Markets questions —
what they're really testing.

The Fed has a dual mandate: price stability — which it defines as inflation around 2% — and maximum employment. The two legs of that mandate have been pulling in different directions over the last few years, and how you evaluate their performance depends on which you prioritise.

On inflation, the Fed overcame one of its biggest credibility tests in decades. After letting inflation run well above target in 2021–22, it hiked aggressively and has now brought core inflation back toward target without triggering a recession — what most economists would call a soft landing. That is broadly seen as a success, even if the path was uncomfortable.

On employment, the labour market has remained remarkably resilient throughout the hiking cycle. Unemployment has stayed low. The question now is less about whether the Fed is meeting its mandate and more about how much further it can ease without rekindling inflation — which is why you are seeing cuts, but cautious ones. Neutral rates are probably higher than they were pre-COVID, and the Fed knows it.

The ones you need to know cold:

• Federal Reserve (US) — Jerome Powell. Currently in a cautious easing cycle. Cuts are happening, but slower and more conditional than markets initially priced.
• European Central Bank — Christine Lagarde. Also cutting, with European growth structurally weaker and inflation having fallen more decisively than in the US.
• Bank of England — Andrew Bailey. Easing cautiously. UK faces a tricky combination of weak growth and stickier services inflation than the continent.
• Bank of Japan — Kazuo Ueda. The outlier. Moving in the opposite direction — gradually tightening after decades of ultra-loose policy, as Japan finally sees sustained wage growth and inflation.
• Bank of Canada — Tiff Macklem. Ahead of the Fed in its cutting cycle, dealing with a more rate-sensitive mortgage market and weaker domestic demand.

The key macro theme across all of them: this is not a return to zero interest rates. Cuts are happening, but neutral rates are higher than they were pre-COVID, and balance sheet policy matters as much as rate decisions now.

The events that move rates markets — roughly in order of impact:

• FOMC meetings — eight per year. The decision itself rarely surprises, but the statement and the dot plot (where FOMC members forecast future rates) can move markets significantly.
• Fed Chair speeches and press conferences — Powell's Jackson Hole speech, for example, has historically moved markets more than some rate decisions.
• Non-Farm Payrolls — first Friday of every month. Employment data is now the key input into how fast the Fed cuts. A surprisingly strong number delays easing; a weak one accelerates it.
• CPI / Core PCE releases — inflation data. Core PCE is actually the Fed's preferred measure, not CPI.
• Treasury auction results — weak demand at a 30-year auction can push long-end yields sharply higher. Fiscal concerns are increasingly on markets' radar.
• Quarter-end rebalancing — pension funds and endowments rebalance large portfolios, creating predictable but sometimes large flows.

Beyond the calendar, keep an eye on 5y5y forward inflation swaps — the market's view on where inflation will be in five years' time, five years from now. It is the cleanest signal of long-term inflation expectations and the Fed watches it closely.

The big story in global macro right now is monetary policy divergence. The US, UK, and Europe are all in easing cycles — but moving at different speeds. Japan is the outlier, moving in the opposite direction entirely.

The Fed is cutting cautiously, constrained by a stronger economy and stickier services inflation than Europe. The ECB has more room to cut because European growth is weaker and the fiscal outlook is more uncertain — particularly in France. The Bank of England is in a similar position to the US: inflation has fallen, but services and wage growth remain elevated, so the pace of cuts is slow.

Japan is the most interesting divergence. After decades of near-zero rates and quantitative easing, the BoJ is gradually normalising policy as Japan finally sees sustained wage growth. That matters globally because the yen carry trade — borrowing cheaply in yen to buy higher-yielding assets elsewhere — is enormous. When the BoJ tightens and the yen strengthens, it forces carry trade unwinds that can move markets globally, as we saw in 2024.

The takeaway: monetary policy is no longer synchronised the way it was during COVID. Divergence creates relative value opportunities in both rates and FX — which is exactly the kind of environment where a good sales desk adds value.

The yield curve is an interpolated line showing the relationship between maturity and yield across government bonds — in the US, that is Treasuries; in the UK, gilts. It is interpolated because bonds do not exist at every possible maturity point, so the curve is constructed by fitting a line through the actual data points.

The curve takes three main shapes:

• Normal (upward sloping) — longer maturities carry higher yields. This is the default state because investors demand more compensation for locking up money longer, and longer-dated bonds are more sensitive to rate changes and inflation. It reflects a healthy economy with positive growth expectations.
• Inverted (downward sloping) — short-term yields are higher than long-term yields. This is a classic recession indicator. It typically happens when the market expects the central bank to cut rates significantly in the future because the economy is expected to slow. The 2s10s inversion in 2022–23 was the longest on record.
• Flat — the transition between normal and inverted, or a sign that the market is uncertain about the growth and inflation outlook. Short and long yields converge.

Right now, the US yield curve is in the process of disinversion — the 2s10s spread had been deeply negative and is now moving back toward positive as the Fed cuts short-end rates. This is called a bull steepener (short end falls, curve steepens) — the textbook early-easing-cycle move.

A curve trade takes advantage of the relative movement between two different points on the yield curve, rather than making a directional bet on rates going up or down overall.

The two most common curve trades are a steepener and a flattener. A 2s10s steepener, for example, would involve going long the 10-year (buying the long end) and short the 2-year (selling the short end). You profit if the spread between them widens — i.e. if the 10-year yield rises more than the 2-year, or the 2-year falls more than the 10-year. This is the kind of trade you would put on if you expected the Fed to cut rates (pushing down the short end) while long-end yields stayed elevated due to fiscal concerns or growth expectations.

A flattener is the opposite — you short the long end and go long the short end. You profit if the spread between 2s and 10s narrows. This would typically be the trade if you expected growth to slow or the Fed to keep rates higher for longer.

In practice, these trades are done with Treasury futures and are duration-weighted — you are not just putting equal notional on each side. You adjust the size of each leg so that a parallel shift in rates leaves you flat, and you only profit from a change in the curve's slope.

