What is Backtesting?

Backtesting is the process of testing a trading strategy on historical data to see how it would have performed in the past.

The Simple Idea

Think of backtesting like a "time machine" for trading. Instead of risking real money today, you go back in time and ask: "If I had followed these exact rules over the last 5-10 years, how much money would I have made or lost?"

How It Works

Why Backtesting Matters

• Eliminates guesswork — you can see actual numbers instead of hoping a strategy works
• Reveals hidden risks — you can discover worst-case scenarios (maximum drawdowns) before they happen with real money
• Saves money — testing on historical data costs nothing compared to losing money in live markets
• Builds confidence — when you can see 10 years of simulated performance, you're better prepared for what to expect

Key Terms You'll See

What is a Trading Strategy?

A trading strategy is a set of precise, mechanical rules that tell you when to buy, when to sell, and how to manage risk.

Think of It Like a Recipe

Just like a cooking recipe has exact steps ("heat oil to 180°C, add onions, cook for 5 minutes"), a trading strategy has exact rules. There's no room for emotion or gut feelings — it's all systematic.

Components of a Strategy

Long vs. Short Trades

Strategies on QuantBucket can go long (buy first, sell later — profit when price rises) or short (sell first, buy back later — profit when price falls). Many strategies use both directions depending on market conditions.

Symbols & Timeframes

Understanding what markets and time intervals QuantBucket covers.

Supported Symbols

Timeframes Explained

The timeframe refers to the interval of the price bars (candles) used by the strategy to make decisions:

Key Metrics Explained

Every number on the dashboard tells a story. Here's what each one means — in plain English.

Create Your Account

Get started with QuantBucket in under a minute.

Sign Up

What You Get for Free

Every new account comes with a 100 credit signup bonus to help you explore the platform, plus 10 free credits every week. Free credits let you browse few strategies, modify them, backtest, view full backtest results every week forever. With signup bonus you can explore robustness and walk forward analysis with ease. You can do a lot on the platform for free before you even think about purchasing credits to build robust portfolio of strategies.

Quick Start Guide

Your first 5 minutes on QuantBucket — from login to understanding your first strategy.

The Home Dashboard

Your personalized command center for finding top-performing strategies at a glance.

Overview

When you log in, the Home page gives you a bird's-eye view of the best performing strategies and multiple ways to discover them:

• Top Strategies by Metric: Quickly jump to top performers in categories like Highest Returns, Lowest Drawdown, and Best Reward/Risk.
• Interactive Heatmaps: Use the "Return vs Max Drawdown" and "Win Rate vs Reward/Risk" heatmaps to discover strategies matching your exact risk profile. Click any cell in the grid to instantly filter and view strategies passing those thresholds (e.g. Return ≥20% with Drawdown ≤30%).
• Quick Access: Instantly view your credit balance and jump back into your bookmarked or unlocked strategies.

All Strategies Page

Browse the entire strategy library using powerful search, filtering, and sorting tools.

Finding Strategies

For a deep dive, navigate to the All Strategies page. Here you can browse the entire strategy library, presented as clean strategy cards.

Advanced Filtering & Searching

The left sidebar offers powerful tools to narrow down your search:

• Search bar: Type any part of a strategy name to find it instantly.
• Basic Filters: Filter by Symbol, Timeframe, or Strategy Type. Sort the results by any key metric.
• Quick Toggles: Check "Unlocked Only" or "Bookmarked Only" to view your saved and unlocked strategies.
• Performance Filters: Set precise minimum and maximum ranges for metrics like Yearly Return, Max Drawdown, Win Rate, and Profit Factor to find strategies that meet your exact criteria.

Strategy Cards

Instead of a dense table, strategies are displayed as clean cards showing their equity curve and key performance metrics. Each card features quick actions:

• ♡ Heart icon: Bookmark a strategy to your "Bookmarked" list for quick access later.
• Strategy Preview: Click any card to slide open a quick preview of its full performance details before jumping into the deep analysis.

Strategy Detail Page

A deep-dive view for each strategy. This is where you configure settings, run backtests, analyze performance, and stress-test reliability.

