The acquisition of Professor Alok Jha was immediately followed by the delivery of the ten high-end computing systems from Patna Tech Solutions. Arjun had committed nearly ₹20,00,000 of the System Funds to this hardware, and every rupee was about to be leveraged by the two S-Rank faculty members. Under the strict supervision of Dr. Rohan Verma, the installation was not a typical plug-and-play setup; it was the birth of Nalanda's specialized research platform.
Verma, armed with the knowledge of future compiler architectures derived from the [Advanced Library Module], directed Rajesh and Vikram in a rapid assembly process. Rajesh's S-Rank Hardware Logic allowed him to anticipate network flow issues and physically optimize the cooling for sustained high performance, while Vikram's S-Rank Hardware Intuition guided the placement of components to minimize electrical resistance and data latency. They were, in effect, building a micro-cluster server optimized for parallel processing—a type of computational architecture unheard of in an educational setting in Bihar in 2000.
"We are not building desktop computers; we are building a single brain with ten dedicated processors," Verma explained to the Core Ten, who watched the frenetic activity. "Professor Jha's Dynamic Currency Model requires continuous parallel computation—it needs to check millions of permutations simultaneously. The software alone is useless without this hyper-optimized hardware foundation."
Arjun, meanwhile, used some of the remaining System Funds to ensure the university had a clean, uninterrupted power supply, installing industrial-grade UPS systems and backup generators. The power grid in Patna was notoriously unreliable, and the [Third Step] Quest] demanded zero downtime for the LID Index calculations. Every operational vulnerability had to be ruthlessly eliminated. The university was evolving from a set of crumbling buildings into a highly resilient, specialized research facility.
(Paragraph 2: The LID Index Framework - 1100 words)
The Core Ten were immediately assigned roles in the LID Index Predictive Modeling project. Professor Jha took charge, transforming the Faculty Planning Room into a strategic War Room. His methodology was brutal in its clarity, and the [Applied Economics & Algorithmic Trading] Specialization Module provided the necessary cutting-edge tools.
"The Liquidity-to-Infrastructure Divergence (LID) Index is simple in concept, complex in execution," Jha told the students. "We are measuring the flow of paper money (Liquidity) into the technology sector and comparing it to the verifiable physical infrastructure (Infrastructure) built by those companies—servers, network towers, physical real estate. When the paper valuation dramatically outstrips the physical reality, the system is based on unsustainable speculation. Our model will identify the mathematical tipping point."
Ritu (S-Rank Data Science) was tasked with creating the algorithms to filter and analyze the raw financial data—the initial paper filings, investment records, and publicly traded volumes. She was applying advanced statistical methods that Jha taught her, drawing directly from the future knowledge provided by Arjun. Her aptitude was accelerating under the sheer complexity of the task.
Vijay (A+ Finance) worked directly with Jha, focusing on defining the variables related to liquidity and market psychology. He was learning how to identify momentum trades and herd behavior—the very mechanisms Jha's model sought to exploit.
Lalita (S-Rank Logistics) was given the crucial role of quantifying Infrastructure. Her expertise in tangible asset management allowed her to assign realistic, quantifiable values to data centers, fiber optic installations, and operational costs, creating a grounding anchor for the model.
Rajesh and Vikram maintained the nascent supercomputer, ensuring the parallel processing remained stable.
Hassan and Priya began drafting the abstract and presentation strategy, anticipating the global outcry once the prediction was made public.
The [Aura of Focus] enveloping the campus was paramount. It allowed the students to absorb Professor Jha's S-Rank instruction—knowledge two decades ahead of its time—at an accelerated rate. The 100x Feedback was evident in Ritu's rapidly executed code and Lalita's innovative classification of non-financial assets. The Core Ten were not just learning; they were co-developing globally significant research.
(Paragraph 3: The Library's Hidden Data Pipeline - 950 words)
To power the LID Index, they needed data far beyond what was publicly available in Patna in 2000. This was where the true power of the System's [Advanced Library Module] came into play. Arjun revealed its secondary function: a subtle, secure, data extraction pipeline.
"Professor, the model needs real-time, global data feeds to track the investment waves," Arjun stated privately. "The university has a privileged digital connection—a secure, invisible line—to global financial archives. We can pull raw, unfiltered data from the world's major exchanges. This is the Oracle for your model."
