Financial conditions: what’s priced in? − speech by Catherine L. Mann

Introduction

The conflict in the Middle East has generated significant volatility and financial market repricing in the UK, relating to uncertainty around the evolution of the conflict, the outlook for UK inflation, and our monetary policy response. Financial conditions are an essential mechanism through which monetary policy transmits and therefore form an important input into my monetary policy decisions. In this speech, I will evaluate the information that financial conditions provide about the current monetary policy stance and transmission, and carefully examine what they reveal about the types of risks driving recent moves.

Financial conditions

Let me start with a headline indicator of financial conditions, which summarizes how a broad range of asset price movements contribute to changes in nominal and real financial conditions. The effect of policy tightening since 2022 on nominal financial conditions in the UK is clearly visible, as the pink line in Chart 1 shows. Despite a modest loosening over 2025, this measure of nominal financial conditions resumed a slight tightening since the escalation of the conflict in the Middle East on account of higher short and long-term nominal interest rates.

Chart 1: Changes in UK financial conditions since 2020

Index points

• Source: Burr (2023) using Bloomberg Finance L.P., Tradeweb and LSEG.
• Notes: The real financial conditions index uses real interest rate variables, exchange rate and equity prices – that is, net of inflation compensation. Latest observation: August 2026.

Nominal financial conditions incorporate inflation expectations and inflation risk premia, which may distort the signal about real tightness, particularly following an inflationary shock. The real financial conditions index in Chart 1 (white line) strips out the effects of rising inflation compensation following the start of the conflict in the Middle East at the end of February. This index suggests that real financial conditions loosened around the beginning of the conflict (consistent with inflation compensation measures rising significantly in March), some of which have since retraced, albeit with a notable compression in spreads.

Given that inflation has been well-above target for five years already and the conflict in the Middle East has contributed to further upside risks to inflation, real and nominal financial conditions need to remain tight. There are two mechanisms through which I can tighten real financial conditions: reducing measures of inflation compensation, and/or, raising nominal yields (and expectations), both of which can be achieved through an increase in Bank Rate. In my view, our current monetary policy stance is not sufficiently tight, which is why I voted in the last two meetings for a 25 basis point increase in Bank Rate.

As financial conditions indices summarize a range of underlying market dynamics, I will unpack some of their key drivers and explore what they reveal about what is priced in. This assessment concludes that the MPC cannot simply rely on policy restrictiveness coming from an upward shift in the nominal yield curve. At some point, we need to follow-through with Bank Rate rises – to maintain credibility, and to avoid policy expectations repricing downwards and inflation expectations repricing further upwards.

What does the gap between markets and participants imply?

Overall nominal financial conditions have remained relatively tight, but what are financial market expectations for the future path of monetary policy? We can gauge market expectations of the policy rate path from a variety of sources. For the UK, these are the yield curve, such as the overnight index swap (OIS) curve, and the Bank of England Market Participants Survey (MaPS).^{footnote [1]}

Chart 2 plots the OIS curve across the UK, US and euro area (EA), and survey-based policy rate expectations from the respective central banks’ latest surveys of market participants. The survey-based measures should offer a cleaner read on policy rate expectations than the OIS curve, because they do not include risk premia or other market-based technical factors. As the differences between the light and dark solid lines in Chart 2 show, there are gaps between the two measures for all three jurisdictions, but the difference is largest for the UK.

If the OIS curve only reflected expectations for policy rate changes, it would imply almost 75 basis points of tightening in Bank Rate over the next 12 months, in contrast to a prolonged hold (and subsequent cuts) implied by the MaPS. I have plotted the OIS curve at the respective dates of survey closure. Since then, the gap has widened further, implying over 100 basis points of tightening in Bank Rate over the coming 12 months. The swathes indicate the interquartile ranges of the survey-based distributions; however, taking that into account does only a little to explain the gap in the UK.

Chart 2: OIS curves and survey-implied expectations for policy rates

Percent

• Sources: Bank of England, Federal Reserve Bank of New York, European Central Bank, Bloomberg Finance L.P. and Bank calculations.
• Notes: UK survey data shows the median response (solid light aqua line) and the 25^th-75^th percentile of responses (shaded aqua area) to the September 2026 Market Participants Survey. US survey data shows the median response (solid light purple line) and the 25^th-75^th percentile of responses (shaded purple area) to the July 2026 Survey of Market Expectations. Euro area survey data shows the median response (solid light orange line) and the 25^th-75^th percentile of responses to the September 2026 ECB Survey of Monetary Analysts. OIS curves (dark solid lines) on the respective dates of survey closure (4^th September, 20^th July and 26^th August). Survey measures typically ask for policy rate expectations (Bank Rate, Federal Funds Rate/Range and Deposit Rate Facility) for UK, US and EA respectively. These do not exactly match the interest rate underlying the OIS (SONIA, SOFR and €STR).

