Overview of Equity Selection | Fundamental Analysis | Technical Analysis

Hello All ! Purpose of this group is to explore '**Backtesting** ***Equity Investment Strategies.***' We'll learn how to backtest trading ideas using historical data, the foundational step towards developing effective Investment Strategies. **This involves learning to retrieve historical stock data using *Google Finance* shortcuts and calculating overall profit/loss for various strategies within specified timeframe.** Experienced investors are encouraged to share their valuable lessons with beginners, fostering a collaborative learning environment for all. An example for a Strategy is: Buy 100 stocks of HDFC BANK when the 20-day simple moving average is greater than the 10-day simple moving average (Close price). Sell when the stock price goes up by INR 20 per share or sell at a stop loss when the price goes down by INR 20 lower than the buy price, a very basic Investment Strategy. Before implementing this strategy into a real trading environment, the strategy is tested on historical stock data to see how it would have performed in the past. This process is called backtesting. *Every individual and institutional investor Backtests their Strategies or Trading Systems using historical stock data. This process helps evaluate past performance and enables them to make probabilistic predictions about future stock prices. Investors typically create and test multiple strategies, adjusting and modifying them based on backtesting results to optimize performance. They carefully calculate risk, allocate capital prudently to absorb potential losses, and finally, implement the most promising strategies with the expectation of achieving optimal returns.* In this group, we try to learn to Backtest similar strategies, calculate the Strategy Output results (Overall net profit/loss, number of profit and loss trades, days with no trade executed etc.) in the given time period. Automate the 'Backtesting Strategy' to get Output results for multiple inputs in One Click using *Google App Script*.