Month: December 2025

Interest Rates and M&A: How Market Dynamics Shift When Rates Rise or Fall

by
Emanuele BAROLI

In this article, Emanuele BAROLI (MiF 2025–2027, ESSEC Business School) examines how shifts in interest rates shape the M&A market, outlining how deal structures differ when central banks raise versus cut rates.

Context and objective

The purpose is to explain what interest rates are, how they interact with inflation and liquidity, and how these variables shape merger and acquisition (M&A) activity. The intended outcome is an operational lens you can use to read the current monetary cycle and translate it into cost of capital, valuation, financing structure, and execution windows for deals, distinguishing—when useful—between corporate acquirers and private-equity sponsors.

What are interest rates

Interest rates are the intertemporal price of funds. In economic terms they remunerate the deferral of consumption, insure against expected inflation, and compensate for risk. For real decisions the relevant object is the real rate because it governs the trade-off between investing or consuming today versus tomorrow.

Central banks anchor the very short end through the policy rate and the management of system liquidity (reserve remuneration, market operations, balance-sheet policies). Markets then map those signals into the entire yield curve via expectations about future policy settings and required term premia. When liquidity is ample and cheap, risk-free yields and credit spreads tend to compress; when liquidity becomes scarcer or dearer, yields and spreads widen even without a headline change in the policy rate. This transmission, with its usual lags, is the bridge from monetary conditions to firms’ investment choices.

M&A industry — a definition

The M&A industry comprises mergers and acquisitions undertaken by strategic (corporate) acquirers and by financial sponsors. Activity is the joint outcome of several blocks: the cost and elasticity of capital (both debt and equity), expectations about sectoral cash flows, absolute and relative valuations for public and private assets, regulatory and antitrust constraints, and the degree of managerial confidence. Interest rates sit at the center because they enter the denominator of valuation models—through the discount rate—and they shape bankability constraints through the debt service burden. In other words, rates influence both the price a buyer can rationally pay and the feasibility of financing that price.

Use of leverage

Leverage translates a given cash-flow profile into equity returns. In leveraged acquisitions—especially LBOs—the all-in cost of debt is set by a market benchmark (in practice, Term SOFR at three or six months in the U.S., and Euribor in the euro area) plus a spread reflecting credit risk, liquidity, seniority, and the supply–demand balance across channels such as term loans, high-yield bonds, and private credit. That all-in cost determines sustainable leverage, shapes covenant design, and fixes the headroom on metrics like interest coverage and net leverage. It ultimately caps the bid a sponsor can submit while still meeting target returns. Corporate acquirers usually employ more modest leverage, yet remain rate-sensitive because medium-to-long risk-free yields and investment-grade spreads feed both fixed-rate borrowing costs and the WACC used in DCF and accretion tests, and they influence the value of stock consideration in mixed or stock-for-stock deals.

How interest rates impact the M&A industry

The connection from rates to M&A operates through three main channels. The first is valuation: holding cash flows constant, a higher risk-free rate or higher term premia lifts discount rates, lowers present values, and compresses multiples, thereby narrowing the economic room to pay a control premium. The second is bankability: higher benchmarks and wider spreads raise coupons and interest expense, reduce sustainable leverage, and shrink the set of financeable deals—most visibly for sponsors whose equity returns depend on the spread between debt cost and EBITDA growth. The third is market access: heightened rate volatility and tighter liquidity reduce underwriting depth and risk appetite in loans and bonds, delaying signings or closings; the mirror image under easing—lower rates, stable curves, and tighter spreads—reopens windows, enabling new-money term funding and refinancing of maturities. The net effect is a function of level, slope, and volatility of the curve: lower and calmer curves with steady spreads tend to support volumes; high or unstable curves, even with unchanged spreads, enforce selectivity.

Evidence from 2021–2024 and what the chart shows

M&A deals and interest rates (2021-2024).
M&A deals and interest rates (2021-2024)
Source: Fed.

