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Risk is most frequently referred to as the amount of exposure to the potential of unfavorable outcomes from an investment. Naturally, there is no such thing as a surefire investment in life – Every investment comes with some probability of failure. Even the Treasury Bills are not strictly risk-free. In fact, governments have defaulted on their loans throughout history. For example, when Greece adopted the Euro as its currency in 2008, the government caved under massive economic instability and ultimately failed to pay off its sovereign debt. Is it possible to take no risk? In a nutshell, the key question is not whether an investment involves risk but rather how much. Risk pervades our daily lives – Facing risk is inevitable, but we can come to a better understanding by quantifying it. For example, for a typical individual, the odds of getting struck by lightning is less than one in a million. Meanwhile, the odds of being attacked by a terrorist while out vacationing is 1 in 1.6 million. Even in the face of this, individuals take risks in such basic situations as commuting to work or going to the supermarket, simply because the probabilities, once considered, are small enough to warrant undertaking. It would be misguided to avoid any risk at any cost in one’s financial life. Rather, the intelligent investor seeks opportunities with minimal risk but satisfactory expected returns. Needless to say, intelligent investing involves cultivating a strong familiarity with the concept of probability as well as a realistic recognition of risk. Identifying assets with low downside probabilities accompanied by great upside potential is what intelligent investing is all about. When it comes to investing, any discussion of risk that does not take into account expected returns is incomplete, and vice versa. For example, many believe that investing in treasury bonds is a safe bet as it comes with a 4.1% yield, most often misleadingly invoked in the industry as the “risk-free” rate. However, one can overlook the fact that by investing in treasury bills one is losing money to inflation, which currently stands at over 8.2%. Is volatility risk? Wall Street is obsessed with volatility (the short-term fluctuations in market value of any asset or equity) and often misconstrues volatility as risk, but in reality volatility simply represents an asset's market value around its average return. By extension, the standard deviation, which indicates how closely a stock's price is clustered around the mean or moving average, can be used to gauge volatility. To calculate the standard deviation, one first collects data about the asset’s market value at different points in time. One then calculates the mean or moving average of these values, which is then subtracted off each individual market value. Each result is thereafter squared and comprehensively summed. Now, we have arrived at the total squared difference from the mean from all the observed values. To find the average level of deviation from the mean, the total squared difference is divided by the total number of data points observed and then squared to yield the final standard deviation of the market value. Thus, volatility is not necessarily a risk. It simply represents the fluctuation of stock prices around their mean values. It gives no clue as to the level of exposure the investor has toward unfavorable business outcomes. Simply put, it provides no information about the fundamental value of the business. Higher volatility indicates great upside opportunities, opening the door for investors to buy high-quality assets at low prices. To better explain our reasoning, consider this example: You’re in Manhattan looking to buy a skyscraper worth $500M, rented to tenants with AAA+ ratings. It generates $50M in profits per year, and the rent is growing 8.26% annually, in tandem with inflation. On this particular day, there is news in the market about a new Covid-19 surge, causing the market value of the skyscraper to fall to $250M. News like this changes on a daily basis, which can impact the sentiments of the market. This can lead to extended periods of general optimism or pessimism. However, given that New York is the world’s financial center, where the majority of global financial firms are headquartered, a permanent decline in the demand for office buildings is extremely unlikely and does not affect the underlying fundamental value when one takes the long view. In this scenario, volatility helps us to exploit opportunities like buying a skyscraper that is really worth $500m for $250m. These forces lead to what is called the margin of safety , the difference between the intrinsic value and the market value. Buying things cheap allows one to achieve asymmetric risk and reward in our investments. Ironically, when it comes to value investing, the optimal time for buying is created when the market is perceived as dreary or unattractive. Reckoning with Uncertainty The final key theme revolves around the importance of understanding uncertainty. We should consider the future, broadly defined, as a spectrum of possibilities rather than a single outcome from a given set of potential scenarios. We must be flexible enough to fully encapsulate all the possibilities and define their relative likelihood, instead of focusing simply on the ones that are most likely to occur. Some of the most significant losses in history occurred when investors dismissed seemingly impossible outcomes. Meanwhile, the risk is often confused with uncertainty. Granted, both risk and uncertainty are to be expected from any undertaking; however, risk and uncertainty are not the same things. There could be very high uncertainty but little risk. For example, imagine Company A has a recurring average net income of $200m, but this figure fluctuates unpredictably from year to year. For example, it earned $600m in 2018, $120m in 2019, $200m in 2020, and $80m in 2021. From the analysts’ perspective, there is a lot of uncertainty in the level of net income as the exact figures cannot be predicted on a yearly basis. Suppose the CEO of Company A offers to sell the company for $200m, would it be an attractive buy? Even if the investor cannot identify a consistent pattern in Company A’s net income, buying the company at $200m would surely still be a bargain. In this case, it is said that Company A has a lot of uncertainty from the variation in income, but not as much risk because the business is reasonably expected to generate a minimum of $200m in annual income over the long run. Figure 2: Uncertainty in earnings of Company A To summarize, investments are comparable to other undertakings in life in the sense that they always involve some level of risk. Common experience dictates that to achieve anything one must be willing to take healthy risks and become philosophical about adverse outcomes. The astute investor therefore must not shy away from risk; rather, he is able to see through the noise of the uncertainty to arrive at an approximate risk-return profile of the asset and seize attractive opportunities when the odds are overwhelmingly in his favor. By: Siddharth Singhai Disclaimer: This White Paper expresses the views of the author as of the date indicated and such views are subject to change without notice. Ironhold Capital has no duty or obligation to update the information contained herein. Further, Ironhold makes no representation, and it should not be assumed that past investment performance is an indication of future results. Moreover, wherever there is the potential for profit there is also the possibility of loss. This White Paper is being made available for educational purposes only and should not be used for any other purpose. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third-party sources. Ironhold Capital Fund 1, L.P. (“Ironhold”) believes that the sources from which such information has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has not independently verified the accuracy or completeness of such information or the assumptions on which such information is based.