Check the current 10-year yield before your interview — it changes daily. At the time of writing it sits around 4.3–4.5%. Your answer should reference whatever level it actually is that week.

The 10-year Treasury is the most watched rate in global finance because almost everything is priced off it — mortgages, corporate bonds, equity discount rates. Three things primarily drive it:

• Growth expectations — a stronger economy pushes yields higher as investors demand more compensation and the market prices in less future easing.
• Inflation expectations — particularly long-term inflation, which you can see in the 5y5y breakeven. Higher expected inflation erodes the real return on a fixed coupon, so investors demand a higher nominal yield.
• Term premium — the extra compensation investors demand for holding a long-dated bond rather than rolling over short-term debt. This has risen as fiscal deficits and Treasury issuance have increased, and as the Fed's balance sheet has shrunk through quantitative tightening.

On the direction: the sell-side consensus is that long rates are range-bound with two-way risk. Disinflation is mostly priced in — which caps the downside in yields. But growth surprises and fiscal concerns can push yields back up quickly. This is not a simple "buy bonds" environment — it is a relative value and curve trade environment.

Bond prices and yields move inversely — when prices go up, yields go down, and vice versa. This is one of the most fundamental relationships in all of fixed income, and it follows directly from the mechanics of how bonds are valued.

A bond pays a fixed coupon. If the yield required by the market rises — because rates have gone up, or the creditworthiness of the issuer has declined — the fixed coupon becomes less attractive relative to what the market now demands. So the bond's price has to fall to the point where its effective yield (the return you get buying it at the new lower price) matches the market rate.

Think of it this way: if a bond pays £5 per year and you paid £100 for it, your yield is 5%. If the market now requires 6%, the price has to drop to around £83 so that the same £5 coupon generates a 6% return on the new price. Price falls, yield rises.

This is also why duration matters. A longer-dated bond is more sensitive to yield changes than a shorter one, because more of its cash flows occur far in the future — and small changes in the discount rate have a bigger effect on their present value.

Almost everything on "Main Street" is priced off government bond yields, particularly at the long end. Mortgage rates are benchmarked off the 10-year. Corporate borrowing costs are benchmarked off Treasuries of equivalent maturity. When long yields fall, the entire cost of credit in the economy gets cheaper — which stimulates investment, borrowing, and growth.

There is also a portfolio rebalancing effect: when government bond yields fall, they become less attractive relative to riskier assets. Investors migrate to corporate bonds, equities, and real estate in search of return — which inflates asset prices and, through a wealth effect, encourages spending.

The Fed watched the long end particularly closely during COVID, when there was a concern that rapidly rising long yields could undo the stimulus from keeping short rates near zero. Some central banks — notably Japan and Australia — have explicitly used yield curve control (YCC), capping government bond yields at a target level by buying as many bonds as needed. The Fed considered it and chose not to, but the fact that it was discussed shows how much the long end matters for the transmission of monetary policy.

A credit spread is the difference in yield between a corporate bond and a government bond of the same maturity. It represents the additional compensation investors demand for taking on credit risk — the risk that the company defaults. A 10-year corporate bond trading at T+250 pays the 10-year Treasury yield plus 2.5% (250 basis points).

Investment grade (IG) spreads are currently very tight — close to historical lows — reflecting healthy corporate balance sheets and investor appetite for yield. High yield (HY) spreads are similarly compressed. The main concern in 2026 is not public credit markets but private credit, where ZIRP-era loans are maturing and defaults are beginning to tick up.

What causes spreads to widen:

• Economic slowdowns or recession fears — default risk rises
• Company-specific deterioration (earnings miss, leverage rising)
• Risk-off events (geopolitical shocks, market stress)
• Supply pressure — heavy new issuance calendar

What causes spreads to tighten:

• Strong economic data — default risk falls
• Central bank easing — improves refinancing conditions
• Demand pressure — large inflows into credit funds
• Company-specific improvement (deleveraging, earnings beat)

Investment grade (IG) bonds are rated BBB- or above by S&P, or Baa3 or above by Moody's. These are companies with strong balance sheets, low default probability, and relatively predictable cash flows — think large multinationals, utilities, financials. IG bonds trade with tighter spreads, lower yields, and high liquidity.

High yield (HY) bonds — sometimes called junk bonds, though nobody on a desk calls them that — are rated below BBB-. These companies have higher leverage, more cyclical earnings, or more uncertain credit profiles. They compensate investors with higher yields and wider spreads. The HY market is smaller and less liquid, meaning bid-ask spreads are wider and executing in size is harder.

On the current state of credit markets: public spreads are historically tight in both IG and HY. On the surface this signals confidence. The concern is that tight spreads can mask underlying risk — particularly in private credit, which has grown enormously and absorbed a lot of the riskier lending that banks no longer do. Roughly 40% of the private credit market is concentrated in a few large managers, and ZIRP-era loans are now maturing in a higher-rate environment. Defaults and even some fraud cases are showing up at the fringes.

I follow credit through a combination of daily news flow and broader research. Each morning I check the FT's markets section and Reuters Global Markets, which both have good coverage of credit moves. For the US credit market, I track the ICE BofA IG and HY effective yield indices — watching whether spreads are compressing or widening gives you a quick read on risk sentiment without needing to go security by security.

For deeper reading, Matt Levine's Money Stuff at Bloomberg is excellent — he explains credit and structured product stories with a clarity that most market commentary lacks, and he flags things that others miss. I also read bank research when I can access it — Barclays Credit Strategy and Goldman's credit commentary are both genuinely useful for the macro-to-credit linkages.

I do not try to follow individual corporate bonds closely at this stage — the primary goal is to understand how credit markets are moving as a whole and what macro events are driving sentiment. The specific security-level knowledge is something you build on the desk.

The major FX pairs — know these cold:

• EUR/USD — the most liquid currency pair in the world. Euro versus Dollar.
• USD/JPY — Dollar versus Yen. The focus of enormous attention right now given BoJ policy normalisation.
• GBP/USD — Sterling versus Dollar. Often called "Cable" — named after the telegraph cable that used to transmit exchange rates between London and New York.
• USD/CHF — Dollar versus Swiss Franc. The Franc is a classic safe-haven currency.
• AUD/USD and USD/CAD — commodity-linked pairs, often used as proxies for global risk appetite and China demand.

