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Strategy for Finding Momentum with Trading Volume! Tried it with Ethereum, but...?

This strategy attempts to identify buying and selling opportunities by looking at the 5-minute price chart of the cryptocurrency Ethereum, using price momentum and the volume of people buying and selling (referred to as \'trading volume\') as indicators. However, unfortunately, it didn\'t work out when put into practice. I\'ll explain clearly why it failed and what might be better going forward.

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

Introduction and Prerequisites

This strategy attempts to identify buying and selling opportunities by looking at the 5-minute price chart of the cryptocurrency Ethereum, using price momentum and the volume of people buying and selling (referred to as \'trading volume\') as indicators. However, unfortunately, it didn\'t work out when put into practice. I\'ll explain clearly why it failed and what might be better going forward.

[Verification] Strategy Backtest Overview

  • Strategy Name: Trend Following Strategy using ROC Volume Filter
  • Trading Pair: ETH/USDT
  • Timeframe: 5m
  • Period: 2024-08-10 to 2025-08-25 (379 days)
  • Initial Capital: $10,000
  • Fees/Slippage: 0.1% / 0.1%
  • Exchange: Binance

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 ETH/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 Trades1831 trades
Win Rate20.48%
Average Profit1.24%
Average Loss-0.77%
Expectancy-0.36%
Profit Factor0.31
Max Drawdown99.89%
Final Return-99.88%
Sharpe Ratio-0.64
HODL (Buy & Hold)79.58%

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. 1When I tested this strategy with historical data, unfortunately, it didn't make any profit at all. The probability of winning was extremely low, and with every trade, the money gradually decreased, eventually nearly disappearing.
  2. 2Specifically, I often bought or sold based on the assumption that high trading volume indicated continued momentum, only to see the price move in the opposite direction immediately after. It seemed that times of high public excitement were often the peak, after which the price reversed.
  3. 3The cryptocurrency market can experience sudden, large price movements due to various reasons like breaking news or global events. Therefore, a simple rule based solely on 'price momentum and trading volume' might not be sufficient to keep up with the current complex market dynamics.

3 Lessons Learned from This Result

  1. 1I learned that not every sophisticated strategy is guaranteed to work. Especially with volatile assets like cryptocurrencies, simple rules may not always be effective.
  2. 2I realized that just because many people are trading doesn't automatically mean the momentum is genuine. When everyone is excited, it might be a time to be cautious and look for other indicators.
  3. 3To be profitable, it's not just about the win rate; the balance between how much you profit on a winning trade and how much you limit losses on a losing trade is crucial. This strategy lacked that balance.

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.How much capital is needed to start with this strategy?

A.Theoretically, you can start with any amount, but it's best to begin with a small amount that you can afford to lose. Trying it out with a paper trading account first is highly recommended.

Q.Can this be used for cryptocurrencies other than Ethereum?

A.Yes, this approach might be applicable to Bitcoin and other cryptocurrencies. However, each cryptocurrency has its own unique characteristics, so it may not perform the same way.

Q.Why use a strategy with a low win rate?

A.Good question! Some strategies can be profitable overall even with a low win rate if the profit on each winning trade is significantly large. However, in this strategy, the profit on wins was small, and the losses on trades were larger, resulting in an overall loss.

Q.What does 'Max Drawdown of 99.89%' mean?

A.This refers to the 'Maximum Drawdown,' which is the percentage decrease from the peak equity to the subsequent trough. In this case, it means that if you had continued with this strategy, your capital would have nearly gone to zero at one point, indicating a very high-risk situation.

Q.What is HODL?

A.HODL is an internet slang term meaning to 'hold on for dear life' without selling or trading cryptocurrencies. This metric compares the performance of the strategy to simply holding Ethereum during the test period. In this case, the results were better when just holding the asset without trading.

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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