Algorithmic Trading Blog
Guides, tutorials, and analysis for building systematic trading strategies on Indian markets. Written for self-directed retail investors who want to move from gut-feel decisions to rules-based portfolios.
Survivorship Bias in Indian Stocks: Modelling the Exit
Survivorship bias in Indian stocks is not fixed by keeping delisted names. Four exit routes, four exit prices, and how to measure it in your own trade log.
Backtest Overfitting: The Deflated Sharpe Test
Run 50 parameter combinations and the best Sharpe is inflated by selection alone. How the Deflated Sharpe Ratio and PBO separate an edge from noise.
Commodity Trend Following on MCX: The Oldest Systematic Trade
Commodity prices are set by physical supply and demand that adjusts slowly. A mine takes years to open, a crop takes a season — which is exactly why commodity trends persist.
Corporate Bonds in India: The Yield Is Real, So Is the Liquidity Trap
Indian corporate bonds quote roughly 30 days a year each. A bond you can buy is frequently not a bond you can sell near where you last saw it marked — and that, not default risk, is what the spread is mostly paying for.
Crypto Trend Following: Why Absolute Momentum Beats Relative
With two correlated assets, a relative momentum screen is always fully invested in whichever is falling less. In an asset class with repeated 70% drawdowns, that distinction is the whole strategy.
Delivery Percentage: The Volume Filter Only Indian Markets Have
Volume tells you how much traded. Delivery percentage tells you how much was actually taken home. For separating real breakouts from intraday churn, the second number is far better — and it does not exist in US markets.
Does Buying Last Year's Best Mutual Fund Work?
It is the most common investment decision in India. The persistence evidence says top-quartile funds stay top-quartile at close to chance rates. Here is a template built specifically so you can test it yourself.
Cross-Asset Momentum: The Version That Held Up Out of Sample
Single-stock momentum has decayed since publication. Momentum across asset classes has held up far better, and Indian ETFs now make it accessible from one account with one order type.
Expense Ratio Is the Only Fund Number You Know in Advance
Past return is a noisy estimate of something that may not persist. Cost is a certainty, charged daily, compounding against you. That asymmetry is why it is the most reliable predictor available.
Country Momentum: Rotating Across Markets, Not Stocks
Equity indices trend for reasons individual companies never explain — currency regimes, policy cycles, capital flows. Cross-country momentum has held up better out of sample than single-stock momentum.
G-Secs Are Two Markets, and Only One of Them Is Liquid
A handful of benchmark government securities trade every day in size. The several hundred others may not print for weeks. Any systematic G-Sec strategy has to select on realised liquidity, not on tenor.
Out of Sample Testing: What a Holdout Can Prove
Reserve the last quarter of your backtest window, rank on the rest, and read retention. What out of sample testing proves, and exactly where it stops.
Brokerage Charges in India: The Full Cost Stack
Brokerage is the smallest line on an Indian delivery trade. STT, stamp duty, GST and a flat DP fee do the real damage, and most backtests ignore all of it.
Insider Buying Is a Signal. Insider Selling Mostly Is Not.
There are a dozen reasons an insider sells and essentially one reason they buy. That asymmetry is why the buy side of SEBI's mandatory disclosures carries information the sell side does not.
Backtesting an Intraday Strategy Honestly (and Why Costs Decide It)
An intraday strategy trades roughly 250 times a year instead of 12. Costs that round to nothing in a monthly backtest become the whole result. Here is how to build one so the backtest is not lying to you.
The Low Volatility Anomaly: Getting Paid to Take Less Risk
Finance theory says higher risk earns higher return. Low-volatility stocks have historically delivered better risk-adjusted returns than high-volatility ones. The explanation is structural, not statistical.
Market-Neutral Investing: Isolating the Factor From the Market
A long-only momentum portfolio earns two things at once, and the market leg dominates. Going long winners and short losers cancels it — but in India the short leg is the binding constraint.
The 200-Day Moving Average: A Drawdown Trade, Not a Return Trade
One of the simplest market-timing rules ever tested roughly halved maximum drawdown across a century of data without giving up much return. It also whipsaws, and you should know that before deploying it.
Mean Reversion: Getting Paid to Provide Liquidity
Buying large caps that have fallen two standard deviations below their own average is not contrarian instinct — it is being compensated for taking the other side of somebody's forced sale.
Momentum Investing in India: Why the Best Signal Skips Last Month
Momentum is the most replicated anomaly in equities, but the standard construction deliberately throws away the most recent month of returns. Here is why, and how to build the screen on the Nifty 500.
Why Blending Factors Beats Picking One
Momentum, quality and low volatility all have multi-year droughts, and the droughts do not line up. Combining them produces a shallower worst drawdown — which is what determines whether you are still holding when it recovers.
Backtest Execution Timing: Fill at the Next Bar's Open
A backtest that fills at the same close it read to decide is reporting returns nobody could have captured. Why next-bar-open is the only honest timing.