On the Dollar right now: the sell-side consensus is for modest Dollar weakness. The logic is that the Fed is cutting, US growth may converge toward the rest of the world, and global risk appetite favours pro-cyclical currencies. EM FX and small open-economy G10 currencies (AUD, NZD, NOK) benefit in this environment. But the weakness is not dramatic — the US economy remains resilient and fiscal deficits make US Treasuries still attractive to foreign buyers, which supports the Dollar somewhat.

In FX, everything is relative — a currency is only strong or weak in comparison to the currency it is trading against. The drivers can be grouped into three categories:

1. Monetary policy and interest rate differentials: This is probably the most important driver over a one-to-twelve month horizon. Higher interest rates attract capital flows seeking better returns, which strengthens a currency. When the Fed raised rates aggressively in 2022–23, the Dollar strengthened sharply. As the Fed now cuts, the rate differential narrows, and the Dollar softens.

2. Economic fundamentals: GDP growth, inflation, trade balances, and current account positions all matter. A country running persistent current account surpluses (like Japan, historically) tends to see its currency supported by repatriation of export revenues. A country with large deficits (like the US or UK) depends on capital inflows to fund them — which makes its currency more sensitive to risk sentiment.

3. Politics and risk sentiment: Political uncertainty, elections, geopolitical events, and global risk-off episodes all drive currencies. Safe-haven currencies — the Yen, Swiss Franc, and to some extent the Dollar — tend to strengthen in risk-off environments as capital flows to perceived safety.

I follow FX primarily through the Financial Times and Reuters, both of which have strong currency coverage. Reuters in particular is good for the daily flow narrative — explaining why the Yen moved 0.5% this morning, or what positioning data from the CFTC futures market is signalling about speculative sentiment.

Beyond news flow, I find it useful to follow the CFTC Commitments of Traders report, which is released weekly and shows speculative positioning in major FX futures. It gives you a sense of whether a trade is already crowded — which is important for thinking about risk, since heavily one-sided positioning often means a sharp reversal when the view gets challenged.

I would be honest that following FX deeply is something you build on the desk — the granular understanding of interbank flows, client activity, and short-term technicals is genuinely something you can only develop by being in the market. But understanding the macro drivers and being able to explain them is something I have put real effort into.

Equity markets are being driven by two competing forces: strong earnings growth and stretched valuations. The sell-side consensus is that S&P earnings grow around 10–14% in 2026, driven by AI-related capex spending, a resilient consumer, and financial sector strength. That is genuinely strong.

The problem is that valuations are already reflecting a lot of good news. The S&P 500 forward P/E is elevated relative to history — not at dot-com levels, but not cheap. The implication is that the index upside is capped in the mid-single digits even with strong earnings growth, because you are not going to get significant multiple expansion from here.

The way to think about valuations is through a DCF lens: equity prices are the present value of future cash flows. Two things boost valuations — higher expected cash flows and lower discount rates. The market got both from 2020–22 (fiscal stimulus plus near-zero rates). Now the discount rate is higher and likely to stay that way, which is a structural headwind for multiples. Earnings have to do the work instead — and so far they are.

The most interesting equity theme right now is leadership broadening beyond mega-cap tech. Industrials, energy infrastructure, financials, and materials are all benefiting from AI capex spillovers, re-industrialisation, and fiscal spending. The Magnificent 7's contribution to index returns is expected to peak — the rest of the market is catching up.

The traditional portfolio construction logic was that bonds and equities are negatively correlated — when equities sell off, investors flee to the safety of government bonds, pushing bond prices up and yields down. This negative correlation was the foundation of the classic 60/40 portfolio.

That relationship broke down significantly in 2022, when both equities and bonds fell simultaneously as inflation forced the Fed to hike aggressively. When inflation is the primary shock, it hits both assets — higher rates push down bond prices, and the same higher rates reduce equity valuations by raising the discount rate.

The correlation has partly normalised as inflation has fallen back toward target, and bonds have started to work as a hedge again in some risk-off episodes. But the relationship is more regime-dependent than it was in the pre-COVID era. In a deflationary recession scenario, bonds hedge equities well. In an inflationary shock, they do not.

This is one reason why the sell-side has been recommending alternatives to the 60/40 — commodities, real assets, and volatility as portfolio hedges — because you cannot rely on bonds to bail you out in all scenarios anymore.

Check the gold price the week of your interview — it changes. At the time of writing gold is trading around $3,000 per ounce, having broken through that level for the first time in early 2025.

The traditional view of gold as primarily an inflation hedge is too simple. Over the past few years, gold has been driven by a broader set of forces:

• Central bank buying — this has been the biggest structural driver. Emerging market central banks, particularly China, India, and those in the Middle East, have been buying gold at record rates as they diversify away from Dollar-denominated reserves. This is a long-term structural bid.
• Real rate movements — gold tends to perform best when real interest rates (nominal rates minus inflation) are falling or negative. As the Fed cuts nominal rates and inflation stays above zero, the real rate environment becomes more supportive for gold.
• Geopolitical risk and de-dollarisation — gold benefits when confidence in the global financial system, or specifically in the Dollar as the reserve currency, comes into question. The freezing of Russian reserves in 2022 accelerated central bank diversification into gold.

The direction is genuinely uncertain. If the macro backdrop softens, real rates fall further and gold likely benefits. But a lot of good news is in the price, and positioning is long — which creates tail risk of a sharp reversal if real rates surprise to the upside.

Check WTI and Brent crude prices before your interview. WTI is the US benchmark; Brent is the global benchmark used in the UK and most of Europe. They typically trade within a few dollars of each other, with Brent slightly higher.

