Thank you, really means a lot!
Hey everyone, I’m sharing a macro essay I wrote titled “The Dying Denominator”
Over the past few months, gold has surged, AI spending has overtaken U.S. consumption as the main GDP driver, and trade flows are shifting in ways that echo past turning points.
It’s a long read, but if you’re curious about where capital might flow over the next few years, I think you’ll enjoy it.
Since my last post on gold, it is up about ten percent. This has been the fastest $500 move in the metal in my investing lifetime. When a (likely?) reserve asset re-prices this quickly, I pay attention. Price alone does not constitute thesis, but it often tells you which story the world is beginning to believe.
Two things can be true at once. First, gold can be volatile over weeks and months. Second, a sharp rise in the safe haven asset usually signals pressure in the monetary system. This memo is about that pressure and what it means for portfolios like ours.
The cracking yardstick
How we measure wealth now matters as much as what we own. In dollars, almost everything still looks fine. Equities show strong gains, houses feel expensive, and paper net worth is high. In gold terms, the picture is flatter and often negative, which tells us real purchasing power is not improving. In bitcoin terms, the gap is largest of all, since many traditional assets have lost ground when measured in that ledger. Luke Gromen calls this the first stage of a unit-of-account fracture. Nominal prosperity survives, real prosperity stalls, and policy makers, media, and investors keep speaking in a yardstick that is quietly melting. That is why wages, prices, and debt feel misaligned.
Wall Street still files bitcoin under the label risk asset. Functionally it is behaving like a parallel reserve ledger that exposes the weakness of nominal accounting. It is the only denominator that makes the post-2020 economy look like Argentina. If bitcoin continues to monetize, the charts we are looking at today will read like a pre-revaluation ledger of the old world being marked down. Gromen’s imperial carry trade framing also helps. The United States attracts global capital, inflates domestic assets in nominal terms, and exports much of the currency risk abroad.
Why gold is being re-rated
Central banks have been voting with their balance sheets. Since 2016, the share of gold in global reserves has risen while the share of the dollar has slipped. Brazil just added almost sixteen tonnes in September, its first addition since mid-2021, lifting holdings to about one hundred forty five tonnes. If gold reaches roughly $5500-5700 per ounce and the same reserve trends persist, gold would overtake the dollar as the largest reserve asset by market value. Tokenization will make gold easier to plug into trade and settlement, which increases its usefulness at the margin. Gresham’s Law explains the migration in plain English. When trust weakens, better collateral crowds out weaker collateral on balance sheets.
Ritesh Jain’s cycle work points to a path toward $8000 over time, consistent with the metal’s historical habit of rising around eightfold off major lows. Luke Gromen’s Treasury reserve lens produces higher end states between $15000-40000 if policy is forced to reconcile liabilities with credible collateral. Arnaud Bertrand reminds us that when gold more than doubles in the reserve currency of the day, history usually records a deep loss of confidence and a change in the political order. The odd feature of the current episode is how little it is being discussed.
Market microstructure tells a similar story. For years, New York hours often saw sellers lean on the tape. Today gold tends to lift when US markets open. That is not retail froth. It is allocation and balance-sheet management. One should also remember the two policy levers that could change the path. The first is a durable move to materially positive real rates. That would end the bull market quickly, yet the debt load makes it unlikely. The second is a simple revaluation of the United States’ 8100 tonnes of gold, which is still recorded at $42 per ounce on Treasury books. A mark-to-market would create liquidity with a pen stroke.
History looks different when priced in ounces. After the 1929 equity peak, the recovery in gold terms took about thirty years. After the 1966 peak, it took roughly thirty two years. The 1999 peak may not recover even after fifty years. By comparison, crises that feel large in dollars, including 1973, 1987, 2008, and 2020, show up as smaller ripples inside the much longer gold cycle. Measured in the scarv layer, which is my shorthand for a living record of a dying denominator, the larger arc is visible.
Silver, the forgotten gear
Silver has not kept pace. The gold to silver ratio sits in the mid eighties while the modern average is closer to sixty. If that ratio reverts while gold holds its ground, the derived range for silver is roughly $53 to $75 per ounce, midpoint of $64, as per the DSP framework. Supply has lagged, and retail participation is still limited. Real bull markets rarely end without some public frenzy. Until that arrives, I treat silver as torque on the gold view. The same supply limited story appears across parts of the commodity complex, notably gold, silver, and uranium.
AI, the modern railroad?
The artificial intelligence buildout is extraordinary in scale and speed. Industry capex is running near $400bn per year while current revenue is roughly $15-20bn. Once you include three to five year obsolescence on data centers and GPUs, the more realistic break-even revenue run-rate is $320-400bn. If the current pace extends through 2026, the cumulative revenue needed to justify the spend approaches one trillion.
What makes this phase unique is that for the first time, U.S. GDP growth has been driven more by AI-related infrastructure spending than by consumption, which has historically been the backbone of the economy. If AI-related capex were stripped out, the most recent quarter’s GDP would likely have been negative. In other words, artificial intelligence is now doing the heavy lifting for headline growth, masking underlying weakness in the consumer and production side of the economy.
This boom draws an eerie parallel to the railroad era of the 1800s, when vast amounts of capital were poured into revolutionary infrastructure that transformed the world but bankrupted many investors. The railways connected economies, created new industries, and changed geography itself, but most railway companies never earned their cost of capital. AI may end up following the same pattern: a technology that reshapes everything but rewards only a few.
Nations may subsidize for security reasons and platforms may prioritise users over profits for a time, but history warns that world changing technology can be a poor investment during the boom. Railroads reshaped the world and still bankrupted many investors. Since AI capex already approaches two percent of US GDP, a pause would hit both markets and the economy. Early signs of circular financing are visible, where companies invest in each other to make the numbers look better. That is a late-cycle tell.
Ritesh Jain notes that the AI capex wave has delayed recession in a consumption-driven economy. He also points out that the large technology leaders are now competing more directly with one another. The Treasury General Account has been rebuilt without obvious market stress. If those balances are later deployed, they could add something like $800bn of liquidity. Oil and bond yields will be the first places to watch for signs that the music has changed.
Banks under fiscal dominance
Highly indebted governments need captive balance sheets. That reality is pulling banks deeper into policy work. Enforcement will widen in the hunt for revenue. Stablecoins will likely be issued or warehoused by banks and backed with government paper, but deposits will still migrate toward higher yielding sovereigns, which drains cheap funding. Essentially, money will move from the financial system to the government, questioning traditional banking. Rising yields push banks to hold more government debt, which crowds out private borrowers. In effect, banks look more like public utilities and less like independent risk managers. Profitability becomes a policy variable rather than a business choice.
Money, output, and the lag
Steve Hanke’s lens on money and output is useful here. The money supply began to contract in April 2022, which is rare. Real activity usually responds with a lag of one to two years. M2 has resumed growing at roughly 4.8% year over year, yet his golden growth rate is nearer 6% if the aim is stable inflation around 2%. GDP grew about 3.8% year over year in the second quarter, but Gross Output grew only around 1.2%. GO captures the full supply chain and the business-to-business economy rather than just final consumption. When GO lags like this, it warns that production and investment are slowing even while consumers still appear active. That is the part of the movie that textbooks miss when they claim consumption drives everything simply because it is two thirds of GDP.
Social seams you can see
The macro does not live in a vacuum. Jobs fairs in Canada see hundreds of people wait for hours on a weekday. Mid-career professionals are competing for entry-level roles after a period of hiring freezes and store closures. Germany is debating a retirement age of seventy three to keep the pension system solvent, with leaders saying the country cannot afford the status quo. These are the stress lines you expect when debt, demographics, and growth are misaligned.
Trade and the new map
China has been shifting purchases toward Latin America. One recent example is soybeans where the autumn US harvest saw no Chinese buying. When a buyer of that scale reroutes demand, the shock is felt across supply chains. This is what a multipolar trading system looks like in practice. It is also what a first stage unit-of-account fracture feels like.
India: patience, pockets, and potential
India’s micro story remains attractive, but the index still needs an earnings trigger. Earnings were downgraded from the third quarter last year. Monsoon effects will dent near term prints for some companies. Commentary will matter.
