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MicroStrategy’s ‘financial engineering’ powers ascent to Nasdaq 100

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MicroStrategy’s ‘financial engineering’ powers ascent to Nasdaq 100

MicroStrategy has raised almost $20bn from investors this year to buy bitcoin, fuelling a meteoric rise for the once-obscure software company into the Nasdaq 100 index of large-cap US technology stocks.

A combination of selling shares and convertible bonds has funded a one-way bet on a rocketing bitcoin price that, despite a sell-off in recent days, has driven its shares up more than 400 per cent this year. Such is the investor demand that the company now has a market value of around $80bn, despite owning around $41bn of bitcoin.

Debt fund managers have been clamouring to get their hands on the convertible bonds, believing they offer exposure to the soaring share price while also providing protection if the price goes into reverse. The stock’s Nasdaq 100 inclusion will compel index-tracking funds to buy billions of dollars more of the company’s shares.

Its index inclusion after the close of trading on Friday — it is part of a trio replacing IT firm Super Micro Computer, Covid-19 vaccine maker Moderna and gene-sequencing company Illumina — is further vindication for founder Michael Saylor, who has become one of the most evangelistic proponents of bitcoin since his company began buying it four years ago.

“It’s some incredible financial engineering,” said a convertible bond portfolio manager invested in MicroStrategy. “[Saylor has] created this incredible situation where a stock trades at three times the price of the underlying bitcoin and then he just sells more shares every day and buys more bitcoin.”

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Donald Trump has promised to make the US a ‘bitcoin superpower’ and ease the regulatory crackdown on cryptocurrency © Justin Chin/Bloomberg

For Saylor, who once tweeted that bitcoin’s “days are numbered” but later recanted, this year has been an extended opportunity to build on his plan to make MicroStrategy a “treasury” for what he calls “the most valuable asset in the world”. In October he announced plans to raise $42bn over the next three years, all to pay for more bitcoin.

The cryptocurrency’s value has more than doubled this year following the arrival of spot bitcoin exchange traded funds in the US and Donald Trump’s presidential election victory in November. Trump’s promises to make the US a “bitcoin superpower” and ease the regulatory crackdown pushed the value of the coin from less than $64,000 at the end of September to more than $108,000 this week, although at one point on Friday it fell close to $92,000.

“My attitude [on bitcoin] has gotten better every quarter,” Saylor told the Financial Times. “Now you have a president[-elect] who is ending the war on crypto.”

MicroStrategy’s success has been helped by the huge premium that investors place on its shares, with the company currently trading at roughly double the net asset value of its bitcoin holdings.

This allows it to issue stock at a premium and buy ever more of the cryptocurrency. Although existing shareholders end up owning a smaller percentage of the company, the underlying value of their shares increases because MicroStrategy now owns more bitcoin per share.

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Line chart of Share price, $ showing MicroStrategy shares have climbed 370% this year

Convertible bonds have also become a key way for MicroStrategy to raise money. Such instruments usually pay a fixed coupon but also convert into shares at an agreed price, allowing investors to benefit from equity’s unlimited upside while providing the perceived downside protection of bonds.

The highly volatile nature of the stock has so far worked well for both the company and investors. It means the company can issue bonds with a higher conversion premium than usual and even offer zero coupon on the debt. Investors, meanwhile, have been drawn to the potential exposure to the firm’s soaring share price and the perceived downside protection.

As MicroStrategy’s shares surged earlier this year, bond investors who had lapped up its March convertibles quickly became equity holders as their bonds were converted. In November, Saylor returned to market for the fifth time this year, issuing $3bn of convertibles for zero interest and a 55 per cent conversion premium.

MicroStrategy Inc. headquarters in Tysons Corner, Virginia,
‘It’s arbitrage feeding arbitrage,’ said one convertible bond trader who has bought MicroStrategy’s bonds and shorted its equity © Stefani Reynolds/Bloomberg

For investors who had snapped up MicroStrategy’s earlier debt, the company’s return to market could hardly have worked out better, as it allowed them to take profits on their shares and buy new bonds.

“This was an absolute home run for us. We got to lock in all of the upside of the past six months, and now we bring in downside protection,” said one convertible bond fund manager who owns MicroStrategy bonds. “There is no better outcome for a convertible bond manager.”

So-called convertible arbitrage hedge funds, which buy such bonds and then short the shares — bet on a falling price — have also provided a ready market for the firm’s mass issuance.

Their strategy is essentially a bet on volatility. They try to make money on their short position if the share price falls, with losses on the convertible limited by the bond’s downside protection. And if the shares climb, the aim is for the short position — which is smaller than the convertible bond exposure — to lose less money than the gain on the equity upside.

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“It’s arbitrage feeding arbitrage,” said one convertible bond trader who has bought MicroStrategy’s bonds and shorted its equity. “Our arbitrage is OK. It’s decent. But [Saylor’s] arbitrage is brilliant.”

