Concepts
Core financial concepts and terminology used throughout the platform.
Stocks & Indices
A stock (or share) represents partial ownership in a company. When you buy a stock, you own a fraction of that company and are entitled to a share of its profits (dividends) and asset value.
A stock index is a collection of stocks that measures the performance of a market or sector. Common indices include:
| Index | Market | Description |
|---|---|---|
| NIFTY 50 | India (NSE) | Top 50 Indian companies by market cap |
| NIFTY 100 | India (NSE) | Top 100 Indian companies |
| NIFTY 500 | India (NSE) | Broad Indian market coverage |
| S&P 500 | US | Top 500 US companies |
Market capitalization(market cap) is the total value of a company's outstanding shares: Price x Shares Outstanding. It determines a stock's weight in most indices and is a key measure of company size.
Key Metrics
These metrics appear throughout the platform. Understanding them helps you interpret analytics correctly.
P/E Ratio (Price-to-Earnings)
How much investors pay per rupee/dollar of earnings. A P/E of 20 means investors pay 20x annual earnings. Lower P/E may indicate undervaluation; higher P/E may indicate growth expectations.
Formula: Stock Price / Earnings Per Share
Beta
Measures a stock's sensitivity to market movements. A beta of 1.0 means the stock moves with the market. Beta > 1.0 means more volatile; beta < 1.0 means less volatile.
Example: Beta = 1.3 means the stock moves 30% more than the market on average
Sharpe Ratio
Risk-adjusted return. Measures how much excess return you receive per unit of risk (volatility). Higher is better. A Sharpe above 1.0 is generally considered good; above 2.0 is excellent.
Formula: (Portfolio Return - Risk-Free Rate) / Portfolio Volatility
CAGR (Compound Annual Growth Rate)
The annualized rate of return, smoothed over the entire period. Tells you the consistent yearly growth rate that would have produced the same total return.
Formula: (Ending Value / Starting Value)^(1/Years) - 1
Maximum Drawdown
The largest peak-to-trough decline in portfolio value. Measures the worst-case loss you would have experienced if you invested at the peak and sold at the trough.
Example: Max Drawdown of -15% means the portfolio dropped 15% from its highest point
Volatility
Standard deviation of returns, usually annualized. Measures how much a portfolio's returns fluctuate. Lower volatility means more stable returns.
Annualized by multiplying daily volatility by sqrt(252 trading days)
Dividend Yield
Annual dividends paid as a percentage of the stock price. A 3% yield means you receive 3% of your investment as dividends each year.
Formula: Annual Dividends Per Share / Stock Price
Factor Models
A factor modelexplains stock returns using common drivers called "factors." Instead of analyzing each stock individually, factor models identify systematic patterns that affect groups of stocks.
Galedge uses a 21-factor risk model with three types of factors:
| Type | Count | Examples | What It Captures |
|---|---|---|---|
| Market | 1 | BETA | Overall market direction |
| Style | 10 | SIZE, MOMENTUM, VALUE, VOLATILITY, QUALITY, GROWTH, LEVERAGE, LIQUIDITY, DIVIDEND_YIELD, EARNINGS_YIELD | Company characteristics |
| Industry | 10 | TECHNOLOGY, FINANCIALS, HEALTHCARE, ENERGY, CONSUMER, INDUSTRIALS, etc. | Sector membership |
Factor exposure measures how much a stock tilts toward a particular factor. A stock with high MOMENTUM exposure has had strong recent returns. A stock with high VALUE exposure trades at a low price relative to its fundamentals.
Factor return is the return earned by that factor over a given period. If the MOMENTUM factor returned 2% this month, stocks with high momentum exposure benefited from this tailwind.
Attribution
Performance attributionanswers the question: "Why did my portfolio return X%?" It decomposes returns into their sources.
Return Decomposition
Splits portfolio return into two components:
- Factor Return — return explained by factor exposures (systematic risk)
- Idiosyncratic Return — stock-specific return not explained by factors (alpha or noise)
Brinson Attribution
Decomposes excess return (vs benchmark) into:
- Allocation Effect — did you pick the right sectors to overweight/underweight?
- Selection Effect — within each sector, did you pick the right stocks?
- Interaction Effect — the combined impact of allocation and selection
Portfolio Optimization
Portfolio optimization finds the best set of weights (how much to invest in each stock) given an objective (maximize return, minimize risk) and constraints (position limits, sector limits, beta bounds).
Galedge uses CVXPY, a convex optimization library, to solve these problems. The optimizer takes historical return data, computes a covariance matrix (how stocks move together), and finds weights that satisfy your objective and constraints.
Key concepts:
- Efficient Frontier — the set of portfolios that give the highest return for each risk level
- Tracking Error — deviation of portfolio returns from a benchmark; minimizing this keeps you close to the index
- Turnover — how much of the portfolio changes at each rebalance; higher turnover means higher transaction costs