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By Erik Skyba, CMT
Senior Quantitative Analyst, TradeStation Labs
Every Wednesday at 10:30 a.m. Eastern time, energy traders analyze and react to the headlines of the U.S. Energy Information Administration (EIA) Petroleum Status Report. This report provides information on petroleum product inventories in the U.S., including those for products produced here and abroad. The popular notion is that changes in crude oil inventories help establish short-term crude oil prices. In this paper, we analyze this relationship to determine how these changes in crude oil inventory levels affect crude oil prices. What we discovered was not what we expected, but was nevertheless impressive.
Note: All times referenced in this paper are U.S. Eastern.
Traders at hedge funds and proprietary trading desks that focus on the energy sector pay very close attention to the EIA petroleum headlines the moment they hit the tape (Weekly Petroleum Status Report). These traders have orders queued to execute the moment they interpret the headlines. The headlines are typically highlighted and look like this in the News window of your TradeStation platform (Figure 1).
Figure 1 – Dow Jones News in TradeStation Platform – (EIA – Crude Oil Stock, Inventory Data)
Note: The Weekly Petroleum Status Highlights Report is a summary of important changes in the data.
The time of day when the weekly petroleum status report is released has varied over the years. In the 1980s, the data was released at 5 p.m. each Wednesday. In the 1990s, the EIA moved the time slot to 9 a.m., and in the spring of 2003, it moved the time to 10:30 a.m. In the 1990s, at the request of major news services, the EIA decided to have a set policy on publication release, which it follows to this day. That is, if there is a Monday, Tuesday or Wednesday holiday, it will publish the report one day late; if there is a holiday on a Thursday or Friday, the publication release is unaffected.
Before we began our study, we theorized that just like the price of any other good or service, crude oil prices are determined by supply and demand. That is, during periods of strong economic growth, one would expect demand to be robust. If inventories decrease, this will lead to increases in crude oil prices. If inventories increase during strong economic growth, prices may not be affected. During a period of sluggish economic activity, demand for crude oil may not be as strong. If inventories are increasing, this may push crude oil prices down. We analyzed crude oil prices using a five-minute Crude Oil Continuous Composite Contract, focusing on Wednesday's trading, from 10 a.m. to 11 a.m. (Figure 2). The ticker symbol for this contract in the TradeStation platform is @CL.C. This symbol includes both pit and electronic trading for the time period between 10 a.m. and 11 a.m., going back to May 2003. We examined crude oil prices going back to May 2003 for two reasons. First, we didn't know the exact dates and times when the EIA began releasing its data prior to May 2003, as mentioned earlier. The second reason is that Crude Oil Continuous Composite Contract had a robust database beginning in 2003.
Figure 2 – @CL.C – Five-Minute Interval, Crude Oil Continuous Contract Composite, 10 a.m. – 11 a.m.
In order to incorporate the crude oil inventory data in our testing, we downloaded the Weekly U.S. Ending Stocks excluding SPR data (http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=WCESTUS1&f=W) from the EIA website. This data could then be charted as "3rd Party" data in TradeStation. (For more information on charting 3rd Party Data in TradeStation and for a list of files available from TradeStation Labs, please email TSLabs@TradeStation.com and request information on our Statistics Library.)
There are many ways to test the cause-and-effect relationship between crude oil inventories and crude oil prices. When it comes to measuring these effects on short-term trading in crude oil prices, it makes sense to compare crude oil inventory levels to their prior-week values. This change can either be a positive or negative number. Barring where we are in the economic cycle, if the change is positive then an inventory rise should theoretically put pressure on crude oil prices, at least in the short term. A negative change should cause crude oil prices to rise. In this part of our study, we wanted to measure the effects on crude oil prices after the 10:30 a.m. release of the EIA inventory data. Our trade rules for this study said that if the EIA inventory data was greater than last week's number (difference is positive), then sell short one crude oil contract at the opening of the 10:30 a.m. bar and cover the position x number of bars later. If the EIA inventory data was less than last week's number, then buy one contract of crude oil at the opening of the 10:30 a.m. bar and sell the position x number of bars later. In Figure 3, we can see the performance results using these rules.
Noteworthy performance, highlighted by the yellow boxes, indicates that the best overall performance (long and short trades) came within five minutes (10:35 a.m.) of the release of the EIA inventory number. Crude oil prices reacted negatively to increases in inventory levels, with the best short performance occurring between 10:40 a.m. and 10:55 a.m. Decreases in inventory levels, however, did not have the reverse effect of increasing prices, as long trades had negative performance for all five-minute bars from 10:40 a.m. to 11 a.m.