The UK seems to be an outlier internationally, but is the current gap also large by historical standards? Chart 3 shows how the average difference between the OIS curve and market participants’ median expectations for Bank Rate has evolved over a 3-year horizon (left panel). There has been a material increase in the gap since the beginning of the conflict in the Middle East, to levels last seen following Russia’s invasion of Ukraine. Because the survey-based measure only captures market participants’ expectations for Bank Rate, movements in the gap can be a crude measure of risk premia. The widening observed this year therefore suggests that investors are demanding greater compensation for UK risk.

Chart 3: Average gap between market-based and survey-implied expectations for policy rates over a 3-year horizon

Basis points

• Sources: Bank of England, Federal Reserve Bank of New York, European Central Bank, Bloomberg Finance L.P. and Bank calculations.
• Notes: The height of the bar reflects the average gap between the respective survey’s median ‘most likely’ (modal) profile for the policy rate and the average OIS curve observed across the survey window over a 3-year horizon.

What risks are investors demanding greater compensation for? There is no single model that allows us to decompose this risk premium into its various sources and drivers. In the remainder of this speech, I will go through various hypotheses, using a variety of different models and data, to pinpoint the types of risks relevant to driving this gap.

The role of the term premium

Movements in nominal government bond yields can be decomposed into contributions from changes in expected interest rates and a term premium. The term premium is the additional compensation required by investors (above and beyond their interest rate expectations) to hold interest rate risk. Before discussing what the charts show, it is worth noting that the term premium, and risk premia in general, are unobservable. We rely on a suite of models to estimate them.

Chart 4 shows a model-implied structural decomposition of a 3-year nominal yield into these two categories across the UK, US and Germany. The model decomposition is an average of three term structure models: Malik and Meldrum (2016), Vlieghe (2016) and Andreasen and Meldrum (2015). For the UK, this structural model-based decomposition complements the survey-based evidence from MaPS on policy expectations.^{footnote [2]} In both the UK and Germany, 3-year government bond yields have risen by around 100 basis points over the past year, but the drivers appear to be different.

According to this term structure model, higher term premia account for around 24 basis points of the increase in the UK, compared with just 4 basis points in Germany. This contribution has been increasingly positive in the UK throughout the year. In the US, a positive contribution from the term premium is only visible more recently, accounting for around 25 basis points of the 140 basis points rise in yields.

Chart 4: Decomposition of UK, US and German 3-year nominal yields

Cumulative differences since January 2026

• Source: Bloomberg Finance L.P., Tradeweb, Federal Reserve Bank of New York and Bank calculations.
• Note: The expected rates and term premium contributions may not sum exactly to the observed nominal yield because they are averages of model-implied decompositions and contain residuals that reflect model fitting error. Latest observation: 25^th September 2026.

To compare results across different models I show, in Chart 5, a decomposition from a different model (Lengyel and Walker, 2026) that adapts a standard affine term structure framework to identify near-term risk premia more cleanly. Relative to classic models, which are typically calibrated to fit the yield curve as a whole, this approach uses OIS instead of government bond yields, allows for a richer factor structure, and directly incorporates survey-based expectations for Bank Rate. While term premia make a larger contribution to yields overall across the UK, US and EA, the result that its contribution is largest for the UK is robust.

Chart 5: Decomposition of UK, US and German 3-year OIS yields

Cumulative differences since January 2026

• Source: Bloomberg Finance L.P. and Bank calculations.
• Note: The expected rates and term premium contributions may not sum exactly to the observed nominal yield because they are averages of model-implied decompositions and contain residuals that reflect model fitting error. Latest observation: 25^th September 2026.

In a historical and international context, it is somewhat unusual that the term premium has contributed significantly to the rise in short-term yields. The term premium is often defined as the additional compensation investors demand to hold a longer-term bond relative to a series of shorter-term bonds (Kaminska, Meldrum and Young, 2015). It is therefore common for the term premium to show up at the longer end of the yield curve. That is, the further into the future you go, the more uncertain the future path of interest rates is. So why is the UK term premium such an outlier, and such a significant driver of short-term yields?

Chart 6 plots the model-implied 1-year and 3-year term premium between 2009 and today. Over this period, the 1-year and 3-year term premium have been negative throughout the 2010s and after the Russia-Ukraine shock. A negative term premium is not unusual. Joyce, Kaminska and Lildholdt (2008) discuss various drivers for the UK, including regulatory changes, excess liquidity, and “flight to quality” dynamics away from risky assets in times of uncertainty. This could also be explained by a negative inflation risk premium (Cieslak and Pflueger, 2023).