Illustration of Synthetic Leverage Credit: Greekshares Leverage is one of the most important concepts in investing. It refers to the use of debt to finance transactions that may not be executed only with one’s own capital. Understanding the implications of leverage is crucial if one wishes to become an intelligent investor. If used well, leverage can increase returns on investment. This is because one can achieve greater absolute returns with more substantial initial capital. But there’s a twist. Formula for Financial Leverage Credit: WallStreet Mojo Suppose that Investor A has $500, which he deploys to buy Company A’s stocks. If, after one year, the shares go up 50%, then his stakes would be worth $750, which translates to a (750-500)/500 = 50% return on equity. Meanwhile, Investor B has $500 and borrows another $500 to buy Company A’s stocks. When the share price rises 50%, Investor B’s stakes would be worth $1,500, $550 of which he will use to pay down the loan. In the end, he gets to keep $1,500 - $550 = $950, which translates to a (950 - 500)/500 = 90% return on equity. However, if things do not go according to plan, using leverage exponentially increases one’s downside . Based on the same example, if Company A’s shares had instead fallen 50%, Investor A (who does not use leverage) would have $250 in the end, whereas after the debt payments Investor B (who uses leverage) would end up with -$50! Note that they both start with the same initial capital ($500). What type of leverage makes sense? In many cases, leverage can be a powerful tool for investors. The most attractive type of leverage is non-recourse , long-term, low-cost debt taken out at fixed rates. This kind of leverage is immune to changes to the macro interest rate environment. Even in the event of default, one cannot be held personally liable. In real estate , for instance, this type of leverage could be a great tool to amplify returns with low risk. If, say, one takes out a $100,000 mortgage loan at a 5% fixed rate for 20 years to buy a commercial property that can generate $75,000 a year in income, then one should be able to comfortably cover both principal and interest, as well as amplify returns. Moreover, in this scenario, the downside is much more predictable and does not change in the short run, unlike with an equity investment. Image Depicting the Impact of Leverage on Profits Credit: Investopedia How much leverage? Thus, the question is not whether to use leverage but rather how much. The bottomline is that any sensible investor would avoid taking on more leverage than he can handle. To keep things realistic, investors should remember that, historically, recessions have happened every 6-7 years on average. During recessions, rentals can drop by 60–70% (temporarily) as demand declines, even for highly desirable apartments. The property's income stream might not be as strong, but if the leverage is not too large, it might still be manageable. Meanwhile, one could get whipped out if the leverage far exceeds equity. When is leverage dangerous? Leverage may not work so well in the stock market, where the investor is taking on both systematic and company risk . In the case of stocks, several forms of leverage – some quite precarious – are available to the investor, such as margin trading and options trading, among others. With margin trading, one needs to pay out of pocket to “cover the margins” if a stock moves in an adverse direction in the short run. When that happens, the broker requests additional funds when the balance in the client's account drops below a set threshold. For instance, suppose the investor purchases a $1,000 security, where he contributes $500 upfront and borrows the remaining $500. If the security price drops to $800 after a month, the loan amount will remain at $500, but the equity would decrease by $200. As a result, the investor must provide an extra $200 to ensure that he can trade again. In some cases, he might even have to sell the security below his purchase price to make cash. This type of action is commonly termed a “ margin call ,” a source of horror for many investors. Image Depicting Margin Trading Credit: firsttrade.com Leverage could be hidden: More generally, leverage can have dark implications for the economy. After all, the Great Financial Crisis of 2008 was partly caused by risky, unrecognized leverage. When financial institutions carelessly granted leverage to investors who lacked the means to pay back, widespread loan defaults set off ripples that endangered the global financial system. This illustrates how leverage can introduce complexity that may not be completely understood, even by so-called experts. In fact, many financial professionals were oblivious to the impending crisis until it actually occurred. Watch out for asymmetry: Excessive leverage introduces downside asymmetry to your portfolio. As Murphy’s Law states: “Anything that can go wrong will go wrong, and at the worst possible time.” In other words, even events with very small probabilities will occur over a long period of time. Consider driving a supercar on an urban highway at 150 miles per hour. Perhaps the odds of having an accident, with some precautions, are very low – at 0.1%. For the first few times that one goes out for a ride, perhaps it is the case that nothing bad happens. However, if one goes out for such rides a hundred thousand times, an accident is bound to happen. Image Depicting a Car Accident Credit: ClipArtMax The same applies to the stock market, where one always carries some exposure to tail risk like that of covid, although these outcomes may not materialize in the short run. However, if one is investing for the long term, even adverse outcomes with a 0.1% probability of occurring will likely happen at some point. If so, losses from positions that are highly leveraged can become catastrophic for the investor, who may see his holdings completely wiped out. To summarize, the intelligent investor must not only be familiar with the potential benefits of leverage, but also the type of leverage, the amount of leverage, and the asymmetry of leverage. Our recommendation would be to avoid using leverage altogether in public markets , as any large number multiplied by zero is zero, and, as we have discussed, in the long run, given enough leverage you run the risk of multiplying your portfolio by zero. By Siddharth Singhai; Chief Investment Officer Disclaimer: This White Paper expresses the views of the author as of the date indicated and such views are subject to change without notice. Ironhold Capital has no duty or obligation to update the information contained herein. Further, Ironhold makes no representation, and it should not be assumed that past investment performance is an indication of future results. Moreover, wherever there is the potential for profit there is also the possibility of loss. This White Paper is being made available for educational purposes only and should not be used for any other purpose. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or a solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third-party sources. Ironhold Capital Fund 1, L.P. (“Ironhold”) believes that the sources from which such information has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has not independently verified the accuracy or completeness of such information or the assumptions on which such information is based.

