■ What is TradeNavi?
TradeNavi allows you to verify the performance of your self-defined trading conditions using historical Bitcoin price data.
It does not perform actual trades. There is no order-placing function, nor is it linked to an exchange account.
When you run a backtest, advice is displayed based on the results. An optimization function allows you to explore optimal values for each parameter.
Execution results are saved in the history and can be managed with stars and tags. You can check the performance for subsequent periods by running the test again later.
It also includes explanations of technical indicators and a glossary, allowing you to learn knowledge applicable to stocks and forex.
■ What you can do
・View results on a chart
The closing price line graph is overlaid with the selected indicator and trading timing. You can scroll left and right, and read the values of any candlestick using the crosshairs.
・Combine and specify purchase conditions
20 types of indicators, including Moving Average (EMA/MA), Bollinger Bands, MACD, RSI, Stochastic, RCI, DMI/ADX, Ichimoku Kinko Hyo, Donchian, Parabolic SAR, etc. * **Combine and specify selling conditions:** 24 types of conditions are available, including 3-stage trailing stop, fixed percentage stop-loss/take-profit, number of positions held, ATR stop, Chandria stop, and consecutive upward/downward trends.
* **Combine up to 3 conditions:** Since you can select AND/OR for each condition, you can create conditions such as "both A and B" or "A or B."
* **9 types of timeframes, 11 periods:** Timeframes range from 1-minute to daily, and periods can be selected from 1 day to 10 years depending on the timeframe. Custom periods with specified start and end dates are also supported.
* **Presets:** With 11 presets, including EMA golden cross and Bollinger Band counter-trend strategies, even beginners can easily get started.
* **Parameter optimization:** You can perform brute-force searches, such as "trying EMA periods from 5 to 100." Up to 3,000 combinations per run. The best-performing conditions are displayed in order of performance.
* **Explosive search:** Up to 3,000 combinations are possible per run. * **Display Advice in History**
Each trade's performance is analyzed, and based on situations such as "too few trades" or "no stop-loss set," suggestions for the next conditions to try are provided.
* **Save Up to 100 Execution History**
Results of trials with different conditions can be displayed and compared side-by-side. Favorites, tags, and notes can be added.
* **Details for Each Trade**
Purchase date/time, sale date/time, profit/loss, and trigger conditions can be viewed for each trade. Monthly and weekly summaries are also available.
* **Send Results via Email**
Trade data (CSV), charts for the entire period (HTML), and calculation codes for indicators used (Python) can be attached.
* **Share**
Backtest results, including total profit, score, and trading conditions, can be shared on social media platforms such as X.
* **Glossary**
Approximately 70 terms are explained, including basic terminology, purchase indicators, selling methods, and evaluation indicators, making it accessible even for beginners.
* **Smartphone and Tablet Compatible**
The display adjusts to the screen width, ensuring text remains legible on tablets. The screen is fixed in portrait orientation. ■ Pricing
Completely free. No feature limitations or in-app purchases.
■ Before Use
・The displayed results are calculated based on historical data and do not guarantee future results.
・Conditions optimized for a specific period may not work in a different period (overfitting).
・Trading fees and slippage are not included in the calculation. You can select the purchase amount and quantity per transaction, but compound interest calculation is not supported.
・Investment decisions are your own responsibility.
■ About Price Data
Data is obtained from a public API. The obtained data is used only on your device and is not sent to the server.
■ Contact Us
https://hagihara-apps.github.io/trade-navi/
You can test trading conditions using historical Bitcoin data and optimize parameters. We'll identify areas for improvement based on performance and suggest conditions to try next. No actual trades are executed.