Page Layout

When you open a strategy, you'll see a clean layout designed for fast analysis:

• Top bar: Strategy name, tags (e.g., Index, Nifty, 15M), date added, and an "Actions" dropdown menu (for saving the strategy or adding it to your basket).
• Left sidebar: Navigation menu divided into Results and Advanced Analysis sections.
• Main content area: Displays the currently selected tab, such as Strategy parameters or Backtest charts.

Available Tabs

The left sidebar provides access to all aspects of the strategy. Here's a quick overview of what each tab does:

Strategy Tab

Your control center for configuring the strategy, viewing its logic, and running backtests.

Strategy Settings & Results Settings

At the top of the tab, you can customize how the backtest is run:

• Strategy Settings: Adjust the Instrument, Symbol, Timeframe, Max Trades Per Day, and Intraday Signal times.
• Results Settings: Define your capital, lot size, slippage %, brokerage, and statutory charges to ensure backtest results match your real-world trading conditions.
• Date Range: Select the exact start and end dates for your backtest.

After changing any settings, click the blue Backtest button to re-calculate the results.

Results Preview

On the right side, a quick Results Preview card instantly updates after a backtest. It shows a miniature equity curve and key metrics like Avg Yearly Returns, Maximum Drawdown, Win Rate, and Risk-Reward Ratio, letting you quickly validate parameter changes without leaving the tab.

Strategy Parameters

Every strategy has core tunable parameters (e.g., Moving Average Periods, ATR Multipliers). You can tweak these inputs directly to see how they impact performance. This allows you to optimize or customize the strategy to your preference.

Strategy Logic (Entry & Exit Rules)

Below the parameters, you'll see the exact trading rules in plain English:

• Buy Entry (Long) / Sell Entry (Short): Detailed pseudo-code explaining exactly what conditions trigger an entry, the order type (e.g., Stop order), entry price calculation, and order validity.
• Exit Rules: How the stop loss and take profit are calculated (e.g., "3.1 × ATR over 140 candles").

Indicator Reference

At the bottom, you'll find reference code for all the technical indicators used by the strategy (e.g., ATR, Gann HiLo Activator). You can view the exact formula in Python or TradingView (PineScript) to understand how the math works.

Backtest Results Tab

Your first stop when evaluating a strategy — the big picture at a glance.

Results Settings

At the top, you'll find the Results Settings panel. This allows you to quickly adjust parameters like Capital, Slippage %, Brokerage, Direction (Long/Short), and active Days without switching back to the Strategy tab. Click Apply Settings to re-run the backtest with your new constraints.

Summary

A compact dashboard card displaying the most critical top-level metrics:

• Headline Metrics: Avg Yearly Returns, Maximum Drawdown, and the all-important Yearly Return / Max Drawdown ratio are highlighted in large text.
• Key Stats: Quick glance at Start/End Dates, Total Returns, Net PnL, Win Rate, Profit Factor, Sharpe Ratio, and more.

Equity Curve

This is the most intuitive chart — it shows how your account balance would have grown (or shrunk) over time. A good strategy has an equity curve that trends upward smoothly. A jagged, choppy line suggests inconsistent performance. The red chart below the equity curve visualizes the drawdowns (periods of loss) along the way.

Monthly Returns Heatmap

A color-coded grid showing profit/loss for each month of each year. Green cells = profitable months, red cells = losing months. The "TOTAL" column on the right shows the full-year return. This helps you spot seasonal patterns and understand consistency.

All Detailed Metrics

Below the charts, you'll find comprehensive metrics broken down into four key areas:

• Overview & Returns: General performance stats, total PnL, initial/final capital, and trade counts.
• Risks & Ratios: Detailed drawdown metrics (max drawdown, average drawdown, days in drawdown) and risk-adjusted return ratios (Sharpe, Return/Max DD).
• Performance by Level: A unique table that breaks down metrics (like Win Rate, Avg Win/Loss, Profit Factor) grouped by individual Trade, Day, Month, and Year.
• Daily Compounding: Shows potential capital appreciation in an ideal scenario with strict daily compounding based on previous day PnL and position size updates.

Trades on Chart Tab

Browse every individual trade the strategy made and visualize exactly why it happened.

Trade List Table

The main view displays a comprehensive, paginated table of every trade executed during the backtest:

• Entry / Exit Details: Exact timestamps and price levels for both the entry and exit of the trade.
• Direction (DIR): Indicates if the trade was Long (L) or Short (S).
• P&L Columns: Shows the profit or loss in raw Points, Gross P&L (before costs), Net P&L (after costs), and Return %.