The jump-scare by Silicon Valley Bank was not a shock for many, short sellers had been calling out SVB and many other lending institutions for a while, but what actually happened? How Banks Work The business model of banks is very simple. Imagine that you deposited your money in the bank, the bank pays you - the depositor, interest on your money. But the bank needs to make money too, so it deploys the depositors’ money by giving out loans, credit lines and other instruments at a higher rate than what it is paying you and pockets the difference. This is called ‘Net Interest Margin’ or NIM. The bank however, cannot give out all of the depositors’ money, it has to have some liquidity in case of emergencies and withdrawals and the difference between the bank’s assets and liabilities which is the equity, acts as a safety net to fall back on. What Happened at SVB? Silicon Valley Bank had assets totaling $212 Billion while liabilities were at $200 Billion (FY 2022). This means that they had a safety net of about $12 Billion. Out of the $212 Billion in assets, deposits were $173.1 Billion; After the banking crisis in 2008, the FDIC made insuring some of the deposits mandatory, this insurance makes sure that depositors get part of their money back should the bank go under. A meager 11% of the deposits were insured, this is a big red flag, as a depositor you want your money insured and as an investor the insurance acts as a checks and balance metric. Lending Practices & Business Model Investors who were concerned about the equity and bank’s collateral were already cashing out of the bank, SVB had to sell its liquid assets for a loss to cover this up. This leads to the bigger question, how were their collateral assets and what were their lending practices like? More than half of the short term loans were given to Venture Capital and Private Equity endeavors, given the current macro setting, their profitability is questionable. So most investors assumed that the loans were essentially bad, which they were. Why were they bad? Their business model explains it all. SVB issues something called ‘Venture Debt’ which they explain on their website: If you are a company that is raising $10 Million at a $50 Million valuation, giving up 20% equity and you are short $2 Million to the target. Instead of raising the $2 Million from investors for 4% equity, you can borrow the amount as Venture Debt for 0.25% equity in the form of warrants which is less dilutive than the former option. SVB is very proud of their VC lending, they have to be given the statistics.So SVB’s business model is to lend to as many start-ups as possible to breakeven on their losses and then some on that one winning IPO. This is quite literally the modus operandi of Venture Capital firms. But here is the fundamental problem where SVB falls behind even VC firms, at least VC firms get into the deal for equity. When you have equity in a business, if the business goes under or liquidates for profit or is even acquired, you as the equity holder will get your share of the pie, there is some form of recovery. But SVB is praying on warrants, and the warrants are only worth something when the companies go public via an IPO and the stock is trading at a premium to the warrants’ exercise price. It is common knowledge that the ‘Tech Bubble’ had recently burst, companies like Google, Amazon and META were down more than 50%, one can only imagine what happened to ‘Tech’ companies that have never had positive cash flow, and the ‘Healthcare’ (vastly referring to BioTech) side was in even dire straits. In such a market environment, no ‘Tech’ or ‘Healthcare’ company would file for an IPO which renders SVB’s collateral warrants worthless. This aspect should be reason enough to sympathize with both the fleeing depositors and shareholders. Interest Rates The Federal Reserve has been increasing interest rates, while the interest rates before mid 2022 were almost at zero, it was very easy for banks to profit; they were essentially paying nothing to their depositors, while lending out at a better rate which increased their NIM. Since the rates have now increased, the NIM has shrunk meaning the bank’s profitability shrunk. In addition, as of Q4 2022, SVB purchased $82 billion worth of 10-year maturity MBS, which is the major asset SVB holds. The increasing rates at 5.2% conversely decreased the value of long term debt, which in the case of banks, are their assets. Silicon Valley Bank’s financials looked right until one read between the lines and looked for ‘unrealized losses’ of securities ‘held-to-maturity’ (HTM). SVB reported it had unrealized losses of $15.1 Billion, so let’s do some math here, they had equity of $12 Billion, but unrealized losses of about $15.1 Billion, this means that equity had and shareholders have been wiped out. You can refer to our last whitepaper on leverage to get a better understanding of the concept as well as the role it played during 2008. Held-to-maturity accounting itself is not to blame here, the bank bought MBS when interest rates were at all time lows, their average yield was 1.56%, after the rise of interest rates, one could buy securities that yielded 4%-5%, since the current interest rates lead to better yielding securities, the securities with lower yield such as SVB’s MBS’ value on the open market has decreased. The decrease in their value is irrelevant because when held to maturity, these securities do not lose money. HTM accounting allows the company to report changes in their interim value as unrealized losses or gains. This lets the investors get an idea of the underlying securities’ mark-to-market value and volatility. Management It should be noted that while SVB had negative equity and a really bad NIM outlook, they still did not have a Chief Risk Officer (CRO), which any bank should have. The reason for the most crucial role being vacant for 18 months is unknown. The CRO’s value in a bank is even more than that of the CEO because a Bank’s balance sheet in its entirety is nothing but risk. The management team, while reassuring the shareholder, sold their own stake with the CEO personally unloading $3.5 Million worth of shares. Ironhold's Prediction In October 2022, our Chief Investment Officer, Siddharth Singhai, already suspected some financial institutions' failure. In an email to MarketWatch, he shared that he hadn’t foreseen another financial crisis, but he believed that certain financial institutions might be in trouble. “ Capital adequacy ratios have been strictly maintained across most big banks. ” Singhai said. “ The trouble would be derivative books: They represent hidden leverage, and these are very complicated black boxes…We do think it’s quite possible that derivative books will get some banks in trouble. It’s however impossible to say exactly since these books are black boxes and quite often the banks themselves can’t make sense of these contracts .” The Federal Government has started the process of auctioning