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Group 8
Group Project 1: Oil Market Paper
Jon Hurley, Khaled Gamaleldin, Ankit Abbi, Mohammed Jaradat, Nirali Desai​
The crude oil market is one of the most volatile and interconnected commodities in the
world. Its ties to the global supply chain create a strong interdependence between oil and nearly
all other industries. Given oil’s role in transportation, manufacturing, and energy, fluctuations in
oil prices can have a serious impact on the global economy. We analyzed the past performance of
crude oil prices to understand the key factors that influence oil's movement. This allows us to
gain insight into the driving factors - and estimate where the oil market may be headed in future
months. Over the course of this paper, we will be investigating the historical performance of
crude oil, analyzing the current market, and examining the various factors that impact oil pricing
to put together a forecast of where we believe the market will be from April until December of
this year.
When analyzing historical pricing trends, it is important to distinguish between nominal
and real prices. While nominal prices can show an exponential climb over time, they don’t
account for inflation and in turn exaggerate the rise in oil costs. By using the real oil price, which
uses the consumer price index to adjust for
inflation, we can better understand the real
oil prices over time and analyze large jumps
or decreases in price against real-world
events. Using the real price of oil removes
the distortion of inflation and provides a
clear view of the evolution of oil prices. The
line graph above shows the delta between
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the real oil prices and the WTI crude nominal price. This graph illustrates how inflation can skew
our view of prices over time.​
Instead of analyzing data dating back to 1970, we determined that focusing on the most
relevant events from the past twenty years will provide a crucial context for understanding oil
price trends today. The below graph of real oil pricing since 2000 details a few key events. From
2000 to mid/late 2007 there was exponential growth. The LGT group states this increase was
largely due to an increase in global demand as emerging economies such as China rapidly grew
(LGT, 2020). The supply could not
keep up with the increased demand
and subsequent pricing increased
from ~$20 to a peak of ~$60. The
2008 financial crisis drastically
reduced global demand, leading to a
rapid decrease in oil prices and
resetting them to early 2000s
levels.. Post-recession pricing showed continuous growth until 2014 when pricing again had a
significant drop. The Bureau of Labor Statistics stated that this large decrease came as a result of
an oversupply of oil relative to demand. Two main factors contributed to this oversupply: 1.
Increased production from the US and 2. OPEC decided to maintain production levels. China and
Europe also shifted towards more fuel-efficient technologies, further decreasing the demand for
oil (Bureau of Labor Statistics, 2015). These factors caused a fairly swift and dramatic decrease
in the equilibrium price of oil - as shown in the line graph from 2013 to 2014. This real price
remained fairly consistent until 2020 when the world economy was shocked with COVID. The
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pandemic caused travel restrictions and economic slowdowns leading to a dramatic decrease in
demand. At the same time, supply chain disruptions caused storage capacities to fill, leading to
WTI pricing to turn negative for the first time in history (US Energy Information Administration,
2021). Since COVID, oil prices have steadily recovered to levels seen between 2015 and 2019.
Despite this recovery, the market has continued to experience fluctuations driven by political and
economic factors.
Regression Analysis
We used historical data on U.S. field production of crude oil and West Texas Intermediate (WTI)
crude oil prices to do a regression analysis with the intention of predicting oil prices between
May and December 2025. The dependent variable in our model is the normal price of crude oil,
which is measured in dollars per barrel. This can be reflected in the market trends which are
influenced by multiple economic and geopolitical factors. There are several independent
variables that can have an impact on crude oil prices such as the global oil supply, the global oil
demand, the inflation rate, the US dollar index, geopolitical disruptions, as well as interest rates
but for the sake of this analysis, we will focus on domestic oil production as our independent
variable.
We took the average crude oil price and average production amount in thousands of barrels per
day on a weekly basis between April 2015 and April 2025 to conduct our analysis. Using a least
square regression analysis model with Y as the dependent variable (oil price), and X as the
independent variable (oil production in barrels), and as the intercept, b as the slope showing how
the independent variable affects the dependent variable), and e as the error term, the model is
expressed as Y = a + bX + e. Ŷ = â + b̂X is the least squares regression line. This approach is the
most effective model as it offers estimates for the unknown parameters (intercept and slope) that
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provide the best-fit line. We evaluate the correctness and dependability of the model using the
regression line as well as statistical techniques like t-statistics, confidence intervals, and the
R-squared value (coefficient of determination). The overall significance of the regression model
is further tested using the F-statistic, which makes sure that all of the independent variables
together account for the variance in the dependent variable. We can forecast the link between
important factors influencing oil prices using this regression methodology.