Filtering & Downloading

At the top of the table, you can filter the trades by a specific date range. You can also click the Download button to export the entire trade history as a CSV file for your own custom analysis in Excel or Python.

Interactive Chart & Trade Lifecycle

This is the most powerful feature of the tab. Clicking the VIEW ON CHART button next to any trade opens a detailed visual breakdown in a modal window:

The Chart View

The left side of the modal displays a fully interactive candlestick chart focused specifically on the period surrounding the trade. It automatically plots:

• Indicators: The exact indicators (e.g., Hull Moving Average, Gann HiLo, ATR) that the strategy used to make its decision, drawn exactly as they appeared at that moment.
• Signal & Execution Markers: Visual icons pinpointing exactly when the signal was generated, where the entry occurred, and where the exit happened.

Trade Lifecycle Panel

The right side of the modal provides a play-by-play breakdown of the trade's logic:

• Signal Logic: Plain English explanation of the exact condition that triggered the trade (e.g., "Hull moving average on high price has been FALLING for 17 candles").
• Entry Logic: Explains how the entry order was placed, what type of order it was (e.g., Stop order), the calculated price, and how long the order was valid for.
• Exit Logic & Reason: Details on how the exit was calculated and why it triggered (e.g., "End of Day", "Stop Loss Hit", "Take Profit Reached").
• Execution Lifecycle: A timeline showing when the pending order was created and when it was finally triggered.

Trade Insights Tab

Advanced analytics breaking down exactly when and how your strategy makes (or loses) money.

Performance Breakdown Charts

At the top of the tab, three bar charts help you identify structural biases in the strategy:

• Long vs Short Bias: Compares the performance and frequency of Buy vs. Sell trades. This tells you if the strategy is heavily dependent on bull or bear markets.
• Day of Week Performance: Shows average returns grouped by Monday through Friday. Useful for spotting days where the strategy consistently struggles (e.g., volatile Wednesdays or quiet Fridays).
• Time of Day Performance: Breaks down returns by the hour of the day (e.g., 09:00, 10:00). Crucial for intraday strategies to see if they perform better during morning volatility or afternoon trends.

Trade Duration vs P&L

Below the bar charts is an interactive scatter plot:

• X-Axis: Trade Duration (in minutes or days).
• Y-Axis: Return (%) per trade.
• Colors: Blue dots represent Long trades, red dots represent Short trades.

This chart is excellent for answering questions like: "Do my biggest winners take a long time to develop?" or "Are quick trades usually losers?". If you notice all your deep losses happen when a trade is held for too long, you might want to add a time-based exit to the strategy parameters.

Filters

You can dynamically update all insights on this page using the filters at the top right:

• Sample Period: Toggle between the full dataset or specific segments (e.g., In-Sample vs Out-of-Sample).
• Filter Year: Isolate the insights to a specific calendar year to see if the strategy's behavior has changed recently.

Trade CSV Download

Export every trade from the backtest as a CSV spreadsheet.

What's in the CSV

The CSV file contains one row per trade with columns including:

• Entry date/time and exit date/time (full timestamps)
• Direction (Long/Short)
• Entry price and exit price
• P&L in points and as a percentage
• Exit reason (Stop Loss, Take Profit, Trailing Stop, End of Day)
• Backtest context parameters (capital, slippage)

How to Download

Click the "Download CSV" button on the strategy detail page. The file will download to your computer. You can open it in Excel, Google Sheets, or any spreadsheet application.

Monte Carlo Simulation

A statistical stress test that answers: "Is this strategy's performance real, or could it be luck?"

The Big Question

Just because a strategy made money in the past doesn't mean it was skillful — it could have just been lucky. Monte Carlo simulation helps you figure out the difference.

How It Works (Simple Version)

Imagine you take the strategy's daily returns and throw them into a bag. Then you randomly pull them out in a different order — 10,000 times. Each random order creates a different "alternate history." By analyzing all 10,000 alternate histories, you can see:

• What's the worst-case drawdown you should expect?
• Is the strategy's Sharpe Ratio statistically significant?
• Is the strategy's return-to-risk ratio just lucky?

What You'll See

At the top, you'll find the Monte Carlo Settings panel where you can choose the number of simulations (e.g., 10,000) and click Run Monte Carlo Simulation.