some segments of SVB, the most recent one being their VC loan book. In the meantime, The FDIC is making sure the depositors get their money back. Ripple and Aftereffect It is clear that depositors’ trust in the banking system is fleeting. Below is a table that depicts uninsured deposits. It can be seen that the three banks that failed, left most of their deposits uninsured, this only adds fuel to the fire and causes contagion. While the depositors have been saved for the time being because of the Federal Government and FDIC stepping in, it is unsure if such a scenario could repeat again. This is precisely the reason why Banks as institutions are hard to gauge and why most investors tend to stay away from them. Today, AT1 holders of Credit Suisse have been wiped out during their acquisition by UBS even though AT1 takes precedence over equity, a small print in the prospectus that bondholders should read actually mentions that the AT1 could end up worthless in case of a write-off, case in point, black boxes and unconventional. Banks are riddled with complex structures, derivatives and agreements that present a difficult time to any investor trying to understand them. In Closing In conclusion, lack of long-term foresight and eased interest rates over a decade allowed SVB to settle into an illusory comfort zone of buying a staggering amount of 10-year MBS while lending to VC and PE endeavors. As VC’s are inherently volatile high-risk borrowers, any negative change in market scenarios would strongly impact their performance. Additionally, SVB was not meticulous in ensuring that its deposits were majorly insured by the FDIC or judicious enough to hire a Chief Risk Officer. While it may be easy to project the current successes into the near future, banks should always be prepared for bear case scenarios. Having a strong risk management department and a diversified portfolio is essential for a lender to survive the highs and lows of the market. The entire situation is a very crucial lesson to investors and banks. Years of complacency have led to today’s sordid affairs and it is uncertain how long the contagion will last, fear makes people irrational, while some institutions might have deserved such contagion, some stand innocent victims to it. By Siddharth Singhai; Chief Investment Officer Disclaimer This White Paper expresses the views of the author as of the date indicated and such views are subject to change without notice. Ironhold Capital has no duty or obligation to update the information contained herein. Further, Ironhold makes no representation, and it should not be assumed that past investment performance is an indication of future results. Moreover, wherever there is the potential for profit there is also the possibility of loss. This White Paper is being made available for educational purposes only and should not be used for any other purpose. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or a solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third-party sources. Ironhold Capital Fund 1, L.P. (“Ironhold”) believes that the sources from which such information has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has not independently verified the accuracy or completeness of such information or the assumptions on which such information is based.

How AI Works For centuries, humans and machines have lived in harmony. Dating back to the development of the wheel which revolutionized farming and human mobility to the computers that landed the first human on the moon in 1969. The newest innovation in the technology sector that has sparked the attention of the public is artificial intelligence or AI. Simply stated, AI refers to the simulation or approximation of human intelligence in machines but, it’s also helpful to understand it in the context of an example. Imagine yourself driving down the street in your neighborhood. What do you see? Most likely, there are other cars either parked or moving, children playing, pets or animals roaming around, and miscellaneous objects such as basketball hoops or trash cans. As humans, we are consciously or subconsciously analyzing our surroundings constantly taking stock of the potential situations that might arise. Due to our comprehension of societal values, we can order the importance of all objects on the road and take the necessary actions to maintain safety. Prior to driving, humans have collected an unquantifiable amount of data points that specifically reference the value of all things, but AI doesn’t have that information. Humans can draw from their life experiences and contextualize the importance of people/things on the road. For example, at a young age humans learn it isn’t ok to hit other people but it is ok to bounce a basketball outside. Humans are alive therefore their safety is more important in comparison to a basketball. They then can correlate that information with their knowledge of driving which provides them the ability to maintain safety to their best efforts. AI programs are attempting to correlate this data so that they can make these decisions correctly. In order to do so they must be supplied with large quantities of high-quality data so that the algorithm can train and improve. With more data and experiences the AI program will teach itself and take incremental steps in becoming a more effective driver. How AI Has Impacted the Market The market's current reaction to the developments and prospectus of AI has been overzealous at the least. In the short run, stocks are susceptible to emotional volatility and therefore deviate from a rational evaluation based on the company’s long term cash flows. One organization that has experienced extreme fluctuations from the emotional movements in the market pertaining to AI is, Nvidia. Nvidia produces graphic processing units which are used in PCs, cars, robots, and now AI. Through their newfound association with AI, Nvidia's market value soured by 184 billion dollars on May 25th. This miraculous 24% gain moved their total market value to 938 billion just shy of joining the world’s one-trillion-dollar club. Another company that has fared well for the market's overreaction to the new developments in AI technology is, C3.ai Inc. They boast negative earnings for the past four fiscal years but their stock price has jumped by 214% thus far in 2023. Palantir is a software company that went public in 2020 and still has yet to report a profitable fiscal year. Despite that, its stock price still trades for about 15 dollars and has surged a total of 136% since the start of 2023. Where AI may be worth the hype McKinsey conducted a study with more than 400 use cases of machine and deep learning across 16 industries and nine business functions. With nearly all industries display clear benefits from AI programming. For instance, predictive maintenance, logistic optimization, and customer service are all business functions that could be enhanced through the assistance of AI. Aside from this