The global pattern over 2021–2024 is consistent with this mechanism. In 2021, deal counts reached a cyclical peak in an environment of near-zero short-term rates, abundant liquidity, and elevated equity valuations; frictions on the cost of capital were minimal and access to debt markets was easy, so the economic threshold for completing transactions was lower. Between 2022 and 2024, monetary tightening lifted short-term benchmarks rapidly while spreads and uncertainty rose; global deal counts fell materially and the market became more selective, favoring higher-quality assets, resilient sectors, and transactions with stronger industrial logic. Over this period, global deal counts were 58,308 in 2021, 50,763 in 2022, 39,603 in 2023, and 36,067 in 2024, while U.S. short-term rates moved from roughly 0.14% to above 5%; the chart shows an inverse co-movement between the cost of money and activity. Correlation is not causation—antitrust enforcement, energy shocks, equity multiple swings, and the rise of private credit also mattered—but the macro signal aligns with monetary transmission.

What does academic research say

Academic research broadly confirms the mechanism sketched above: when policy rates rise and financing conditions tighten, both the volume and composition of M&A activity change. Using U.S. data, Adra, Barbopoulos, and Saunders (2020) show that increases in the federal funds rate raise expected financing costs, are followed by more negative acquirer announcement returns, and significantly increase the probability that deals are withdrawn, especially when monetary policy uncertainty is high. Fischer and Horn (2023) and Horn (2021) exploit high-frequency monetary-policy shocks and find that a contractionary shock leads to a persistent fall in aggregate deal numbers and values—on the order of 20–30%—with the effect concentrated among financially constrained bidders; at the same time, the average quality of completed deals improves because weaker acquirers are screened out. Work on leveraged buyouts links this to credit conditions: Axelson et al. (2013) document that cheap and abundant credit is associated with higher leverage and higher buyout prices relative to comparable public firms, while theoretical models such as Nicodano (2023) show how optimal LBO leverage and default risk respond systematically to the level of risk-free rates and credit spreads.

Related posts on the SimTrade blog

   ▶ Bijal GANDHI Interest Rates

   ▶ Nithisha CHALLA Relation between gold price and interest rate

   ▶ Roberto RESTELLI My internship at Valori Asset Management

Useful resources

Academic articles

Adra, S., Barbopoulos, L., & Saunders, A. (2020). The impact of monetary policy on M&A outcomes. Journal of Corporate Finance, 62, 1-61.

Fischer, J. and Horn, C.-W. (2023), Monetary Policy and Mergers and Acquisitions, Working paper Available at SSRN

Horn, C.-W. (2021) Does Monetary Policy Affect Mergers and Acquisitions? Working paper.

Axelson, U., Jenkinson, T., Strömberg, P., & Weisbach, M. S. (2013) Borrow Cheap, Buy High? The Determinants of Leverage and Pricing in Buyouts, The Journal of Finance, 68(6), 2223-2267.

Financial data

Federal Reserve Bank of New York Effective Federal Funds Rate (EFFR): methodology and data

Federal Reserve Bank of St. Louis Effective Federal Funds Rate (FEDFUNDS)

OECD Data Long-term interest rates

About the author

The article was written in November 2025 by Emanuele BAROLI (ESSEC Business School, Master in Finance (MiF), 2025–2027).

   ▶ Read all articles by Emanuele BAROLI.

Drafting an Effective Sell-Side Information Memorandum: Insights from a Sell-Side Investment Banking Experience

by
Emanuele BAROLI

In this article, Emanuele BAROLI (ESSEC Business School, Master in Finance (MiF), 2025–2027) explains how to draft an M&A Information Memorandum, translating sell-side investment-banking practice into a clear, evidence-based guide that buyers can use to progress from interest to a defensible bid.

What is an Info Memo

An information memorandum is a confidential, evidence-based sales document used in M&A processes to enable credible offers while safeguarding the sell-side process. It sets out what is being sold, why it is attractive, and how the deal is framed, and it is structured—consistently and without redundancy—around the following chapters: Executive Summary, Key Investment Highlights, Market Overview, Business Overview, Historical Financial Performance and Current-Year Budget, Business Plan, and Appendix. Each section builds on the previous one so that every claim in the narrative is traceable to data, definitions, and documents referenced in the appendix and the data room.

Executive summary

The executive summary is the gateway to the memorandum and must allow a prospective acquirer to grasp, within a few pages, what is being sold, why the asset is attractive, and how the transaction is framed. It should state the perimeter of the deal, the nature of the stake or assets included, and the essence of the equity story in language that is direct, verifiable, and consistent with the evidence presented later. The narrative should situate the company in its market, outline the recent trajectory of scale, profitability, and cash generation, and articulate—in plain terms—the reasons an informed buyer might assign strategic or financial value. Nothing here should rely on empty superlatives; every claim in the summary must be traceable to supporting material in subsequent sections and to documents made available in the data room. Clarity and internal consistency matter more than flourish: the reader should finish this section knowing what the asset is, why it matters, and what next steps the process anticipates.

