Commercial Awareness Update: 19th October 2026

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Three stories from the last week that connect in ways worth understanding properly.

Here's what we're covering:

These aren't three unrelated headlines.

They're three different consequences of the same problem: the cost of capital is rising, and investors are becoming much more selective about where their money goes.

Let's get into it.

Prepare for interviews, under pressure.

On Tuesday, Goldman Sachs reported its third-quarter earnings.

And the numbers tell a fascinating story about what's happening on Wall Street.

The bank generated $6.44 billion in equities trading revenue, an increase of 72% compared with the same quarter last year.

That's approximately $70 million in equities trading revenue every single day over the three-month period.

Its investment banking fees also increased 21% year-on-year to $3.22 billion.

And overall, Goldman reported $5.29 billion in quarterly profit, comfortably beating analysts' expectations.

At first glance, everything looks fantastic.

But here's where things get interesting.

Global M&A activity fell 41% compared with the previous quarter.

The total value of announced deals dropped to $993 billion, falling below $1 trillion for the first time since the second quarter of 2025.

So how can one of the world's largest investment banks report such strong results when global dealmaking is slowing dramatically?

Here's the mechanism, because understanding it will make you much better at discussing investment banks in interviews.

Investment banks don't make money from one activity.

They operate several businesses with fundamentally different revenue drivers.

Take M&A advisory.

A company wants to acquire a competitor for £10 billion.

It hires Goldman Sachs to advise on the acquisition.

Goldman's bankers analyse the target, help negotiate the transaction, structure the deal and advise on financing.

If the transaction completes, Goldman earns advisory fees.

But imagine interest rates suddenly increase.

The buyer's borrowing costs rise.

The acquisition becomes less attractive.

The buyer might delay the transaction, negotiate a lower valuation or abandon the acquisition entirely.

That means fewer completed deals and potentially fewer fees for investment banks.

Trading, however, works differently.

When financial markets become volatile, institutional investors often need to reposition their portfolios.

Imagine you're managing a £20 billion pension fund.

You become worried that rising interest rates will hurt technology stocks.

You decide to sell £2 billion of equities and increase your exposure to government bonds.

You need a bank to help execute those transactions.

Now imagine thousands of institutional investors doing similar things simultaneously.

That creates enormous trading activity.

Banks can generate revenue by facilitating those transactions, providing liquidity, earning bid-ask spreads and managing associated risks.

And that's part of what happened at Goldman.

Higher interest rates, geopolitical uncertainty and volatility in technology stocks encouraged clients to reposition their portfolios.

Equities trading revenue increased 72%.

But there's an important distinction.

More volatility doesn't automatically mean more trading profits.

Banks can also lose money when markets move unexpectedly, especially if they're holding positions that become difficult to hedge or sell.

Goldman's fixed-income, currencies and commodities revenue actually fell 1% year-on-year.

So even within Sales & Trading, different desks can experience completely different outcomes.

And this is where Morgan Stanley's results become interesting.

Morgan Stanley reported $5.8 billion in equities trading revenue, an increase of approximately 41% year-on-year.

Its fixed-income trading revenue, meanwhile, declined 7.3%.

Two of Wall Street's largest investment banks are showing the same broad pattern:

Equities trading is performing exceptionally well, while bond trading is struggling.

Morgan Stanley also revealed something fascinating about its Wealth Management division.

The business attracted a record $232 billion in net new assets during the quarter, with more than half associated with IPO-related flows.

Some of those flows were connected to the SpaceX IPO earlier this year.

Think about that.

A company goes public.

Early investors and employees suddenly hold publicly traded shares.

Those shares may be transferred into wealth management accounts.

And the bank can potentially build long-term advisory relationships with those newly wealthy clients.

One IPO can therefore create opportunities across Investment Banking, Sales & Trading and Wealth Management.

That's the kind of connection worth understanding.

Know what happened: Goldman Sachs reported a 72% increase in equities trading revenue to $6.44 billion, while global M&A deal value fell 41% quarter-on-quarter. Morgan Stanley experienced a similar divergence between strong equities trading and weaker fixed-income performance.

How does it impact the firm? Diversified investment banks can offset weaker performance in one business with stronger results elsewhere. However, exceptional trading revenues may not be sustainable every quarter.

How does it impact the division?

How does it impact clients? Corporate clients may delay acquisitions or capital raising. Institutional investors may need to rebalance portfolios or hedge exposures. Wealth clients may require advice after IPOs or other liquidity events.

What's your opinion?

"I think Goldman's results demonstrate the value of having a diversified investment banking business. The equities trading performance is impressive, but I wouldn't assume that level of growth is sustainable. I'm more interested in whether the bank's strong advisory pipeline converts into completed deals once interest rates and valuations stabilise."

What would you watch next?

I'd watch M&A volumes, the IPO pipeline, interest-rate expectations and whether the exceptional trading activity continues.

The important question is whether we're seeing a temporary pause in dealmaking or a longer period of expensive financing.

For most of 2026, investors have been obsessed with one theme.