Chart 6: UK model-implied 1-year and 3-year term premium

Percent

• Source: Lengyel and Walker (2026) using Bloomberg Finance L.P., Tradeweb and Bank calculations.
• Note: Latest observation: 25^th September 2026.

However, term premia rose at the start of the conflict in the Middle East and have recently turned positive. That is also true for the 3-year term premium, which stands out as particularly high in recent history, and was only exceeded during the post-GFC period and when Russia invaded Ukraine. The Middle East energy shock is notable, but not as large as the Russia-Ukraine energy shock.

Staff work finds that the UK term premium, especially at the short end, has become more volatile and responsive to news about economic and financial market developments. In part, this reflects higher sensitivity of (international) investors (Mann, 2026) and a different composition of demand for government debt, including a reduced role of preferred habitat investors such as insurance companies and pension funds, as Beltran and Li (2026) also find for the US.

Lengyel and Walker (2026) argue that risk premia at the short end of the curve reflect the compensation investors require for uncertainty around the policy rate path. It is therefore important for monetary policymakers to understand whether changes in nominal yields reflect changing policy expectations or uncertainty around them – distinguishing between the two has important consequences on how to interpret the moves in financial conditions.^{footnote [3]}

I explore the role of near-term policy uncertainty in the next section.

What is the role of uncertainty?

Chart 7 shows the option-implied distributions of SONIA (the risk-free overnight interest rate for sterling markets, and the rate underlying the overnight index swap) 12 months ahead, and its equivalents for the US (SOFR) and the euro area (€STR) based on the methodology of Clews et al. (2000).^{footnote [4]} While the OIS rate shown in the earlier Chart 2 reflects a summary statistic of the underlying distribution, the full distribution in Chart 7 contains additional information. Prior to the conflict (orange), the distributions for all three jurisdictions are tight – implying little uncertainty, and high conviction, about the future path of policy rates. Since the conflict began, the distributions for all three have shifted to the right and widened. The UK distribution, however, has widened slightly more, implying that perceived risks and uncertainty about the future policy rate have increasingly been priced in by markets, and particularly more so for the UK.

Chart 7: Option-implied distribution of interest rates, 12 months ahead

For SONIA, SOFR and €STR

• Source: ICE, CME and Bank calculations
• Note: The underlying rate for the UK distribution is the 3-month SONIA rate 12 months ahead. Latest observation: 25^th September 2026

Furthermore, the skewness of SONIA has turned sharply positive following the outbreak of the conflict in the Middle East, which implies that upside risks to interest rates are perceived to be materially larger than downside risks. This degree of positive skewness was last observed following the post-Covid supply chain disruptions in 2021 and Russia’s invasion of Ukraine in 2022.

The increase in uncertainty and the positive skewness could simply reflect a repricing of the outlook for the economy – reflecting uncertainty about how the conflict in the Middle East could play out, how the resulting supply shock will affect the UK economy going forward, and how it is passed through to broader pricing dynamics. However, such trade-off inducing shocks (shocks that are inflationary but have contractionary effects on activity) also make it more challenging for monetary policymakers to set policy, and uncertainty about the policy rate path could also be higher.

Financial markets are trying to price in both: uncertainty about the economic outlook and uncertainty about the monetary policy response. There is no “textbook” monetary policy response to supply shocks, and therefore, the market’s understanding of how members of the MPC might respond (that is, our reaction function) could be incomplete or unclear. Given that inflation has remained above target for five years and is expected to increase further as the energy shock propagates, the market might be pricing in a reaction function that is not consistent with bringing inflation back to the 2% target sustainably in the medium-term.

Is there a monetary policy uncertainty premium?

Could uncertainty about the monetary policy response to the conflict in the Middle East have also contributed to the gap between the OIS curve and market participants’ expectations for Bank Rate? Research about the effects of monetary policy has generally focused on the effect of changes in the level of Bank Rate on the UK economy (see for instance Brandt et al., 2026; Braun et al., 2025; Di Pace et al., 2025). Uncertainty about future interest rates and its effects on financial markets and the real economy has received less attention.

Based on a methodology developed by Bauer et al. (2022), Raviraj (forthcoming) constructs a financial market-based measure of UK monetary policy uncertainty^{footnote [5]} surprises that uses changes in the standard deviation of the option-implied distribution of SONIA around MPC announcement dates. Using the surprise series as an instrument for a monetary policy uncertainty shock in a structural VAR allows the author to causally identify the effects of monetary policy uncertainty on a set of outcome variables.

