Market Research In Finance

As someone who grew up in the leveraged finance markets, I can say with confidence that today's high yield market is not the one we all once knew. My team and I have spent considerable time analyzing the evolution of global credit markets and what it means for asset allocation, portfolio construction, and risk management. And with all the twists and turns of the past decade, one of the quietest transformations has been hiding in plain sight: high yield. That is why I wanted to share my recent Financial Times op-ed on why we believe the high yield market is positioned for its second act. ➤ The asset class has fundamentally changed. With a record 57% of US high yield and 68% of European high yield rated BB, lower software exposure relative to loans and direct lending, shorter duration than at almost any point in the past 15 years, and first lien secured bonds at an all-time high of 33% of the US market, this is not your grandfather's junk bond market. ➤ And the technical backdrop is shifting in its favor. As CLO appetite has grown more selective and direct lending terms have tightened, more issuers are rediscovering what high yield has always offered: a deep, diversified, and durable investor base that prices risk when others step back. It did it through the GFC. It did it through COVID and it is doing it again now. ➤ For investors, despite tight spreads, the all-in yield remains compelling in absolute terms and increasingly attractive on a risk-adjusted basis relative to alternatives carrying more risk for only modestly more yield. The junk bond label was earned forty years ago and the market has spent the last decade writing its new chapter. I hope you will give the op-ed a read, and for a more global deep-dive on how KKR is thinking about the opportunity set, my colleagues Jeremiah Lane, Eddie O'Neill, and I recently published “High Yield’s Second: What AI Revealed about Credit Quality" 📎Read it here: https://go.kkr.com/4w7bXWK

Bond yields moved higher in the first two months of the year as the market repriced #Fed expectations. But what’s the outlook for interest rates and fixed income investments as we kick off March?   While we anticipate another healthy employment number this Friday, we still expect 75bps of cuts in 2024, starting midyear. Our near-term range on the 10-year US Treasury #yield is 4% to 4.5%, before moving toward 3.5% by year-end.   While a temporary move toward the top of that range is possible, we believe this would likely require a shock in the form of materially higher #growth or inflation, and we would be strong buyers around the 4.5% level.   In terms of positioning, CMBS continues to outperform, particularly the lower-rated BBB segment. We remain most preferred in the higher-quality CMBS sector. While spreads tightened over the past six weeks, CMBS remains cheap relative to their corporate credit counterpart.   With inflation expectations rising, TIPS have outperformed their Treasury counterparts, and we remain with a preferred allocation in 5-year TIPS given we still think inflation will remain above the Fed’s 2% target this year. Read more in the full report below from Leslie Falconio and John Murtagh.

Considerations for the High Yield Bond Market: The BB-rated High Yield (HY) bond market has shown strong performance, with favorable news recently related to growth and inflation.  Fundamentally, the companies represented in the HY Index have a favorable upgrade-to-downgrade ratio. BB-rated bonds constitute 50% of the HY market, distinguishing them from lower-rated B and CCC companies. BB HY bonds typically feature fixed rate, comparatively lower coupons, resulting in lower liability costs and more manageable debt service. In Contrast, the CCC-rated segment shows a concerning trend, with an upgrade-to-downgrade ratio below 0.5 (2x as many downgrades). The credit quality dispersion, shown in the chart below, reveals that BB vs. CCC-rated bonds trade at a spread margin of ~400 to ~1,200 bps, currently sitting inside of 750 bps.  While CCC credits can generate substantial returns during robust economic growth in a low default rate environment, and have rallied with the market in recent days, CCC deterioration is most pronounced during distress and recession. During the first half of 2020, the BB-CCC spread differential reached 1,200 bps, and in 2016, CCC spreads were even wider. It is noteworthy that Europe is straddling recession, and the BB-CCC European HY bond spreads have recently widened to 1,400 bps, surpassing its peak in 2020. So despite, the recent rally in lower-rated HY bonds, caution is warranted for the weakest segment of corporate credit. The HY bonds historical default rate: BB’s 0.4% default rate, B’s 1.4% default, and CCC’s a stunning 14.3% historical default rate! During a recession, default rates tend to increase significantly from historical measures. Composition of HY Index: 50% BB, 39% B, 11% CCC. 1 year ago, the HY Bond Index had 1.2% default rate. Today, the trailing 12M default for the HY bond market is 2.6%. By Q2 2024, I expect the default rate for high yield bonds exceed 4%. Michael Schlembach, Marathon Asset Management’s PM for High Yield, expects default rates to increase in 2024, with peak default rates potentially reaching ~1.0%, ~3.0%, and >20%+ for BB, B, and CCC’s, respectively. The key will be to invest in the debt of companies with solid fundamentals and financial strength to navigate the pending downturn. If you believe as I do that an economic slowdown (potential recession) is likely in 2024, it might be best to focus on higher quality credits with robust operating businesses within the HY market. Ford serves as a prime example in the BB sector, having recently been upgraded to Investment Grade by S&P, marking it as the largest 'rising star'. Ford represents 2% of the HY index with $41 billion of bonds, its upgrade has spurred demand for other quality BB-rated bonds to replace it. While recent inflows have tightened BB spreads, I advise against trading based solely on the technicals, as this post is intended purely for informational purposes. U.S. HY rated BB vs. CCC Differential:

