TradingView has become one of the most popular trading platforms for technical analysis and charting. Its online charting software is free to use and packed with powerful features for analyzing financial markets.
One of TradingView’s most advanced capabilities is its backtesting tool. Backtesting allows you to test automated trading strategies on historical data to see how they would have performed.
But is TradingView’s backtesting feature a viable option for rigorously testing your trading strategies? In this comprehensive review, we’ll take an in-depth look at TradingView backtesting to see if it’s an ideal solution for strategy testing and development.
Overview of TradingView Backtesting
TradingView’s backtesting feature allows you to test trading strategies on historical price data to gauge their hypothetical performance. You can backtest stock trading strategies, forex strategies, crypto strategies and more.
Some key things to know about TradingView backtesting:
- Programming Required – You need to know Pine Script, TradingView’s proprietary coding language, to program your strategies.
- Customizable – You can fully customize strategies with indicators, conditions, orders types, etc.
- Flexible Timeframes – Backtest across minute, hourly, daily or weekly timeframes on the timeframe of your choice.
- Detailed Statistics – TradingView provides extensive backtesting statistics to evaluate performance.
- Cloud Processing – Strategies are run on TradingView’s cloud servers for faster backtesting.
- Visual Replay – Watch a visual replay of your backtest on the chart.
- Strategy Sharing – You can publish strategies for others to see, test, and automate.
Key Benefits of TradingView Backtesting
TradingView backtesting provides several advantages for testing and developing trading systems:
1. Easy to Use Interface
The backtesting interface is integrated directly into TradingView’s charting application. This makes it easy to quickly backtest ideas without having to export data or learn another platform.
Settings like strategy logic, initial capital, commissions, slippage etc. can all be configured through their simple UI.
2. Cloud Processing Speed
Since backtests are run on TradingView’s cloud servers, you can get results much faster than local backtesting software. Strategies can be run on multiple historic years in just seconds or minutes.
This allows you to quickly iterate on strategy ideas without waiting hours or days for a backtest.
3. Detailed Performance Metrics
TradingView provides in-depth statistics on key performance metrics:
- Profitability – Gross profit, gross loss, profit factor, expectancy
- Risk – Max drawdown, Sharpe Ratio, sortino ratio, calmar ratio
- Efficiency – Return on equity, return on investment
- Trade Activity – Number of trades, percent profitable, average trade
The metrics give you quantitative insights into a strategy’s hypothetical viability.
4. Visual Replay on Charts
One big advantage TradingView has over standalone backtesting software is the ability to visually replay your full backtest on the chart.
You can watch each entry and exit play out on historical data to better understand the strategy’s actions. This helps quickly identify flaws or areas for improvement.
5. Easy Strategy Sharing
You can publish backtested strategies on TradingView’s platform for free. Other traders can then easily test your strategies and provide feedback.
Sharing also allows you to automate strategies by connecting TradingView to brokers that support automated trading. Published strategies can be turned into bots.
6. Integrated Strategy Development
Having backtesting directly in the TradingView environment leads to an integrated workflow for developing strategies.
You can seamlessly switch between building/coding a strategy in Pine Script, backtesting it, then analyzing it on the charts – all within the same platform.
This helps accelerate strategy R&D versus using separate tools.
Limitations of TradingView Backtesting
While TradingView backtesting offers many benefits, it does have some limitations:
Limited History for Cryptocurrencies
TradingView has abundant historical tick data for stocks and forex currencies often going back decades. However, for cryptocurrencies, the historical data is more limited.
For some crypto pairs, TradingView may only have daily data going back a few years. This makes robust backtesting more difficult for crypto strategies.
Assumptions of Perfect Orders
TradingView backtesting currently assumes all orders are filled perfectly at the exact requested price and timestamp. This does not account for potential slippage and gaps you would experience in live markets.
So performance results may be inflated compared to real-world trading where orders can slip or fail to fill. More sophisticated order execution logic is needed.
Coding Required
You must learn TradingView’s Pine Script language to code strategies which has a learning curve. It’s less accessible to traders without programming experience compared to visual strategy builders.
This can limit the pool of traders able to utilize TradingView backtesting and share strategies.
Limited Optimization
While you can optimize parameters in TradingView, the optimization methods are basic and local optimizers. More advanced global optimization and machine learning techniques cannot be applied.
No Portfolio-Level Backtesting
TradingView currently only allows backtesting one strategy/system at a time. You cannot backtest a whole portfolio of multiple systems to analyze correlations, drawdowns, risk management etc.
This limits its usefulness for fund-level strategy analysis. You would need additional software to backtest multiple strategies simultaneously.
Costs for Live Trading
To connect TradingView strategies to live brokers for automated trading costs upwards of $15/month for the API connection. This recurring fee eats into profitability when going live.
The platform is less amenable to very low cost, high frequency trading. Costs add up quickly as you scale strategies.
TradingView Backtesting vs Alternative Platforms
TradingView is far from the only platform that provides backtesting functionality. How does it compare to popular alternatives for more advanced users?
Below we compare TradingView to MetaTrader 4, QuantConnect, and Deltix for professional-level backtesting:
| Feature | TradingView | MetaTrader 4 | QuantConnect | Deltix |
|---|---|---|---|---|
| Software Type | Browser-based | Desktop | Cloud | Desktop/Cloud |
| Language(s) | Pine Script | MQL4/MQL5 | C#, Python, F# | Python, C++, C#, Java |
| Ease of Use | High | Moderate | Moderate | Low |
| Backtest Speed | Very Fast | Moderate | Very Fast | Very Fast |
| Customization | High | High | Very High | Very High |
| Strategy Optimization | Basic | Moderate | High | Very High |
| Tick Resolution | Tick, Min, Hour, Day | Tick, Min, Hour, Day | Tick, Second | Tick, Nanosecond |
| Machine Learning Capabilities | None | None | Extensive | Extensive |
| Portfolio Backtesting | No | Yes | Yes | Yes |
| Cost | Free platform $15+/month deployment | Free | $99/month Fee discounts over $100k | >$4,000/yr |
As we can see, TradingView provides the easiest user experience given its web interface and visual backtesting. It also leverages cloud servers for very fast backtesting speeds.