study, generative AI has also proven itself to have numerous personal and professional utilization. Amongst the most common forms of generative AI is ChatGPT which can generate endless hours of content. ChatGPT can be utilized to perform marketing, sales, operation, IT, engineering, risk, legal and R&D applications. The potential applications for AI seem almost unlimited but predictions rarely unravel perfectly. Industries with large quantities of high-quality secure data can benefit the most from AI technology. E-commerce, Digital Advertising, Insurance, and other Data-heavy industries have the greatest potential benefit from the use of AI. For instance, companies such as Netflix that collect and exclusively own huge amounts of behavioral data could integrate AI and gain a competitive edge. Understanding what people viewed, for how long, and at what time could help Netflix's advertisers better target their customers, Since Netflix exclusively owns all this data - it could be a source of a moat . We believe access to large amounts of high-quality Data is the prerequisite for developing superior Artificial Intelligence. Falls short of expectations The usefulness of AI drastically decreases the larger the role random probability plays in a particular situation. For example sports, the 2023 eastern conference finals showcased the Miami Heat vs. the Boston Celtics. Before the series started ESPN gave the Heat a 3% of advancing to the finals. In game seven Jayson Tatum twisted his ankle in the first quarter and played horribly the rest of the game. Inevitably the Heat won and advanced to the NBA finals. ESPN's sophisticated analytics couldn’t predict that the series would go to seven games and absolutely couldn't foresee Tatum's injury in a pivotal elimination game. Much like sports life is full of curveballs that can’t be predicted, even by AI. Wherever randomness is a major factor - past data becomes less and less important and so does A.I. Additionally, from an investment standpoint, if AI is easily replicated by all, it wouldn’t create a significant difference in the competitive advantage one company has over the other in an industry. The company's intrinsic value would be derived from its future cash flows. The company has to either gain market share or improve its return on capital on assets to improve its long-term cash flows. This improvement would also have to be permanent for AI to affect stock prices meaningfully in the long run. Meaning just because you have good AI now doesn't mean that you deserve a better valuation. Simply, Unless AI can drastically increase the future cash flows of an organization by either cutting costs or growing revenues(capturing market share) there won’t be any clear advantages to the firm for using AI. Conclusion As investors, we should be mindful and cautious of the hype surrounding AI especially when it comes to the evaluation of a business. For many companies, in a number of industries, AI has the potential to significantly improve productivity. However, just because a company uses A.I it doesn't mean that the company now deserves an astronomical valuation. Ultimately for a company to be worth more it has to improve its long-term free cash flows. In cases where the adoption of A.I improve long-term competitive positioning or operating margins it's worth the hype, but in other cases, it's not. It's unlikely that the recent surge in AI stocks is warranted and investors should consider all that has been discussed thus far before they jump on board the AI train. By: Paul Gray; Chief Executive Officer Siddharth Singhai; Chief Investment Officer Disclaimer This White Paper expresses the views of the author as of the date indicated and such views are subject to change without notice. Ironhold Capital has no duty or obligation to update the information contained herein. Further, Ironhold makes no representation, and it should not be assumed that past investment performance is an indication of future results. Moreover, wherever there is the potential for profit there is also the possibility of loss. This White Paper is being made available for educational purposes only and should not be used for any other purpose. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or a solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third-party sources. Ironhold Capital Fund 1, L.P. (“Ironhold”) believes that the sources from which such information has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has not independently verified the accuracy or completeness of such information or the assumptions on which such information is based.

Cyclicals have long been the most hated and unpopular stocks among both institutional and retail investors. One reason for this is the inherent volatility that comes with cyclicals. You have years of bountiful profits followed by years of agonizing losses, often back-to-back. The psychological pain of holding on to these volatile stocks, especially during the troughs, is usually too great for investors. Consequently, we see very emotional responses to the valuation of these stocks as they navigate through peaks and valleys. credit : istockphoto However, in markets, the opportunities are most splendid when the pain is greatest. Cyclicals, if identified correctly, can be exceptionally profitable investments. This white paper will discuss the most critical variables to look for in cyclical businesses and investments. While not exhaustive, it provides a framework that, if understood and applied, has the potential to offer exceptional returns to investors while minimizing psychological pain. Supply and Demand To start with, supply and demand are critical factors in the cycle. Ideally, we want to be in cyclical businesses where the supply and demand equation is more or less predictable. Take, for instance, our past investment* in Greenbrick Partners. Greenbrick is a home builder in the Dallas-Fort Worth, Texas region. Positioned as they were, owning the majority of the lots in the area, they controlled supply. On the supply side, we knew how long it would take for them to build houses and get them to market. That was predictable. On the demand side, housing starts are driven by employment growth and household formation, both of which are slow-moving and predictable. It was straightforward to gauge where we were in the cycle and roughly how long it would last. Such insights into supply and demand allowed us to identify our position in the cycle. In the case of Greenbrick Partners, we were at the beginning of an uptick that we estimated would last about 3-4 years. Greenbrick would be able to sell its inventory and lots and build homes at attractive prices for a while. This information allowed us to make an investment that more than doubled when we exited our position slightly over a year later. Exit Costs Supply cannot be absorbed quickly in many businesses, leading to high exit costs, and home building is a prime example. Once you build the