Oil is driven by the push and pull between OPEC+ production discipline and global demand, with US shale supply as the swing factor. The key dynamics right now:

Supply side: OPEC+, particularly Saudi Arabia, has maintained production cuts to support prices. But these create a free-rider problem — non-OPEC producers like the US benefit from higher prices without cutting their own output. US shale production has been remarkably resilient and continues to grow, which caps how high OPEC can push prices before losing market share.

Demand side: China is the most important swing factor for global oil demand, given its industrial economy and the pace of its energy transition. Weaker Chinese growth is a headwind; stronger growth is a tailwind. European demand remains subdued given weak industrial activity.

The honest answer is that you do not need a strong directional thesis on oil unless you are applying to a commodities desk. Knowing the current price, the OPEC+ dynamic, and the basic supply/demand framework is what interviewers expect.

The indicators that move markets — roughly in order of frequency and impact:

• Non-Farm Payrolls (NFP) — monthly, first Friday. The headline number, unemployment rate, and wage growth are all key inputs to the Fed's thinking. This is often the single most market-moving regular release.
• CPI / Core PCE — monthly inflation data. CPI is the more watched headline number; Core PCE (excluding food and energy) is what the Fed officially targets.
• GDP — quarterly. The broadest measure of economic health. Advance, preliminary, and final estimates are released sequentially — the advance reading gets the most attention.
• PMI (Purchasing Managers' Index) — monthly flash estimates. A leading indicator of economic activity. Above 50 = expansion, below 50 = contraction. The manufacturing and services PMIs are tracked separately.
• Initial Jobless Claims — weekly. A high-frequency read on labour market health. A sudden spike signals stress in hiring or layoffs.
• 5y5y breakeven inflation swap — not a traditional economic release, but a market-derived signal the Fed watches very carefully. It shows where markets expect inflation to be in 5 years, 5 years from now — the cleanest measure of long-term inflation credibility.

If forced to choose one: NFP, because employment is the lagging indicator that tells you whether the Fed's policy is working — and right now, it is the primary input into how fast rate cuts proceed.

This is a classic cross-asset scenario question. The chain of causation:

Rates: A re-acceleration in inflation would force the Fed to pause — or even reverse — its cutting cycle. Markets would price out future cuts, pushing up short-end yields. Long-end yields would also rise as the term premium reprices for inflation risk. The yield curve would likely flatten or potentially invert again as the front end sells off.

Credit: Higher rates increase the cost of refinancing debt and raise concerns about corporate debt serviceability — particularly for high-yield and private credit. Spreads would widen. Investment grade would be less affected than high yield, but both would reprice.

Equities: A higher discount rate means lower present values of future cash flows — which hits growth stocks hardest (their cash flows are further in the future). Value sectors and financials (which benefit from higher rates through wider net interest margins) would be more resilient. Overall, equities would likely sell off.

FX: A hawkish Fed pivot would strengthen the Dollar as rate differentials move in its favour and capital flows back into the US seeking higher yields.

Gold: Mixed. Historically, gold underperforms when real rates rise sharply. But if the inflation shock is driven by geopolitical or fiscal concerns, gold could actually benefit from uncertainty.

The VIX is the CBOE Volatility Index — it measures the implied volatility of S&P 500 options over the next 30 days. In plain English, it is the market's expectation of how volatile equity markets will be in the near term.

The VIX is often called the "fear gauge." When it spikes, it signals that option buyers are paying significant premiums for protection — which typically coincides with periods of market stress or uncertainty. A VIX below 15 is generally considered calm; above 25 signals elevated stress; above 40 signals genuine fear (as seen during COVID or the 2008 financial crisis).

The important nuance is that the VIX is forward-looking, not backward-looking. It does not measure how volatile the market has been — it measures how volatile the market expects to be. You can have a period of high realised volatility where the VIX is falling, because the market expects things to calm down. Or the VIX can spike on a calm day if options demand suddenly surges.

For 2026, the sell-side consensus is that volatility is structurally higher than the 2017–2021 era — driven by AI uncertainty, fiscal dominance, high valuations, and policy uncertainty. Sharp drawdowns are expected but are not seen as cycle-ending events. Snapbacks tend to be faster too.

This is a personal question — your answer should reflect what you genuinely follow. Do not pick something obscure just to look impressive; pick something you can actually discuss in depth. Below is a model answer for rates, adapted to show the structure.

Example answer — rates-focused:

"I've been watching rates markets most closely, specifically the 2s10s curve and how it's been disinverting as the Fed cuts. The interesting dynamic is that while the front end is falling as expected, the long end has been sticky — term premium has been rising as markets worry about fiscal deficits and Treasury supply. That's creating a bear steepener environment rather than the classic bull steepener you'd expect early in a cutting cycle, and that has quite different implications for how you position a rates book."

The structure to use: what you're watching → why it's interesting right now → one specific nuance that shows depth. Keep it to 60–90 seconds and expect a follow-up.

This is primarily a superday question. It is rare in first-round interviews. The format to follow:

1. State the theme — what macro dynamic are you expressing?
2. State the instrument — how are you expressing it?
3. Entry, stop-loss, and take profit — in the right units.
4. What breaks the trade? — what would make you wrong?

Example — long USD/JPY as BoJ normalisation trade:

"The Bank of Japan is gradually tightening policy for the first time in decades, as Japan finally sees sustained wage growth and inflation. This creates a structural tailwind for the Yen. However, the pace of BoJ normalisation is likely to be very slow and cautious — they have a 30-year history of policy reversals when they tightened too early. At the same time, the US economy is resilient and the Fed is cutting slowly. The net effect is a narrowing of the USD/JPY rate differential, but gradually. I would express a modest short USD/JPY position — entering around 150, with a stop at 155, and a take profit at 140. The trade breaks if US data surprises strongly to the upside, or if the BoJ reverses course on normalisation."

Keep it to two minutes maximum. Stay away from complex options structures in the interview — the follow-up questions will quickly go beyond what you can answer.

Pick something you genuinely read about this week. Below is a model answer on private credit stress — but tailor to whatever is actually in the news at the time of your interview.

