Complete Stock Market Training with Practical Approach

Open a Zerodha trading account by submitting PAN card, Aadhaar, income proof, and bank details. Complete OTP verification, Digilocker linkage, and e-sign to receive login credentials.

Open an ICICI Direct trading account by submitting PAN, Aadhaar, signature, linking bank and demat accounts, and complete KYC via Digilocker or Aadhaar with penny drop and e-sign.

Learn how to add funds to your trading account and withdraw funds across three brokers, including ICICI Direct and Zerodha, with bank linkage, UPI, net banking, and withdrawal delays.

Explore the ICICI Direct trading terminal, log in to view your portfolio, place delivery or intraday orders, and review the order book. Allocate funds by category and track positions.

Navigate Zerodha Kite's trading terminal to add scripts, view MarketWatch, access charts and market depth, and analyze fundamentals, technicals, and option chains on a feature-rich dashboard.

Learn how to place delivery (cash and carry) and intraday orders, understand leverage and limit versus market orders, and manage squaring off and demat holdings.

Acquire one ICICI Bank share on July 10, verify the trade via contract notes and emails, and confirm it is credited to your demat account for long-term or intraday trading.

Sell an ICICI Bank share from a demat account at market rate, exiting the position after completing CDSL verification. Track the margin and funds remaining after the sale.

Master stop loss orders to cap losses and secure profits using trigger prices, with intraday and cnc distinctions and the cover order that couples exit with entry.

Explore after-market and pre-market order types, multi-day orders, iceberg and delivery orders, plus margin and stop-loss options across brokers like Zerodha and ICICI Direct.

Derivatives, including futures and options, are risky and costly, with a 90% trader loss rate and a need for expert understanding and tested strategies.

Explore the history of derivatives through forward contracts, where buyers and sellers commit to future delivery at a set price, highlighting counterparty risk and market scenarios.

Futures contracts overcome forward contract problems by standardizing quantity and dates, trading on regulated exchanges with margin and counterparty risk, and involving underlying assets, lot size, contract size, and expiry.

Learn how leverage in futures works, with a 10x example from a 1 crore contract funded by 10 lakhs, and why derivatives risk management matters to avoid large losses.

Put up the total margin before entering a futures trade to prevent counterparty risk. Monitor margin as volatility changes, since margin requirements can rise and are released when you exit.

Learn to place a futures buy order, monitor margin and leverage, exit with small losses, and use baskets to combine long July with short August to reduce margin.

Explore how a zerodha contract note illustrates futures trading in derivatives, highlighting how a small price difference, lot size 400, and taxes and brokerage turn profits into losses.

This lecture explains mark-to-market (M2) in futures trading, showing how daily profit and loss, margin revisions, and near-expiry volatility drive settlements and possible additional funds.

Understand expiry settlement: buyers pay the settlement price and sellers deliver shares or gold. Indices settle in cash, and near expiry traders roll over.

Explore how open interest tracks active futures contracts and how volume records transactions, illustrating build-up and unwinding of positions, and how 95% market-wide limits trigger a ban on new contracts.

Explore options, including call and put options, as derivatives. An apartment example shows how a five lakh rupees non-refundable surety creates leverage and exposes buyers and sellers to expiry outcomes.

Learn how stock options work, including underlying, strike price, premium, and expiry, and distinguish call and put options with a concrete Infosys example.

Learn how a long call on Infosys works: profits rise above the break-even (strike plus premium) while losses stay limited to the premium, with seller profits mirroring buyers.

Explore how put options provide a right to sell at a strike price by paying a premium, and examine profit, loss, and breakeven scenarios at expiry.

Learn how selling an option requires higher margin due to unlimited risk, while buying options keeps risk limited, and how put and call hedging protects positions using real Infosys examples.

Explore the option chain concept with strike prices for Infosys, detailing call and put options, moneyness, ATM, in the money, and out of the money.

Explore the basics of technical indicators, what they are, how they forecast trends, and how to code them in Python for trading strategies, featuring Bollinger bands, RSI, MACD, and EMA.

This lecture shows how moving averages smooth stock price data to reduce noise. It compares simple and exponential moving averages, using 5-, 12-, and 26-day windows with Python and charts.

Compute the MACD by subtracting the 12-day fast EMA from the 26-day slow EMA, and plot a 9-day signal line. Identify bearish and bullish crossovers as trend reversals.

Learn how Bollinger bands measure volatility, using a 20-day simple moving average with upper and lower bands two standard deviations away, identifying overbought and oversold signals.

Measure market volatility with the average true range, comparing it to Bollinger bands, by computing true range and applying a 14-day exponential moving average.