Where valuations are still reasonable and tailwinds are visible, setups in Dairy, Alcohol premiumization, and financials that are heavy on gold and fixed rate loans, plus some financial services look attractive. Several areas have tailwinds but require bottoms-up work for valuation comfort. Autos leave no room for error and will only deliver if expected earnings arrive. CDMO is case by case. Defence looks better in select R&D names with real IP and in systems or sub-systems manufacturers, including shipbuilding.
Consumption seems to be improving. Retailers are posting better numbers. If that broadens, contract manufacturers for FMCG and certain payments names can benefit. A few unique SaaS plays in tourism and banking can look interesting.
Cement and Hotels deserve a note. Consolidation and demand supply dynamics are already well known. The GST angle is under discussed and can be meaningful. East and South oriented cement companies may do better on the next leg.
The patience bucket is exporters. If a deal lands, rerating can happen in days rather than weeks. You can still find 25-30% EBITDA margin businesses at 10-15 times trailing earnings. That is where one may want to hunt.
(This entire section is credited to Saurabh Varshney)
Where this could be wrong
If central banks sharply raised real rates and pledged to hold them there, they could end the gold and silver bull overnight. The debt load makes this unlikely, but not impossible. If AI converts capex into durable, high margin revenue faster than expected, the macro drag I worry about will not show up. If money growth returns to Hanke’s 6% zone and stays there, GO should re-accelerate and recession odds would fall.
Way forward
I try not to predict. I try to position. The signals I am watching are simple. Reserve composition keeps tilting toward gold. The gold to silver ratio remains elevated. AI capex and energy prices are joined at the hip. Money growth is below the comfort range and GO has softened. Labor markets are showing stress at the margins. European pensions and entitlements feel tight. Trade flows are moving to new routes.
In that world, I want more assets that do not rely on perfect capital markets to survive, more real collateral, more businesses that can self finance, and more patience.
Ending note
Amidst all the macro noise and gold’s rapid rise, it’s easy to see why everyone’s catching the gold bug. But I want to reiterate that while I remain very bullish on silver and gold, I am, at my core, a bottoms-up investor. My focus stays on understanding companies deeply, valuing them rationally, and letting cycles play out without losing sight of fundamentals.
I would like to credit most of this work to my teachers Ritesh Jain, Luke Gromen, and Steve Hanke. I wrote this piece simply as a means of consolidating all their knowledge to paint a digestible picture for you all.
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Portfolio as of November 1st
| Stocks & Commodities | Value |
|---|---|
| Gold | 11.0% |
| Narayana Hrudayala | 4.4% |
| Samhi Hotels | 13.8% |
| TD Power | 15.0% |
| JM Financial | 6.6% |
| Aditya Birla Capital | 5.5% |
| Time Technoplast | 4.9% |
| Silver | 13.5% |
| Goodluck India | 5.0% |
| Oswal Pumps | 4.2% |
| Max Estates | 3.9% |
| Parag Milk | 5.7% |
| Alpex Solar | 4.0% |
| Cash | 2.4% |
Changes made in October:
- Exited Fineotex Chemical
- Increased allocation in Parag Milk slightly
- Bought Alpex Solar
Purchase Thesis
- Alpex Solar: A business riding India’s renewable energy story. They’re looking to scale capacity by 3x by FY27, as well as backward-integrating into aluminum frames. I’ve posted a thorough analysis with the valuation math here.
Key Learning
In October, I had suggested that markets were in the panic or capitulation stage of the Market Psychology Cycle. I was slightly early. In hindsight, we were closer to despondency, the final exhaustion phase before recovery. The rebound since then makes that clear. One factor I underweighted was the growing likelihood of a Fed pivot. With the Fed now signaling an end to tightening by December, risk assets have more room to climb.
Macro Note
Next is an article I wrote titled The Architecture of Fragility. It’s long, but it helps frame the context in which all our portfolio decisions sit. Highly recommend giving it a full read.
The Silent Repricing of Money
The shift beneath the surface
Since 2022, much of the conversation around de-dollarization has focused on visible signs such as trade settlements, SWIFT transactions, or oil contracts. Yet the real change lies deeper, in balance sheets and reserve composition. What central banks and households choose to hold quietly reflects where trust resides. On that metric, the shift is already clear. The East has been accumulating gold steadily for two decades, and now its households are following suit.
Gold as the BRICS stablecoin
Ritesh Jain’s framing captures the transition well. For the Western system, the stablecoin is emerging as a permissioned settlement asset that functions within its own regulatory perimeter. For the BRICS bloc, gold already serves that role: an apolitical form of collateral and settlement outside Western banking infrastructure.
Three facts underline this evolution:
- Around 70% of the world’s gold reserves are now held by BRICS countries or have migrated from Western to Eastern balance sheets over the past 20 years.
- The two most significant marginal producers are Russia and China.
- The West is reluctant to endorse gold’s return as a reserve asset precisely because most of it is now concentrated outside its control.
The resistance to gold is therefore not economic but geopolitical. Should the dollar’s reserve share decline, Western policymakers would prefer that global savings flow into a US-regulated digital-dollar or stablecoin framework rather than into a metal held by their strategic competitors. The outcome is the emergence of two overlapping financial systems: one based on jurisdictional control, the other on neutral collateral.
Households join the state
The chart attached below, showing the sharp rise in Chinese household demand for gold ETFs, demonstrates how this transition has broadened. ETF flows surged to multi-billion-dollar levels, revealing that Chinese households have started allocating savings to gold in the same direction as their central bank.
This pattern appeared soon after the freezing of Russia’s foreign reserves in 2022, ramping it up even though they started buying in 2014. Once that event occurred, China moved to diversify its reserves and trade exposures. Households appear to be mirroring the same logic. This is not yield-seeking behavior but an instinctive response to sanction risk and an effort to protect purchasing power. When both the state and the citizen hedge through the same neutral asset, it signals a deep shift in confidence.
Why the West cannot follow easily
The United States still holds about 8,100 (allegedly?) tonnes of gold, valued on the Treasury’s books at $42 per ounce. A simple revaluation to market prices could expand its balance sheet substantially. However, the problem is now geopolitical rather than financial. The ownership of marginal gold has shifted eastward. Any return to a gold-linked framework would implicitly validate that shift and reward the BRICS bloc.
Historical parallels
Arnaud Bertrand provides a useful historical reference. When gold has more than doubled in the reserve currency of the day, it has almost always coincided with a profound loss of confidence in the monetary and political order. Such moments accompanied the fall of Rome, the decline of Spain, the French Revolution, and the end of Bretton Woods. In each case, the repricing of gold reflected a transfer of real wealth from currency users to asset holders, widening inequality and triggering political change.
Real versus nominal prosperity
Mike Maloney illustrates the same theme through silver. Adjusted for 1980 dollars, silver today trades near $12 an ounce, implying it would need to quadruple to match its previous real peak. The Roman denarius took roughly two and a half centuries to lose its value. Modern fiat systems have achieved similar debasement in less than half that time, not by melting coins but by expanding digital claims at will. When creation of money becomes effortless, trust and collateral become the true constraints. That is why gold is being re-rated across balance sheets.
Central banks have already voted
Steve Hanke observes that global central banks now hold more gold than at any point in the last decade. This shift reflects both precaution and policy. The dollar has been increasingly used as a geopolitical instrument through sanctions and asset freezes, while the US fiscal position has weakened. Federal debt now approaches $38 trillion and total system debt nearly $100 trillion, or over 300% of GDP. Add to it the NPV of another $100 trillion of unfunded debt. Gurmeet Chadha’s framework of reserve-currency cycles (rise, peak, over-extension, and decline) suggests that the United States has entered the phase where fiscal and military overreach erode confidence.
The logic of diversification
For many reserve managers, the calculus is simple. Assets held in another country’s legal jurisdiction can be frozen; neutral assets cannot. The next evolution of reserve management therefore tilts toward collateral that can be stored, tokenized, and settled without Western intermediaries.
A bifurcated system
The most plausible outcome is not the collapse of the dollar but the coexistence of two systems. One will be a gated dollar environment managed through stablecoin regulations and compliance networks. The other will be a portable gold and commodity network, facilitated by tokenization and clearing centres in the East. Because credible collateral is finite while the volume of dollar claims keeps expanding, the relative price of that collateral must rise to restore balance.