Artificial intelligence.

Nvidia.

Data centres.

Semiconductors.

Cloud computing.

Companies have been committing extraordinary amounts of money to building the infrastructure required to power increasingly sophisticated AI models.

But last week, something changed.

The S&P 500 and Nasdaq suffered their largest weekly declines since June.

Semiconductor stocks were hit particularly hard, with the Philadelphia Semiconductor Index falling more than 10%.

And the reason wasn't that AI had suddenly stopped working.

It was that investors were becoming increasingly concerned about how much money companies are spending to build it.

That's a crucial distinction.

The technology can be revolutionary while the investment returns disappoint.

Imagine you're running a technology company.

You believe AI will transform your industry.

So you commit $50 billion to building data centres, purchasing GPUs and securing electricity.

Your competitors are doing the same.

You don't want to fall behind.

But there's a problem.

That $50 billion is being spent today.

The revenue you expect to generate from those investments might not arrive for several years.

And even when it does arrive, there's no guarantee it will be sufficient to justify the original investment.

This creates two separate questions.

Question 1: Will AI become enormously important?

Probably.

Question 2: Will every company investing billions in AI generate attractive returns?

Not necessarily.

And that's where investors are starting to become more cautious.

Here's the financial mechanism worth understanding.

Imagine a company expects a new data centre to generate £1 billion in annual free cash flow for ten years.

If investors use an 8% discount rate, those ten annual cash flows have a present value of approximately £6.7 billion.

Now imagine the discount rate rises to 12%.

Those exact same expected cash flows are suddenly worth approximately £5.7 billion.

Nothing about the data centre changed.

The expected cash flows are identical.

But its present value has fallen by around £1 billion simply because the required return increased.

Now imagine this happening across an industry where companies are committing hundreds of billions of dollars to projects whose cash flows may not arrive for years.

That's why higher interest rates are particularly important for capital-intensive growth industries.

And AI infrastructure is becoming one of the most capital-intensive industries in the world.

There's a second problem: debt.

Some companies are financing these projects by borrowing enormous amounts of money.

Debt can amplify returns when an investment performs well.

But it also creates fixed obligations.

Interest needs to be paid.

Debt eventually needs to be refinanced or repaid.

And lenders don't particularly care whether your long-term AI thesis is correct if you can't meet your obligations today.

That's why the market is becoming increasingly sensitive to AI-related leverage.

But here's what I find particularly interesting.

The largest technology companies often have substantial existing cash flows.

They may be able to fund much of their AI investment internally.

Smaller infrastructure companies may not have that luxury.

They may depend on continuous access to debt and equity markets.

If financing conditions tighten, the strongest companies can continue investing while weaker competitors may be forced to slow down.

Higher interest rates could therefore accelerate consolidation across the AI industry.

And that creates opportunities for investment banks.

Companies might need to raise capital.

Others might sell assets.

Some may merge with competitors.

And financially distressed businesses may need restructuring advice.

So a slowdown in AI investment doesn't necessarily mean fewer opportunities across every part of investment banking.

It may simply change the type of work banks are doing.

Know what happened: AI-related equities experienced a sharp sell-off, with semiconductor stocks particularly affected as investors questioned the scale of AI infrastructure spending and the financing required to support it.

How does it impact the firm? Banks could see more demand for capital raising, restructuring, risk management and M&A advice. However, weaker investor sentiment could make financing transactions harder to execute.

How does it impact the division?

How does it impact clients? Technology companies may face higher financing costs. Institutional investors may reduce concentrated AI exposures. Private equity and infrastructure funds may reassess project returns.

What's your opinion?

"I'm structurally positive on AI, but I think investors are right to distinguish between technological adoption and financial returns. The companies best positioned to benefit may not necessarily be those spending the most, but those capable of converting AI demand into sustainable free cash flow."

What would you watch next?

I'd watch the upcoming earnings reports from major technology companies, particularly Meta, alongside changes in AI capital expenditure guidance.

The question isn't simply whether spending continues increasing.

It's whether revenue, margins and free cash flow grow quickly enough to justify it.

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Here's something that might surprise you.

The Federal Reserve is increasingly concerned that the AI investment boom itself is contributing to inflation.

Think about that.

AI is often described as a technology that will make businesses more productive, reduce costs and potentially lower prices.

But building the infrastructure required to achieve those productivity gains is creating enormous demand for resources today.

Electricity.

Construction workers.

Data-centre equipment.

Semiconductors.

Land.

Power infrastructure.

And capital.

When demand for those resources increases faster than supply can respond, prices can rise.

So AI could potentially be inflationary in the short term and disinflationary in the long term.

That's a fascinating economic contradiction.

And it's creating a problem for central banks.

Here's what's happening.

Last week, the yield on the 10-year US Treasury reached approximately 5.25%.

That followed one of the sharpest quarterly increases in US government borrowing costs in decades.

Several factors are contributing.

Energy prices remain elevated because of geopolitical tensions.

The US economy has remained relatively resilient.