Example — private credit spillover into public HY:

"I've been following the growing stress in private credit markets. Public IG and HY spreads remain historically tight, but private credit is showing early signs of stress — defaults are rising, payment-in-kind structures are becoming more common, and roughly 40% of the market is concentrated in a handful of managers. What concerns me is that many private credit borrowers are the same companies that appear in public high yield markets. If stress in private credit escalates, it could spill into public HY through risk sentiment and forced selling — even though the direct linkage is not always obvious.

To express this, rather than shorting individual HY bonds (too security-specific), I'd look at selling HY CDX protection — essentially buying protection on an index of high yield names. The trade is not a directional bet on a collapse but a hedge against spread widening if private credit stress transmits into public markets. Stop loss if HY spreads tighten further; take profit if they widen by 75–100bps."

I try to balance daily news flow with more forward-looking research. My daily routine:

Morning: Financial Times markets section and Reuters Global Markets. I am looking for the key overnight moves — what happened in Asia, what is priced into European markets, and what economic releases are coming today. I then focus on the stories most relevant to rates, FX, and credit.

Throughout the day: Matt Levine's Money Stuff (Bloomberg) is essential reading — it explains why things matter, not just what happened. For rates specifically, I follow the key yields and swap rates. For FX, I track the major pairs and any unusual moves in EM currencies.

Weekly: I look at bank research — Barclays Markets Weekly, Goldman's macro research, and strategy notes on rates and FX when I can access them. These are more forward-looking and help me form my own views rather than just reacting to headlines.

I also follow the economic calendar closely — NFP, CPI, FOMC — and try to think in advance about what each print means for the market view, rather than just reacting to the number when it comes out.

This question has no model answer — it should come from something you actually read this week. Below is the structure, not the content.

Structure:

• What happened — briefly, in one or two sentences. No more.
• Why it's interesting — what does it tell you about the broader macro picture, or about a specific market dynamic you've been watching?
• What it means for markets — cross-asset implications, if you can draw them. How does this story connect to rates, FX, credit, or equities?
• Your view — do you agree with the consensus interpretation? Is there a trade here?

The story itself matters less than your ability to analyse it. Interviewers are not testing whether you picked the right story — they are testing whether you can articulate why something is interesting and what it means beyond the headline. Keep the answer to 90 seconds and expect follow-up.

The Efficient Market Hypothesis (EMH) holds that asset prices fully reflect all available information — which means you cannot consistently beat the market through analysis or timing. In its strong form, even insider information is already priced in.

The intellectually honest answer is: it depends on the market and the timeframe. Liquid, transparent markets like large-cap US equities or on-the-run Treasuries are probably close to efficiently priced at any given moment. There are enough smart investors with access to the same information that mispricings get arbed away quickly.

But there are clear reasons markets are not perfectly efficient: transaction costs, information asymmetry, behavioural biases, and liquidity constraints. The less liquid and less transparent the market — distressed credit, EM bonds, structured products — the more likely that mispricings persist long enough to be exploited. This is actually one reason why the sell-side exists: helping clients navigate markets where efficient pricing is not guaranteed.

In practice, what S&T actually does is not "beat the market" — it is provide liquidity and help clients execute at the best available price. The EMH debate matters less on the desk than the ability to price things fairly and manage the resulting risk.

AI is genuinely transformational, but the sell-side consensus is appropriately cautious about the near-term financial picture. The tension is between real productivity gains and uncertain monetisation timelines.

For the broader economy and markets: AI is already driving a significant capex supercycle — data centres, semiconductors, energy infrastructure. This is creating an AI-adjacent investment theme that has helped industrials and energy infrastructure outperform alongside tech. Productivity gains are coming, but they are slow to show up in GDP data because adoption takes time. The concern is that capital expenditure is accelerating faster than revenue generation — which eventually becomes a credit story if companies borrowed heavily to fund the buildout.

For S&T specifically: AI is changing the flow of information and the speed of market analysis, but it is not replacing judgment or client relationships. The desks most affected are electronic market-making and flow trading — where speed and pricing models are commoditising. The desks least affected are those that require relationship management, credit judgment, and structuring for complex client needs. This is actually one reason why sales and solutions-oriented roles remain attractive even as technology displaces more repetitive trading functions.

The honest view: AI will likely prove more valuable over a decade than markets are pricing in right now for productivity — and potentially less valuable near-term for individual stocks where valuations have run ahead of the actual earnings story.

The classic 60/40 portfolio — 60% equities, 40% bonds — is more complicated in this environment than it was pre-COVID. Higher neutral rates mean bonds provide more yield than they did in 2020–21, but they are no longer the reliable hedge they were in the ultra-low rate era. I would think about allocation in four buckets:

40% global equities: Overweight the US given resilient earnings growth, but diversified — with exposure to industrials and financials benefiting from AI capex spillovers and the broadening leadership theme. Underweight pure mega-cap tech at current valuations.

25% investment grade fixed income: Short to medium duration given the range-bound rates environment. UK gilts and US Treasuries in the 5-year area — capturing yield without excessive duration risk if long rates surprise higher.

20% alternatives / real assets: Given the breakdown in the bond-equity correlation, I'd want a genuine diversifier. A combination of gold (structural bid from central bank buying, real rates likely falling) and commodities (energy infrastructure, benefiting from AI power demand) makes sense.

15% EM: Selective exposure to EM FX and EM equities in markets benefiting from a weaker Dollar and Chinese stimulus — focusing on countries with strong fiscal positions and commodity links.

Keep it humble at the end: "Obviously this is a simplified view — a real portfolio would require much more granular thinking about correlation, liquidity, and specific client constraints."

Two different things are being asked here — do not confuse them.

Current yield is the simplest: it is just the annual coupon payment divided by the current price. A 10% coupon on a bond with face value 100 pays £10 per year. The bond trades at 90. So current yield = 10 ÷ 90 = 11.1%.

Yield to maturity (YTM) is more precise — it accounts for the capital gain you receive at maturity on top of the coupon. Since the bond was bought at 90 and redeems at par (100), there is a gain of 10 on top of the coupon of 10. Total return over one year = 20. Divided by the purchase price of 90: YTM = 20 ÷ 90 = 22.2%.