Let me start by showing what this monetary policy uncertainty variable looks like and how it relates to MPC announcements. On average across the sample period (1997 to 2026), a monetary policy announcement leads to a resolution of uncertainty about short-term interest rates, as the decrease in the aqua line following the day of an MPC announcement in the left panel of Chart 8 shows. Monetary policy and communications around MPC decisions have acted as a stabilizing force in the economy, resolving uncertainty around the future path of interest rates.

Chart 8: Changes in monetary policy uncertainty around MPC announcementdates

Percent (LHS) and factor score (RHS)

• Source: Raviraj (forthcoming).
• Note: The solid aqua line in the left chart shows the average change in short-rate uncertainty on trading days around MPC announcements from June 1997 until July 2026. The pink line shows the change in short-rate uncertainty around the March 2026 MPC announcement. The shaded area represents the 95% confidence interval. In the right chart, monetary policy uncertainty factors are constructed by applying Varimax rotation to principal components of changes in short-rate uncertainty and first moment interest rates around MPC announcements.

However, there is one notable meeting where our decision and communications do not seem to have played that role. In the left panel of Chart 8, I also plot (in pink) changes in uncertainty around the March 2026 decision – the first monetary policy meeting after the escalation of the conflict in the Middle East. One may argue that this simply reflects elevated levels of uncertainty following the outbreak of the conflict in the Middle East. However, the identification strategy for the monetary policy uncertainty shock isolates changes in uncertainty on MPC announcement days – these changes should therefore largely reflect news associated with the monetary policy decision and associated communications. It strips out any first moment, level effects of monetary policy and captures shocks associated with MPC announcements beyond what markets had already priced in. I plot the estimated monetary policy uncertainty factor in the right panel of Chart 8, which shows that monetary policy uncertainty increased significantly following the March decision, which cannot simply be attributed to uncertainty around the economic outlook resulting from the conflict.^{footnote [6]}

What are the implications of an increase in monetary policy uncertainty? Using the monetary policy uncertainty shock series, we can evaluate the impact of such a shock on financial market variables. The left panel of Chart 9 shows the impulse response function of short rate uncertainty^{footnote [7]} to a one standard deviation increase in monetary policy uncertainty. An increase in monetary policy uncertainty also leads to a rise in the 1-year OIS rate, driven by both a higher term premium and higher interest rate expectations. An increase in monetary policy uncertainty tightens financial conditions.

Chart 9: Impulse response functions of short rate uncertainty, term premium and expected interest rates to a monetary policy uncertainty shock

Percentage points

• Source: Raviraj (forthcoming).
• Note: Impulse response functions to a one standard deviation structural monetary policy uncertainty shock, proxied by the monetary policy uncertainty factor presented in the right panel of Chart 8. Shaded areas represent 68% and 90% confidence intervals.

Yet, why did such a clear signal, a unanimous decision to hold Bank Rate, result in higher uncertainty? It could be because our communication about the outlook for the economy, beyond what was already priced in by markets, was too focused on the uncertainty resulting from the conflict in the Middle East, rather than the underlying dynamics of the economy. Or our reaction function to the shock – the balance between looking through the shock and responding to signs of propagation – was not clearly articulated.

What does this mean for the role of monetary policy uncertainty in driving current risk premia? The committee’s vote splits in the past have revealed differences in views about both the economic outlook and the appropriate monetary policy response. The unanimous vote at the March meeting deviated from these previously communicated reaction functions in light of the conflict in the Middle East. Central bank communication – including our Monetary Policy Report, Monetary Policy Summary and minutes, press conferences, and speeches – is an important tool to explain past monetary policy decisions and to manage expectations about the economy and potential Bank Rate paths. Communication should provide clarity about our reaction function and reduce uncertainty around the future interest rate path (Blinder et al., 2008; Gebauer et al., 2024), even without having to provide explicit forward guidance.

Our communications in March highlighted larger uncertainties. Perhaps they were not clear on how the MPC’s reaction function would evolve with new information – it appeared we were in “wait mode”, which discounted our assurance to the markets that we would “act as necessary” to reach the inflation target. And, as discussed by my colleague Alan Taylor (Taylor, 2026), not publishing a baseline forecast in April most likely did not help either.

The March announcement and the uncertainty it reflected did trigger a strong upward shift in the OIS curve, contributing to the gap between OIS and MaPS. My concern is that this gap has continued to increase, and that one spike in monetary policy uncertainty may have had lasting effects, particularly in an environment with a higher sensitivity of term premia to shocks.

What about risk premia in other assets?