Demonstrates plotting close prices and ATR on shared axes, with a twin y-axis for ATR to reveal volatility and trend sustainability. Shows ATR and Bollinger bands as complementary volatility indicators.

Explore the relative strength indicator (RSI), a leading momentum oscillator from 0 to 100 that measures the internal strength of an asset, flagging oversold and overbought conditions.

Explore how to compute the relative strength index (RSI) from gains and losses, using 14-day averages and a loop, then visualize close price and RSI in two subplots.

Learn the supertrend, a trend-following indicator using average true range, upper and lower bands, and a multiplier, for intraday trading signals and trend reversals.

Compute the supertrend in Google Sheets by calculating true range and seven-period ATR with an exponential moving average, then derive basic upper and lower bands and identify trend reversals.

Apply Python to compute the supertrend using ATR with a 7-period range and a 3 multiplier, determine final and basic upper bands, and visualize trends with Plotly.

Explore Renko charts, a data visualization technique that forms bricks from price movement rather than fixed time intervals, and learn how brick size and price thresholds shape time series data.

Learn how to build renko bricks in python using brick size for algo trading and data visualization, with green or red bricks by trend.

Calculate Renko brick size with ATR and visualize Renko charts using the finance library built on matplotlib, plotting Nifty data and coloring bricks green or red.

Learn how ADX measures trend strength (0–100) to show whether bulls or bears control, while plus and minus directional indicators confirm direction and filter sideways markets.

Calculate adx in Google Sheets or Excel by building true range, directional momentum (plus and minus), and a smoothed p value using 14-period rolling sums.

Learn to compute the ADX in Python with a pandas library from high, low, and close values in one line of code, compare results to Google sheets and plot indicators.

Explore how investors use qualitative and quantitative fundamental analysis to size up companies, identify undervalued stocks, and assess cash flows and competitive advantages.

Harvest insights from annual and quarterly reports to assess financial health, strategy, and risks using balance sheets, income statements, cash flow, and management discussion and earnings calls.

Analyze the income statement to understand revenue from operations, other income, expenses, taxes, and net profit, and learn margin calculations like gross, operating, and net margins.

Explore a company’s balance sheet by examining assets and liabilities across current and non‑current sections, assessing liquidity with current and quick ratios, and evaluating equity, debt, and key trends.

Analyze the cash flow statement to understand operating, investing, and financing activities, and assess liquidity, solvency, free cash flow, and non-cash items.

Learn how algorithmic trading uses computer programs to automate stock trades, remove emotion, and execute decisions at optimal times using Python and Zerodha Kite Connect API.

Set up data science environment with Anaconda, creating separate Python environments for projects like Kite Connect. Install and use Jupyter Notebook and Spyder to manage libraries on Mac or Windows.

Launch and use Jupyter Notebook to write, run, and organize code with cells and markdown, then explore Spider and MySQL server for databases and SQL queries.

download historical ohlc data across intervals from 5 minutes to daily using the historical api addon, with token conversion. fetch 100-day chunks and save to a database or csv.

Download live tick data with the kite ticker library in Python, login via Kite Connect, and fetch instrument tokens for symbols like Nifty 50, Infy, and TCS.

Master placing and managing orders in Kite Connect with the Python wrapper, including market, limit, and stop loss orders for intraday futures and options, plus order validity.

Explore a practical stock trading strategy by testing top moving stocks with MACD and Supertrend indicators in real time using Zerodha, including code-driven order execution and risk-aware tuning.

Learn how emotions drive trading decisions and how to cultivate emotional maturity and serenity. Develop awareness, acceptance, and action to detach from impulsive moves and improve stock market outcomes.

Explore how the brain processes information. Filter input through selective attention and use inference and heuristics to form biases like delete, distort, and generalize in decision making.

Understand how amygdala hijack disrupts stock market decisions and learn to switch from reflexive gut responses to reflective, logical thinking to guard against emotional biases.

This lecture introduces factfulness, highlighting our blind spots and overconfidence in what we think we know about the world. It encourages data-based opinions, humility, and checking assumptions with facts.

Understand how probabilities guide better investing decisions by examining base rates and risks, as the likelihood of consistently making money in stock trading remains very low.

Explore loss aversion as a key of prospect theory, where fear of losses outweighs gains. Learn how System 1 and System 2 drive risk and trading choices.

Explore anchoring, a cognitive bias where initial information forms a reference point, influencing stock market decisions, investor valuations, and price expectations.

Distinguish trading from investing by outlining short-term positioning versus long-term wealth building. Highlight risks, discipline, and concepts such as leverage, costs, and risk management.

Expose the truth about derivatives trading, detailing leverage, margin calls, mark-to-market, and risk while challenging overhyped claims and emphasizing informed, cautious investing.