Once run, you will see three panels, each containing a summary metrics table and a distribution histogram:

1. Max Drawdown Analysis

Shows the range of maximum drawdowns across 10,000 shuffled scenarios. Key values:

• 5% Best Case (P5): The drawdown was this low or less in 5% of scenarios.
• 50% Median (P50): The typical expected drawdown.
• 95% Worst Case (P95): You should plan for this level of drawdown as a worst-case scenario.

2. Return/MaxDrawdown Ratio Analysis

Tests whether the risk-adjusted return ratio is statistically different from zero (i.e., from pure randomness). Key values:

• 95% Conservative Bound (P5): We are 95% confident the true ratio is above this value.
• P-Value: If below 0.05, the ratio is statistically significant (probably not luck).
• Prob. Return/MaxDrawdown Ratio > 1.0: Probability that the true ratio exceeds 1.0.

3. Sharpe Ratio Analysis

Same analysis as above, but specifically for the Sharpe Ratio. Tells you how confident you can be that the strategy's risk-adjusted performance is genuine.

Robustness Tests

Stress-test a strategy's two most vulnerable points: lucky trades and parameter sensitivity.

Why Robustness Matters

A strategy might look amazing in backtesting but fail in real trading for two common reasons:

1. Lucky trades: The overall profit comes from just a few exceptional trades — remove them and the strategy falls apart.
2. Over-optimization (curve fitting): The strategy parameters are tuned so precisely to past data that even tiny changes break it.

QuantBucket's robustness tab is split into two sections to test both of these vulnerabilities.

1. Outlier Sensitivity

This test checks if your strategy's profitability depends on a few "lucky" trades. It progressively removes your top performing trades to see if the core strategy remains viable.

Outlier Sensitivity Settings

• Remove Best: Choose whether to remove a specific Number of trades or a Percentage of trades.
• Number of trades: Define the steps (e.g., 1, 5, 10).
• Click Run Outlier Sensitivity (This is a free test).

Outlier Sensitivity Analysis Table

The results populate a table comparing the Baseline (all trades) against the scenarios where top trades are removed (e.g., Remove Best 1, Remove Best 5, Remove Best 10). It displays comprehensive metrics like Avg Yearly Returns, Maximum Drawdown, Risk-Reward Ratio, and Profit Factor.

What to look for: If removing just 5 trades cuts your Avg Yearly Returns in half or destroys the Yearly Return / Max Drawdown ratio, the strategy is overly dependent on outliers.

2. Parameter Stability

This test systematically adjusts your strategy's parameters slightly up and down to see if performance crashes. If a strategy only works with a Hull Moving Average of exactly 85 and falls apart at 84 or 86, it's fragile.

Parameter Stability Settings

• Variation Steps: How far to test around the baseline (e.g., ±2 Steps).
• Step Sizes: Control the increment size for whole numbers and decimals.
• Target Parameters: Select which specific parameters to test. Each selected parameter adds to the total test combinations.
• Click Run Parameter Stability (Costs credits based on the number of parameters and steps).

Parameter Stability Analysis Charts

Once run, you can select a specific Chart Metric (like Return/MaxDrawdown Ratio) and a Stable Zone Tolerance (e.g., within 25% of Peak). You will see a line chart for each parameter:

• Tags: Each parameter is automatically tagged as Stable or Sensitive.
• Green Highlighted Regions: Indicate the "stable zones" where performance stays within your selected tolerance.
• Wide green plateaus mean the parameter is safe. Sharp peaks indicate the parameter is dangerously over-optimized.

Walk Forward Analysis

The gold standard for preventing curve-fitting by simulating real-world rolling optimization.

What is Walk Forward Analysis?

Instead of optimizing a strategy on the entire dataset (which leads to curve-fitting), Walk Forward Analysis breaks the data into chunks. It optimizes parameters on an "In-Sample" (IS) period, and then strictly tests those parameters on the immediate "Out-of-Sample" (OOS) unseen future data. It rolls this process forward across the entire history.

1. Setup & Generation

Before running the analysis, you must generate the optimization data:

• Parameters Selection: Choose the strategy parameters you want to optimize and define the list of values to test for each.
• Generate Data: Clicking Generate Walk Forward Data will test every combination of those parameters across the entire dataset. (Note: Costs credits based on combinations).