A widening gap between East and West
Luke Gromen’s observation that Western investors would need to buy gold daily for several years merely to match Eastern holdings underlines how early this process remains. The reallocation has only begun. When Western institutions finally acknowledge gold as a parallel reserve asset rather than a speculative instrument, the pace of repricing could accelerate sharply.
AI and the Debt-Based System
A productivity boom with a paradox
Artificial intelligence is often presented as the new industrial revolution, a transformative force capable of lifting productivity, reshaping labour markets, and driving growth. What receives less attention is how such a transformation fits within a monetary system that is built on debt and employment. The more that machines replace labour, the less income circulates through the traditional credit and consumption channels on which the system depends. In a consumption-driven economy like the United States, the scale of investment in AI has become so large that without it, second-quarter GDP growth would likely have been negative, a reminder that the boom now sustains the very growth it was meant to enhance.
The second-derivative problem
The apparent paradox is what Luke Gromen calls the second-derivative problem: productivity may rise, but the system built on debt and wages cannot survive a decline in income velocity. As automation spreads, employment and wage growth decelerate while credit obligations remain fixed. The very efficiency that boosts margins undermines the cash flow that services the debt.
The chain reaction
The logic is straightforward. As automation spreads, employment falls and wage growth turns negative. With fewer paychecks, mortgage and loan repayments decline, leading to credit losses for banks. Those banks hold a large proportion of their reserves in US Treasuries. To offset losses, they sell Treasuries into the market, pushing yields higher just as unemployment rises. The outcome is an emerging-market-style crisis within the issuer of the global reserve currency: unemployment, wage deflation, and rising interest rates occurring simultaneously.
Such a cycle would normally be broken by policy intervention. Yet the scale of leverage in the modern financial system makes traditional solutions difficult. If rates fall to cushion unemployment, inflation risk rises; if they remain high to protect the currency and bonds, asset markets and credit creation weaken. Either path leads to further dependence on central banks to stabilize both the fiscal and the financial system.
From private UBI to public UBI
This pattern is not entirely new. During the early 2000s, as manufacturing jobs were offshored to China, household living standards in the United States were maintained through what Gromen calls private universal basic income . Credit standards collapsed, allowing households to borrow against inflated home values to preserve consumption even as wages stagnated. When the housing bubble burst, the losses moved onto the Federal Reserve’s balance sheet.
The current transition appears to be the next iteration of that cycle. Artificial intelligence may create another gap between productivity and employment, only this time there is no new industrial sector left to absorb displaced workers. The likely policy response would be public universal basic income, funded not by private credit expansion but by government transfers and monetary creation.
The fiscal constraint
Public UBI raises an immediate question: who finances it? With total US debt approaching $100 trillion across households, corporations, and government, the fiscal capacity for large-scale redistribution is limited. The Federal Reserve can monetize deficits for a period, but doing so permanently would erode the credibility of Treasury securities as the world’s primary reserve asset.
In that sense, AI’s economic impact may accelerate the fiscal and monetary convergence that was already underway. The need to maintain social stability would require further money creation, while the requirement to protect bond market confidence would argue for restraint. Bridging this contradiction will likely involve new financial architecture (digital currencies, tokenized Treasuries, and programmable transfers) but the underlying pressure will remain.
The employment mismatch
Artificial intelligence’s reach extends well beyond software. Entire categories of white-collar employment are exposed. In healthcare, administration and billing constitute the largest share of jobs across most states, and these are precisely the roles that AI can perform faster, cheaper, and with fewer errors. In professional services, entry-level and mid-tier programming, documentation, and support functions face similar risk. If the largest employers in the country become vulnerable to automation, the implications for credit demand, housing, and consumption are profound.
The historical rhyme
The last time such a displacement occurred was when industrial jobs were lost to globalization. Between 2001 and 2005, the US workforce experienced an economic shock as manufacturing moved offshore. Policy responded by relaxing credit, creating a temporary illusion of stability. When that illusion ended, the debt moved to the public balance sheet. The current cycle follows the same structure but with no external geography left to absorb displaced labour.
Policy inevitability
Eventually, the burden of sustaining incomes in an economy with shrinking wage share falls to the state. The sequence is visible already: growing fiscal transfers, rising deficits, and renewed discussions of income support. These are fiscal responses to a technological displacement problem. From a monetary perspective, they represent the next phase of the long transition from private to public balance-sheet expansion.
Market consequences
If this interpretation is correct, the financial system faces a structural choice. Either artificial intelligence’s productivity gains are slower and less disruptive than expected, allowing the current debt-based model to survive longer, or the transition happens quickly and forces a reconfiguration of policy, taxation, and money itself. In either case, assets that sit outside the credit system, such as gold and bitcoin, gain relative credibility. They are not claims on future income but stores of value in a world where income generation itself is being mechanized.
An uncomfortable symmetry
The irony is that the technology designed to make production infinitely efficient may simultaneously make the monetary system that funds production increasingly unstable. The more perfect the efficiency, the fewer the paychecks; the fewer the paychecks, the greater the reliance on credit and fiscal transfers; the greater the transfers, the weaker the currency. The logic loops back on itself.
Artificial intelligence therefore represents more than a technological shift. It is an accelerant for an already fragile monetary order, forcing a collision between exponential productivity and linear debt obligations. The outcome is not yet visible, but the direction of tension is clear: a world where growth depends on policy-created income and where collateral, not credit, becomes the true measure of safety.
Fragile Fiscal Math in the United States
The dependence on asset prices
The United States’ fiscal position is now so stretched that market stability has effectively become a policy objective. Between 15-20% of federal tax revenues are derived from capital gains, compared with 2-3% in countries like India. Any prolonged correction in equities or housing would therefore reduce fiscal receipts and widen an already large deficit. Rising markets are no longer a sign of prosperity alone; they have become essential to fiscal viability.
The constraint of high valuations
Steve Hanke’s observation that the ratio of US market capitalization to money supply is approaching dot-com levels highlights the fragility of this arrangement. With valuations already stretched and liquidity ratios deteriorating, any monetary tightening aimed at restoring balance risks impairing tax revenues and financial stability simultaneously.
Fiscal and monetary authorities thus face a narrow path. They must sustain growth and asset prices to preserve revenues, yet must also manage inflation and currency credibility.
India: Reflating a High-PE Market
This entire section is credited to Ridham Desai
A divergence from the global rally
Until early 2024, India’s equity markets moved almost in lockstep with the S&P 500, maintaining a correlation above 90%. That link has now broken. While global indices have advanced on the back of artificial intelligence optimism and liquidity expansion, Indian equities have lagged. The reason lies in the arithmetic of nominal growth and valuation.
The problem of low nominal GDP
In India, corporate profitability and equity valuations depend on both volume growth and price growth. Together they form nominal GDP. For over two decades, India’s nominal growth averaged around 12%, a level that allowed the market to sustain higher valuation multiples. In the current cycle, nominal GDP growth has fallen to about 8%.
At this pace, the earnings power of the economy cannot justify the same price-to-earnings ratios as before. The market’s structural premium, long anchored by expectations of double-digit nominal growth, becomes harder to defend. Without inflation providing the price component, and with volume growth moderating, valuations begin to rest on a thinner base.
Policy responds through reflation
The authorities have recognized this imbalance. Coming out of the pandemic, India’s policymakers ran tighter monetary and fiscal settings than most emerging markets. The Reserve Bank of India and the government feared post-COVID inflation and acted pre-emptively, tightening liquidity and keeping real rates positive. The result was one of the world’s most controlled inflation outcomes, but it came at the cost of slowing nominal growth.
By mid-2024, as election-related spending subsided and a poor monsoon reduced rural demand, growth softened further. Fiscal deficit fell from 6% to about 3.5% of GDP, real rates rose, and credit conditions tightened. The policy pivot began in February 2025. The central bank cut the repo rate and the cash reserve ratio, infused liquidity through open market operations, and encouraged banks to lend more freely. In capital-market terms, this is a deliberate reflation trade .
India is now attempting to raise inflation instead of suppressing it. For nearly a decade, policy was disinflationary; the next phase aims to restore nominal momentum. If successful, the next twelve months could see stronger corporate earnings, higher credit growth, and a recovery in nominal GDP toward its long-term average.