And enormous AI-related investment is adding to demand across parts of the economy.

Higher Treasury yields matter because government bonds form the foundation for pricing huge amounts of debt throughout the financial system.

When Treasury yields rise, corporate borrowing costs often rise too.

Mortgage rates can increase.

Leveraged buyouts become more expensive.

And equity valuations can come under pressure.

But the AI connection creates an additional complication.

The companies driving AI investment may be less sensitive to higher interest rates than the rest of the economy.

Imagine two businesses.

Company A is a small manufacturer that wants to borrow £5 million to expand its factory.

Company B is a technology giant generating tens of billions of dollars in annual cash flow.

The central bank raises interest rates.

Company A's financing becomes significantly more expensive.

It may cancel its expansion.

Company B, however, might continue spending billions on AI infrastructure because it has substantial cash reserves and considers the investment strategically essential.

So higher rates successfully discourage investment at Company A.

But they barely affect Company B.

Now multiply that across the economy.

Central banks are trying to slow demand.

But some of the companies generating enormous demand for electricity, equipment and construction continue investing regardless.

That means the burden of higher interest rates can fall disproportionately on smaller businesses, households and industries that depend heavily on borrowing.

And that's the dilemma facing the Fed.

If it doesn't raise rates enough, inflation may remain elevated.

But if it raises rates too aggressively, it could damage parts of the economy that aren't responsible for much of the new investment boom.

There's also a potential feedback loop.

AI infrastructure investment increases demand for scarce resources.

That contributes to inflationary pressure.

The Fed responds with higher interest rates.

Higher rates increase financing costs.

Those higher financing costs make AI infrastructure projects more expensive.

Some projects are delayed or cancelled.

That eventually reduces investment demand.

But the adjustment may take time, particularly when large technology companies can continue funding projects internally.

This is why the relationship between AI, inflation and interest rates is worth following.

It's not just a technology story.

It's a monetary policy story.

And because interest rates influence valuations, borrowing costs and investment decisions, it's relevant to almost every major division of a financial institution.

Know what happened: US Treasury yields climbed to around 5.25% last week, while Federal Reserve officials increasingly identified AI-related investment as a potential contributor to inflationary pressure.

How does it impact the firm? Higher rates can support certain interest-earning activities but may weaken borrowing demand, increase funding costs and create greater market and credit risk.

How does it impact the division?

How does it impact clients? Corporate clients face more expensive financing. Private equity firms may struggle to achieve target returns on leveraged transactions. Pension funds and insurers may benefit from higher yields on new fixed-income investments, while existing bond holdings can suffer mark-to-market losses.

What's your opinion?

"I think the most interesting aspect of the current rate environment is that monetary policy may be affecting different parts of the economy very unevenly. Large technology companies can continue funding AI investment through internal cash flow, while smaller businesses and households face significantly higher borrowing costs. That makes the Fed's task of controlling inflation without damaging growth particularly difficult."

What would you watch next?

I'd watch US inflation, labour-market data, energy prices and the next Federal Reserve decision.

I'd also monitor whether the AI investment boom continues expanding despite higher financing costs.

If inflation remains elevated while economic activity outside technology weakens, the Fed could face increasingly difficult trade-offs.

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Three stories this week, one connecting thread.

Goldman Sachs generated $6.4 billion in equities trading revenue while global M&A activity slowed.

AI stocks suffered a sharp sell-off as investors questioned the economics of enormous infrastructure investments.

And US government borrowing costs reached levels that are forcing businesses and investors to reconsider how much risk they're willing to take.

They're all connected by one fundamental concept:

The cost of capital.

When interest rates rise, borrowing becomes more expensive.

That affects the economics of acquisitions.

It changes the value of future cash flows.

It makes investors more selective.

And it forces companies to think more carefully about where they allocate capital.

But the effects aren't uniform.

Some businesses benefit.

Others struggle.

Trading desks may perform well while advisory activity slows.

Large technology companies may continue investing while smaller businesses cut spending.

Institutional investors may find attractive opportunities in bonds while growth stocks become more difficult to value.

That's why commercial awareness isn't about memorising headlines.

It's about understanding how changes in one part of the financial system affect everything else.

And if you're preparing for interviews, here's the framework I want you to use every time you read a financial news story.

1. What happened? Know the headline, key numbers and underlying facts.

2. How does it affect the firm? Think about revenue opportunities, costs, risks and strategic implications.

3. How does it affect the division? Connect the story to the actual work the team performs.

4. How does it affect clients? Consider how businesses, investors and other customers might respond.

5. What's your opinion? Develop a reasoned view rather than simply repeating what analysts have said.

6. What happens next? Identify the developments that could support or challenge your view.

Most candidates stop after the first question.

The strongest candidates can work through all six.

That's the difference between knowing what's happening in financial markets and actually understanding how finance works.

That's all for now. Have a good week ahead!

Afzal

Ps. Whenever you’re ready, get ongoing help from me, and join others securing interviews and offers, inside Finance Fast Track.