Key investment highlights

This section filters the equity story into a small number of decisive arguments, each of which combines a clear assertion, hard evidence, and an explicit investor implication. The prose should explain, not advertise sustainable growth drivers, defensible competitive positioning, quality and predictability of revenue, conversion of earnings into cash, discipline in capital allocation, credible management execution, and identifiable avenues for organic expansion or bolt-on M&A. Each highlight should read as a self-contained reasoning chain—statement, proof, consequence—so that a buyer can connect operational facts to valuation logic.

Market overview

The market overview demonstrates that the asset operates within an addressable space that is sizeable, healthy, and legible. Begin by defining the market perimeter with precision so that later revenue segmentations align with it. Describe the current size and structure of demand, the expected growth over a three-to-five-year horizon, and the drivers that sustain or threaten that growth—technological shifts, regulatory trends, customer procurement cycles, and macro sensitivities. Map the competitive landscape in terms of concentration, barriers to entry, switching costs, and price dynamics across channels. Distinguish between the immediate market in which the company competes and the broader industry environment at national or international level, explaining how each influences pricing power, customer acquisition, and margin stability. All figures and characterizations should be sourced to independent references, allowing the reader to verify both methodology and magnitude.

Business overview

The business overview explains plainly how the company creates value. It should describe what is sold, to whom, and through which operating model, covering products and services, relevant intellectual property or certifications, customer segments and geographies served, and the logic of revenue generation and pricing. The text should make the differentiation intelligible—quality, reliability, speed, functionality, service levels, or total cost of ownership—and then connect that differentiation to commercial traction. Operations deserve a concise, concrete treatment: footprint, capacity and utilization, supply-chain architecture, service levels, and, where material, the technology stack and data security posture. The section should close with the people who actually run the company and are expected to remain post-closing, outlining roles, governance, and incentive alignment. The aim is not to impress with jargon but to let an investor see a coherent engine that turns inputs into outcomes.

Historical financial performance and budget

This chapter turns performance into an intelligible narrative. Present the historical income statement, balance sheet, and cash flow over a three-to-five-year window—preferably audited—and reconcile management accounts with statutory figures so that definitions, policies, and adjustments are transparent. Replace tables-for-tables’ sake with analysis: show where growth and margins come from by decomposing revenue into volume, price, and mix; explain EBITDA dynamics through efficiency, pricing, and non-recurring items; separate maintenance from growth capex; and trace how earnings convert into cash by discussing working-capital movements and seasonality. In a live process, the current-year budget should set out the explicit operating assumptions behind it, the key milestones and risks, and a brief intra-year read so a buyer can compare budget to year-to-date performance. If carve-outs, acquisitions, or other discontinuities exist, present clean pro forma views so the time series remains comparable.

Business plan

The business plan translates the equity story into forward-looking numbers and commitments that can withstand diligence. Build the plan from drivers rather than percentages: revenue as a function of volumes, pricing, mix, and retention; costs split between fixed and variable components with operational leverage and efficiency initiatives laid out; capital needs expressed through capex, working-capital discipline, and any anticipated financing structure. Provide a three-to-five-year view of P&L, cash flow, and balance-sheet implications, making explicit the capacity constraints, hiring requirements, and lead times that link initiatives to outcomes. A sound plan includes a base case and either sensitivities or alternative scenarios, together with risk mitigations that are actually within management control. If bolt-on M&A features in the strategy, describe the screening criteria, integration capability, and the nature of the synergies in a way that distinguishes aspiration from execution.

Appendix

The appendix holds detail without overloading the core narrative and preserves auditability. It should contain the full legal disclaimer and confidentiality terms, a glossary of definitions and KPIs to eliminate ambiguity, detailed financial schedules and reconciliation notes, methodological summaries and citations for market data, concise contractual information for key customers and suppliers where material, operational and ESG indicators that genuinely affect value, and a process note with timeline, bid instructions, Q&A protocols, and site-visit guidance. The organizing principle is traceability: any figure or claim in the memorandum should be traceable to a line item or document referenced here and made available in the data room.