"Is $20/month too much for our product?" Instead of guessing, we used the Van Westendorp method to find our pricing sweet spot. 4 questions revealed exactly what users would pay (and we haven't touched our pricing since). Here's the framework any founder can steal: 1. Send a survey to actual users, not prospects We surveyed people already using Gamma. They understood the real value of our product, not hypothetical value. Too many founders survey their waitlist or randomly select people who have never used their product. That's like asking someone who's never driven about car prices. 2. Ask these 4 specific questions - At what price would this be too expensive for you to consider it? - At what price is it expensive but still delivering value? - At what price does it feel like a bargain? - At what price is it so cheap you'd question if it's reliable? These create bookends for perceived value. You're mapping the entire spectrum of price psychology, not just asking "what would you pay?" 3. Plot the responses and find where the lines intersect Graph responses from lots of users. Where "too expensive" and "too cheap" lines cross: that's your acceptable range. Where "expensive but fair" meets "bargain": this is your optimal price point. 4. Test within the range, don't just pick the middle The intersection gives you a range, not a number. We ran pricing experiments within that range to see actual conversion rates. A survey shows willingness to pay; testing reveals actual behavior. 5. Lean towards generous (especially for product-led growth) We chose to be more generous with AI usage than our "optimal" price suggested. Word-of-mouth growth matters more than maximizing initial revenue. Not everything shows up in the numbers. 6. Lock it in and stop tinkering Once you find the sweet spot through data, stick with it. We haven't changed pricing in 2 years. Every month debating pricing is a month not improving product. Remember: pricing is a signal, not just a number (Image: First Principles)

Stop copying competitor pricing. These 4 questions will tell you exactly what your specific customers will pay. When we first launched Attic salt, we spent n no of weeks trying to figure out a pricing strategy that will work. Attic Salt is democratising the fashion by bringing in value at a sharp price yet we have to maintain fair wages for our artisans and  technicians who bring the garment alive with so much innovation,skill and dedication. Then I found the Van Westendorp Pricing Model, a simple 4 question method helps you understand how customers really see your price. Used by brands like Dropbox, HubSpot, and Mailchimp, the Van Westendorp model was developed by Dutch economist Peter Van Westendorp.    Here's how it works… You ask potential customers four key questions about price: 📍At what price would this product feel too cheap to trust? 📍At what price would it feel like a good deal? 📍At what price would it start to feel expensive but acceptable? 📍At what point would it feel too expensive to buy?     Now plot these answers on a graph. The intersection points reveal your: Indifference Price Point → where people are split between “cheap” and “expensive”Optimal Price Point → where hesitation from both ends is minimal Acceptable Price Range → your sweet spot for maximum traction When we used this model, we realized we were underpricing. Customers thought the product was “too affordable to be good.” We adjusted, and sales went up without changing a single feature. If you’re launching something new or entering an unfamiliar market, don’t guess. Use this model. Gut feelings are great for design. Not for pricing. Are you still trusting yours? #PricingStrategy #ConsumerInsights #D2CBrands #FashionBusiness

