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Methodology
Practical frameworks for modelling, backtesting, factor research, portfolio construction and disciplined decision-making.
80 articles
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What Is Data-Driven Investing? A Practical Framework for Indian Investors
Data-driven investing uses explicit evidence and repeatable rules, while preserving context, sources and human judgement. Here is a practical Indian framework.
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Alpha Is Discipline: Why Better Investing Is Often Boring
Investment alpha is not created by discipline alone, but a repeatable process is what keeps a real edge alive through decisions, costs and changing markets.
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Position Sizing Methods: Equal Weight, Conviction Weight and Risk Parity
Position sizing decides how much capital each holding gets. Equal weight, conviction weight and risk parity are the main methods, and each buys a different trade-off.
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All methodology articles
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Global Intelligence: What World Markets Mean for India's Businesses
A dated, sourced reading desk for global rates, energy, AI investment and capital flows, connecting wealth-manager theses to Indian business evidence.
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Sector Intelligence or a Good Story? How to Test a Sector Thesis
A practical framework for assessing sector outlooks: date the claim, trace the business mechanism and decide what evidence would challenge the thesis.
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Sector Intelligence India: From Wealth-Manager Theses to Business Evidence
A sourced sector-intelligence reading desk for India: distinguish published macro views from operating evidence in banking, consumption, IT and infrastructure.
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Diwali Moves Every Year: Your Sales Comparison Should Too
Diwali Laxmi Pujan moves from October in 2025 to November in 2026 on the NSE calendar. Learn to compare festival windows without mistaking timing for demand.
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How to Compare SIFs in India: Look Beyond NAV Returns
A practical SIF research checklist for Indian analysts and family offices: compare mandates, plans, holdings, short exposure, costs and evidence, not just NAV returns.
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Quarterly vs Year-to-Date Results: How to Reconcile the Numbers
Avoid double-counting quarterly results: reconcile Q1, H1, nine-month and annual financial statements, handle cash flows correctly and flag incompatible reporting bases.
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The Revenue Growth Bridge: Volume, Price, Mix and Acquisitions
Revenue rose, but why? Build a volume-price bridge, separate product mix, acquisitions and currency, and turn quarterly results into defensible model assumptions.
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How to Analyse a Stock in India: A Professional Research Checklist
A source-first framework for analysing an Indian stock: business model, financials, management, valuation, risks, portfolio fit and monitoring.
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How to Analyse Auto Company Results: Volumes, Pricing, Mix and Capacity
A practical method for analysing Indian automobile results through volumes, realisations, product mix, margins, capacity, subsidiaries and cash flow.
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How to Analyse Bank Results: NIM, CASA, Credit Costs and Asset Quality
A practical framework for analysing Indian bank results through growth, funding, margins, asset quality, credit costs, capital and return on assets.
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How to Analyse Defence Company Results: Order Books, Execution and Working Capital
A practical framework for analysing Indian defence-company results through executable order books, revenue recognition, margins, advances, inventory and receivables.
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How to Analyse Hotel Company Results: Occupancy, ARR, RevPAR and Room Mix
A practical guide to analysing Indian hotel results across occupancy, room rates, RevPAR, owned and managed rooms, margins, capex and cash flow.
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How to Analyse IT Services Results: Growth, Margins, Deals and Headcount
A practical guide to reading Indian IT services results through constant-currency growth, deal conversion, margins, utilisation, headcount and cash generation.
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How to Analyse Pharma Company Results: India, US, Specialty and R&D
A practical framework for analysing Indian pharmaceutical results across geography, product mix, launches, R&D, regulation, margins and cash generation.
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How to Analyse Power Utility Results: Regulated Returns, Capex and Leverage
A practical guide to Indian power-utility results across generation, transmission, availability, regulated returns, receivables, capex, debt and cash flow.
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How to Analyse Steel Company Results: Realisations, Costs, Capacity and the Cycle
A practical framework for analysing Indian steel results through volumes, realisations, raw-material costs, geography, capacity, leverage and the commodity cycle.
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How to Analyse a Demerger: An Indian Investor’s Source-Checked Framework
A practical demerger analysis framework covering share entitlement, business boundaries, debt, cash, shared costs, valuation and unresolved risks—with Vedanta as a current source-check example.