Top 30 or Top Decile? Why Fixed Counts Hide a Changing Bet
Holding a fixed number of names assumes the universe is constant. It is not — and a top-30 screen is a much more concentrated bet when only 200 stocks qualify than when 450 do.
Point in Time Data: Knowing What You Knew That Day
Publication lag, restatements and index reconstitution quietly hand your backtest information nobody had. How point-in-time data closes each of those gaps.
Promoter Pledging: The Risk That Turns a Decline Into a Collapse
Pledged promoter shares convert an ordinary price fall into forced selling. The mechanism is mechanical, disclosed quarterly, and easy to screen out — which makes it one of the highest-return filters available to Indian retail investors.
The Quality Factor: Screening for Businesses, Not Charts
Profitable, unlevered companies have historically outperformed, and the reason has more to do with how investors form expectations than with risk. How to build a quality screen from Indian filings.
REITs and InvITs: The Asset Class Most Indian Portfolios Skip
SEBI requires them to distribute most of their distributable cash flow. That makes their return profile closer to a bond with inflation participation than to an equity — and different from everything else you own.
Your 60/40 Portfolio Is Really a 90/10 Portfolio
Equities are roughly four times as volatile as bonds, so a 60% equity allocation contributes about 90% of portfolio variance. Risk parity fixes the accounting — and hierarchical risk parity fixes risk parity.
Sector-Neutral Factors: Why Cross-Sector Ratio Screens Mislead
Banks carry high leverage because lending is their business. Software firms carry high ROE because they hold little capital. A screen that ignores this is mostly a sector bet wearing a factor label.
Short Selling in India: What a Retail Account Can Actually Do
You cannot carry a cash-market short overnight. That single rule determines the shape of every short strategy a retail Indian investor can realistically run — and most backtests ignore it.
Slippage in Trading: Why Live Fills Are Worse
NSE will not admit a stock to the Nifty 50 unless a ₹10 crore order moves it less than 0.50%. Your backtest assumed zero. Here is how to close that gap.
State Development Loans: 44 Basis Points for a Technicality
SDLs are state government borrowings auctioned by the RBI, settled like G-Secs, and yielding meaningfully more. RBI Retail Direct made them buyable directly — and almost nobody does.
Selection and Sizing Decay at Different Speeds
Which companies deserve to be in the portfolio changes slowly. How much risk each position contributes changes quickly. Running both on the same clock forces a bad compromise.
Value Screens That Survive Contact With Indian Data
Price-to-book and price-to-earnings both break in predictable ways. Using two multiples with a profitability gate in front removes most of the fake cheapness a naive value screen collects.
Volatility Targeting: Sizing Is a More Reliable Lever Than Timing
Tomorrow's volatility is predicted far better by recent volatility than tomorrow's return is by recent returns. That single asymmetry is why scaling position size works when forecasting direction does not.
Bulk Deals vs Block Deals vs Shareholding Patterns
A bulk deal, a block deal, and a shareholding pattern filing each show a different, incomplete slice of who owns a stock. How to read all three.
From a Plain-English Thesis to an Editable Strategy
the Saral Agent — saral.money's AI assistant — turns a plain-language investment thesis into an editable, white-box strategy flow — the same rule nodes you can open and change. What it does, why it stays inspectable, and what it deliberately does not do.
The Indian Algo-Tooling Gap: What Streak, Tradetron and AlgoTest Can't Do
India's no-code algo platforms are either single-stock signal generators or options backtesters. None offer no-code, multi-rule portfolio backtesting on 15+ years of data. A fair look at the gap — and where each incumbent genuinely wins.
Retail vs the Machines: Who Is on the Other Side of Your Trade
Algorithms now drive over half of NSE turnover, and SEBI says 96–97% of prop and foreign-investor profits came from them. Here is what that means for retail — and how to stop bringing manual decisions to an automated fight.
What SEBI's Feb 2025 Retail Algo Framework Actually Changes for You
In February 2025, SEBI gave retail investors a sanctioned path to algorithmic trading for the first time. What the framework permits, the white-box vs black-box distinction, the order thresholds, and what it means for no-code platforms.
Why 93% of F&O Traders Lose — And What Actually Changes the Odds
SEBI's own research finds 9 in 10 Indian F&O traders lose money. The cause is documented behaviour, not bad luck. Here is the evidence — and the one habit that changes the odds.
Why Algorithmic Investing in India Has to Be No-Code
Coders are a low-single-digit share of India's investors, only ~11% report any English, and most new demat accounts come from beyond the metros. The case for why systematic investing here cannot require Python.
Cognitive Biases That Destroy Algo Trading Strategies
From overfitting to survivorship bias, the most common cognitive and statistical biases that lead algo traders astray, and how to avoid them.
What is Algorithmic Trading? A Complete Guide for Indian Traders
Algorithmic trading uses computer programs to execute trades based on predefined rules. Learn how algo trading works, its benefits, SEBI regulations, and how to get started in India.
Backtesting Trading Strategies: A Step-by-Step Guide
Learn how to backtest trading strategies properly. Avoid common pitfalls like look-ahead bias and overfitting. A practical guide for Indian market traders.