houses, there is no easy way to eliminate the excess supply quickly. Since household formation or demand for these houses is relatively sluggish and predictable, complete absorption of this supply also takes many years. The same applies to other industries. For instance, blast furnaces, once built, will be operational for at least ten years. In cases where supply absorption is slow, the down cycles can be excruciatingly long. Therefore, understanding supply absorption rates is essential to avoid prolonged, painful down cycles. Shortcut However, there is a way to gauge our position in the cycle even when the supply and demand equation is largely unpredictable. This can be seen as a shortcut to finding the bottom. When an industry goes through a trough, economic profits are the lowest for everyone; the most efficient or lowest-cost producers are either breaking even, slightly profitable, or losing a little money, while everyone else, the more inefficient competitors with thinner margins, are losing money hand over fist. At this point, we are typically at the bottom or trough of the cycle. Eventually, the high-cost producers start cutting down on production as they can no longer sell at unprofitable prices. The most inefficient players are forced out of the industry, and the supply equation starts to recover. However, investors should be cautious and consider how long the supply will take to absorb. The Winning Horse Understanding supply and demand is essential, but which horse do you bet on when you’re at the bottom of the cycle? The answer is the lowest-cost producer . Lowest-cost producers are businesses with the thickest margins. When times are tough, the lowest-cost producers only have a headache, while others are terminally ill. It’s straightforward to identify the lowest-cost producers. You can look at gross margins and operating margins across financials over time and compare them to their peers. However, it’s important to understand the reasons behind the cost advantages to ensure that low-cost leadership is maintained. Various factors, such as bargaining power over suppliers, economies of scale in production, technological edge, or a combination of all these, allow them to produce and sell goods at the highest margins. Investors should evaluate which competitive advantages allow for the low-cost position and if these advantages can be sustained over time. Balance Sheet Being the lowest-cost producer alone does not ensure success during the down cycle. You should also have a solid balance sheet. Over-leveraged businesses struggle when prices are low, margins are thin, but interest payments remain the same. Investors should seek the lowest-cost producer with a fortress balance sheet. A net cash profile is preferred, but a conservative amount of leverage is acceptable. Excessive leverage, however, puts even the most efficient producers at risk of failing to meet their debt obligations. There’s no point in betting on the fastest horse if it cannot run the entire race. The Right Jockey credit : istockphoto Intelligent leadership is akin to having the right jockey. A management team focused on aggressive expansion during good times will struggle when bad times roll around. Investors can look at capital expenditure levels during the up-cycle to gauge how the management thinks about cycles and cross-cycle profitability. An intelligent management team should return more cash to shareholders, recognizing their cyclical business and avoiding adding excess capacity at the top. They should also maintain a conservative balance sheet. Incompetent management teams do the opposite: they add leverage and oversupply at the top, fail to return excess cash flow to shareholders, and create risks by taking on too much leverage. This failure to think full-cycle can even tank a low-cost producer. Hence, the management team becomes crucial; betting on the fastest horse is futile without the right jockey. Price Matters Valuation is a crucial part of any investment. A great business bought at a terrible price is still a lousy investment, and a poor business bought at a cheap enough price can still turn out to be a good investment. Although investors should focus on buying high-quality businesses, even the greatest business cannot make you money if you overpay for it. In investing, price matters. To value cyclicals correctly, we cannot simply take bottom earnings and extrapolate them or top-of-the-cycle earnings and extrapolate them. This will lead to either too pessimistic or too optimistic valuations. Normalized earnings, or earnings of a business over time adjusted for cyclicality, are vital. We must normalize the down and up cycles and evaluate a base level of earnings for the cyclical business. Top-of-the-cycle and bottom-of-the-cycle multiples are both meaningless and should be avoided. Moreover, we should ascribe the correct growth to cyclicals based on the average long-term growth rates of the industry. For instance, the steel industry will only grow at 2% over the long run. However, growth rates leading into the peak of the cycle could be well in excess of 5%, 15%, or even 20%. This is not representative of the entire cycle. We must consider earnings multiples, being cognizant of long-term, across-cycle growth rates. Failure to do so will lead to over- or under-valuation. Home Stretch In conclusion, lowest-cost producers purchased at cheap valuations and run by competent management teams can turn out to be wonderful investments over time. However, a robust understanding of all the factors outlined in this white paper is necessary to avoid typical cyclical investing traps. *Ironhold Capital no longer holds a position in Greenbrick Partners. The article above was published as a collaboration between Ironhold Capital and Ms. Luca Blaumann Chief Editor at Stoxpo.com , to read the original publication click here . By: Paul Gray; Chief Executive Officer Siddharth Singhai; Chief Investment Officer Luca Blaumann, Editor-in-Chief Stoxpo Disclaimer This White Paper expresses the views of the author as of the date indicated and such views are subject to change without notice. Ironhold Capital has no duty or obligation to update the information contained herein. Further, Ironhold makes no representation, and it should not be assumed that past investment performance is an indication of future results. Moreover, wherever there is the potential for profit there is also the possibility of loss. This White Paper is being made available for educational purposes only and should not be used for any other purpose. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or a solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third-party sources. Ironhold Capital Fund 1, L.P. (“Ironhold”) believes that the sources from which such information has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has not independently verified the accuracy or completeness of such information or the assumptions on which such information is based.

