Algo Trading Course in Ludhiana

Teaching markets to somebody who will inherit a business

This is a different brief from teaching somebody who wants to become a trader, and it is worth separating.

Somebody who will eventually run the family business does not need to become a full-time market participant. What they need is to be competent with surplus capital: to understand what they are buying, to size a position by a rule, to know what a bad year looks like before living through one, and to be immune to the person who calls with a sure thing.

Systematic trading teaches all of that faster than reading about investing does, for one reason. When rules have to be written as code they cannot stay vague, and when every decision is logged the feedback is honest. A twelve-month record of what your own rules actually produced is a better education than any amount of theory, and it is available without risking much, because the practice happens in a virtual trading environment first.

The failure mode to avoid is handing a young person capital and a trading account and calling it experience. That teaches gambling with a delay.

Seasonal income changes how you size a position

Something specific to this city's businesses that nobody writing about trading accounts for.

Hosiery income is not spread across the year. The bulk of it arrives in a compressed season, and the months before it are when working capital is tightest. So the balance in an account in October and the balance in March describe two different businesses, and neither describes the family's actual capital.

Here is why that matters. The near-universal instinct is to size a position against whatever is currently sitting in the trading account. Do that with seasonal income and you will systematically take your largest positions immediately after the season, which is when the account is fullest and the market has no idea that money is spoken for.

The correct basis is total capital, measured once and reviewed rarely, with the trading account funded from it deliberately rather than topped up whenever cash appears. Written into code as a fixed fraction of a number you set annually, this problem disappears. Left to judgement, it recurs every single year.

The related discipline: business working capital and trading capital in separate accounts, with no informal movement between them. Once a supplier payment depends on a position closing well, the rules have stopped governing the position.

What is taught, module by module

The programme is fifty-plus modules long and the sequence matters. It opens with Python taught from nothing, then moves to the Zerodha Kite Connect API — logging in, pulling prices, sending orders, reading positions back.

Then testing: running a set of rules across years of history with brokerage and slippage subtracted, which is where most attractive ideas quietly fail. After that, automating entries and exits, building a scanner against your own filters, pulling live market data into a spreadsheet, and practising in a virtual trading system with no capital at risk.

It ends in production — the strategy on a cloud server, restarting itself when it fails, logging as it goes, with the static IP your broker requires registered against your account.

Position sizing gets its own attention, for the reasons above.

Can a parent and a child take it together?

Practically, yes, and it tends to work well — but the accounts and the capital should stay separate even when the learning is shared.

The parent usually brings the judgement about risk, having lived through cycles in the business, and the younger person usually gets through the Python faster. Splitting it that way is fine. What is not fine is the parent taking the decisions while the child runs the software, because then nobody has learned the thing that mattered.

One licence covers one person; if two people want their own access, that is two enrolments. The demo call is the place to ask about that.

The arrangement that works best, from families who have done it: the younger person builds and runs the system, the parent reviews the monthly log and asks awkward questions about it. That keeps the experience where it needs to be while the judgement still gets applied.

Fees and how to start

Algorithmic Trading with Python is priced at Rs 24,900 as a one-time payment — lifetime access, all future updates, no renewals and nothing sold afterwards. Enrolment is at study.thefinbaba.com and teaching is online in a Hindi-English mix.

Begin with the free demo on WhatsApp. If the person who will take it has not yet placed a trade, expect to be pointed at the Rs 2,500 beginners course first — that is the honest sequence, and it costs less.

This is education and nothing else. There are no tips, no signal group, no managed accounts and no promises about returns. Losses are a real possibility in trading and automation does not change that. The instructor is Atul Shrivastava — 16+ years trading, 8+ years mentoring Python algo trading, and a registered Zerodha Authorised Person (AP2516003481).

Disclosure: the account-opening link on this page is under Atul Shrivastava's Zerodha Authorised Person registration (NSE AP Reg: AP2516003481; Zerodha Broking Ltd. SEBI Reg: INZ000031633) and earns a revenue share. TheFinBaba is not a SEBI-registered Investment Adviser — this content is educational, not investment advice.