However, platforms like QuantConnect and Deltix offer features more tailored for advanced users andinstitutions. This includes highly-customizable backtesting, optimization methods, ultra high-resolution data, machine learning, and portfolio-level analysis.
So while TradingView meets the needs of many retail traders, institutions may prefer more heavy duty platforms with additional capabilities and support.
Key Criteria for Evaluating TradingView Backtesting
Now that we’ve looked at the benefits and limitations of TradingView backtesting, how can we evaluate if it’s a viable tool for your strategy development and testing needs?
Here are the key criteria to consider:
Data Quality and History
- Does TradingView offer clean, accurate data for the securities you will trade?
- Is there sufficient historical data available for robust backtesting?
Customization
- Can you program the precise strategy logic and rules required?
- Does TradingView support the indicators, trade management techniques, and order types you need?
Statistical Significance
- Can your strategies be reliably tested across 20+ years of data and a wide range of market conditions?
- Will the platform allow extensive parameter optimization and Monte Carlo analysis?
Quality of Performance Metrics
- Does TradingView provide all the performance statistics and visualizations you need to properly evaluate strategies?
- Can trading costs, execution slippage, and real-world factors be modeled?
Ease of Automation
- How difficult is it to automate strategies for live trading after backtesting on TradingView?
- What are the costs associated with automated trading through TradingView?
The more of these criteria TradingView can meet, the better suited it will be for your specific backtesting and development requirements.
Best Practices for Effective Backtesting on TradingView
If you determine that TradingView fits your needs, then what are some best practices to ensure you conduct rigorous, insightful backtests? Here are some tips:
- Always verify strategy logic – Code review the Pine Script to check for errors before backtesting. Fix bugs first.
- Optimize carefully – Don’t overfit parameters. Walk forward optimize and verify on out of sample data.
- Test multiple timeframes – Evaluate performance on both short and longer timeframes when relevant.
- Vary initial conditions – Test across different starting capital, dates, and market conditions.
- Check statistical relevance – Ensure you have a large enough sample size for conclusions to be valid.
- Account for trading costs – Add conservative commissions and slippage estimates to results.
- Visualize key metrics – Create charts of equity curves, drawdowns, trades etc. to analyze performance.
- Replicate live environment – Model real-world performance factors like partial fills and execution lag.
- Compare to benchmarks – Contextualize performance versus buy and hold returns and other benchmarks.
Following best practices helps ensure your backtesting is informative, representative of reality, and avoids performance overfitting.
Questions and Answers
Here are answers to some frequently asked questions about TradingView backtesting:
Q: What training is needed to use TradingView backtesting?
A: You’ll need to learn Pine Script which does involve a learning curve. Experience coding in other languages like Python helps. TradingView has documentation and a Pine Script course to get started. Having background in trading strategy design is also very helpful.
Q: Can I backtest strategies for stocks, forex, crypto, and other markets?
A: Yes, TradingView supports backtesting on stocks, forex, crypto currencies, commodities, indices, and more. The historical data availability varies across different asset classes though.
Q: Is there a limit to how long I can backtest?
A: No set limit, but your strategy complexity, data resolution, and computer memory are factors. You can backtest across very long time periods of 10-30+ years if you have the historical data. Execution speed becomes slower the longer the backtest duration.
Q: Does TradingView allow multiple strategy backtesting?
A: Currently TradingView only allows backtesting one strategy/system at a time. You cannot yet combine multiple systems into a portfolio backtest. This is a limitation compared to more advanced platforms.
Q: Can I automate my TradingView strategies to trade live?
A: Yes, you can deploy TradingView strategies to trade live by connecting to supported brokers like Oanda using their API. This does involve monthly fees of around ~$15 per connection to brokers.
Q: Is there a way to account for slippage in backtesting?
A: TradingView does not inherently model slippage, but you can account for slippage in your strategies by incorporating static or dynamic slippage deductions on each trade as part of your logic.
Q: Can I speed up backtesting by using pine script V4?
A: Yes, Pine Script V4 includes performance improvements that can significantly speed up backtesting, particularly when using functions like security() and timeresolution.
Conclusion – A Strong Backtesting Choice for Many Traders
TradingView delivers an accessible backtesting solution that fits the needs of many retail traders and investors. The integrated charts and developer-friendly Pine Script language allow rapid prototyping and analysis without the complexity of traditional backtesting software.
The tool provides extensive strategy customization, abundant historical data for major markets, fast cloud processing, and detailed performance statistics to empower informed development. TradingView community sharing also unlocks added value.
Limitations exist around cryptocurrency data coverage, lack of portfolio-level testing, and order execution realism that affects applicability for very sophisticated users. Furthermore, acquiring the knowledge to properly build and interpret backtests requires significant learning.
But for individual traders seeking robust free software they can grow into, TradingView is likely the strongest online web platform available right now for backtesting and automating trading strategies across stocks, forex, and crypto. The platform combines accessibility for coding beginners with advanced customization for power users.
If you invest the time into mastering Pine Script and apply proper backtesting principles, TradingView provides an exciting environment to research, develop, and even ultimately deploy your own custom trading strategies.
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