For maturities longer than one year, you cannot simply divide — you need to use an iterative formula (or trial-and-error) to find the discount rate that sets the present value of all future cash flows equal to the current price. For a two-year bond with the same parameters, the estimated YTM comes out at approximately 15.8%. You do not need to do this in your head — the interviewer wants to see you understand the formula and the logic.

The key insight: YTM > current yield whenever a bond trades below par, because YTM captures both the income return and the capital appreciation at redemption.

DV01 — Dollar Value of a basis point — measures how much the value of a bond or portfolio changes for a one basis point (0.01%) move in yield. It is the primary risk metric on a rates desk. If a position has a DV01 of £10,000, a one basis point rise in yields costs £10,000; a one basis point fall gains £10,000.

To hedge a rates position, the goal is to get your net DV01 to zero — meaning a one basis point move in yields leaves your P&L unchanged. In practice, you do this by taking an offsetting position in Treasury futures. Futures are the instrument of choice because they are highly liquid, off-balance-sheet, and easy to size precisely.

For example: if you are long a corporate bond with a DV01 of £50,000, you would short enough Treasury futures to generate a DV01 of -£50,000 on the hedge leg. The net DV01 is then zero — you are rate-neutral and only exposed to credit spread moves, not outright rate moves.

In equity derivatives, the equivalent concept is delta hedging — going long or short the underlying shares in exactly the right proportion to offset the directional exposure of an options position, leaving you market-neutral (delta = 0).

Three measures you should know:

IRR (Internal Rate of Return) — the discount rate that makes the net present value of all cash flows from an investment equal to zero. It is the annualised return on an investment accounting for the time value of money. Private equity and credit desks use it heavily when evaluating deals. A higher IRR is better, but it must be compared against a hurdle rate or cost of capital to be meaningful.

MOIC (Multiple on Invested Capital) — simply the total value returned divided by the amount invested. If you put in £100 and get back £250, your MOIC is 2.5x. Unlike IRR, it does not account for time — a 2x return in one year is very different from 2x in five years. MOIC and IRR are used together in private credit and PE: MOIC tells you how much you made; IRR tells you how fast.

Sharpe ratio — measures risk-adjusted return: (portfolio return minus the risk-free rate) divided by the portfolio's standard deviation. It answers the question "how much return are you getting per unit of risk?" A Sharpe ratio above 1 is generally considered good; above 2 is excellent. It is widely used in asset management and hedge funds for comparing strategies with different risk profiles.

Present value (PV) is what a future cash flow is worth today, given a discount rate. The formula: PV = FV ÷ (1 + r)^n, where FV is the future value, r is the discount rate per period, and n is the number of periods.

Intuitively: a pound today is worth more than a pound tomorrow, because today's pound can be invested and grow. The denominator (1 + r)^n is the discounting mechanism — the further into the future the cash flow, and the higher the discount rate, the smaller its present value.

This formula is the foundation of almost everything in finance. A bond's price is the present value of all its future coupon payments plus the redemption value, discounted at the prevailing yield. An equity's price, in theory, is the present value of all future dividends or free cash flows. When rates rise, the discount rate rises, and present values fall — which is why higher yields push down both bond prices and equity valuations simultaneously.

For markets, the practical implication is constant: any change in the discount rate — Fed decisions, inflation expectations, term premium — ripples through the present value of every asset in the world. This is why rates are the foundation that everything else is priced off.

Two frameworks reshaped S&T after 2008:

Basel III — an international framework developed by the Bank for International Settlements (BIS), fully implemented in 2019. Basel III is about capital and liquidity: it forces banks to hold more and higher-quality capital against their risk-weighted assets, and introduces liquidity requirements (LCR and NSFR) that ensure banks can survive a 30-day stress period without central bank support. For S&T, this means holding securities on the trading book is more expensive in capital terms — which has materially reduced the willingness of banks to warehouse risk and provide liquidity in less liquid markets. In the UK, the PRA is the regulator that implements Basel standards.

Dodd-Frank / The Volcker Rule — US legislation passed in 2010 (Dodd-Frank Act), with the Volcker Rule being the most directly relevant element for S&T. The Volcker Rule restricts proprietary trading — banks can no longer take speculative positions unrelated to client activity. Every trade must be justified as market-making, client facilitation, or hedging. In the UK, the equivalent framework is the ring-fencing regime under the Financial Services Act, which separates retail banking from investment banking.

The combined effect: banks are less able to warehouse risk, less willing to make markets in size in illiquid instruments, and more focused on client-driven flow. This is why the role of the salesperson — connecting client demand to the trader — became structurally more important.

A standard company's balance sheet has physical assets (property, equipment, inventory) on the left and a mix of debt and equity on the right. A bank's balance sheet is almost entirely financial: assets are loans, securities, and trading positions; liabilities are deposits, wholesale funding, and debt. The bank is essentially borrowing money (from depositors and markets) and lending it at a higher rate — the spread between those rates is the core of how it makes money.

Banks make money through three main streams:

• Net interest income (NII) — the difference between what the bank earns on loans and securities and what it pays on deposits and funding. This is the core of retail banking. When rates are higher, banks typically earn more NII because lending rates rise faster than deposit rates.
• Trading and markets revenue — bid-ask spreads on market-making, gains on hedging positions, structured product fees. This is what S&T generates. It is more volatile than NII and depends heavily on client activity and market conditions.
• Fee income — M&A advisory, ECM/DCM underwriting fees, asset management fees, FX transaction fees. These are largely volume-dependent and less capital-intensive.

Another key concept: mark-to-market accounting. Unlike a manufacturing company where assets sit at historical cost, banks mark their trading book to market value daily. In stressed markets, the value of held securities falls even if they have not defaulted — which can make a bank appear capital-constrained and force selling at precisely the wrong moment. This was central to the 2008 crisis.