Using the System's interface, Arjun helped Jha structure a series of complex data queries designed to extract millions of records: the trading volumes of key IT stocks, the private equity funding rounds, and the quarterly reports of the largest telecom companies. This was the computational problem Jha couldn't solve conventionally; the data was simply too vast and too instantaneous for 2000's infrastructure. The Nalanda Supercomputer, fueled by the System's invisible data stream, was now an operational, future-ready financial lab.
Over the next week, the Core Ten lived and breathed the LID Index. They worked in four-hour shifts, fueled by the dedication instilled by the [Aura of Focus]. The atmosphere was one of silent, profound urgency. They were seeing market forces at work with a mathematical clarity that no other institution in India, and few globally, could match. They saw the greed, the herd mentality, and the sheer, blind speculation driving valuations to absurd, infrastructure-less heights.
The System, meanwhile, kept Arjun updated on the progress.
[System Status Update]: "LID Index Calculation Progress: 15%. Confidence Metric: 45% (Insufficient data validation)."
[Student Aptitude Report]: "Ritu Sharma (Data Science) - Aptitude gain: +0.02% daily. Vijay Varma (Finance) - Aptitude gain: +0.018% daily. Elevated gain due to S-Rank faculty mentorship."
(Paragraph 4: The Discovery of the Date - 800 words)
Around Day 30 of the 90-day quest, the LID Index calculation reached a critical threshold. The entire team gathered around the main monitor in the lab. Dr. Verma had finalized the integration of the preliminary asynchronous compiler, and the ten-processor machine was running the full Monte Carlo simulation.
Jha, his eyes bloodshot from lack of sleep but blazing with S-Rank intensity, typed the final command. The screen filled with a dense, colorful graph. The yellow line (Liquidity) had soared vertically, leaving the blue line (Infrastructure) far below. The point where the model predicted a catastrophic correction—the moment the market's psychological confidence would snap due to fundamental reality—was flashing on the screen.
Ritu, hands hovering over the keyboard, announced the outcome, her voice trembling slightly. "Professor, based on a 90% confidence interval, the model predicts the divergence will trigger a market correction of at least 35% in the IT sector within a three-day window. The most probable starting date is…"
She typed the final predicted variable: October 18, 2000.
It was less than sixty days away. The prediction was dangerously close to the present, giving them minimal time to prepare the research paper and presentation. It was not a prediction of a distant future; it was a mathematical warning about the immediate present.
Jha slumped back in his chair, a manic triumph in his eyes. "It's perfect. It's too close for the traditional systems to absorb and react before the event. If we release this paper just two weeks before the date, we will give the world a verifiable, undeniable chance to pull back. We prove our model, and the financial world collapses around a paper written in Patna."
Arjun looked at the date. The magnitude of what they had done—using future knowledge to see a present disaster—was staggering. The [Third Step] Quest] was now a ticking time bomb.
(Paragraph 5: Strategic Planning and the Ethical Line - 500 words)
Later that night, Arjun, Shraddha, and Priya met to discuss the ethics and strategy of the prediction.
"We have a moral obligation to warn the market," Arjun began. "But we also have a strategic obligation to Nalanda. The paper must be published and validated before the crash, not after."
Priya, the A+ strategist, took command. "We will prepare a final, irrefutable academic paper. We cannot just publish it locally; we must target a global financial news agency and a prestigious academic body simultaneously. I will craft a presentation that is less a warning and more a mathematical demonstration of superior predictive modeling. The press conference must be timed precisely to maximize impact."
Shraddha, pragmatic as always, addressed the System's reward. "The [Third Step] Quest] demands Global Recognition. We need a renowned external body to acknowledge the research. We should submit the paper to a global financial think tank two weeks before the predicted date. If they acknowledge its novelty, we hit the quest objective."
Arjun nodded, feeling the immense responsibility. "The focus is now on polishing the LID Index paper and crafting the perfect pitch. We are not here to manipulate the market; we are here to demonstrate the superiority of the Nalanda Methodology. Priya, prepare the communications strategy. Professor Jha, finalize the proofs. The countdown continues."
[System Status Update]: "LID Index Calculation Progress: 100%. Prediction confirmed: October 18, 2000. Remaining time for Quest: 59 Days."