Dear Network, In finance, there is 𝘢 𝘱𝘳𝘪𝘰𝘳𝘪 𝐧𝐨 𝐫𝐞𝐚𝐬𝐨𝐧 𝐭𝐨 𝐛𝐞𝐥𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 𝐚 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐢𝐬 𝐢𝐧𝐭𝐫𝐢𝐧𝐬𝐢𝐜𝐚𝐥𝐥𝐲 𝐫𝐚𝐧𝐝𝐨𝐦. A stock, a bond, an option, or a portfolio does not carry randomness as an internal property. 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐫𝐚𝐧𝐝𝐨𝐦 𝐢𝐬 𝐭𝐡𝐞 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐢𝐭: liquidity, rates, volatility regimes, macro variables, credit conditions, order flow, regulation, and systemic feedback. This is precisely the paradigm Pasha Zavari 𝐚𝐧𝐝 𝐈 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧. A classical SDE often writes price variation as the sum of a deterministic drift and an intrinsically random diffusion: dXₜ = μ(t,Xₜ)dt + σ(t,Xₜ)dWₜ. This is powerful, but it suggests that randomness enters the product through infinitesimal noise. Random Differential Equations offer another view: dx(t,ω)/dt = F(t,x(t,ω),ξ(t,ω)). For each realized environment ω, the system is an ordinary differential equation. The randomness comes from the external environment ξ. First realize the world. Then solve the dynamics. This is useful in several financial contexts: 1) 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐝𝐲𝐧𝐚𝐦𝐢𝐜𝐬: Portfolios react to regimes, constraints, signals and liquidity. RDEs model this pathwise reaction more naturally than injecting diffusion directly into the portfolio. 2) 𝐒𝐭𝐨𝐜𝐡𝐚𝐬𝐭𝐢𝐜 𝐯𝐨𝐥𝐚𝐭𝐢𝐥𝐢𝐭𝐲: Volatility is often driven by structured forces: macro news, risk appetite, clustering, microstructure. RDEs allow volatility to be driven by these external signals. 3) 𝐈𝐧𝐭𝐞𝐫𝐞𝐬𝐭-𝐫𝐚𝐭𝐞 𝐦𝐨𝐝𝐞𝐥𝐬: Yield curves react to inflation paths, central-bank policy and liquidity conditions. RDEs are well suited to scenario-based term-structure dynamics. 4) 𝐂𝐫𝐞𝐝𝐢𝐭 𝐚𝐧𝐝 𝐝𝐞𝐟𝐚𝐮𝐥𝐭: Default risk depends on macro deterioration, refinancing constraints, sector contagion and balance-sheet stress. RDEs make those drivers explicit. 5) 𝐒𝐭𝐫𝐞𝐬𝐬 𝐭𝐞𝐬𝐭𝐢𝐧𝐠: A stress scenario is not a Brownian increment. It is a structured path. RDEs naturally separate the scenario from the system’s response. 6) 𝐒𝐲𝐬𝐭𝐞𝐦𝐢𝐜 𝐫𝐢𝐬𝐤: Contagion is about networks, feedback loops and amplification. RDEs allow shocks to propagate through a structured financial system, path by path. The point is not that SDEs are wrong. The point is that they are not the only language for uncertainty. When uncertainty is local and diffusion-like, SDEs are natural. When uncertainty is external, structured, path-dependent or scenario-driven, RDEs may be more interpretable. Not noise inside the product. 𝑫𝒚𝒏𝒂𝒎𝒊𝒄𝒔 𝒊𝒏𝒔𝒊𝒅𝒆 𝒂 𝒓𝒂𝒏𝒅𝒐𝒎 𝒘𝒐𝒓𝒍𝒅. #Mathematics #AppliedMathematics #BanachFixedPointTheorem #FixedPointTheory #QuantitativeFinance #PortfolioTheory #DynamicProgramming #Optimization #FinancialEngineering #RiskManagement #NumericalMethods #DataScience