The Beige Book (officially the "Summary of Commentary on Current Economic Conditions") is published eight times a year by the Federal Reserve, timed to FOMC meetings. It is a collection of anecdotal economic evidence gathered by the twelve Federal Reserve district banks from businesses, economists, and market participants across the US. Unlike hard data releases, it captures qualitative signals — whether businesses are hiring, whether consumers are spending, whether supply chains are stressed. Markets watch it because it often captures turning points in economic sentiment before they show up in official data.

The Monetary Policy Report is the Fed's semi-annual report to Congress, providing a detailed assessment of the economy and the rationale for recent policy decisions. It is the definitive official statement of how the Fed sees the world.

UK equivalents: The Bank of England publishes its Monetary Policy Report (MPR) quarterly — previously called the Inflation Report — which includes the MPC's forecasts for growth, inflation, and unemployment. The BoE also publishes its Financial Stability Report twice yearly, covering systemic risks. For markets participants, the MPC minutes (released two weeks after each decision) are often more market-moving than the rate decision itself.

GDP (Gross Domestic Product) measures the total value of goods and services produced within an economy over a given period. The expenditure approach gives us the standard equation: GDP = C + I + G + NX.

• C — Consumer spending: Personal consumption expenditure — durables (cars, appliances), non-durables (food, clothing), and services (healthcare, finance). In the US, consumer spending accounts for roughly 65–70% of GDP. This is why retail sales, consumer confidence, and NFP are so closely watched — they feed directly into the biggest component.
• I — Investment: Business investment in equipment, software, and structures, plus changes in inventories. Residential investment (housing) also falls here.
• G — Government spending: Federal and state/local spending on goods and services. Transfer payments like Social Security do not count — only direct government purchases.
• NX — Net exports: Exports minus imports. The US runs a persistent trade deficit (imports > exports), so NX is typically negative and drags on headline GDP.

For 2026, the US GDP growth consensus is around 2.3–2.6% — resilient but not booming. Consumer spending has held up better than most expected through the rate hiking cycle, supported by strong labour markets and excess savings, though that buffer is now thinning.

Three different inflation measures, each doing something slightly different:

CPI (Consumer Price Index) — measures the change in prices of a fixed basket of goods and services that a typical urban consumer would buy. It includes food and energy, which are volatile. This is the most-watched headline number in the media and in markets.

Core CPI — CPI stripped of food and energy prices, which are excluded because they are driven by supply shocks and seasonal factors that do not reflect underlying demand-driven inflation. Core CPI gives a cleaner signal of whether inflation is structural or transitory.

Core PCE (Personal Consumption Expenditures) — this is what the Federal Reserve actually targets at 2%. PCE differs from CPI in two important ways: it uses a broader and more dynamic basket (it adjusts as consumers substitute between goods), and it gives different weights to healthcare costs, which are a much larger share of actual consumer spending than CPI reflects. PCE consistently runs slightly below CPI — which is why you should not assume the Fed is satisfied just because CPI is at 2%.

For the UK, the equivalent is CPI (not PCE — the Bank of England targets CPI at 2%) and CPIH, which includes owner-occupied housing costs and is increasingly the preferred measure.

The 5y5y (five-year, five-year forward inflation swap) is a market-derived measure of where participants expect inflation to be over the five-year period starting five years from now. In plain English: it is the market's view of long-run inflation expectations, filtered out from the near-term noise of current inflation data.

Why it matters: near-term inflation is heavily influenced by supply shocks, energy prices, and base effects — all things that may not persist. The 5y5y strips all that out and asks a purer question: do people believe the central bank can keep inflation anchored at 2% over the medium term? That is the heart of central bank credibility.

When the 5y5y rises, it signals that markets are questioning the Fed's (or BoE's) ability to control inflation — which typically causes long-end yields to rise, equity valuations to fall, and the central bank to communicate more hawkishly. When it is anchored near 2%, it gives the central bank more flexibility to cut rates without triggering a credibility crisis.

During 2021–22, the 5y5y rose sharply before the Fed acted — an early warning that markets were losing confidence in "transitory" inflation. It has since come back down as the hiking cycle succeeded. The Fed watches it as closely as any official data release.

PMI stands for Purchasing Managers' Index. It is a monthly survey of purchasing managers at companies across manufacturing and services, asking whether conditions — new orders, output, employment, inventories, supplier delivery times — have improved, stayed the same, or worsened versus the previous month.

The index is constructed so that 50 is the neutral level: above 50 means the majority of respondents see improving conditions (expansion); below 50 means the majority see deterioration (contraction). The further from 50, the stronger the signal.

PMI moves markets for two reasons. First, it is a leading indicator — purchasing managers are making decisions about future orders and hiring, so the PMI tends to anticipate changes in GDP and employment before they show up in official data. Second, it is released as a flash estimate early in the month, making it one of the first reads on the current period's economic conditions.

Watch both the manufacturing PMI (more sensitive to global trade and industrial cycles) and the services PMI (more relevant for the US and UK economies, which are predominantly service-based). A divergence between the two — manufacturing contracting while services holds up, for example — is itself informative about the nature of any economic slowdown.

Two different windows on the labour market — one high-frequency, one monthly:

Non-Farm Payrolls (NFP) — released on the first Friday of every month at 8:30am EST. It measures the net change in the total number of paid workers in the US economy, excluding farm workers, private household employees, and non-profit employees. The headline number, the unemployment rate, and average hourly earnings (wage growth) are all reported simultaneously. NFP is arguably the single most market-moving regular data release — it directly informs how fast the Fed can cut rates, because strong employment data suggests the economy can handle higher rates for longer.

Initial jobless claims — released every Thursday at 8:30am EST. It measures the number of people who filed for unemployment insurance for the first time in the previous week. It is a high-frequency, real-time signal of stress in the labour market. A sudden spike in claims — even for one week — can move markets if it signals a turn in hiring conditions. Unlike NFP, which is an employment measure (how many people are employed), initial claims is an unemployment measure (how many people are newly losing jobs).

The two complement each other. NFP gives the definitive monthly read; jobless claims provides a weekly pulse check in between.