Why should you be interested in this post?

For students interested in corporate finance and M&A, this post shows how to translate sell-side practice into a rigorous structure that investors can actually diligence—an essential skill for internships and analyst roles.

Related posts on the SimTrade blog

   ▶ Roberto RESTELLI BCapital Fund at Bocconi: building a student-run investment fund

   ▶ Louis DETALLE A quick presentation of the M&A field…

   ▶ Ian DI MUZIO My Internship Experience at ISTA Italia as an In-House M&A Intern

Useful resources

Corporate Finance Institute – (CFI) Confidential Information Memorandum (CIM)

DealRoom How to Write an M&A Information Memorandum

About the author

The article was written in December 2025 by Emanuele BAROLI (ESSEC Business School, Master in Finance (MiF), 2025–2027).

   ▶ Read all articles by Emanuele BAROLI.

“It’s not whether you’re right or wrong that’s important, but how much money you make when you’re right and how much you lose when you’re wrong.” – George Soros

by

Hadrien Puche

In financial markets, everyone wants to be right. The temptation to make accurate predictions, about earnings, interest rates, recessions, or stock prices, is universal. But as George Soros reminds us, accuracy alone is meaningless. What truly matters is how much you profit when you’re right, and how much you lose when you’re wrong.

This quote challenges one of the deepest misconceptions in trading: the belief that success depends on predicting the future. In reality, trading success mostly depends on risk management, position sizing, and the discipline to adjust when the market proves you wrong.

About George Soros

George Soros
Warren Buffett

Source: EU

George Soros (born in 1930) is a Hungarian-American investor and philanthropist. He founded Soros Fund Management, a global macro hedge fund known for making large, directional bets across currencies, bonds, equities, and commodities.

Soros became globally famous in 1992 when he “broke the Bank of England” by shorting the British pound, a trade widely reported to have earned over $1 billion.

The European Exchange Rate Mechanism (ERM) was created to stabilize European currencies ahead of the future monetary union by keeping exchange rates within narrow fluctuation bands. When the UK joined, it agreed to maintain the pound within this band, but entered at a rate that many considered overvalued.

Seeing this imbalance, George Soros spent months building a large short position against the pound. On “Black Wednesday” in 1992, the British government failed to defend the currency through interest-rate hikes and interventions, forcing a devaluation. Soros reportedly earned over $1 billion and became known as “the man who broke the Bank of England.”

Not all of Soros’s trades were successful. In 2016, he reportedly lost close to $1 billion after wrongly predicting that markets would fall following Donald Trump’s election.

Beyond trading, Soros developed the theory of reflexivity, which argues that markets are shaped by feedback loops between perceptions and fundamentals. His philosophy emphasizes uncertainty, adaptability, and the psychological drivers behind market behavior.

The context behind this Quote

This quote is not actually from Soros. It comes from Stanley Druckenmiller—Soros’s former chief strategist—in The New Market Wizards (1994). Druckenmiller explains that the most important lesson he learned from Soros was not the importance of being right, but of structuring trades so that being right pays off and being wrong costs little.

Book cover of the new market wizards

The quote therefore reflects Soros’s investment philosophy: markets cannot be predicted with certainty, so success depends more on managing risk than on forecasting.

This mindset is foundational to modern risk management and a key reason Soros is considered one of the most influential investors of the past century.

Analysis of the Quote

The quote captures three essential ideas:

  • asymmetric returns
  • risk management
  • intelligent position sizing

Being right doesn’t matter unless it pays. For example, even if you forecast Nvidia’s earnings perfectly, you may still fail to profit because:

  1. You may not have any position.
  2. Your position may be too small.
  3. The market may behave irrationally.
  4. Losses on other trades may outweigh this one win.

This is the essence of risk management: structuring positions so that winners meaningfully contribute to performance while losers remain contained.

Let’s introduce three key financial ideas that relate to this quote.

1. Diversification and Position Timing

Even if your analysis is correct, the market might not react as expected, or not at the right time. This is where the distinction between trading and investing matters.

Soros’s quote speaks the language of trading: position sizing, timing, and controlling downside on each bet.