Two trends have caught my attention and signal a growing trend in the M&A landscape: the rise of equity-funded deals and improving market reaction to M&A.   With valuations at record highs and range-bound interest rates, the cost of equity and debt are converging. Consequently, I’m seeing more boards contemplate equity considerations alongside debt funded cash considerations as a genuine alternative to all cash — enough to push equity-funded deals to 23% of total activity, up from 18% a year ago. It is also notable that this consideration mix is evident in large-scale transactions, with $10bn+ deals making up a larger proportion of M&A volumes this year.   Market and shareholder dynamics are also shifting. In 2022, the median day-one share price move for acquirers in large equity deals was -5.3% relative to the market. This year, it’s closer to -1.5%. For shareholders, ownership is increasingly concentrated among a smaller number of institutional investors, amplifying their influence on deal outcomes. Together, these trends underline: ▪️Day one isn’t destiny. There’s no clear link between the first day’s move and long-term returns – around half of deals see a negative day-one reaction, yet many go on to deliver positive three-year share price performance. ▪️Shareholder makeup is also an important factor. Greater ownership concentration among the largest index investors can amplify share price volatility. Early alignment with key active investors is critical. ▪️Messaging matters. The way a deal is communicated, before and after announcement, can materially shape sentiment, reduce activist risk, and secure shareholder support. This is critical to an effective roll-out strategy. As we head towards Q4, I expect the strongest M&A outcomes will come from a combination of disciplined execution and a compelling strategic narrative.

Interconnected Risks: The Synergy Between Credit and Market Risks In the realm of banking and finance, risk management often involves a multitude of categories, each demanding its specific analytical tools and mitigation strategies. However, an understanding of the interconnected nature of these risks can provide a more comprehensive view, thereby enabling more effective decision-making. Among these, the synergy between credit and market risks stands as a pivotal example. Traditionally, credit risk and market risk have been treated as distinct domains within risk management frameworks. Credit risk focuses on the likelihood of a borrower defaulting on a loan, while market risk examines the potential impact of market variables such as interest rates, currency exchange rates, and equity prices. Although the analytical methods for these risks differ, they are far from mutually exclusive. A volatile market can have a cascading effect on credit risk. For instance, sharp declines in asset values can weaken a borrower's financial position, thereby increasing the probability of default. Similarly, a surge in interest rates could make loan repayments more difficult for borrowers, again amplifying credit risk. Thus, fluctuations in market variables should be incorporated into credit risk assessments to obtain a more accurate and realistic view. Conversely, an increase in credit defaults within an economy can affect market conditions. A spate of loan defaults can reduce investor confidence, leading to a potential decline in asset values. This cycle creates a feedback loop where credit risk and market risk perpetually influence each other, necessitating an integrated risk management approach. Technological advancements offer innovative methods for analysing and understanding this interconnectedness. Advanced risk modelling techniques, such as stress testing and scenario analysis, enable treasuries to simulate various market conditions and assess their impact on credit risk, and vice versa. However, the efficacy of these techniques is predicated on the availability of accurate and reliable data, reinforcing the essential role of data integrity. Financial regulations, too, are increasingly recognising the importance of this interplay. Regulatory frameworks such as Basel III include provisions for an integrated approach to managing credit and market risks, thereby acknowledging their interconnected nature. For bank treasuries, adapting to these regulatory shifts is not just prudent but also advantageous for maintaining a robust risk management framework. In summary, recognising the synergy between credit and market risks is not an optional exercise but an essential element of modern risk management. By adopting an integrated approach, bank treasuries can more accurately assess and mitigate risks, leading to better-informed decisions and stronger financial performance. #InterconnectedRisks #BankTreasury #CreditRisk #MarketRisk #IntegratedRiskManagement