Sensex in gold terms
When measured in gold, the Indian equity market tells a different story. The Sensex’s value in ounces of gold has fallen sharply, now hovering near levels last seen during major crisis episodes such as the 2000 tech bust, the 2008 global financial crisis, and the 2020 pandemic. The difference today is that there is no visible crisis. Measured against the world’s oldest yardstick of purchasing power, Indian equities are trading at historically low real valuations.
This divergence illustrates the theme from earlier sections: nominal prosperity can mask real stagnation. In rupees, the market appears expensive; in gold, it looks depressed. The coexistence of these two realities shows how asset inflation and currency depreciation can offset each other, leaving real wealth unchanged.
Why foreign investors remain cautious
Foreign institutional investors have been slow to return. Several reasons explain their restraint:
- Absolute valuation discomfort : Although relative valuations have improved (India now trades near 20 times earnings versus China’s similar multiple) absolute levels remain high by emerging-market standards.
- Absence of an AI trade : The global rally has been driven by artificial intelligence and technology themes. India lacks a direct AI analogue, and its listed universe offers few ways to participate in that narrative.
- Strong domestic ownership : A powerful domestic bid continues to support equities. Foreign investors competing with local mutual funds and retail flows must drive prices materially higher to attract supply, reducing potential returns.
- Passive outflows : India’s weight in global and emerging-market indices surged through 2023 but has since receded as China outperformed. Index rebalancing has mechanically triggered selling, compounding net foreign outflows.
These factors have combined to create one of the longest periods of foreign selling in recent years, despite India’s strong macro fundamentals.
Reflation as the bridge
Ridham Desai’s framework provides a useful lens. The current policy shift is designed to reflate the system, to push inflation and nominal GDP higher so that valuations and earnings can reconnect. Early indicators suggest that the effort is gaining traction. Lending growth is improving, rural demand is recovering, and government capital expenditure remains elevated. If inflation settles near 4-5% and real growth remains around 6%, nominal growth could return to the 12% zone that historically supports market multiples.
The immediate risk is overshooting. If liquidity injections lift asset prices faster than earnings, valuation pressure will reappear before fundamentals catch up. Conversely, if the reflation fails to ignite demand, corporate earnings will continue to lag and the market may drift sideways despite abundant liquidity.
The illusion of stability
While valuations remain high and earnings visibility uncertain, the volatility index tells a different story. The India VIX has fallen to one of its lowest readings on record. The market is pricing tranquillity at precisely the point where macro conditions are being rewritten. Currency weakness, uneven monsoon patterns, fragile external demand, and global policy divergence are all present, yet implied volatility is lower than during periods of sustained calm.
Such compression often precedes expansion. Periods of artificially low volatility signal not the absence of risk but the abundance of liquidity. When the liquidity cycle turns or policy priorities shift, volatility tends to reprice suddenly.
Reading the divergence correctly
The apparent contradiction between low volatility and weak participation captures the market’s uncertainty. Domestically, investors see reflation as a policy tailwind; globally, allocators perceive stretched valuations and limited new narratives. The result is a stand-off: steady prices, low volatility, and little conviction.
For patient investors, this environment offers opportunity. Businesses positioned to benefit from reflation (those exposed to credit, housing, consumption, and infrastructure) may experience meaningful earnings growth if nominal momentum returns. Equally, the market’s discount in gold terms implies that India’s real assets remain relatively inexpensive for those measuring wealth in alternative units of account.
A market waiting for confirmation
India’s next leg of performance depends on two confirmations: the success of policy-induced reflation and a revival in earnings momentum. If these materialize, the market can justify its valuations and rejoin the global rally. If not, India will remain an expensive market in nominal terms and a stagnant one in real terms.
The paradox is that both readings are true. Nominal prosperity and real cheapness coexist, just as they did in earlier cycles when the denominator (money itself) was shifting beneath the surface.
Way forward
Position, not predict
Forecasting turning points in monetary regimes is rarely possible. Positioning, however, can be deliberate. The world that is emerging favors assets that do not depend on perfect financial intermediation to hold their value. Collateral will matter more than credit, self-financing capacity more than leverage, and tangible utility more than narrative.
Build portfolios around collateral strength
Within that framework, gold and silver remain the clearest expressions of balance-sheet caution. They represent the reassertion of collateral over promise. Bitcoin, though more volatile, functions as an additional ledger of scarcity. Equities backed by real cash flow and low external financing needs fit the same logic.
India’s opportunity and test
For India, the path ahead is one of policy credibility. Reflation can succeed if it restores nominal growth without eroding fiscal discipline. Domestic liquidity is ample, demographics are supportive, and the credit cycle is favorable. What the market now requires is confirmation that earnings can translate nominal recovery into sustainable profit growth.
I would like to credit most of this work to my teachers Ritesh Jain, Luke Gromen, Steve Hanke, Ridham Desai, Mike Maloney, Arnaud Bertrand, Ishmohit Arora, and Gurmeet Chadha. I wrote this piece simply as a means of consolidating all their knowledge to paint a digestible picture for you all.
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Hey everyone,
A lot of people have reached out asking what books I’ve read this year and what I usually recommend. So I decided to put everything in one place.
I made a sheet that lists all the books I’ve finished this year, along with the ones I plan to read next. If you have any recommendations you can either comment directly in the sheet or email me at dhruvmeisheri@gmail.com.
Here’s the link:
https://docs.google.com/spreadsheets/d/1NnfJlrI0XyV6c2t67vYHVOmNcY-jlO2s54Nlcjnk6zM/edit?usp=sharing
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Sharing another macro essay I wrote titled “A Cycle Built on Borrowed Time”.
It covers the stress building in US liquidity markets, the AI capex boom, the misunderstood debt cycle, India’s long-awaited consumption turn, and the growing constraints around energy and infrastructure.
A quick heads-up: this is a long one. It’s the most thorough memo I’ve written so far, and I think it’s also my best. It’s worth reading slowly.
What changed this month
Over the last few weeks a few quiet indicators have started to move together in a way that is hard to ignore. None of them, on their own, is dramatic. Taken together, they say more about where we are in the cycle than another all time high in the index.
On the plumbing side, the secured overnight funding markets have started to strain. As Luke Gromen has pointed out, repo rates have been ticking higher at the same time that the US Treasury has been rebuilding its General Account from $300bn to close to $1tn. That cash has to come from somewhere. In practice it means more bills, more frequent refinancing, and more demand for short term funding in a system that has struggled to term out its debt.
At the same time, rate expectations have swung sharply. Ritesh Jain notes that the probability of a December rate cut went from almost 90% at the end of October to roughly 30% a few weeks later. The Federal Reserve itself is split down the middle between those who want to cut and those who do not. It is rare to see such a divide inside the committee. Markets have spent most of the last month repricing that shift in expectations rather than responding to any single data point.
Beneath the headline indices the real economy is losing momentum. Job postings on Indeed are back to levels last seen in early 2021. Challenger’s layoff data shows job cuts in October running at almost three times September’s pace. S&P Global counts the highest number of large corporate bankruptcies in about fifteen years. Visitor traffic to Las Vegas is falling at a rate last seen during the global financial crisis. All of these are small straws, but they point in the same direction.
The policy response is already forming. The Kobeissi Letter has been tracking a new wave of fiscal and monetary support: proposed stimulus cheques in the United States, fresh packages from Japan and China, Canada restarting quantitative easing, the Federal Reserve winding down quantitative tightening, and more than 300 rate cuts globally over the last two years. Global broad money is at a record high. In other words, just as labour and demand begin to soften, another round of stimulus is lining up.
This sits on top of an artificial intelligence capex boom that is still doing much of the heavy lifting for headline growth. The same data centre spend that props up reported GDP also raises questions about power, water, and the durability of the assets being built. I will come back to that later in the memo, because it matters for both credit and equity markets.
The U.S. funding system is starting to creak
The clearest stress this month has come from repo market. As Luke Gromen has highlighted, secured overnight funding rates have begun to rise in a way we haven’t seen for years. It may look like a small move on the surface, but repo is the foundation of the entire US funding architecture. When that market tightens, it usually means something upstream is forcing the system to work harder than it wants to.