Risk premia and term premia are not synonymous. Term premia specifically refer to the additional compensation required for interest rate risk on risk-free bonds. Risk premia is a general term referring to the additional compensation required by investors for holding risky over risk-free assets.

One would expect uncertainty about the economic outlook arising from geopolitical and energy shocks to be reflected in risk premia for a range of assets. For example, the equity risk premium is the additional compensation for risk associated with holding stocks. Chart 10 plots model estimates of this risk premium (Kontoghiorghes et al., 2025). While there is a temporary spike following the conflict in the Middle East, equity risk premia do not appear elevated in historical context (other than in the US since 2020), likely driven by a robust demand for equities as an asset class in general, or reflecting lower perceived (relative) risk across asset classes.

Chart 10: Equity risk premium

Percent

• Source: Kontoghiorghes et al. (2025).
• Note: The measure used follows the lower-bound ERP estimate of Chabi-Yo and Loudis (2020) over a one-year time horizon, and uses options on the FTSE 100, S&P 500, and EUROSTOXX 50 for the UK, US, and euro area, respectively. Latest observation: 16^th September 2026.

But there is another source of risk premia that is of particular concern for an inflation-targeting central bank – the inflation risk premium. Chart 11 (left-hand panel) shows cumulative changes in the 3-year inflation swap since February, decomposed into contributions from changes in inflation expectations and inflation risk premia. It shows that the inflation risk premium has contributed significantly to the rise in the 3-year inflation swap this year. Rising CPI inflation expectations have also played a considerable role. This reduced slightly in June and July, when the Memorandum of Understanding between the US and Iran was in place, but subsequently rose again following re-escalation of the conflict.

Chart 11: Decomposition of UK 3-year inflation swap rate (LHS) and 3-yearnominal yield (RHS)

Cumulative differences

• Source: Kaminska et al. (2018) for LHS, and Bloomberg Finance L.P., Tradeweb and Bank calculations for RHS.
• Note: The left panel is estimated using a model proposed in Kaminska et al. (2018). Latest observation: September 2026 (LHS) and 25^th September 2026 (RHS).

The right-hand side panel shows that the contribution to the rise in 3-year nominal yields has been almost entirely accounted for by a rise in inflation compensation, which is a combination of inflation expectations and the inflation risk premium. This brings me back to my very first chart where I showed that while nominal financial conditions have tightened following the escalation of the conflict in the Middle East, real financial conditions remained looser.

Monetary policy strategy

What does all this mean for my monetary policy strategy?

The supply shock resulting from the conflict hit at a time when the disinflationary process from previous supply shocks was still incomplete, with nominal rigidities limiting the speed of normalization. Inflation has been above target for the last five years and the Bank’s updated short-term inflation forecast from September projects inflation to increase to over 4% in Q1 2027. This raises inflation above the attentiveness threshold of households and firms ahead of wage negotiations next spring.

Given rising upside risks to inflation, a risk management strategy to monetary policy is appropriate. When there is uncertainty about inflation dynamics and second-round effects, raising Bank Rate to commit to the inflation target can help ensure a sustainable return of inflation to the 2% target, with smaller losses to economic activity.

With the ‘sporadic continuance’ of the conflict in the Middle East, uncertainty around the outlook for the economy and inflation risks have remained elevated. Uncertainty about the MPC reaction function should not compound the problem. Ensuring that this communication is clear and that the reaction function is well understood is the purpose of collective communications. When a policy decision deviates from the collective, speeches such as this can provide additional clarity on the outlook, risks, and decisions.

Against this backdrop, as a monetary policymaker, I cannot take comfort from tighter nominal financial conditions when much of that tightening reflects a higher inflation risk premium and, possibly, a monetary policy uncertainty premium that our own decisions and communications may have contributed to. These premia raise nominal yields without necessarily tightening the real financial conditions that matter for demand and inflation. In my view, real financial conditions are insufficiently tight. The appropriate response therefore is not to rely on risk premia to do the work of policy, but to reduce inflation risk and policy uncertainty through a clearly communicated reaction function and a sufficiently restrictive path for Bank Rate.

The views expressed in this speech are not necessarily those of the Bank of England or the Monetary Policy Committee.

Acknowledgments

I would like to thank Natalie Burr and Christoph Herler for their help in the preparation of this speech.

I would also like to thank Harry Austin, Sofia Carollo, Alan Castle, Rohan Churm, Céline Gondat-Larralde, Iryna Kaminska, Alex Kontoghiorghes, Andras Lengyel, Clare Lombardelli, Rebecca Maule, Nades Raviraj, Tuli Saha, Martin Seneca and Bradley Speigner for their comments and help with data and analysis.

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