2. Walk Forward Settings

Once data is generated (or loaded from a previous run), configure the rolling windows:

• IS : OOS Split: The ratio of training data to testing data (e.g., 4:1).
• OOS Months: The strict duration of the Out-of-Sample testing window.
• Rolling Windows Schedule: A visual chart showing how the IS (blue) and OOS (green) windows overlap and roll forward through time.

Click Run Walk Forward Optimization to evaluate the strategy using these windows (Costs 1 credit).

3. Evaluating the Results

The results section provides a comprehensive breakdown of the walk forward performance:

Walk Forward Evaluation

The strategy is graded on five strict criteria. Passing these means the strategy is highly robust:

• Returns Stability: Does the Out-of-Sample profit hold up compared to the In-Sample profit?
• Drawdown Stability: Are the OOS drawdowns proportional to the IS drawdowns?
• Profitable OOS Runs: Is the strategy consistently profitable across the different rolling windows?
• Max Profit in Single Run: Ensures the strategy isn't dependent on a single lucky window.
• Min Trades in any IS run: Ensures statistical significance in the training data.

Detailed Metrics & Heatmap

You can toggle between different views (OOS, Full, WF, Baseline) to compare performance. The Monthly Returns Heatmap and All Detailed Metrics panels update instantly to show you the exact performance of the Walk Forward strategy (WF) versus the standard Baseline.

Walk Forward Windows Analysis

This panel breaks down each individual window. You can see the Optimal Parameters that were chosen for that specific window, and compare the IS vs OOS performance side-by-side. The final window even provides Suggested Forward-Test Parameters to use going forward.

My Strategies

The foundation of your portfolios: your personally saved custom strategies.

Overview

The My Strategies page acts as your personal library. Whenever you tweak parameters on the Strategy Detail page and hit "Save", the strategy lands here.

Building From Here

To begin building a portfolio, you first need to collect strategies. From the My Strategies page, you can click the Add to Basket button on any strategy card to queue it up for analysis. You can also add strategies to your basket directly from the Strategy Detail page itself.

The Portfolio Basket

Your workbench for combining, weighting, and analyzing multiple strategies together.

Populating the Basket

The Basket is where the magic happens. You can populate it in two ways:

• Bottom-Up (Add as you go): As you browse and save strategies across the app, simply click Add to Basket. They will accumulate here.
• Top-Down (Import): Open the Basket directly and click the Import Strategies button. This opens a menu allowing you to search and bulk-select multiple strategies from your "My Strategies" list to drop straight into the Basket.

Analyzing Your Combination

Once your strategies are in the Basket, you can:

• Adjust the capital allocation/weighting for each strategy using the Settings menu.
• Define a global date range for the combined backtest.
• Click Analyze to merge the equity curves, trades, and metrics into a single unified performance report.

You can instantly view correlation matrices to ensure your strategies are truly diversified, and compare the combined performance against the individual strategy contributions.

Saving Your Work

If you are happy with the combined analysis, click Save as Portfolio at the top right. Give it a name, and it will be permanently stored in your account.

My Portfolios

Track and manage the final custom portfolios you have created and saved.

Overview

The My Portfolios page lists all the combined strategy baskets you have previously saved via the "Save as Portfolio" action.

Creating & Editing

• + Create New Portfolio: Clicking this button at the top right acts as a shortcut. It opens a modal where you can name a new portfolio and instantly select strategies to include from your saved list. Clicking "Create" will then load these directly into the Basket for analysis.
• Re-Analyze: Click the play icon on any existing portfolio card to reload those exact strategies back into the Basket, allowing you to edit weights or run a fresh analysis.
• Delete: Click the red trash icon to permanently remove a saved portfolio.

Profile Settings

Manage your account details, security, and trading configs.

Overview

Access your settings by clicking your profile icon in the top navigation bar. The Profile Settings page is divided into three main tabs on the left:

1. Account & Security

Manage your core identity and login credentials here:

• Profile Details: Update your Email Address, Display Name, and Phone Number.
• Security: Secure your account by entering a New Password (leave blank to keep current).

2. Credits

Track your platform usage and balance:

• Balance: View your total available credits, split between Free (refills automatically) and Paid (never expires).
• Buy Credits: Instantly purchase more credits if you run low.
• Recent Activity: A ledger showing exactly when and where your credits were spent (e.g., Walk Forward Generate, Monte Carlo Simulation).