Figure 3 – Performance Results – Comparing Oil Inventories to the Prior Week (results do not include commission and slippage costs)
When examining the relationship between a fundamental or economic news event and a particular asset class, we typically plot the cumulative returns of the security as it traded around the time of release of the news event. We do this to get a feel for how, on average, the security's price trades around the release of a news event. In this study, we analyzed one year of cumulative price changes of crude oil returns between 10 a.m. and 11 a.m., on the day that the EIA inventory data is released. In Figure 4, using the crude oil continuous contract (@CL.C), we see cumulative simple return averages, for that period of trading, on an annual basis from May 2003 to the present. This analysis is helpful in visualizing changes in the relationship of a security and a particular news event.
This pattern to which we draw your attention was not so obvious at first glance. But as Figure 4 shows, the turning points in crude oil are fairly apparent. With the exception of 2003, there is an obvious change in price movement between 10:30 a.m. and 10:40 a.m. Either the price of crude oil runs higher into the 10:30 – 10:40 a.m. period or it sells off into this period. This change in short-term price trend is right around the time of the EIA inventory data release. The changes in price trend are circled in Figure 4.
Figure 4 – Yearly Cumulative Simple Return Averages, 10 a.m. – 11 a.m., May 2003 – Present
Without concerning ourselves with the cause of this price behavior, we can test these observations by once again stating some simple rules about the price movement. If the cumulative percentage return from 10 a.m. to 10:30 a.m. is below zero, then buy on the open of the 10:30 a.m. bar and sell the position x number of bars later, until 11 a.m. at the latest. If the cumulative percentage return from 10 a.m. to 10:30 a.m. is above zero, then sell short on the open of the 10:30 a.m. bar and cover the position x number of bars later, until 11 a.m. at the latest. Figure 5 demonstrates the results.
Figure 5 – Performance Results – Rules: Cum Return < 0 Ten Buy and Cum Return > 0 Then Sell Short, May 2003 – Present (results do not include commission and slippage costs)
Notice that overall net profit ("Long & Short Trades Cum Return < & > 0" column) increases as the 11 a.m. bar approaches. The highest net profit of $34,410 was reached in the 11 a.m. hour. Seventy-three percent of that profit was derived from short trades, which amounted to $25,050 in net profit. Short trades performed better than long trades, though all long and short exits were profitable (10:35 – 11 a.m.).
Figure 6 is an example of what an equity curve looks like using these rules (long and short trades) along with the 11 a.m. bar exit. As we can see in Figure 6, the equity curve moved sideways until around 2007. From that point to the present, the equity curve has been moving higher. It is important to note that the equity curves for most of the exits had a fairly similar shape.
Figure 6 – Strategy Performance Report, Equity Curve Detailed – Long and Short Trades Using the 11 a.m. Exit, One Contract Traded, May 2003 – Present (results do not include commission and slippage costs)
The first set of rules we studied in this paper compared the week-over-week change in crude oil inventories. Prior to our testing, we postulated that if inventories rose, we would see short-term weakness in the price of crude and vice versa if crude oil inventories were lower. Of course, this view did not take into consideration the economic cycle. The results for the most part were inconsequential, though traders might be interested in long and short trades in the first five minutes after the EIA releases its numbers, as well as all bar exits between 10:40 a.m. and 11 a.m. for short trades. Consistent profitability in both long and short trades for the first five minutes after the inventory data is released makes sense, especially as traders who trade off these numbers have a short-term bias because they are trading the news event.
The first five minutes of trading is the only exit period that showed profitability for both long and short trades. What is intriguing for long trades is that as soon as the EIA inventory news hit the tape, profitability decreased (Figure 3). With short trades, profitability held steady until about 10:50 a.m. When we review short trades from this part of the study, it is very difficult to say why they did better than long trades. If we refer back to Figure 4, you will notice years when crude oil reached a high around 10:30 a.m. and proceeded lower into 11 a.m., but this price behavior only occurred in 2007, 2008 and 2009. Further analysis would be required to determine where the bulk of profits for short trades came from.
In the second part of our study, we tested a trading pattern that we recognized in crude oil prices that occurred between 10 a.m. and 11 a.m. (Figure 4). These rules exhibited positive value for both long and short trades overall. Once again, short trades had better performance than longs and the percentage of trades profitable averaged about 50 percent. Although the EIA inventory data release was not incorporated in these rules, one wonders what effect the release of this data had on crude oil prices between 10 a.m. and 10:30 a.m. on Wednesdays, prior to the data being released. What we do know is that for every other hour we tested (9 – 10 a.m., noon – 1 p.m., etc.) using these exact rules, performance results revealed more random returns. So there is definitely something going on with respect to the relationship between crude oil and inventories. We could reason that crude oil traders speculate in concert before the number is released, in that they buy (sell short) leading up to the number and then sell (cover) on the news, the moment it hits the tape. But as we showed in the first part of the study, this relationship is tenuous for long trades, with the exception of the first five minutes after the inventory data was released. As we mentioned, short trades were profitable for all five-minute bars until 11 a.m.
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