As I wrote earlier, part of the strain comes from the Treasury’s rebuilding of its General Account. The balance has climbed from roughly three hundred billion dollars to almost one trillion in only a few months. To refill that account the Treasury has had to issue an enormous volume of short-dated bills. More bills mean more refinancing. More refinancing means more reliance on repo. And more reliance on repo raises the clearing rate for every leveraged participant in the system.
That brings us to the marginal buyer of long-end Treasuries. It isn’t China or Japan anymore. According to the Federal Reserve’s own data, the biggest incremental buyer has been a cluster of Cayman-domiciled hedge funds running highly levered basis trades. They own close to $1.8tn of Treasuries, financed largely in repo at leverage ratios that can run 50-100x. When repo rates rise, the funding leg of that trade gets squeezed. If that squeeze continues, they may have to shrink their positions. Shrinking those positions in an illiquid long-end market pushes yields higher, weakens equities, and feeds back into more deleveraging. This is the cycle Gromen has been warning about.
There is also a broader macro consequence. Consumption makes up roughly 2/3 of US GDP, and a meaningful part of consumption growth now depends on asset prices rising. Net capital gains and taxable distributions alone are almost twice the annual growth of personal consumption expenditures. In plain terms, the household sector cannot keep spending if equity markets decline.
AI: Productivity boom and credit risk
Artificial intelligence is often described as the new general-purpose technology, something that can lift productivity across the economy the way electricity or the internet once did. That may be true, but as Luke Gromen keeps reminding, productivity alone doesn’t tell you how the credit system absorbs that shock. The United States is built on a model where employment, wages, and debt service reinforce each other. When technology weakens the wage component, the rest of the structure feels it.
The closest historical parallel is not another tech cycle but what China’s entry into the WTO did to the American industrial belt. A massive wave of cheaper supply, far more efficient production, and fewer constraints on labour and regulation. Unemployment in certain cohorts fell by a third in the years that followed because the entire employment base shifted. The early signs of something similar are already visible in the US. Unemployment among bachelor-degree holders in the 20-24 age group is around 7%. If a comparable shock hits the 25-45 age band, which anchors mortgages, car loans, and most consumer credit, the entire lending system comes under pressure.
The capex cycle itself carries echoes of past bubbles. In the telecom boom of the late 90s, companies borrowed heavily to lay fibre long before they had the revenues to justify it. The shale boom a decade later followed the same pattern: rapid capacity buildout funded by cheap debt, declining well productivity, and poor recovery values on the underlying assets. AI risks the same dynamic but with one important difference. Data centre chips have a useful life of three to four years. By the time the next generation arrives, the current generation is close to obsolete. That might question the recovery value of the capex that is being built today.
The bottleneck is no longer the chip itself but the infrastructure that supports it. Electricity, water, and specialized labour are all becoming constraints. Several data centre projects on the US West Coast have been pushed out toward the end of the decade because utilities cannot guarantee the power. Bloomberg recently wrote about NVIDIA-linked facilities sitting unused because they cannot get the required hookups. Water-cooled chips sound elegant until you have to source and transport the volume of water these clusters require.
For now, much of the AI spend has been funded through retained earnings and equity. That is changing. Companies have begun issuing debt to keep pace with the capex cycle. If the returns on that investment arrive slower than expected, the mismatch between short-lived assets and longer-dated liabilities becomes important.
AI may well raise long term productivity, but in the short run it widens the gap between output and income. That gap sits at the heart of the US credit system.
The U.S. labour market is weakening
The softening in the labour market has been gradual rather than dramatic. The headline unemployment rate still looks stable, yet the underlying indicators tell a different story. Steve Hanke notes that job postings on Indeed have fallen more than 6% YoY, returning to levels last seen in early 2021. Openings have been slipping for months, and the gap between available jobs and job seekers is closing quickly.
Layoff data reinforces this. According to Challenger, Gray and Christmas, US companies cut more than 150,000 jobs in October, nearly triple the number from September. They span technology, logistics, retail, and even sectors that benefitted from the post-pandemic recovery.
Bankruptcy trends echo the same theme. S&P Global reports that more large US companies have gone bankrupt this year than at any point in the last 15 years. The failures are not limited to over-levered businesses. They include firms facing weaker demand, higher financing costs, and declining pricing power.
The stress is now visible in consumer behavior. Las Vegas visitor traffic, often a good proxy for discretionary spending, has fallen sharply, matching rates seen during the global financial crisis. Surveys show household sentiment deteriorating, especially among younger graduates and middle-income households.
None of these indicators on their own mark a turning point. But taken together, they describe a labour market losing breadth and confidence just as stimulus discussions reappear. It is the combination that matters: softer demand, rising layoffs, and a policy environment shifting back toward liquidity support.
Why “bad news for consumers” is becoming “good news for markets”
One of the stranger dynamics in this cycle is the widening gap between the economy that households experience and the one financial markets are pricing. The Kobeissi Letter captured it well: even as the S&P 500 hits new highs and the largest technology companies exceed $20tn in market capitalization, a majority of Americans believe they are in a recession. Young graduate unemployment is nearing 10%, and real disposable incomes remain under pressure.
This divergence matters because it shapes policy. When consumer sentiment deteriorates and labour markets weaken, governments respond with stimulus regardless of whether asset prices are already elevated. That pattern is now global. The United States is preparing direct transfers, Japan has announced a $100bn package, China has approved more than a trillion dollars in fiscal support, and Canada is restarting quantitative easing. Central banks worldwide have cut rates more than 300 times in the last two years, and global money supply has reached a record $137tn.
The irony is that the sectors driving equity indices (large-cap technology, AI infrastructure, and capital-light digital businesses) do not need rate cuts or stimulus. But everyone else does. And because markets are now so heavily weighted toward companies that benefit from liquidity rather than broad economic strength, stimulus meant for households ends up amplifying asset prices instead.
The result is a redistribution effect: nominal asset values rise while real consumer conditions lag. Asset owners gain, wage earners tread water, and the distance between the two widens. It is the logical outcome of a system where financial easing is the default response to economic strain. Markets read weak consumer data not as a warning but as a signal that more liquidity is coming.
This is the uncomfortable symmetry of the current regime. The worse conditions look for the median household, the more supportive the environment becomes for financial assets.
DSP’s contra view: The debt story is not what people think
This entire section is credited to Sahil Kapoor from DSP.
Every cycle produces at least one perspective that sharply diverges from consensus. Sahil Kapoor from DSP provides that counterweight this time. While most commentators frame the United States as drowning in debt and heading toward inevitable currency debasement, he argues that the real picture is more nuanced and, in some ways, misdiagnosed.
The hidden truth about U.S. debt
The headline number, federal debt at nearly $38tn, is alarming. But when DSP decomposes the system into its three borrowers (households, non-financial corporates, and the federal government), a different pattern emerges. After the 2008 crisis, households deleveraged aggressively, and corporate borrowing grew at a manageable pace. The only balance sheet that truly blew out was the federal one.
Total non-financial debt as a share of GDP was about 250% in 2009. After rising sharply during COVID, that ratio has fallen back to roughly 246% today, almost the same level as fifteen years ago. In other words, the system is not uniformly over-levered. What has deteriorated is Washington’s balance sheet, not the private sector’s. That distinction is often lost in the broader narrative.
Why foreign central banks really stopped buying treasuries
The popular explanation is that foreign central banks “lost faith” in U.S. Treasuries and switched into gold. Sahil challenges this. If preferences had truly shifted years ago, gold should have risen sharply starting in 2014. It didn’t. For nearly a decade, gold was flat to down.
The more compelling explanation is that EM central banks did not stop buying Treasuries because they disliked them, but because they stopped earning the dollars needed to buy them. After the 2013–14 U.S. shale boom, America dramatically reduced crude oil imports. Countries that once ran large surpluses against the U.S. suddenly saw those flows evaporate. Without dollar inflows, they could not accumulate Treasuries even if they wanted to.
Reframing the USD bear narrative
The U.S. fiscal position is undoubtedly stretched, and long-term sustainability is a legitimate concern. But the private sector is far healthier than the headline numbers imply. Household leverage is contained, corporate balance sheets are stable, and the overall debt-to-GDP ratio has not deteriorated materially relative to the past.