3. Backtesting Configs

This is where you define your global default trading assumptions per asset class (Index, Index Option Buying, Index Option Selling, Index Futures, Equity). These act as your personalized templates:

• Capital & Lot Size: Define your default starting capital and lot size/lots.
• Brokerage & Slippage: Accurately model your real-world trading costs by selecting your Brokerage Type (e.g., Min(%, ₹)) and entering precise Slippage and Brokerage percentages/flat fees.

Credits

QuantBucket uses a simple credit system — pay only for the compute power you use.

Credit Costs

Free Credits

Every account gets free credits that reset weekly. These are always consumed first before paid credits. Free credits let you explore the platform and test a few strategies at no cost.

Paid Credits

Purchased credits never expire. You can buy them from the Pricing page.

Checking Your Balance

Your credit balance is displayed in the top-right corner of every page. To see a detailed breakdown of your free vs. paid credits, go to Profile Settings and select the Credits tab.

Pricing

Credit packs with increasing value at higher tiers. All purchased credits never expire. Go to Pricing Page →

Referrals

Invite your friends to QuantBucket and earn free credits.

How It Works

Key Rules

• No Expiry: Referral credits never expire, unlike weekly free credits.
• Unlimited Referrals: There is no limit to how many friends you can invite. The more you refer, the more credits you earn.
• Verification Required: Your friend must verify their email for the bonus to trigger.

Idea Board

Pitch new features, strategies, or improvements and help shape the future of QuantBucket.

Community Ideas

The Idea Board is where our community voices what they want to see next. If you have an idea for a new strategy, a platform feature, or a UI improvement, post it here!

• Post Ideas: Click the "New Idea" button to pitch your concept.
• Upvote: Browse ideas posted by other users and upvote the ones you want us to prioritize building.

Glossary

All the technical terms used on QuantBucket, explained in plain English.

Frequently Asked Questions

Quick answers to common questions.

General

Do I need to know how to code?

No. QuantBucket is designed for non-programmers. All strategy logic is shown in plain English, and all analysis is point-and-click.

Are these real trading strategies?

Yes — they are systematic, rule-based strategies generated and tested on real historical market data from Indian exchanges (NSE/BSE). However, past performance does not guarantee future results.

Can I use these strategies for live trading?

The strategies are provided for educational and research purposes. You should thoroughly understand the risks involved and do additional forward testing before risking real capital.

Account & Credits

Do credits expire?

Paid credits never expire. Free credits reset weekly.

What happens when I unlock a strategy?

For 1 credit, you gain lifetime access to the strategy's core details and advanced tools. This unlocks the Strategy Logic, Trade List, and Trade Insights tabs, and allows you to run advanced analysis like Monte Carlo simulations, Robustness Tests, Walk Forward Analysis, and download trade data as CSV.

Can I get a refund for purchased credits?

No, all credit purchases are final and non-refundable. Because every account receives a 100-credit signup bonus and 10 free weekly credits to thoroughly test the platform risk-free, we do not offer refunds on purchased add-on packs. However, purchased credits never expire and will remain in your account indefinitely.

What happens if a test is cancelled midway?

Advanced tests (like Walk Forward or Parameter Stability) deduct the maximum possible cost upfront. If you cancel a test midway, or if the engine skips invalid parameter combinations, the credits for the remaining un-run tests are instantly and automatically refunded to your QuantBucket balance.

Technical

What does "RESULTS MAY BE OUTDATED" mean?

This warning appears when the pre-computed results for a strategy are stale because the strategy's code was recently updated. The admin will regenerate the cache soon. If the strategy looks interesting, you can still run a live backtest using the "Run Backtest" button to confirm it still holds up.

Why are the backtest results different when I change slippage?

Slippage affects the price at which trades are filled. Higher slippage means worse fill prices, which reduces profit. Even 0.01% slippage can noticeably impact results over thousands of trades.

What data is used for backtesting?

QuantBucket uses real, 1-minute OHLC (Open, High, Low, Close) price data from Indian markets. Strategy indicators are computed on the strategy's timeframe (5M or 15M), but stop-loss and take-profit checks happen on the 1-minute data for maximum precision.