If the U.S. produces more oil than it exports, why do prices still rise here?

At first glance, it seems puzzling. The United States is now one of the largest oil producers in the world and in many periods produces more petroleum than it consumes. If that is the case, students naturally ask: shouldn't domestic prices be insulated from global shocks?

 

The short answer is no, because oil markets are fundamentally global.

 

Crude oil is a globally traded commodity. Even if the United States produces a large volume of oil, the price that producers receive—and refiners pay—is determined largely in the global benchmark markets, particularly Brent and West Texas Intermediate (WTI). If a supply disruption occurs in the Middle East, or if global demand increases in Asia or Europe, prices tend to adjust worldwide. American producers can export oil, and American refiners can import oil, so domestic prices remain tightly linked to international markets. In economic terms, oil is part of an integrated global market, not a closed domestic one.

 

Another factor students often overlook is the role of the U.S. Strategic Petroleum Reserve (SPR). The SPR is the world's largest emergency stockpile of crude oil, created after the 1970s oil embargo to help cushion supply disruptions. The reserve stores crude oil in large underground salt caverns along the Gulf Coast of Texas and Louisiana, where the geology allows enormous quantities of oil to be stored safely and relatively cheaply.

 

According to the Department of Energy, these caverns were created by dissolving salt formations deep underground and can hold hundreds of millions of barrels of crude oil. The entire system has an authorized capacity of about 714 million barrels and currently holds a little over 400 million barrels, meaning it is well below full capacity.

 

The SPR acts as a strategic buffer, not a daily supply source. Oil stored there cannot immediately offset large market movements because it can only be withdrawn at a limited rate and is intended primarily for major disruptions such as wars, natural disasters, or severe supply shocks. Even when releases occur, they mainly help stabilize markets temporarily rather than permanently change the underlying global supply-demand balance.

This also illustrates an important limitation of many risk models used in finance. Traditional Value-at-Risk (VaR) approaches often assume that price movements follow relatively stable statistical distributions. But commodity markets—especially oil—are heavily influenced by global geopolitical events, policy decisions, and sudden supply disruptions. When an unexpected event shifts expectations about global supply or demand, prices can move far more dramatically than a normal distribution would predict. In statistical terms, these markets exhibit fat tails, meaning extreme price changes occur more frequently than simple models assume. The global integration of oil markets, combined with the possibility of large supply shocks, is one reason risk managers often complement traditional VaR models with alternative approaches that better account for tail risk.

 

Markets that depend on geopolitics rarely behave like the tidy bell curves we put in our spreadsheets.

On the limits of VaR

WTI has risen 38.94% in one month. (2/6/2026 - 3/6/2026) 

To put that in perspective, I looked at monthly WTI returns from 1980–2026 and calculated: 6

• Average monthly return: 0.63% 

• Standard deviation: 10.04% 

• Z-score for a 38.94% move, 3.82 

Under a normal distribution, a move of 38.94% in one month is a 99.9932th percentile event. That sounds dramatic, and it is. In plain English, if monthly oil returns were perfectly normal, a move like this would be expected only about 1 time in 14,707 months — roughly 1,226 years. 

VaR gives us a disciplined framework for thinking about risk. But it also has limitations: 

 • It assumes returns behave “normally”. 

 • It underestimates the likelihood of extreme moves. 

 • It is built from the past, while markets enter new regimes (new normal) very quickly. 

 • It tells us a lot about what is likely in “regular” times, but nothing about what happens when the world stops behaving normally. 

 So the lesson is not that VaR is useless. The lesson is that models are tools, not truth. When a price move looks like an “1,226-year event,” the correct reaction is not blind confidence in the calculation. The correct reaction is to ask: Are markets really normal? Are extreme events more common than the model assumes? What risks live in the tails that our spreadsheet may not fully capture? 

That is where good financial modeling begins: not with worshiping the output, but with questioning the assumptions. 

I leave you with a dad joke. According to the model, this was a once-in-800-years event. According to markets, it just happened.

Reflection: 1968, 1998, and 2025?