As for the idea that the world is “moving away from the dollar,” DSP argues that this, too, is incomplete. A dollar shortage still exists across large parts of the emerging world. Without sustained surpluses against the U.S., they cannot rebuild Treasury holdings even if they wished. That structural constraint keeps the dollar stronger for longer than the bearish narrative often suggests.
DSP doesn’t dismiss long-term risks. But their work is a reminder that monetary transitions are rarely linear.
India’s consumption slowdown and the turn
The story of India over the past two years is largely the story of its middle class. Consumption accounts for roughly 60% of the economy, and when the middle-income segment slows, the broader economy inevitably follows. That slowdown became visible after the initial post-pandemic rebound faded.
Why India Slowed
A combination of policy and labour-market dynamics created the drag. To finance one of the largest public-capex cycles in recent history, the government increased income-tax collections and GST revenues. Middle-class households absorbed the bulk of that adjustment. Higher taxes could have been offset by strong job creation, but by 2022 the pace of hiring began to weaken. Wage growth in the top 50 listed companies averaged just 3% over three years, while inflation held near 6%, pushing real wages negative. At the same time, household leverage rose sharply. Excluding home loans, households now carry debt equal to roughly 1/3rd of their annual income, among the highest ratios globally. When taxes rise, wages stagnate, and leverage climbs, consumption inevitably slows.
The 6.3 Trillion Rupee Stimulus Reversal
The good news is that policy has pivoted decisively. Since the start of the year, a coordinated easing across taxes, regulation, and monetary policy has redirected an estimated 6.4tn rupees back into household cash flows. Income-tax cuts delivered around 1tn. A suite of GST reductions added another 2tn. The ban on real-money gaming redirected close to 700bn. Expected curbs on F&O trading could release nearly 1tn more into the real economy. The RBI contributed with four rate cuts amounting to a full percentage point, injecting an additional 1.6tn rupees through lower borrowing costs. Together, this is one of the most significant pro-consumption adjustments in recent years. The effects should begin to surface meaningfully from December onward.
Household Balance-Sheet Risks
The challenge is that Indian households enter this recovery from a weak starting point. According to Marcellus’ survey data, 14% have no emergency savings, and roughly half have buffers equal to only 20% of their income. Household savings as a share of GDP are near a fifty-year low. These metrics do not prevent a consumption rebound, but they make it more sensitive to employment trends and policy support. The new stimulus will help, but repairing balance sheets will take time.
The direction of travel is now improving. Policy has shifted toward reflation, liquidity conditions are easing, and early indicators show stabilization in household demand. Whether this translates into a sustained earnings recovery will depend on how quickly consumption resets after two years of pressure.
Energy, infrastructure, and power as the new constraint
One of the clearest signals that the global economic model is shifting comes from electricity. For years, cheap power and abundant grid capacity were taken for granted in developed markets. That assumption is now breaking down. Ritesh Jain’s recent observations make the scale of the issue hard to ignore.
In Oregon, a Berkshire Hathaway–controlled utility that contracted power to Amazon in 2020–21 can no longer deliver the electricity it promised. Similar strains are emerging across the United States. Several NVIDIA-linked data centre projects in California are reportedly sitting dark because the grid cannot support them. Developers in other states are pushing completion timelines out to 2030 simply because they do not expect to receive timely grid connections. The bottleneck is not chips, or capital, or software talent. It is power.
This constraint is becoming visible in household economics as well. Over the past fifteen years, US electricity prices have quadrupled. For households in the bottom income quartile, electricity now consumes close to 30% of take-home pay. In Virginia, political campaigns centred on reducing power bills were decisive in recent elections. Energy affordability has quietly become a frontline economic issue in a country that once treated electricity as an afterthought.
The link to artificial intelligence is direct. AI is an energy-intensive technology. Every incremental wave of compute requires disproportionately more power, cooling, and infrastructure. Unlike the telecom and shale-capex cycles, which at least created long-lived assets, the useful life of AI hardware is short. Chips turn over every few years, but the electricity and water required to operate them are continuous constraints. As data-centre construction accelerates, the grid is becoming the limiting factor on growth.
In macro terms, this is the new scarcity. For four decades, the binding constraint was capital. Today, it is energy infrastructure. The fiscal and geopolitical implications are significant. Countries with surplus electricity, stable grids, and reliable generation will attract the next wave of industrial and digital investment. Regions with fragile grids will face higher costs, delayed projects, and political pressure to subsidize power.
Way forward: Position, don’t predict
The themes across this memo point in one direction: the system is moving toward a world where collateral, energy, and nominal liquidity matter more than forecasts. The task is not to predict turning points but to position portfolios around the constraints that are already visible.
The first anchor is real collateral. Gold, silver, and other hard assets remain the clearest safeguards in a regime where monetary claims expand faster than the income required to support them. They are the insurance against fiscal and geopolitical fragility. In the same vein, equities backed by tangible assets, self-financing models, and low dependence on external leverage offer better durability than capital-light businesses reliant on perpetual liquidity.
The second anchor is power and energy infrastructure. Electrification is becoming the defining bottleneck of this cycle. Countries and companies with stable grids, surplus generation, and efficient transmission networks will capture outsized investment flows.
A related opportunity lies in the AI supply chain, but with a specific lens. The bottleneck is not chips alone; it is electricity, cooling, water, and grid access. Businesses positioned upstream of the compute cycle (power, engineering services, specialized infrastructure, and efficiency technologies) will likely see more durable demand than the end-users of the chips themselves.
India offers its own distinct path. A revival in consumption, supported by the 6.3tn rupee policy reversal, can unlock earnings growth across credit, housing, staples, and discretionary categories. The opportunity is not broad-based yet, but the direction of policy suggests that domestic demand will strengthen over the coming quarters.
Across regions, the likelihood of nominal asset inflation remains high. Global liquidity is expanding, fiscal stimulus is accelerating, and central banks have already demonstrated a willingness to ease at the first sign of labour-market weakness. In such an environment, asset prices may continue rising even as real economic strain persists.
The path ahead does not require perfect foresight. It requires alignment with the structural forces now shaping the cycle. Choose hard collateral over credit, energy capacity over narratives, and domestic demand over speculative liquidity. Positioning, not predicting, is my central discipline.
I would like to credit most of this work to my teachers Ritesh Jain, Luke Gromen, Steve Hanke, Ishmohit Arora, Saurabh Mukherjea, Sahil Kapoor, and The Kobeissi Letter. I wrote this piece simply as a means of consolidating all their knowledge to paint a digestible picture for you all.
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Portfolio as of 1st December
| Stock/commodity | Value |
|---|---|
| Gold | 10.71% |
| Bondada Engineering | 6.30% |
| Samhi Hotels | 13.00% |
| TD Power | 12.40% |
| JM Financial | 6.19% |
| Aditya Birla Capital | 5.95% |
| Time Technoplast | 4.50% |
| Silver | 15.47% |
| Goodluck India | 4.61% |
| Oswal Pumps | 3.08% |
| Max Estates | 3.94% |
| Parag Milk | 7.24% |
| Alpex Solar | 3.97% |
| Cash | 2.63% |
Changes made in November:
- Exited Narayana Hrudayalaya
- Bought Bondada Engineering
- Trimmed position in TD Power
Purchase Thesis:
- Bondada Engineering: An EPC and O&M business operating in the telecom and solar energy industry. They’ve got strong order book visibility and operate high-growth, lucrative businesses such as BESS, renewable energy, and is also preparing to launch its first IPP project. I’ve posted a thorough analysis with the valuation math here.
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Hi Sir,
Please share your learning and research sources, I am a beginner relatively.
Please don’t call me sir, I’m still in college!
I will break this answer into two parts: Stock/sector-specific and macro.
For stocks and sectors, the best resource is, with no doubt, SOIC. If you can get their membership, it would be pivotal in your approach to screening and analysis, but Ishmohit also uploads videos on YouTube for free. I also use the ValuePickr community a lot as it helps for scuttlebutt research. For industry insights, there’s always a few journals available online, as well as sell-side reports you can read to get a feel for the sector.
