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ENERGY


WTI Weekly: Overnight Flush To Key Statistical Support Finds Buying Interest.

06/11/20 03:34:58 PM
by Taylor Ireland

In this article, we examine the order flow and limit order book data in the WTI futures market that provides insight into the rotation between resistance and support in Monday, April 6, 2020's auction. Market structure and order flow provide insight into the actual transactional activity of a dual-auction's price discovery process. Analysis of this data provides real-time insight into the actions of market participants, providing a dynamic dataset to inform one's risk management process.

Security:   WTI
Position:   N/A

April 6, 2020

The structural framework provided in Sharedata's Daily Dashboard for Monday, April 6 was for price discovery higher. Our daily dual probability path assigned the primary expectation for price discovery higher, noting statistical resistance targets were: 30.73s/31.96s/33.19s, respectively. Qualitatively, these levels had held as resistance 69%, 77%, and 95% of recent market auctions (respectively) based on the market generated data. This data provided a buy-side framework with a probable resistance "zone" between 30.73s-31.96s. As discussed frequently, markets are probabilistic not deterministic. Within this framework, the secondary expectation was for price discovery lower with a probable support "zone" between 25.95s-24.72s. 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 06 Apr 2020.
Graphic provided by: Sharedata Futures, Inc..
 
Heading into Monday's auction, aggressive price discovery lower to 25.28s ensued in Sunday's Globex auction. Buying interest emerged amidst buy excess, halting the selloff near Monday's Average Daily Range Low Target. Rotation higher developed to 28.24s into the London open at/near prior key support. Sell excess formed there as balance then developed, 27.02s-27.90s, into the NY open. Selling interest emerged early in the NY auction before rotation lower developed to 25.91s back toward Monday's ADR Low Target into the NY close.

Figure 2. WTI Daily Dashboard 03 Apr 2020.
Graphic provided by: Sharedata Futures, Inc..
 
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 Auction 06 Apr 2020.
Graphic provided by: NinjaTrader.
 
In this week's analysis, although the primary expectation was for price discovery higher, the market initially saw an aggressive selloff through the key support level, 28s. After the relief rally to re-test this level, sell excess developed there. This was structural indication of potential lower prices. Price discovery lower developed toward the ADR Low target in the NY trade where buying interest emerged. Rotational trade predominated in the NY auction. Ultimately, the market traded lower to re-test the ADR Low target into the NY close.

Figure 4. WTI Limit Order Book 06 Apr 2020.
Graphic provided by: NinjaTrader.
 
The overnight failure of key support resulted in a selloff toward Monday's ADR Low target where market structure indicated (via the buy excess) the selloff had terminated. The daily framework identified statistical support targets and their qualitative potential to hold as support. The failure at key support, order flow, and limit order book data then indicated the primary expectation had been invalidated, thus favoring sell-side activity. 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.



Taylor Ireland

Sharedata Futures, Inc. provides historical data mining and visualization for the benchmark NYMEX Energy Futures Markets.

Sharedata combines structural analysis of the market generated data, dynamic systems analysis, and Bayesian causal inference techniques favored by the scientific and intelligence communities to provide a robust framework for addressing the uncertainty and risk in energy pricing.

Title: Founder
Company: Sharedata Futures, Inc.
Dallas, TX
Website: www.sdfanalytics.com
E-mail address: support@sdfanalytics.com

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