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Investment Research Software Checklist for Indian Firms
A vendor-neutral checklist for evaluating Indian equity research software: source links, point-in-time data, calculations, models, monitoring, security and Excel verification.
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Alpha Is Discipline: Why Better Investing Is Often Boring
Investment alpha is not created by discipline alone, but a repeatable process is what keeps a real edge alive through decisions, costs and changing markets.
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What Is Data-Driven Investing? A Practical Framework for Indian Investors
Data-driven investing uses explicit evidence and repeatable rules, while preserving context, sources and human judgement. Here is a practical Indian framework.
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The Filing Is Late. The Footprints Arrive Every Day.
A practical guide to alternative data for Indian stock research: what Altys tracks, why point-in-time history matters, and how to avoid false signals.
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Quantitative vs Qualitative Stock Research in India: Why Serious Portfolios Need Both
Quantitative research makes selection consistent; qualitative research explains why the numbers exist. A governed Indian equity process needs both.
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Why India Needs Rule-Based Portfolio Governance
Rule-based portfolio governance makes an investment process explicit, testable and reviewable without pretending judgement can be automated away.
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FII and DII Ownership Changes: What Moved in Q1 FY27?
Altys data for 75 quality-gated Indian companies shows a broad Q1 FY27 pattern: foreign ownership fell in 53 while domestic institutional ownership rose in 55.
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How to Do Fundamental Analysis of Indian Stocks Using AI
A source-linked workflow for using AI in Indian stock fundamental analysis, from filings and financials to modelling, valuation, verification and monitoring.
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Financial Data Platforms in India: What Serious Research Requires
What to demand from an Indian financial data platform: primary sources, consistent statements, point-in-time history, corporate actions, auditability and workflow.
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Point-in-Time Financial Data in India: A Buyer’s Guide for Investment Teams
A practical checklist for evaluating point-in-time Indian financial data: publication dates, vintages, restatements, corporate actions, derived metrics, missing values and reproducible backtests.
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Benchmark Selection for Portfolios: How the Wrong Benchmark Invents Alpha
Choosing a benchmark is not administrative. The benchmark defines what counts as skill, so a mismatched one manufactures alpha or hides it. Here is how to select one properly.
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Building a Factor Scorecard: Turning Definitions Into a Repeatable Score
A factor scorecard converts factor definitions into one comparable number per stock. Here is how to build one that is precise, point-in-time, and honest about what it cannot see.
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Building an Exit Framework: How a Rules-Based Sell Discipline Is Designed
An exit framework is the written set of conditions under which a position is reviewed or reduced. Here is how one is designed, documented and reviewed, without prescribing any rule.
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Common Backtesting Mistakes That Make Results Look Better Than Reality
The most common backtesting mistakes are future information leaking into past decisions, survivorship in the universe, ignored costs, and testing so many variations that something looks good by luck.
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Equal Weight vs Market-Cap Weight: Two Default Schemes, Two Different Portfolios
Equal weight and market-cap weight are the two default weighting schemes. They hold the same names but produce very different size tilts, turnover and concentration.
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Factor Crowding Explained: When Too Much Money Chases the Same Signal
Factor crowding is what happens when many investors hold the same factor exposure at once. It raises valuations, correlates positions, and makes unwinds sharper.
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Factor Cyclicality and Drawdowns: Sizing for the Droughts
Factors go through long periods of underperformance. Factor cyclicality analysis measures how deep and how long those droughts run, so position sizing and governance can survive them.
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Factor Exposure Analysis: What Your Portfolio Is Actually Exposed To
Factor exposure analysis measures which characteristics, such as value, quality, momentum or size, actually drive a portfolio, using holdings-based scores or returns-based regression.
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How Often Should You Rebalance a Portfolio?
Rebalancing frequency is a trade-off, not a rule. Calendar, threshold and hybrid schedules explained, with the costs, turnover and tax drag each one carries.
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How to Backtest a Stock Strategy in India: An End-to-End Walkthrough
Backtesting a stock strategy in India means testing explicit rules on historical data that was actually knowable at each date, with realistic costs, a fair benchmark, and honest reporting.
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How to Identify Momentum Stocks: The Measurement Method
Momentum is identified by ranking a defined universe on risk-adjusted past return over a fixed lookback window. Here is the measurement method, step by step, with no lists.