For the macro environment, I mainly read the news (FT, WSJ, Bloomberg) and listen to experts on YouTube. My favorites are Ritesh Jain, Luke Gromen and Ridham Desai.
Lastly, you could also read books. As one of my mentors once told me, after you read 15 books on self-help and investment philosophy, you should prioritize reading books on industries. Few books I’ve read on this that I recommend are Chip War by Chris Miller, The Killchain by Christian Brose, and AI Superpowers by Kai-fu Lee.
Hope this helped! If anyone has extra resources, please do share them.
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Was reading Annie Duke’s “Thinking in Bets” this morning and had some reflection. Where did I go wrong this quarter (I allocated during this quarter)? I guess one could say we were fooled by Q2 earnings? There were loads of companies at 50+ PE multiples that were unjustified and the gap between public and promotor shareholding was close to its all time low.
This one was tough to foresee and easy to say in hindsight. But I definitely followed a group of people who built an echo chamber of my own perspectives. Had I come across people who questioned my views and encouraged me to be open-minded, maybe I would have been more conservative in my thinking, who knows.
But, on the bright side, ATHs in gold and silver are saving me!
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Hi Dhruv,
Great portfolio and even greater insights.
Have you checked Afcom Holdings by any chance?
I already have Alpex in my portfolio, was planning to add one more SME. Bondada/Oriana both look great from the Renewable energy space, but for sector diversification I am tilting towards Afcom.
Would be great to hear your thesis on it or other small//micro cap stocks you are tracking.
I read through the entire thread Dhruv. Good insights.
From May to Nov, in 6 months, you have churned ~40% of your portfolio (exiting NH, Thangamayil, Pokarna and Garware) that is quite a bit of churn.
I have some of the stocks in my portfolio as well. My only word of caution - I saw a lot of names that you mentioned from where you are learning - a lot of them are good marketeers - and they will be able to build a thesis for any business. (case in point: Relaxo, Marcellus). And many of these stocks are popular among the punters. So make sure you try to seek more contrarian views.
At the end of the day, a lot of business building is executing well on boring stuff for a long period of time, being in the right industry and not doing illegal things.
Again good work and all the best.
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Thank you sir!
I haven’t researched Afcom yet, but will get to it soon and post my thoughts here.
Regarding Alpex and other renewable energy cos, I’ve heard there is massive oversupply in the market. One of my teachers told me that, out of every 10 Private Equity offers he gets, 6-7 are in renewable energy. I am considering exiting Alpex, but at the same time we have the Indian solar mandate in June 2026.
Some other cos I am tracking are:
- Aarti Pharmalabs (see my note here)
- Acutaas Chemicals
- Vishnu Chemicals
As you can probably tell I want some exposure to specialty/pharma chemicals.
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Thank you for your feedback sir, I noticed the churn too and will try to keep it to a minimum next year. Think I fell for some of the market lows and got impatient. As Pulak Prasad says “do not confuse stock price fluctuation with business punctuation.”
You made a good point on the people I follow, and I’m definitely actively seeking out contrarian views. My stock theses are almost entirely built upon my own research, but I do rely on a lot of names for my macro understanding, which is why I plan on expanding my sources for the coming macro memos.
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My thoughts on Afcom Holdings
I was unable to find Q1 or Q2FY26 concalls, so am basing this off external research as well as the VP thread made by @rks00 recently (It was brilliantly written, worth reading):
The growth is really from the 3 planes to be added by end of FY26, bringing the total fleet to 5. But one aircraft will be kept as backup so its utilization will be low. Even on conservative assumptions, I believe they can double revenue at a minimum (management has guided for ~4x growth for FY26) This expansion will make them a scheduled operator which enables them to get fixed slots assigned and 1% less tax on fuel, along with other cost benefits.
Also, there is definitely public and promotor interest, as one can see in their recent BSE announcement.
However, my issue comes with their utilization rates and few instances of misinformation by management mentioned by @TatTvamAsi. He noted that recently the frequency of trips increased but revenue has not matched this, as there was a lower proportionate increase. So, unless we see significant increase in cargo volume, utilization rates are decreasing.
To put it simply: there is route expansion, fleet expansion, topline + margin expansion, and equity expansion with promotor participation. So, at face value, all in the right direction. I would monitor their utilization rates in the coming quarters.
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Thanks for the reply 
Had similar doubts, but have taken some position for now, will be tracking closely!
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Happy New Year! Many people have been curious about my performance, so I decided to share an annual note. I do not plan to share this over shorter time periods, as my objective is not to optimize for short-term compounding.
In 2025, my portfolio delivered an absolute return of 27%, with an XIRR of 44%. A meaningful portion of this performance was driven by my positions in gold and silver, where I was able to enter at an attractive point with a sizeable allocation. Without commodities, the absolute return for equities was 19%. The higher XIRR reflects the impact of timing, so it should be taken with a pinch of salt.
This was an exceptional year, and I do not expect the commodity rally to continue at the same pace. As many of you know, I remain conservative in my assumptions and expectations. While the outcome was a pleasant surprise, there was an element of luck involved and I do not expect this level of growth to persist going forward.
Portfolio as of 1st Jan 2026
| Stock/Commodity | Value |
|---|---|
| Gold | 10.4% |
| Silver | 16.0% |
| Bondada Engineering | 5.7% |
| Samhi Hotels | 11.2% |
| TD Power | 9.9% |
| JM Financial | 5.5% |
| Aditya Birla Capital | 5.6% |
| Time Technoplast | 4.1% |
| Aarti Pharmalabs | 1.5% |
| Goodluck India | 3.8% |
| Oswal Pumps | 2.8% |
| Max Estates | 3.5% |
| Parag Milk | 6.0% |
| Alpex Solar | 3.7% |
| Kilburn Engineering | 4.1% |
| Cash | 6.0% |
Changes made in December
- Bought tracking position in Aarti Pharmalabs
- Sold and re-bought silver at a lower price (explained below)
Theses
- Aarti Pharmalabs: An internationally recognized manufacturer of generic API & Intermediates, Xanthine derivatives, and offers CDMO/CMO services. I am expecting high growth in the high-margin CDMO segment, and they are making significant expansions in Xanthine production as well. I’ve posted a thorough analysis with the valuation math here.
- Silver: In the last 2 weeks, we saw silver go from $70 to $80 in a few days. Looking at technicals and the fact that this level of momentum can’t be sustained for a commodity, I decided to sell my position. On average silver is roughly 2% of the value of gold, so at current prices one could say its fair value is $88. My thinking was the following: I will buy silver back at lower levels, but if it continues to rally I will not be entering again and am happy with my gains.
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Sharing my macro essay titled “A World of Binding Constraints”. I am only sharing the section I wrote on India, but if you are interested in the full piece, you can click the link below. I wrote more about electricity bottlenecks in America, the AI “bubble”, and gold.
Section on Indian Markets
The Market Everyone Gave Up On (Ridham Desai)
India’s equity market has been the weakest-performing large market globally over the past year. Among the top twenty markets by size, it ranked last, while peers delivered gains ranging from 20% to 70%.
The slowdown was driven by a cluster of idiosyncratic factors. Election-related pauses in government spending slowed activity at the margin, excessive rainfall disrupted parts of the rural economy, monetary policy remained tight for longer than expected. Together, these forces weighed on GDP growth and corporate earnings momentum, and that softness fed directly into share prices. That phase is now turning. The RBI has pivoted decisively, cutting the cash reserve ratio and interest rates in April in a move that is rare outside periods of acute stress. This shift has been reinforced by fiscal and regulatory actions from the government, creating an unusually coordinated policy impulse aimed at restoring growth. The breadth and timing of that response suggest the cyclical downswing is ending.
Valuations have also done a large part of the adjustment. India’s relative multiples had reached extremes that made foreign capital increasingly cautious, but over the last year, that premium has compressed sharply. On few measures, India now trades near lows relative to global peers. As valuation pressure eases, the marginal incentive for foreign selling diminishes.
A separate headwind came from the global obsession with AI. Capital crowded aggressively into markets and companies offering a direct AI narrative, leaving India structurally underrepresented in that trade.