Please allow me to share with you a few ideas that keep churning in my head. History rarely moves in straight lines. Instead, it follows cycles—periods of upheaval, transformation, and recalibration. To understand the world today and the potential changes ahead, we can look back at two pivotal years: 1968 and 1998. Each marked a turning point, and as we stand at another crossroads, we must ask: Are we on the verge of another seismic shift? If so, what will define the new era? 1968: A World Divided by Ideology In 1968, the world was in turmoil. The Cold War had split nations into two opposing ideological blocks—a capitalist, democratic West and a communist, state-controlled East. Protests erupted across the globe: in the U.S., the civil rights and anti-war movements questioned authority; in France, workers and students took to the streets; in Czechoslovakia, reformers sought liberalization, only to be crushed by Soviet tanks. The old order struggled to contain these demands for freedom, rights, and self-determination. Yet, despite this division, the global structure was stable. Each side knew its place, and the threat of nuclear war ensured that neither pushed too far. Governments, for better or worse, exercised strong control over economies and societies. There was certainty in the structure, even as revolutions simmered beneath the surface. 1998: The Triumph of Globalization By 1998, the world looked vastly different. The Soviet Union had collapsed (1991), and democracy and free markets seemed to have won. Trade flourished, technology accelerated, and economic interdependence linked nations in ways that made war seem impractical. China, still under communist rule, had embraced market reforms, integrating into the global economy. The European Union expanded, offering a new model of cooperation. In the United States, prosperity soared as the internet revolutionized commerce and communication. Globalization created unprecedented economic growth, lifting millions out of poverty, but it also introduced new challenges: wealth disparities widened, industries shifted overseas, and financial markets became fragile. The world was no longer divided into two ideological camps, but new tensions emerged. Who would benefit from this prosperity? Would the democratic order hold, or would inequalities and cultural divides create new fault lines? Today: A Return to Division? Now, in the 2020s, the world seems to be shifting again. The certainty of the post-1998 era is unraveling. Some key developments: Rising geopolitical tensions: The U.S. and China are locked in strategic competition, reminiscent of the Cold War. Nations are forming economic and political alliances based on security rather than open markets. Erosion of democratic consensus: While democracy expanded after 1998, it is now facing challenges from within. Polarization, distrust in institutions, and the rise of authoritarian-leaning governments suggest a rethinking of political structures. Economic realignments: The once-unquestioned power of free markets is being challenged. Countries are reshoring industries, questioning trade dependencies, and emphasizing national resilience over pure economic efficiency. Technology as a new battlefield: In 1968, nuclear weapons defined power. In 1998, trade did. Today, technology—AI, data, and cyber capabilities—determines influence. Are we returning to a world divided into two ideological camps? Not necessarily in the same way as 1968, but we do see the rise of competing political and economic models. On one side, a coalition of liberal democracies continues to promote openness, while on the other, authoritarian-leaning states emphasize control, stability, and state-led economic growth. Looking Ahead: Are We at Another Turning Point? Just as 1968 and 1998 were moments of transition, today’s world is shifting toward something new. The open question is: What will this new era look like? Will democracy and free markets adapt, or will rising inequalities, social unrest, and geopolitical tensions force a new structure upon us? For students, the lesson is clear: history does not move in one direction. Every period of stability is eventually disrupted by forces that demand change. The choices made today—about governance, economic policy, technology, and international relations—will define the next 30 years just as 1968 and 1998 shaped the decades that followed them. If the world is indeed shifting, the key question is: Will this transition bring greater prosperity and fairness, or deeper divisions and conflict? The answer, as always, depends on the decisions YOU make now.

How to calculate average rates earned on a lump sum?

 Imagine you invest $10,000 this year in a fund that promises the following returns over the next 5 years:

Your money would grow thusly.

It would be wrong to simple average the rates per year since this ignores any compounding. We use the function "RATE" from excel.

Wrong approach: (10 + 8 + 6 + 4 +2) / 5 =   6%

Correct approach: =RATE(5 , 0 , -10000 , 13358.44) = 5.962%

assigning a value based on price

 Dear students,  

I was asked for help with the grading tab, specifically on how to weigh each exam based on the performance. The example below should help. Is about allocating money according to price. 

Using vlookup in a range

 Imagine you are looking for the perfect sparkling wine. You have a database that looks like this.

The set has thousands of bottles to chose from. You want to begin the process by eliminating those deemed too cheap or too expensive. Your price ranges are as follow.

 
Your function should tell excel: Go look at the price that is stored in cell "G2", get it and find it in "Table array". Once you find it, bring the value stored in column 2 of "Table array". 

One problem is that vlookup can not understand "$15 - up". vlookup can look for only 1 value, so the first thing you want to do is to change those price ranges to a single price that vlookup could read.  Like the one below.

In red you see what does not work, in green what excel understands. It is key that the table array is sorted from low to high!

Excel will look place every price between $0 and $7 as "Cheap", anything between $7 and $15 as value... and so on. So in practice you create ranges in a vertical way.

The formula would look like this.

 

How to calculate the total interest paid over the life of a loan?

Assume you are going to buy a house that is for sale at $500,000. You have saved $100,000 for downpayment so the mortage will be for $400,000.

The bank quotes you two options. A 30 year, monthly payments loan at 6% or a 15 year loan at 5%.

Your friends tell you that if you go 15 years the total interest paid will be hundreds of thousands less.

You don't believe them so decide to do the math.

Easy way. Not surprisingly, there is an app for that. Excel has a formula.

CUMIPMT(rate, nper, pv, start_period, end_period, type)

For the 30 year loan it would be

CUMIPMT(6%/12 , 12*30 , $400,000, 1, 360, 0) 

Hard way. Do an amortization table and add all interest payments.

Curious about the answer?

Check the spreadsheet, you can make a copy and change it to your needs.

Total interest paid xls