The recent surge in Agentic AI and Generative AI has stirred considerable discussion about the future of software as a service. Vibe coding, in particular, has lowered the friction involved in building applications. Today, a developer—or even a technically curious individual—can describe a product in a prompt and generate a working application. In many cases, this can be done without a dedicated front-end developer, back-end engineer, or UI/UX designer. The results are often surprisingly functional. They may not be perfect. Depending on complexity, they can still be buggy. But they work. Markets, as they often do, have reacted quickly. Over the past few quarters, several major software companies have seen meaningful erosion in their market values. This naturally raises a question worth considering: Is it really over for software? What makes Software? To think clearly about this question, it helps to step back and understand what software actually consists of. Most applications can be broken down into three basic components: the back-end, the front-end, and the UI/UX layer. The back-end is everything that happens behind the scenes. When you open an Uber app and request a ride, the app sends your GPS location, finds nearby drivers, calculates pricing based on supply and demand, allows the driver to accept the request, and processes payment. All of that logic takes place in the back-end. The front-end is what the user interacts with. The buttons you click, the reviews you read, the ratings you see, the map where you enter your destination—all of these elements are part of the front-end. Then there is UI/UX. This governs the visual and experiential layer: how the fonts look, which buttons stand out, the colors, the themes, and the overall look and feel of the front-end. In essence, most software can be reduced to these three pieces. Once we understand that, another question naturally arises. Is it impossible for a new small team to disrupt the back-end, front-end, or UI/UX of an existing software company? The answer, in most cases, is no. There is nothing inherently sacred about these layers. Given sufficient time, talent, and capital, they can be rebuilt. And in the age of AI, that process may become even faster. If a company’s advantage rests primarily on an extensive feature set, broader functionality, or a cleaner interface, that advantage may be more fragile than it appears. The real durability of a software company does not lie in whether someone can replicate its product. It lies in whether customers can realistically and economically switch away from it. Software was never about being the best It’s tempting to think that the best software wins. But historically, that hasn’t really been the case. The major software companies of the world—whether Microsoft, Oracle, or hybrid software-hardware companies like Cisco and Apple—did not dominate primarily because they had the best back-end or the most elegant interface. They built ecosystems. And ecosystems tend to be sticky. As is usually the case with technology, advantages tend to narrow over time. Tesla, for instance, once appeared to produce electric vehicles that were two or three times better than the competition. That edge did not last forever. Competitors eventually caught up. The same pattern has appeared again and again throughout technological history. Software, in the long run, was never really about having the best back-end, front-end, or UI/UX. What makes Software durable? If superior technology alone is not the moat, then what is? Historically, durable software companies benefited from other factors. Switching costs. Access to valuable data. Stickiness driven by the difficulty of migrating systems. Integration into workflows. Network effects. And in some cases, ecosystem lock-ins with hardware. It’s also worth noting that the success of a software product has never depended solely on how good its features are or how intuitive its interface feels. Those things help, of course. But even historically, small teams have been able to replicate features. AI tools may simply accelerate that process. But when software is mission-critical, reliability matters more than novelty. After all, no business wants a system that works 70 percent of the time and throws major bugs the rest of the time—even if that system was cheap and built in-house in five days. Consider something as simple as a website. If your website disappears from search engines, if the fonts render incorrectly, if users can’t log in, or if contact forms stop working, the damage extends beyond the technical problem. It affects brand perception. Great software requires constant maintenance. Every time new features are added—whether to the back-end, front-end, or UI/UX—new bugs inevitably appear. That is simply the nature of complex systems. As a result, mature software platforms rely on continuous cycles of testing, fixing, and updating. A one-and-done application can not replicate that. Commoditized vs Mission critical? Not all software is created equal. Some applications are used casually and can be replaced easily. Food delivery apps provide a simple example. If one platform doesn’t offer a good discount, users switch to another. They search for the same restaurant, build the same meal, and compare prices instantly. This is what low switching costs look like. Software that behaves like this will likely struggle in a competitive environment. Mission-critical software operates differently. When a company has stored years of operational data inside a system—when that system connects to payroll, accounting, compliance, and internal workflows—switching becomes difficult. Employees must be retrained. Data must be migrated. Processes must change. That friction creates durability. High net revenue retention over time is typically a great indicator of durability. AI's impact on Software stocks? From an investor’s perspective, AI should be evaluated through the lens of outcomes rather than excitement. Ultimately, the value of any business is the future cash flows it will generate over its lifetime. If superior AI technology leads to superior and sustainable cash flows, then it deserves attention. But the real question is not simply whether a company is using AI. The real question is whether its AI is meaningfully superior to competitors—and whether that superiority can endure. Going back to Tesla, there was a time when Tesla’s vehicles were dramatically better than competing EVs. Over time, however, competitors closed the gap. The probability that technology alone—whether EV technology then or AI technology today—will function as a long-lasting moat is unlikely . Technology advantages tend to compress. From an investor’s perspective, this has practical implications. If a portfolio is full of software companies that are unprofitable, lack defined moats, and were purchased at steep valuations, then AI may indeed represent a serious risk. It could potentially wipe out a large portion—if not all—of the market value of those businesses. But investing without understanding what you are buying has always been a bad idea. It was a bad idea before AI, and it remains a bad idea to invest in businesses outside your circle of competence . There are also specific metrics investors can track. The most important ones are churn and net revenue retention. How many users who signed up one or two years ago are still active today? If they remain customers, that’s a strong indication of switching costs. Of course, the next step is to understand why  retention is high. Is it because of ecosystem lock-ins with hardware? Is it because the software bundles multiple mission-critical tools together? Is it because years of operational data are embedded in the system? Whatever the reason, an investor should understand it clearly and then further evaluate if the advantage is threatened by AI. Two Buckets? In the end, it may help to place software investments into two simple buckets. Bucket A consists of mission-critical software businesses with high switching costs and strong net revenue retention. Bucket B consists of speculative software businesses with no clearly defined or proven moat. Ideally, a portfolio is concentrated in the first bucket. If the switching costs are real and the moat is understood, those businesses may prove resilient even in the face of rapid AI-driven change. But if a portfolio is concentrated in the second bucket, the situation looks very different. An environment where technological change is accelerating, that deterioration may not happen gradually. It can happen very quickly. By: Paul Gray; Chief Executive Officer Siddharth Singhai; Chief Investment Officer Disclaimer This White Paper expresses the views of the author as of the date indicated and such views are subject to change without notice. Ironhold Capital has no duty or obligation to update the information contained herein. Further, Ironhold makes no representation, and it should not be assumed that past investment performance is an indication of future results. Moreover, wherever there is the potential for profit there is also the possibility of loss. This White Paper is being made available for educational purposes only and should not be used for any other purpose. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or a solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third-party sources. Ironhold Capital Fund 1, L.P. (“Ironhold”) believes that the sources from which such information has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has not independently verified the accuracy or completeness of such information or the assumptions on which such information is based.