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How to Read a Backtest Report
Read a backtest report in reverse order: setup and assumptions first, then risk and turnover, and the return figure last. Here is the sequence and the red flags.
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How to Read an RRG Chart: A Practical Method and Its Limits
Read an RRG in a fixed order: check the benchmark and universe first, then quadrant position, then tail direction and length, and only then form a view.
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How to Read FII and DII Data Without Misreading the Market
FII and DII data is best used as slow context, not a daily signal. Learn which Indian flow dataset to use, how to chart it and which claims it cannot support.
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In-Sample vs Out-of-Sample Testing: The Minimum Honest Backtest Check
In-sample data is where a strategy is built and tuned. Out-of-sample data is held back and used once to judge it. Splitting the two is the least you can do to avoid fooling yourself.
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An IPO Analysis Framework: How to Read a DRHP Section by Section
A structured framework for analysing an Indian IPO from its DRHP: what each section contains, what to extract, and where the document is designed to be least informative.
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Liquidity Constraints in Backtesting: Why a Paper Strategy Cannot Always Be Filled
Liquidity constraints decide whether a backtested trade could actually have happened. A guide to volume caps, capacity, thin stocks and the filters that keep a test honest.
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Monte Carlo Simulation in Investing: What It Adds and Where It Breaks
Monte Carlo simulation runs thousands of randomised paths to turn uncertain inputs into a distribution of outcomes, and inherits every flaw in the assumptions behind it.
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Multi-Factor Investing Explained: Blending vs Integrating
Multi-factor investing combines several return drivers such as value, quality, momentum and low volatility into one portfolio, either by blending sleeves or by integrating scores.
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Portfolio Construction Basics: From an Idea List to an Actual Portfolio
Portfolio construction is the step that turns a list of researched ideas into weights, constraints and a rebalancing rule. Here is what each decision does and what it costs.
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Portfolio Drawdown Management: Planning for Losses Before They Happen
Drawdown management is the discipline of deciding in advance how a portfolio responds to losses. Here is how teams size, document and stress-test that plan before it is needed.
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Portfolio Review Checklist: A Structure for the Periodic Review
A portfolio review checklist is a fixed agenda run at a set interval covering records, positions, structure, performance and process, so every review asks the same questions.
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Position Sizing Methods: Equal Weight, Conviction Weight and Risk Parity
Position sizing decides how much capital each holding gets. Equal weight, conviction weight and risk parity are the main methods, and each buys a different trade-off.
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Rebalancing Frequency and Backtest Results: How Often You Trade Changes What You Measure
Rebalancing frequency changes turnover, cost and signal decay all at once. A guide to why backtest results move with frequency and how to test frequency without fooling yourself.
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Rebalancing Methods Compared: The Mechanics of Each Approach
Rebalancing methods compared: full restore to target, band-edge trades, cashflow rebalancing, buy-only tilts and risk-based schemes, with the mechanics and trade-offs of each.
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Scenario Analysis Explained: Building Coherent Futures, Not One Forecast
Scenario analysis replaces a single point forecast with a small set of internally consistent futures, each with its own assumptions, so you can see how a view breaks.
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Sector Rotation Strategy in India: How Rotation Is Measured and Analysed
Sector rotation is the observation that leadership moves between sectors over time. This is how rotation is measured in Indian markets, and where the analysis breaks down.
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Sensitivity Analysis Explained: Which Assumption Actually Moves the Answer
Sensitivity analysis changes one input at a time to see how much the output moves, revealing which assumptions carry a model and which barely matter at all.
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Slippage and Impact Cost: The Gap Between the Modelled Price and the Real One
Slippage is the difference between the price a backtest assumes and the price a trade actually gets. A guide to spread, delay and market impact, and how to model each.
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Stress Testing a Portfolio: Historical and Hypothetical Shocks
Stress testing asks what a portfolio would do under a severe but conceivable shock, using either a replayed historical episode or a designed hypothetical one.
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Survivorship Bias in Backtests: Why Today's Index Lies About the Past
Survivorship bias is testing a strategy on companies that survived to today. Delisted, merged, and dropped names disappear from the sample, so historical results improve for reasons unrelated to the strategy.