 🚩A Crucial Market Is Sending Its First Warning Signal The Fed’s rate-hiking campaign could still weigh heavily on the economy, not least by making it harder for companies to access funding. But on the surface, investors seem confident that most US companies will generally be able to handle a slowdown without shutting down. That’s clear in the fact that the high-yield spread — that’s the extra yield that investors demand for buying riskier corporate bonds over safer government bonds — is still quite narrow. This indicates that investors aren’t too concerned about a spike in company failures, which would wipe out the interest from the riskier bond’s payments. But as always, the devil is in the details. Look deeper within the high-yield sector, and you’ll see investors are now asking for much higher rewards for holding the riskiest “junk bonds” – specifically those rated CCC (light blue line in the chart) – compared to the slightly less risky B-rated junk bonds (dark blue). Of course, it’s hardly surprising that CCC bonds boast higher yields than single B’s. They’re marginally riskier, after all. But historically, that difference has been slight. And over the past few months, the gap has been widening significantly. That suggests that investors are increasingly wary of defaults within the most speculative pockets. Now, that could be due to sector-specific concerns – CCC bonds are more common in media, consumer products, and high technology – or concerns that a tougher economic environment could wipe out companies with a weak spot financially. That's a worrying trend. As you can see in the chart, the last time we saw such a gap was right before the dot-com bubble burst. Investors poured money into highly speculative ventures during the tech boom, many of which carried CCC ratings. And as the sustainability of those businesses came into question, investors demanded much higher returns to offset the heightened risks. That led to a sharp spike in the yield spreads of CCC-rated bonds over B-rated bonds, a clear signal that investors saw potential for severe financial distress in those companies. That warning sign started flashing about a year before the bubble burst. A similar pattern unfolding today suggests that not everything is stable beneath the surface. The rise in CCC-rated yields indicates that the chance of defaults for the most speculative companies are rising, and is higher than the high-yield spread suggests. The risk from here is that the economy slows down more aggressively or borrowing costs stay high for longer than hoped, then these fears of defaults could spread to other companies – as it did before the dot-com bubble popped. More worryingly, that could bring trouble for private credit lenders, which loan to similarly smaller, debt-laden private companies. And since private markets may represent an important threat to our financial system, this is a risk worth watching. > Finimize

With equity volatility creeping up in August, attention is shifting to credit markets given equity volatility is a key component of credit spread valuation models. While the VIX index has moved up to 17% from a low of 13% in July, credit spreads are little changed and have yet to respond to the rise in equity volatility. The valuation challenge for credit would become bigger if the rise in equity volatility persists, if government bond yields rise further or if the downgrade/default cycle evolves. In fact, compared to government bonds, credit looks already expensive as implied by the low level of corporate bond spreads compared to government bond yields. The rise in downgrades including downgrade reviews by ratings agencies suggests that a US credit cycle is already evolving. Rating downgrades including downgrade reviews typically precede defaults and are more timely indicators of credit perception changes. Indeed defaults appear to be following rising downgrades with this year’s volume of defaults on track to be the third highest on record in dollar terms. Rising downgrade risk appears to be already putting downward pressure on total vs. credit spread returns. The other valuation challenge for publicly traded credit markets stems from their comparison with private credit markets. Over the past year activity from public leveraged loan markets has shifted to private credit markets, suggesting price discovery for new credit is increasinglytaking place in private markets. And the yield divergence between private and public credit markets remained wide in July at around 300bp, posing a valuation challenge for public credit markets. Finally delinquencies are rising in consumer credit and commercial real estate. The Trepp US CMBS delinquency rate for office jumped by 338bp since December, suggesting that the deterioration in credit quality in office sector may already have entered a non-linear phase. Moreover, Trepp reported for July a greater rate of delinquency for larger (above $50m) loans, a rare occurrence as typically larger loans have lower delinquency rate. This occurrence happened only twice in the past during periods of economic weakness I.e. in July 2012 and June 2020 when the overall delinquency rate went above 10% in both cases. In all, rising downgrades, defaults and delinquencies suggest that a US credit cycle is emerging which is likely to worsen into 2024 given stalled credit creation and persistently high refinancing costs.