What makes this cycle different from earlier slowdowns is what has changed beneath the surface since 2007 and 2013. India’s historical vulnerability lay in its external balance sheet. Oil shocks translated directly into balance-of-payments stress, currency weakness, and policy tightening. That channel has been structurally altered. Oil intensity has fallen sharply through a combination of logistics efficiency, highway expansion, GST-led removal of border delays, near-complete railway electrification, rural electrification, and ethanol blending. Even when oil prices spiked in 2022, India avoided the crises that defined earlier cycles.
Capital flows have also become more stable. Foreign direct investment has risen as a share of inflows, reducing dependence on volatile portfolio capital. In prior downturns, FPI outflows amplified domestic slowdowns and forced abrupt adjustment, and that amplification mechanism is weaker today. Capital committed to long-term capacity, services, and manufacturing is less sensitive to short-term sentiment and currency moves.
The income structure of the economy has transformed as well, with extreme poverty being largely receded. India now has a meaningful cohort of households with global-level purchasing power, layered above tens of millions of consumers whose spending responds quickly to incremental income gains and price changes. Small shifts in policy, taxation, or financing conditions translate into large changes in demand. As a result, India already contributes close to a fifth of global growth, and that share continues to rise. For many multinational companies, India now accounts for a disproportionate share of incremental revenue growth.
Manufacturing, long discussed but rarely delivered, is also becoming viable in a sustained way. The constraints that once held it back (complex taxation, weak infrastructure, rigid labor laws, and high logistics costs) have been systematically addressed. The combination of physical infrastructure buildout, tax reform, digital public goods, and regulatory simplification has lowered the threshold for scale. This does not produce instant results, but definitely changes the trajectory.
Is 10% Nominal Growth Enough? (Sahil Kapoor)
India’s nominal GDP growth has slowed to roughly 9–10%. On the surface, this appears reasonable due to uneven global growth. The problem lies in the asymmetry. Inflation has declined from around 7% to closer to 5%, a compression of roughly 200 basis points. Nominal growth, however, has fallen by more, closer to 260–300 basis points.
At this stage of India’s development, 10% nominal growth is not sufficient. Sustained over the next 15–20 years, it would fail to fully monetize the demographic dividend, complicate the transition to middle-income status, and leave the economy vulnerable to stalling just as the demographic window begins to close. For a country still converging toward higher income levels, nominal growth needs to be meaningfully higher to absorb labor, build capital stock, and compound incomes fast enough.
The key point is that 10% nominal is an outcome of deeper balance-sheet dynamics.
The first constraint sits with households. India’s growth model relies on a simple structure, and households are the only net savers in the economy. Corporates and the government are net borrowers, making household balance sheets the foundation of sustainable growth.
During the prior strong cycle from FY01 to FY13, consumption growth was driven by rising incomes rather than leverage. Wage growth was robust, household savings were healthy, and consumption loans were falling as a share of spending. This created the most durable form of demand expansion: income-led consumption that reinforced savings rather than eroding them.
In the current cycle, the composition has shifted. Income growth has slowed, while household debt accretion has risen. Consumption has weakened because incremental spending is increasingly debt-funded rather than income-funded. This dynamic caps how fast demand can grow. Even moderate leverage growth, when combined with slower income expansion, places a ceiling on nominal GDP growth. The result is an economy that grows, but not fast enough for its stage of development.
The second constraint is investment. To test whether capex could offset softer consumption, a broad-based tracker covering all major sources of investment was constructed by DSP. The conclusion is unambiguous: Central government capex is the only component outperforming the previous cycle. Every other driver is growing more slowly, often below nominal GDP.
The most striking datapoint comes from listed corporates. Capex by BSE 500 companies compounded at roughly 26% during FY01–FY13. In the current cycle, that figure has fallen to around 9%. Even 9% growth is not weak in isolation, but it is far below what India historically delivered when it was successfully accelerating up the income curve. Most other capex indicators now sit in the mid–single digits, compared with double-digit or 20% plus growth previously. Government spending is filling part of the gap, but it cannot substitute for broad-based private investment.
The third pillar, exports, has also underperformed. Global demand constraints and shifting trade dynamics have limited export growth, preventing it from compensating for weaker household demand or subdued private capex. Exports are contributing, but they are not acting as a swing factor.
Taken together, India’s nominal growth rate reflects a three-way slowdown. Household income growth has softened, pulling down consumption momentum. Private capex has reset sharply lower relative to the prior cycle. Exports have remained modest. The arithmetic of these three engines leads naturally to nominal growth settling around 10%.
For India, that pace is not enough. Raising nominal growth meaningfully requires repairing household income dynamics and reigniting private investment, not merely sustaining government spending. Until those engines regain traction, nominal GDP growth is likely to remain capped near current levels, leaving a significant portion of the demographic opportunity underutilized.
Behavioral Insight: Buying at the “Worst Time” (Indian Markets)
(Ishmohit Arora & Siddhant Bhandari)
Timing worries most investors. The fear of being wrong at precisely the wrong moment. My teachers Ishmohit Arora and Siddhant Bhandari conducted a useful thought experiment that reframes this concern and grounds the broader macro discussion in actual investor behavior.
The exercise starts in January 2018, the exact peak of a prior Indian market cycle. Assume an investor who had missed the rally leading up to that point. Valuations looked stretched, markets were rising daily, and hesitation felt prudent. Eventually, frustration overtook caution and capital was deployed at the worst possible time. Importantly, this investor did not buy the index blindly. They did what most real investors do when entering late: they gravitated toward already “discovered” quality companies with strong narratives, visible earnings, and perceived durability.
The resulting basket included businesses such as Info Edge, Astral, Berger Paints, Motilal Oswal, DLF, Prestige, and similar names that were widely owned, widely discussed, and widely considered expensive at the time. From a psychological standpoint, this was the least comfortable entry point imaginable.
Yet the outcome challenges the conventional lesson drawn from market peaks. Despite buying at the top, the median return from this diversified basket of quality small and mid-cap companies compounded to roughly 3-4x capital over the next 6 years.
This matters because it reframes risk. The dominant fear during periods of uncertainty is that valuation errors permanently impair capital. What this experiment shows is that high-quality companies with strong competitive positions, clean balance sheets, and reinvestment runways tend to compound through cycles, even when purchased during moments of maximum discomfort.
In the current environment, noise is abundant. This translates into waiting for clarity that rarely arrives in real time. The lesson from my teachers’ work is not to ignore risk, but to redirect focus. Long-term compounding still accrues to businesses that execute well, reinvest intelligently, and survive difficult periods.
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Hi Dhruv,
I read through the thread and I must say you have great insights at 19 years old.
Had few questions:
- You started off trying to follow Mohnish Pabrai and his 10x10 portfolio strategy. I can see it’s changed since. So how do you approach portfolio allocation now?
- Just wanted to ask your views on Gold and Silver since It’s one of your bigger bets, especially with silver’s rally recently.
- What are your thoughts on Neogen Chemicals?
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Thank you!
- My allocation strategy has changed slightly, as I want exposure to different sectors. I don’t want to commit to a specific number but I’ll keep making sizeable investments. My top 5 bets account for almost half my portfolio.
- I believe there’s much room to grow as the Fed will likely continue cutting rates, central banks have steady demand, and there’s a lot of ongoing geopolitical tension. Gold usually moves in 8x cycles. I believe our current cycle started at ~$1150, meaning gold could potentially reach $8000 levels. We can’t expect the same growth as last year, but I do expect gold to reach $5200+ this year. Silver is, on average, 2% of the value of gold. So the fair value at that point would be $100+. It will be volatile but I am confident on the direction.
- I started tracking Neogen recently. They made a few wrong decisions in the last few years, such as the LiPF6 bet. They built capacity too early at a time where there was no customer base in India, and it’s difficult to compete with Chinese prices in export markets.
Having said that, with China’s anti-involution policies, we are seeing capaciy phasing out and consolidation in China. According to some experts, this can help India enter the export market as they won’t compete with the fragmented Chinese industry which used to sell at low prices. We are also seeing an increase in LiPF6 prices, leading to higher margins. There could be some turnaround in Neogen this year, but I would also look at Gujarat Florochem to compare.
disc: nothing is a buy/sell recommendation. Please do your own due diligence.
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Given you are studying in US, and US is leader in AI, why don’t you have any US stock in your PF?