Traders exploiting the volatility of MicroStrategy’s shares have been helped by billions of dollars of inflows into highly levered exchange traded products that track the stock but amplify investors’ potential gains and losses. Two MicroStrategy ETFs, including the Defiance Daily Target two-times long MSTR ETF, own about $10bn of the company’s stock via swaps and options. 

Unlike traditional ETFs, which buy and hold shares, leveraged ETFs rebalance at the end of every trading day to hit their targeted returns. This means that when the underlying asset rises in price, fund managers must buy more of the stock, and vice versa should prices fall.

These end-of-day rebalancing flows can “significantly impact the underlying MicroStrategy stock price, amplifying price moves, thus enhancing volatility”, said JPMorgan strategist Nikolaos Panigirtzoglou.

But some investors are getting nervous. They fear that the virtuous circle that has driven up the share price so quickly could easily go into reverse if the bitcoin price falls substantially.

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“Borrowing dollars to buy bitcoin is just a massive dollar short position, not a new financial invention,” says Barry Bannister, chief equity strategist at Stifel. “As any short seller in history knows, the price of being wrong is ruin.”

“If bitcoin traded down 90-95 per cent and stayed there, there would be no liquidation or debt accelerations,” Saylor told the FT. “Presumably our equity would suffer some dilution, but we still would not sell, or need to sell, our bitcoin.”

The shares could also fall if investors simply decide to place less of a premium on MicroStrategy stock. Since their peak on November 21, the shares are down around 40 per cent, while bitcoin is down just 5 per cent.

One North American hedge fund executive said they had held a position in bitcoin and a bet against MicroStrategy “to capture that spread”. This bet “worked on and off until the trade became a meme”, added the person, who now prefers to short one of the twice-leveraged ETFs.

Some suggest that share sales by insiders undermine the company’s pitch to investors: that bitcoin remains undervalued. MicroStrategy directors have sold a total of $570mn of the company’s stock so far this year, according to company filings.

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MicroStrategy did not respond to a request for comment on the share sales.

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“The subjects change — now it’s crypto — but over the centuries human investment behaviour does not deviate from the script one iota,” said Bannister.

Anyone buying assets “built on thin air” should be prepared to watch their money “vanish”, he added.

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How Natura &Co Is Transforming Finance with Generative AI on SAP S/4HANA

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How Natura &Co Is Transforming Finance with Generative AI on SAP S/4HANA

For a company navigating one of the most consequential transformations in its history, financial clarity is not optional—it is essential. Natura &Co, the Brazilian personal care and cosmetics group behind iconic brands such as Natura and Avon, has long been committed to combining purpose-driven business with commercial performance. After a period of strategic portfolio reshaping, including the divestiture of its Aesop and The Body Shop holdings, the company is now sharpening its focus on profitability and operational excellence across Latin America and global markets.

At the center of that effort sits a deceptively complex challenge: understanding, in real time, which revenue and cost factors are driving or eroding gross margin across a highly diversified business. For years, answering that question meant manual reporting, delayed insights, and finance teams spending valuable time on data gathering rather than analysis.

That’s now changing, thanks to a co-innovation initiative developed together with SAP and Numen, a global SAP partner specializing in digital transformation and enterprise software implementation.

From manual reporting to proactive decision intelligence

An enterprise AI platform built for your business

The project’s goal was to replace a labor-intensive gross margin analysis process with a generative AI application embedded directly into Natura &Co’s financial workflows. Built on SAP Business AI Platform, SAP’s unified foundation integrating business technology, data, and AI capabilities, the application connects directly to data in SAP S/4HANA to provide finance teams with automated insights and narrative recommendations in real time, without the need for manual data pulls or offline reporting.

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The application enables users to explore revenue, cost, and margin drivers interactively, identifying at a glance which elements are protecting or eroding margin performance across markets and product lines. Crucially, human oversight remains central to the design: the AI application generates insights, while finance professionals retain full control over interpretation and decisions.

“The implementation of gross margin analysis using AI in SAP S/4HANA marked an inflection point in the analytical capability of our finance area,” said Rogério Dias Garcia, tech manager, ERP Latam, Natura &Co. “We overcame delays and raised the standard of insights by integrating margin analysis from SAP S/4HANA with a large language model connected via the SAP AI Core layer. This architecture allowed us to provide, in an agile, secure, and completely anonymous manner, a stratified and precise view of gross margin offenders and protectors—discriminating exactly which revenue or cost elements were driving market performance.”

A collaborative architecture for scalable AI adoption

Natura &Co’s application derived from a prototype SAP partner Numen created in early 2024 at SAP’s global Hack2Build on business AI, leveraging the generative AI capabilities of SAP Business AI Platform. The solution was designed and developed through close collaboration between Natura &Co, Numen, and SAP. From the outset, the approach was to align AI adoption with concrete business priorities, ensuring the application would be scalable and production-ready rather than a standalone prototype.

