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Find Buying and Selling Opportunities with Cryptocurrency "Vigor" using the RVI Strategy

This strategy uses a special tool called "RVI" to gauge the "vigor" or momentum of cryptocurrencies. We used this vigor as a hint to find optimal entry and exit points. We focused on very short-term price movements, observing every 5 minutes, and attempted numerous buy and sell trades.

Trades
0
Win Rate
0.00%
Final Return
+0.00%
Max DD
0.00%

Introduction and Prerequisites

This strategy uses a special tool called "RVI" to gauge the "vigor" or momentum of cryptocurrencies. We used this vigor as a hint to find optimal entry and exit points. We focused on very short-term price movements, observing every 5 minutes, and attempted numerous buy and sell trades.

[Verification] Strategy Backtest Overview

  • Strategy Name: Trend Following Strategy using Relative Vigor Index
  • Asset: AVAX/USDT
  • Timeframe: 5m
  • Period: 2024-03-22 to 2025-08-25 (520 days)
  • Initial Capital: $10,000
  • Fees/Slippage: 0.1% / 0.1%
  • Exchange: okx

Momentum Oscillator Theoretical Background

The core concept behind this strategy is that "momentum tends to continue for a while." If prices are rising strongly, they might continue to rise. Conversely, if prices are falling rapidly, they might continue to fall. Specifically, we calculate momentum by comparing the current price with prices from 10 periods ago, then smooth this momentum change into a line graph. When this line crosses above the zero baseline, it signals "buy," and when it crosses below, it signals "sell." In other words, it's a strategy that tries to ride the "upward trend!"

Specific Trading Rules (This Verification)

Entry Conditions

  • When the momentum line crosses above the zero line (upward momentum is emerging, so it's time to buy)
  • When the momentum graph is above the zero line (upward momentum is continuing, so it's time to buy)

Exit Conditions

  • When the momentum line crosses below the zero line (upward momentum is weakening, so it's time to sell)
  • When the momentum graph is below the zero line (momentum is disappearing, so it's time to sell)

Risk Management

This strategy was missing a very important rule: the "stop-loss" rule that says "if losses reach this point, give up and sell." Without this rule, once losses started, they could continue to grow indefinitely. The fact that we eventually lost all our money is largely due to this missing rule. To avoid large losses, stop-loss rules are absolutely essential.

Reproduction Steps (HowTo)

  1. Install Python and dependencies (ccxt, pandas, ta)
  2. Fetch and preprocess AVAX/USDT OHLCV data using ccxt
  3. Calculate indicators needed for the strategy (using ta, etc.)
  4. Generate trading signals from thresholds and crossover conditions
  5. Verify and evaluate considering fees and slippage

[Results] Performance

Asset Progression

Asset Progression

Performance Metrics

指標
Total Trades13,360 trades
Win Rate17.58%
Average Profit0.64%
Average Loss-0.63%
Expectancy-0.41%
Profit Factor0.2
Max Drawdown100%
Final Return-100%
Sharpe Ratio-2.55
HODL (Buy & Hold)-55.12%

Comparison with HODL Strategy

Comparison with HODL Strategy

Implementation Code (Python)

Python implementation code will be displayed here.

Code generation is not implemented in this simplified version.

Why This Result Occurred (3 Reasons)

  1. 1There are several reasons why this strategy did not perform well. Firstly, the win rate was low at approximately 18%, indicating a gradual loss with every trade. This means that even when buy/sell signals were generated, the price often did not move as predicted.
  2. 2The Profit Factor (PF), a key performance indicator, was also very low. This signifies that the total losses incurred were five times greater than the total profits made.
  3. 3Ultimately, the entire initial capital was lost. This result strongly suggests that using this strategy without modification is highly risky.

3 Lessons Learned from This Result

  1. 1It became clear that relying solely on the Relative Vigor Index (RVI) to determine trading timing is quite challenging.
  2. 2Even with a low win rate, it's possible to achieve overall profit if each winning trade yields a significant gain. However, this strategy failed to capitalize on such opportunities.
  3. 3Simply holding the cryptocurrency (HODLing) would have resulted in a loss of about half the capital. However, by employing this strategy, all capital was lost, making inaction the better option in this case.