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Systematic vs Discretionary Investing: An Honest Comparison
Systematic investing applies a fixed rule to every case; discretionary investing judges each case on its merits. Here is what each is genuinely good and bad at.
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Tracking a Model Portfolio: Model Versus Actual, Drift and Record-Keeping
A model portfolio is the intended holdings on paper. Tracking it means keeping a dated record of the model, comparing it with actual accounts, and explaining every gap.
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Transaction Costs in Backtests: Brokerage, STT, Stamp Duty and GST
Transaction costs turn a paper strategy into a real one. A guide to the categories of Indian trading cost, how to model them in a backtest, and how turnover multiplies the drag.
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Walk-Forward Analysis Explained: Rolling Re-Estimation as a Stricter Test
Walk-forward analysis fits a strategy on a past window, applies it to the next unseen window, then rolls forward and repeats. It is a harder test than a single out-of-sample split.
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What-If Analysis in Financial Models: Structuring It So It Changes a Decision
What-if analysis tests how a model responds to changed assumptions. Done well it is decision useful, done badly it produces a wall of numbers nobody acts on.
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What Is Overfitting in Backtesting? Curve-Fitting, Parameters and How to Detect It
Overfitting in backtesting is tuning a strategy until it describes the noise in one sample of history rather than any durable pattern. It looks like a great result and behaves like a coin flip.
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Why Backtest Results Don't Repeat in Live Investing
Backtest results rarely repeat live because of overfitting, regime change, crowding, and the costs a test omits. Here is what actually causes the gap and what to expect.
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P/E Below 20 Worked for Me. Until It Didn’t.
Five FY26 IT companies all traded below 20 times earnings, yet their growth, returns on capital and cash conversion were very different. The threshold was only the first question.
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Same Score, Different Stock: What Factor Ratings Can Hide
Two stocks can reach the same composite score through opposite strengths. Read value, quality and trend separately before trusting the total.
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A Practical Guide to Forensic Accounting for Indian Stocks
Forensic accounting is a set of practical checks you run on reported numbers, cash versus profit, receivables and inventory, related parties, revenue timing, and auditor signals, before you trust the headline.
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Building KPI Trees for Indian Companies
A KPI tree connects a company's operating drivers to its financial statements as a hierarchy. Here is how to structure one, top-down, with an Indian-company shaped example.
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Common Modelling Mistakes Analysts Make
The recurring errors that quietly ruin financial models: hardcoding, false precision, restated history, straight-lined growth, circular references, and single-case thinking, with plain fixes for each.
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How Sell-Side Analysts Forecast Revenue
Sell-side analysts forecast revenue by combining top-down market sizing with bottom-up driver models, cross-checking both against management guidance and channel checks, then publishing an estimate that feeds consensus.
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Why Unit Economics Matter More Than Earnings
Unit economics show what one unit of a business earns after the cost to serve it, which reveals whether a company is healthy long before the reported profit line does.
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How to Build a DCF Model for Indian SaaS Companies
Build a DCF for an Indian SaaS company by projecting revenue from growth drivers, modelling the burn-to-cash-flow path, and discounting future cash flows back.
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How to Build a Three-Statement Financial Model
A three-statement model links the P&L, balance sheet and cash flow into one connected file. Build the P&L first, then the balance sheet, then let cash flow fall out.
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How to Model Asian Paints Gross Margins
Asian Paints gross margin is a crude-linked spread: model revenue as volume times realisation, cost of goods as input costs plus mix, then stress it against crude.
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How to Write an Investment Memo (With a Template)
An investment memo is the document that argues for a position. Here is what a strong one contains, plus a reusable template you can adapt.
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A Management Guidance Database for India: What It Is and Why It Matters
A management guidance database is a structured, searchable record of what company managements say they expect, tracked over time so you can see how the story changes.
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Management Guidance: What It Is and Why Analysts Track Every Word
Management guidance is the forward-looking view a company's leaders give on growth, margins and demand. Analysts track its revisions as a leading signal.
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The Equity Research Process, Step by Step
The equity research process is a repeatable workflow that turns filings and data into a reasoned view: screen, study, model, value, write, and monitor.
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Data Quality Beats Model Quality: A Year Reading Indian Filings
After a year building AI to read Indian company filings, the biggest gains came from boring data discipline, not from a better model. Here is what actually moved the needle.
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