that was the case. At least, it is not something I have ever encountered. I assume you looked at the links I provided. A CSR may be responding based on how it used to be. Honestly, these appear to be decisions that their security AI is making. It is probably not an issue they address everyday. I can understand your feeling of betrayal. Honestly, I have had issues when their 3rd party BillPay service did not do as I expected. But, at least for us, I think overall, their offering are head and shoulders above the alternatives. This is how Google AI explains it: when did Fidelity's policy on holding initial investments begin? Fidelity Investments' notably stricter policy regarding extended holding periods for initial and uncollected deposits began in October 2024. While Fidelity has always had a standard processing hold of 1–3 business days for electronic fund transfers (EFTs) and checks, they abruptly extended these holding periods up to 16 to 21 business days for many customers in the fall of 2024. Why the policy shifted Fidelity enacted these aggressive, temporary fraud-reduction restrictions following a viral social media scam. A widespread mobile check-fraud scheme (frequently referred to online as the "#fidelityboyz" glitch) targeted Fidelity Cash Management accounts. Scammers were depositing fake or altered checks via the mobile app and immediately withdrawing the cash before the checks could clear. In response to this wave of fraud, Fidelity took immediate action by: • Slashing mobile check deposit limits for certain accounts from $100,000 down to $1,000. • Enforcing rigid, extended security holds (up to 16+ business days) to ensure funds completely clear from the originating bank before allowing withdrawals or transfers. Current Guidelines Fidelity has maintained stricter baseline holds since that security crackdown, with uncollected EFTs or check deposits frequently showing a holding period of up to 10 business days before they are fully cleared for withdrawal. Note: You can usually still use these pending funds to trade basic stocks or mutual funds immediately, but you cannot transfer or withdraw the cash until the hold period concludes. To entirely bypass these holds, Fidelity recommends "pushing" funds from your bank using direct deposit or initiating a bank wire, which are credited immediately upon receipt. If you are experiencing a hold on your account, I can help you look up the expected collection date or explain alternative transfer methods that clear instantly. Would that be helpful? Fidelity Investments About Fidelity - Fidelity Investments In 1974, Fidelity became the first company to sell retail mutual funds directly through a toll-free telephone line and to offer a check-writing capability from ... Fidelity Investments How hold times and processing periods affect the status of your transfer Definitions: Processing period is the time for Fidelity to receive requested funds (trade up to $25,000 on day of deposit if submitted before 4 p.m. ET on a bus... Reddit Spoke to Fidelity about the extended deposit and transfer hold periods Oct 21, 2024 — only Does that not seem like the bare minimum? At this point, the app and website are blatantly lying to customers by falsely saying, " EFT's take 1-3 days to s... WSJ Exclusive | Fidelity Slashes Mobile Deposit Limits Following Fraud Wave - WSJ Incident: Mobile check-fraud scheme targeting Fidelity Investments cash-management accounts via social media promotion (#fidelityboyz). Action: Fidelity reduced... Reddit What's up with the 10 day hold on transfers from outside institutions? Apr 6, 2025 — Comments Section You can learn more about sending a bank wire out of your Fidelity account on the page below: Bank wire transfers to and from Fidelity Also, as ... Reddit Don’t Understand Why It Takes Fidelity So Long To Clear Funds Jul 28, 2025 — Comments Section Hey, u/Comfortable-War7209. Thanks for reaching out to us and welcome to our sub. There is a holding period of up to 10 business days for check... Personal Finance Club Fidelity has started holding deposits for 16 business days! Nov 19, 2024 — Fidelity has started holding deposits for 16 business days! * Created November 19, 2024 * Last updated November 19, 2024

Thanks for reaching out to this community. I am happy to help. It sounds like you may be looking at a fund in your workplace plan, like a 401(k). You can see the transaction history, including dividends, on NetBenefits.com. Once you are logged in, follow these steps. 1. Click the 3 vertical dots next to the account 2. Select “Transaction History” 3. On the next page, tap on “Transaction History,” change the time period to what you want to see, and look for a transaction type that includes “Dividends” Our workplace teams would be happy to help you if you have further questions. You can call them using the number at the following link. If it is a 401(k), the team is generally available Monday – Friday, 8:30 a.m.—8:30 p.m. ET. You can say “401(k)” when prompted to be directed to the correct team. [Contact us](https://www.fidelity.com/customer-service/contact-us) You are always welcome on our sub, and I look forward to seeing you here again soon!