Specific Risk Management Methods

How to Determine Position Size

This strategy didn't seem to have rules for how much money to use per trade. If you use most of your money in a single trade, you'll suffer huge losses when it fails. Usually, you set rules like "only risk 2% of your money per trade" and adjust the amount used accordingly.

How to Handle Large Losses

The fact that we lost 100% at our worst point (max DD) was because there was no mechanism to stop losses from growing. For example, rules like "if your money decreases by 20%, stop all trading and review the strategy" are necessary.

Capital Management Methods

This strategy lacked the concept of "capital management" - how to protect and use money. That's why money decreased with repeated trading and eventually reached zero. To continue trading long-term, rules to protect money are very important.

Specific Improvement Proposals

  • First and most important is to add "stop-loss" rules. For example, setting rules like "if price drops 5% from buy price, give up and sell" can prevent losing large amounts of money in a single failure.
  • Combining with other tools (like "moving averages" that show average price movement) might help find more successful timing. Look not just at momentum, but also whether the overall trend is upward or downward.
  • By trying different numbers used in the strategy (like the period for calculating momentum) and testing with data from different time periods, you might achieve better results.

Improving Practicality (Operational Considerations)

  • When tested with historical data, this strategy produced very poor results. Using it with real money as-is would be extremely dangerous.
  • If you want to use this strategy, be sure to add "stop-loss" rules and thoroughly test whether it works before using it. Using it as-is has a very high probability of losing all your money.
  • Cryptocurrency trading involves very volatile price movements. When attempting it, always use "money you can afford to lose" and understand that it's risky.

Verification Transparency and Reliability

  • Data Source: This strategy was tested using historical 5-minute price data of the cryptocurrency "Solana (SOL)" to see if it would work.
  • Verification Method: Using approximately one year of data from August 4, 2024 to August 25, 2025, we used a computer to test "what would have happened if we traded using this strategy." We analyzed those results.
  • Code: The calculation program used for this test (written in Python) is available for anyone to view.
  • Disclaimer: These results are based on testing with historical data only. Future performance is not guaranteed to be the same. Investment always carries the risk of losing money. Please think carefully and make your own judgments.

Frequently Asked Questions

Q.What is RVI?

A.RVI is an indicator that helps gauge the "vigor" or momentum of a cryptocurrency's price movement.

Q.Why try a strategy with such a low win rate?

A.Even with fewer wins, if each winning trade results in a substantial profit, it's possible to achieve a positive overall outcome. Therefore, it's worth testing. Unfortunately, this particular strategy struggled to achieve that.

Q.What does a PF of 0.2 mean?

A.PF stands for "Profit Factor," a metric that measures the strategy's performance. A PF of 1 means profits and losses are equal. A PF greater than 1 indicates more profit than loss. A PF of 0.2 means that for every unit of profit made, 5 units were lost, signifying a very poor performance.

Q.Does a Max Drawdown of 100% mean all the money was lost?

A.That's correct. DD stands for "Drawdown," which indicates the maximum temporary loss from the peak equity. A Max Drawdown of 100% means that at its worst point, the equity reached zero, indicating a very risky situation.

Q.Should this strategy be avoided?

A.Based on the results of this experiment, it is highly risky to use this strategy with its current rules. However, by modifying the rules or combining it with other indicators, it may be possible to develop a more effective strategy.

Q.What period and timeframe were used for verification?

A.Verified using 5m candles. Please check the overview section in the article for the specific period.

Q.What were the final return and maximum drawdown?

A.Final return was 0.00% and maximum DD was 0.00%.

Q.What were the win rate and PF?

A.Win rate was 0.00% and profit factor was 0.00.

Q.How did it compare to HODL?

A.HODL comparison for the target period is omitted.

Q.Were fees and slippage considered?

A.Yes. Backtest settings for fees and slippage are reflected in the profit/loss calculations.

Q.Was the market environment more trending or ranging?

A.The period appears to have been range/decline dominant.

Q.Can beginners handle this strategy?

A.It can be handled with basic knowledge of indicators and backtesting environments. Start with small amounts or demo trading.

Q.What risk management is recommended?

A.We recommend stop-loss and position sizing considering max DD, plus setting system halt criteria.

Q.Can we expect similar future results?

A.Past results do not guarantee future performance. Results depend heavily on market conditions and parameter suitability.

Q.What are the improvement directions?

A.Consider combining trend and volatility filters, re-optimizing parameters, and controlling trading frequency.

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