The summary output shows us that the regression model is statistically significant, meaning oil
production does impact oil prices in a meaningful way. However, R² of 0.30 indicates moderate
explanatory power which implies that production alone doesn't fully explain oil prices and about
70% of the variation can be attributed to other factors such as demand, global markets,
geopolitical issues, etc. We can interpret the impact of the independent variable of domestic
production as statistically significant with a very low p-value of 0.036. The model yields a slope
of 0.006518 meaning for every additional 1,000 barrels/day of domestic production, the oil price
is predicted to increase by about $0.00652 per barrel.
Overall, the statistical significance is strong and both the model and production coefficient are
significant. Our main takeaway from the regression analysis is that the effect is seemingly
positive: as domestic oil production increases, oil prices slightly increase. It is important to
consider that this may reflect lagging effects, demand signals, or market optimism instead of
direct causation. It is possible that higher past prices could have incentivized the production
increases we are seeing now, and the regression may be picking up this residual effect. It is also
possible that both oil price and domestic production quantity are responding to a more dominant
variable such as a surge in demand, but we did not have access to historical demand data.
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Supply and Demand Analysis and Forecast
The crude oil market is driven by the fundamental principles of supply and demand. Price
fluctuations occur when there is an imbalance between these forces due to geopolitical events,
production cuts or increases, changes in global economic growth, and shifts in energy
consumption patterns.
On the supply side, major oil
producers, including OPEC+, the
United States, and Russia, play a
critical role in determining global
production levels. Historically, oil
prices have been sensitive to
OPEC+ production decisions.
When OPEC decides to cut
production, the supply curve shifts to the left, leading to higher equilibrium prices. Conversely,
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when new production technologies, such as U.S. shale oil extraction, increase supply, the curve
shifts to the right, leading to lower prices. In 2025, we anticipate potential supply-side
disruptions due to geopolitical instability in key oil-producing regions and possible OPEC+
intervention to stabilize prices. A likely scenario includes production cuts to maintain favorable
price levels. As illustrated in the graph below, a leftward shift in the supply curve would result in
higher oil prices if demand remains unchanged.
In addition, due to the extreme cold weather that was experienced in January and February a lot
of natural gas was consumed and a decrease can be seen in the natural gas reservoir of 6% in
March compared to February. Global oil inventories are also predicted to fall due to the
decreasing crude oil production in Iran and Venezuela. These combined factors are predicted to
shift the supply curve to the left. Due to this decrease in supply, the price per barrel is predicted
to go up.
On the demand side, global economic growth, industrial activity, and transportation needs
influence oil consumption. The demand for oil tends to increase during periods of strong
economic growth, particularly in emerging markets such as China and India. Additionally, colder
winters or increased travel activity can drive short-term spikes in demand. Looking ahead to
2025, the world economy is expected to grow moderately, with energy demand rising. This
increased demand will shift the demand curve to the right, further pushing oil prices higher.
There is also a greater focus on domestic production of oil causing the demand curve to shift to
the right. However, structural shifts such as energy transition efforts, the rise of electric vehicles,
and government policies promoting renewable energy sources may slow the rate of demand
growth over time. Overall, with the decrease in supply and increase in demand, we predict that
oil prices will continue to rise throughout the year.
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US Energy Information Administration. (2021, 1 5). Crude oil prices briefly traded below $0 in
spring 2020 but have since been mostly flat. EIA. Retrieved 3 30, 2025, from
https://www.eia.gov/todayinenergy/detail.php?id=46336
LGT. (2020, 9 18). Long-term investment trends: the crude oil boom in the 2000s. LGT.
Retrieved 3 30, 2025, from
https://www.lgt.com/global-en/market-assessments/insights/financial-markets/long-term-investm
ent-trends-the-crude-oil-boom-in-the-2000s-20108
Bureau of Labor Statistics. (2015, 5 1). The 2014 plunge in import petroleum prices: What
happened? BLS. Retrieved 3 30, 2025, from
https://www.bls.gov/opub/btn/volume-4/pdf/the-2014-plunge-in-import-petroleum-prices-what-h
appened.pdf
“Crude Oil Prices: West Texas Intermediate (WTI) - Cushing, Oklahoma.” FRED, 2 Apr. 2025,
fred.stlouisfed.org/series/DCOILWTICO.
“U.S Energy Information Administration - Petroleum Data.” Weekly U.S. Field Production of
Crude Oil (Thousand Barrels per Day),
www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=WCRFPUS2&f=W.
U.S. Energy Information Administration - EIA - independent statistics and analysis. Short-Term
Energy Outlook - U.S. Energy Information Administration (EIA).
https://www.eia.gov/outlooks/steo/