Since the start of the new year, uncertainty and fear from various external factors have sparked a market correction and a rotation of positive sentiment out of growth and into value equities. For most of the pandemic, growth stocks outperformed due to the incredible amount of stimulus and low-interest rates, despite the looming fear of COVID-19’s lasting impact on our society and economy. The abundance of monetary policy decisions may have given investors too optimistic of an outlook on the future. Low rates and trillions in federal spending cannot sustainably continue for long periods. The Fed’s decision to wane off its spending and hike rates was needed to slow down the inflation caused by the COVID-19 stimulus. This is a large part of why value stocks have a higher sentiment than growth at the moment – inflation and rising rates lead to market uncertainty. Additionally, the developments in the conflict between Russia and Ukraine add to the worsening market sentiment and higher levels of caution from investors, catalyzing a rotation to value equities. It is essential to clearly differentiate between value and growth when talking about this trend. Intelligent investing is the search for value in the sum of a company’s free cash flows generated over its lifetime. These cash flows are discounted to the present to understand the company’s current value. The opportunity for a value investment comes from searching for undervalued or cheap companies compared to their discounted free cash flows. Some speculation about the future is used in predicting performance for value stocks. Still, sensible forecasts use historical trends and data. Therefore, the range of possible outcomes for the investment is smaller than that of a growth investment, significantly reducing the risk of loss. In contrast, investing in a speculative, or growth, stock comes with the ability to profit from the future value created by the company’s future growth of cash flows. The lifetime cash flows of the company are still summed and discounted to the present, except, since all or most profit lies in the future, the company trades at a hefty multiple of its current earnings in anticipation of future growth. Accordingly, the levels of speculation for growth investments are much higher than that of an intelligent value investment. Unlike value stocks, growth stocks have minimal amounts of concrete, historical information upon which to base their predictions for the future. Therefore, the risk factor associated with a growth investment is much higher due to uncertainty and a high dependence on unknown future performance. In a growth investment, risks of market share loss, cyclical downturn in demand, credit crunch, etc., are ever-present. The technicalities of the differences between intelligent and speculative investments, or growth and value stocks, explained above can be simplified down into an example in real estate. For example, a value-based stock investment would be comparable to a rental apartment in Manhattan. The property is worth $1,000,000, located in a low-crime area with an abundance of nice stores and restaurants, and set to bring in $50,000 of annual rental free cash flow for the owner. This apartment is undervalued since other properties in the area are worth $1,500,000, and the rental rates can be formulated from the history of payments in previous years. In addition, the property will appreciate 5% annually, judging from the trends of appreciation in the area. With this knowledge, it is safe to believe that these trends will continue in the future. However, this is not to say the owner could lose money from the investment in the case of a fire or flood, demonstrating the ever-present risk in all forms of investing. Property on the surface of mars provides an analogous example to speculative investment. Since the property is highly dependent on future growth, a $2,000,000 investment is required for purchase. At the time of payment, say there is no societal development yet on the planet and that nobody is willing to rent out the property. As space exploration and colonization become increasingly popular in the coming years, this investment could provide massive returns to the owner. However, it is still too early to know with any confidence. There are no previous trends or data to base the decision on; it is purely speculative with a lot of associated risk. As a result, one most likely would not commit to the purchase during a time of economic or political uncertainty. After making the distinction and connection between value and growth, it’s apparent why the market has begun a rotation to value and the possibility for the trend to continue for the foreseeable future. Due to the high levels of speculation involved in growth investing, uncertainty in the economy, politics, business climate, or any other external factor can severely impact growth equity sentiment. During periods where this does happen, value stocks are seen as a safer, more intelligent investment since people want companies with a history of profitability that are also undervalued. There is already a lot of guessing involved in growth investing, and factors like inflation, rising rates, and the conflict between Russia and Ukraine only increase the risk of wrongfully predicting the future cash flows of a company. Seeing the current market and the state of the world, an excellent environment for value to outperform growth now exists. These fears and uncertainty have led to an optimal market for value stocks. Siddharth Singhai Chairman & CIO of Ironhold Capital Disclaimer : This White Paper expresses the views of the author as of the date indicated and such views are subject to change without notice. Ironhold Capital has no duty or obligation to update the information contained herein. Further, Ironhold makes no representation, and it should not be assumed that past investment performance is an indication of future results. Moreover, wherever there is the potential for profit there is also the possibility of loss. This White Paper is being made available for educational purposes only and should not be used for any other purpose. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or solicitation to buy any securities or related financial instruments in any jurisdiction. Certain information contained herein concerning economic trends and performance is based on or derived from information provided by independent third-party sources. Ironhold Capital Fund 1, L.P. (“Ironhold”) believes that the sources from which such information has been obtained are reliable; however, it cannot guarantee the accuracy of such information and has not independently verified the accuracy or completeness of such information or the assumptions on which such information is based