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April 14, 2020: The structural framework provided in Sharedata's Daily Dashboard for Tuesday, April 14 was for price discovery lower. Our daily dual probability path assigned the primary expectation for price discovery higher, noting statistical support targets were: 19.87s/18.52s/17.18s, respectively. Qualitatively, these levels had held as resistance 68%, 86%, and 91% of recent market auctions (respectively) based on the market generated data. This data provided a sell-side framework with a probable support "zone" between 19.87s-18.52s. As discussed frequently, markets are probabilistic not deterministic. Within this framework, the secondary expectation was for price discovery higher with a probable resistance "zone" between 24.95s-26.30s. Within the daily sell-side context, it was observable in the option data that the WTI contract held large open interest at the $20 strike. Option strikes with large open interest often function as meaningful support/resistance levels, and price is often pulled to these prices. This type of daily framework, while useful, is more effective when using live order flow and structural analysis to confirm or negate the most probable daily inference. The failure of the market at key resistance early in Monday's auction was structural indication that the primary expectation was invalidated. |
Figure 1. WTI Daily Dashboard 14 Apr 2020. |
Graphic provided by: Sharedata Futures, Inc.. |
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Heading into Tuesday's auction, selling interest developed at key support, 22.30s, into the London auction. A sell-side breakdown developed to 21.13s. Sellers trapped as balance developed, 21.13s-21.92s early in NY trade. Buyers trapped at 21.92s, before the selloff continued to 19.95s near Tuesday's Average Daily Range Low Target. Sellers trapped there, halting the selloff as retracement higher to 20.80s developed into Tuesday's NY close. |
Figure 2. WTI Daily Dashboard 13 Apr 2020. |
Graphic provided by: Sharedata Futures, Inc.. |
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The practice of analyzing market structure developments is best accomplished with the use of order flow and limit order book (LOB) analysis. In short, plotting the buy and sell transactions of significance (in this case volume equal to or greater than 150 contracts) as well as the resting limit bids and offers (equal to or greater than 75 contracts) allows us to see both the actions and intent of larger participants (who significantly affect price). |
Figure 3. WTI Daily Auction 14 Apr 2020. |
Graphic provided by: NinjaTrader. |
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In this week's analysis, the primary expectation was for price discovery lower, and key support, 22.30s, failed in the Globex auction. Subsequently, price discovery lower continued through 21s as selling interest absorbed large bid liquidity in the LOB. The selloff continued through 20.50s as large bid liquidity was again absorbed, driving price lower to 19.95s near Tuesday's Average Daily Range Low Target (and the large Option Wall residing at the $20 strike). Sellers trapped there amidst large bid liquidity in the LOB, halting the selloff at major support into the NY close. |
Figure 4. WTI Limit Order Book 14 Apr 2020. |
Graphic provided by: NinjaTrader. |
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A sell-side breakdown through key support developed in the Globex auction as price discovery lower developed, forming a Gap Lower into the NY Open. The selloff continued toward the Average Daily Range Low target. The daily framework identified statistical support targets and their qualitative potential to hold as support. The failure at key resistance, order flow, and limit order book data then indicated the primary expectation had been validated, thus favoring sell-side activity while also qualifying the 20-support area as significant. This confluence of structural, statistical, and order flow data provided insight into the auction's outcome based not on lagging fundamental data or media hype but rather structural formation and transactional behavior of significant quantity that drives price discovery. |
Title: | Founder |
Company: | Sharedata Futures, Inc. |
Dallas, TX | |
Website: | www.sdfanalytics.com |
E-mail address: | support@sdfanalytics.com |
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