Investing, by contrast, relies less on precise timing and more on diversification, which reduces exposure to unpredictable events and smooths returns across different regimes.

Mathematically, diversification lowers portfolio variance because asset returns are imperfectly correlated. Even when individual positions behave unpredictably, a well-constructed portfolio can achieve far better risk-adjusted results than any single trade. In that sense, diversification plays a similar role for investors as stop-losses and disciplined position sizing do for traders: it manages the impact of being wrong.

The following graph illustrates how adding more independent positions reduces overall portfolio risk.

A graph representing the overall risk of a portfolio as a function of the number of positions

2. Avoid cutting winners to reinforce losers

This behavioral trap affects most investors. Soros’s approach is the opposite:

  • cut losing positions quickly
  • let winners run

Yet, due to loss aversion (as formalized by Kahneman & Tversky (1979) in Prospect Theory), investors often do the reverse:

  • sell winners too early
  • hold losers too long

This pattern is well-documented in the literature. Shefrin & Statman (1985) termed it the disposition effect: the systematic tendency to “sell winners too early and ride losers too long.” The emotional discomfort of realizing a loss often outweighs the rational need to exit a bad position.

Momentum works partly for this reason. Rising prices attract reluctant investors who delayed selling their winners, amplifying trends; meanwhile, stubbornly held losers can drift downward for longer than fundamentals alone would justify.

3. Quantitative trading: the power of averaging out

Quantitative trading is built on making many small, systematic bets with a positive expected value. The goal is not to win every trade, but to win more (or bigger) on average.

This is the practical application of the idea that:

  • being right occasionally with large wins
    is more valuable than
  • being right frequently with small gains.

This also echoes Jesse Livermore’s famous line: “The market is never wrong, only opinions are.” (link)

My view on this quote

One limitation of Soros’s statement is that it implicitly assumes the reader is an active trader. In reality, today’s markets are dominated by algorithms, quantitative models, and high-frequency strategies, an environment in which most individuals are unlikely to outperform professional traders. For traders, Soros’s point is straightforward: you will often be wrong, so what matters is how you size positions and manage risk when you are.

At a literal level, the quote may also seem paradoxical: you cannot know in advance which trades will be winners or losers. But the message isn’t about prediction, it’s about discipline.

This distinction becomes especially clear when you contrast trading with investing.

  • Traders live in a world of short-term uncertainty and constant position adjustments, where the asymmetry between gains and losses determines survival.
  • Investors, on the other hand, think in years, not minutes. They rely less on timing and more on letting fundamentals and compounding work over time. For them, the “how much you lose when you’re wrong” part translates into diversification, staying invested, and avoiding irreversible mistakes rather than optimizing each individual decision.

Seen this way, Soros’s line applies to both groups, just at different scales: traders manage outcomes trade by trade; investors manage them across decades. Either way, the principle holds: success depends less on being right and more on controlling the cost of being wrong.

Why should you care about this quote ?

The lesson is not about predicting markets or mastering sophisticated position sizing. The deeper message is:

  • Don’t rely on being right.
  • Structure your trades so that mistakes are limited and successes compound.

A diversified ETF strategy naturally achieves this.
In cap-weighted indices:

  • winners grow in weight
  • losers shrink, limiting their impact
  • the portfolio trends with long-term market growth

This simple, robust approach aligns with Soros’s philosophy: control the downside, let the upside work.

Related Posts

Useful Resources

  • Soros, George (1987). The Alchemy of Finance. Soros explains reflexivity, asymmetry of payoff, and his macro-trading framework.
  • Schwager, Jack (1994). The New Market Wizards. Contains Stanley Druckenmiller’s interview where the famous quote originates.
  • The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence — Hersh Shefrin & Meir Statman (Journal of Finance, 1985, 40(3), 777–790).
  • Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263–291.

To learn more about Soros’s famous 1992 British pound trade:

  • Eichengreen, Barry & Wyplosz, Charles (1993). “The Unstable EMS.” A leading academic analysis of why the European Exchange Rate Mechanism (ERM) became vulnerable and how the 1992 crisis unfolded.
  • Bank of England (1993). Report on the Withdrawal of Sterling from the ERM. Official institutional account of the events surrounding Black Wednesday.

About the Author

This article was written in December 2025 by Hadrien Puche (ESSEC, Grande École Program, Master in Management – 2023–2027).