EBITDA — Earnings Before Interest, Tax, Depreciation, and Amortisation — is a measure of a company's core operating profitability, stripped of financing decisions (interest), tax jurisdiction, and non-cash accounting charges (D&A). You get to it from net income by adding back interest expense, tax, depreciation, and amortisation.

In credit markets, EBITDA is foundational for two reasons:

1. Leverage ratios: The most common credit metric is Net Debt / EBITDA — how many years of earnings it would take to pay off net debt. A company with £500m of net debt and £100m EBITDA is 5x leveraged. Investment grade companies typically run at 2–3x; highly leveraged buyouts can be 6–7x. Debt covenants almost always reference an EBITDA-based leverage ceiling.

2. Coverage ratios: EBITDA / Interest expense (the interest coverage ratio) measures whether the company generates enough operating cash flow to service its debt. A coverage ratio below 2x is a warning sign; below 1x means the company is not covering its interest from operations.

One important nuance: EBITDA is not cash flow. Capital expenditure, working capital changes, and taxes all hit cash before it reaches creditors. "Adjusted EBITDA" — often used in leveraged finance — can add back numerous one-off items and should be scrutinised carefully. Private equity sponsors are notorious for aggressive EBITDA adjustments.

The three standard valuation approaches:

1. DCF (Discounted Cash Flow) — project the company's free cash flows forward (typically five years), then apply a terminal value, and discount everything back to the present at the weighted average cost of capital (WACC). The DCF is untethered from current market prices — it is a fundamental, intrinsic value approach. Its weakness is that it is highly sensitive to the discount rate assumption and the terminal growth rate.

2. Comparables analysis (comps) — look at how similar publicly traded companies are valued in the market, expressed as a multiple of EBITDA (EV/EBITDA) or revenue. Apply that multiple to the company being valued. Fast and market-anchored, but limited by how comparable the "comparable" companies actually are.

3. Precedent transactions — look at what acquirers actually paid in past M&A deals for similar companies. Transaction multiples typically exceed trading multiples because acquirers pay a control premium. Useful for M&A contexts; less useful in normal market analysis.

For fixed income and credit, the DCF mindset is most directly relevant — a bond is simply the present value of its future cash flows discounted at the appropriate yield. Credit analysts also use EBITDA multiples to assess leverage and compare a company's debt load to peers. The equity valuation framework matters too because credit and equity are two claims on the same company — a deteriorating equity story almost always precedes spread widening.

Alternative asset classes are broadly defined as anything outside the traditional listed markets of equities, government bonds, and cash. The main categories:

• Private equity — direct ownership of companies outside public markets. The largest institutional allocation category for pension funds and endowments. ZIRP-era vintages are now facing higher-for-longer rates on their leveraged buyouts, and exit markets have been slow to reopen.
• Private credit / direct lending — the fastest-growing alternative asset class. Banks retreating from leveraged lending post-GFC created the space. Now a $2trn+ market globally and the main credit fragility concern for 2026, as discussed.
• Real estate — commercial property, particularly offices, has faced structural headwinds from remote work. Residential continues to be supply-constrained. REITs saw significant repricing as rates rose.
• Hedge funds — multi-strategy and macro funds have outperformed in the higher volatility environment. Global macro in particular has done well navigating rate and FX divergence themes.
• Commodities — gold at multi-year highs; energy infrastructure benefiting from AI power demand and re-industrialisation.
• Crypto / digital assets — Bitcoin has re-emerged as an institutional allocation for some funds. Institutional adoption has grown since spot Bitcoin ETFs were approved in the US. Correlation with risk assets remains high — it has not proven itself as a true safe haven.

A key theme across alternatives: the breakdown of the bond-equity correlation has driven investors toward real assets and alternatives as true portfolio diversifiers.

For a client whose primary objective is reliable income, the portfolio construction logic shifts away from growth and toward predictable cash flows with capital preservation. The current rate environment — where investment grade bonds yield 4–5% — is actually more favourable for income-seeking investors than it was in the 2010–2021 ZIRP era.

A reasonable structure in today's environment:

• 40% investment grade corporate bonds (5–10yr maturity): Core income engine. IG yields are near multi-year highs. Focus on financials, utilities, and defensive industrials — sectors with stable cash flows. Provides predictable semi-annual coupon income.
• 25% government bonds / gilts (UK or US Treasuries): Lower yield but maximum liquidity and capital safety. Short to medium duration to reduce interest rate risk if rates move higher.
• 20% dividend-paying equities: Growth element to preserve real purchasing power over time. Focus on sectors with sustainable dividend cover: healthcare, consumer staples, infrastructure.
• 15% high quality IG bond fund / short-duration credit: Adds diversification within credit, improves liquidity versus individual bond holdings.

Expected income at current rates: roughly £35,000–45,000 per year (3.5–4.5% blended yield), before tax. In a UK context, ISA wrappers and the personal savings allowance should inform the structure for a retail client.

The three financial statements and how they connect:

Income statement — shows revenues, costs, and profit over a period. Starts with revenue, subtracts cost of goods sold to get gross profit, subtracts operating expenses to get EBIT, then interest and tax to get net income. EBITDA is derived from EBIT by adding back D&A. Net income flows into retained earnings on the balance sheet.

Balance sheet — a snapshot at a point in time of assets, liabilities, and equity. Assets = Liabilities + Equity (the fundamental accounting equation). Cash on the balance sheet is the ending cash balance from the cash flow statement. Retained earnings accumulate net income over time minus dividends paid.

Cash flow statement — shows actual cash generated and used over the period, split into three sections: operating cash flow (cash from core business), investing cash flow (capex, acquisitions), and financing cash flow (debt issuances, repayments, dividends). The cash flow statement reconciles between the beginning and ending cash balance on the balance sheet.

The linkage: net income from the income statement feeds into both retained earnings (balance sheet) and is the starting point for operating cash flow (CFS). Depreciation is added back in the CFS because it is a non-cash charge on the income statement. Capex flows through the CFS investing section and builds into PP&E on the balance sheet.