Numen brought deep SAP implementation expertise to the project, combining knowledge of SAP S/4HANA architecture with hands-on experience in building solutions on SAP Business AI Platform. The technology stack—SAP S/4HANA, SAP AI Core, SAP Fiori, and SAP Business Technology Platform—provided the secure, integrated foundation needed to connect financial data with generative AI capabilities in an enterprise context.

“SAP enabled the transformation by providing the technological foundation and expert support,” said Carlos Aravechia, head of Data Design & Intelligence at Numen.

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The success of the project has validated a broader conviction at Natura &Co: that generative AI, embedded directly in ERP workflows, can fundamentally reposition finance from a transactional function to a strategic business partner.

A blueprint for other businesses

The Natura &Co project demonstrates a pattern that other organizations can replicate, particularly those running SAP S/4HANA. The combination of structured ERP data with the contextual reasoning capabilities of large language models creates a foundation for decision intelligence that goes well beyond traditional business intelligence tools.

The project was built within a six-month co-innovation sprint and went live in August 2025. It is currently in use across Natura &Co’s Equador operations.

Looking ahead, Natura &Co is already planning the next phase: integrating Joule Agents to further automate the extraction of standard analytical content and deepen the AI-driven optimization of financial processes.

“The success of this initiative validates the transformative potential of embedded AI within our ERP,” Dias Garcia noted. “We are now ready to move forward—deepening these insights and integrating the capability of Joule Agents to maximize the extraction of standard content and further optimize our business decisions.”

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For SAP customers evaluating how to move from AI experimentation to AI in production, the Natura &Co project offers a concrete, replicable model: start with a high-value, well-defined business process, embed AI directly into existing workflows, and build in human oversight from the start.


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Low-income Chinese girl aces gaokao, inspires live-streamers offering help

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Low-income Chinese girl aces gaokao, inspires live-streamers offering help

A girl from a disadvantaged rural family in central China topped this year’s gaokao, attracting numerous live-streamers eager to finance her education, which she declined.

The home of 18-year-old secondary school graduate Han Yaping in a Henan province village was recently bustling with live-streamers.

This attention came after Han achieved an impressive score of 699 out of 750 in the gaokao, China’s national college entrance exam.

She has received offers from China’s two leading universities, Tsinghua University and Peking University.

Han’s accomplishment is particularly remarkable given her family’s impoverished circumstances.

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Her mother suffers from ankylosing spondylitis, an inflammatory arthritis affecting the spine, preventing her from working. Her father, who earns a living through farming and odd jobs, serves as the family’s sole provider. Han also has a younger sister.

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UK financial regulator publishes landmark AI review

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UK financial regulator publishes landmark AI review

The UK’s Financial Conduct Authority (FCA) published a landmark review on Monday that proposes recommendations to regulate the impact of artificial intelligence (AI) on the financial decisions made by consumers.

The review, titled the Mills Review, anticipates that both consumers and firms will start delegating “more financial decision-making to AI systems,” including for agreements, initiating transactions, and executing decisions “within agreed parameters.” One of the key findings of the review outlined that while AI can help bridge advice gaps and “support growth,” there remain risks “associated with fraud, cyber security, and consumer harm.” Conducting the review, Sheldon Mills highlighted that “AI can also amplify risks: bias, discrimination, exclusion, opaque decision-making (particularly when multiple AI models interact), misleading or hallucinatory advice and erosion of consumer trust.”

The review stated that presently, one in five adults in the UK are “already open to AI making decisions for them,” particularly when decisions feel “complex or high stakes.” It found that roughly 26 percent of the population “trust general-purpose tools such as ChatGPT, Claude or Gemini for financial advice” with little awareness that such platforms provide no “formal routes to recourse” or protections.

Overall, the Mills Review identified four areas that it anticipates will be impacted by AI in the financial sector: “the transformation of firms,” “new consumer journeys,” “a reshaped competition landscape,” and “amplified financial crime and cyber risk.” The FCA projected the shift in how consumers and firms consult AI to take place by 2030.

The Mills Review put forth seven “priority” recommendations to be considered by the FCA Board. It recommended that any transitions to autonomous AI models be monitored and that regulatory frameworks and perimeters be adapted and secured. The review called for the strengthening of “system-wide coordination and oversight,” the scaling up of the FCA’s AI Lab to enable it to support AI models and innovation for agentic finance, and an “AI-enabled agentic supervisory model” to be built and adopted.   Finally, it recommended that a trusted “public-interest AI-enabled financial capability service” be developed.

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The FCA announced, in the press release, that it will launch an AI “good and poor practice publication” in late 2026.

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