Whale Strategy Full Report (20200101 - 20250701)


πŸ“Š Strategy Overview

This report is produced by https://www.itrade.icu Quantitative Trading Lab.

We used real market data combined with a quant backtesting engine to conduct a continuous 5 years and 7 months backtest and live trading test on the Whale Strategy, achieving impressive results.


Lookahead Bias Test

The strategy underwent Lookahead Bias Analysis, and the results show:

  • has_bias: No β†’ No lookahead bias

  • biased_entry_signals: 0 β†’ No biased entry signals

  • biased_exit_signals: 0 β†’ No biased exit signals

  • biased_indicators: None β†’ No biased indicators

This means the strategy did not use future data during backtesting, so results are not artificially inflated.

                                                        Lookahead Analysis
┏━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓
┃           filename ┃        strategy ┃ has_bias ┃ total_signals ┃ biased_entry_signals ┃ biased_exit_signals ┃ biased_indicators ┃
┑━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩
β”‚ WhaleStrategyV1.py β”‚ WhaleStrategyV1 β”‚       No β”‚            20 β”‚                    0 β”‚                   0 β”‚                   β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Backtest Report

The strategy was backtested using data from 2020-01-01 to 2025-07-01. View full reports here: Quarterly Report | Semi-Annual Report | Annual Report


Backtest Charts


Quarterly Report

Metric
Value

Total Trades

2,038

Total Return (%)

1,422.36%

Total Profit (USDT)

142,236.83

Avg. Quarterly Return (%)

64.65%

Avg. Quarterly Profit (USDT)

6,465.31

Avg. Win Rate (%)

66.77%

Max Drawdown (%)

47.70%


Semi-Annual Report

Metric
Value

Total Trades

2,039

Total Return (%)

1,544.03%

Total Profit (USDT)

154,403.11

Avg. Semi-Annual Return (%)

140.37%

Avg. Semi-Annual Profit (USDT)

14,036.65

Avg. Win Rate (%)

66.80%

Max Drawdown (%)

47.70%


Annual Report

Metric
Value

Total Trades

2,075

Total Return (%)

2,843.71%

Total Profit (USDT)

284,372.16

Avg. Annual Return (%)

473.95%

Avg. Annual Profit (USDT)

47,395.36

Avg. Win Rate (%)

66.73%

Max Drawdown (%)

47.70%


πŸ†š Whale Strategy Source Code

This article was produced by the Quantitative Trading Lab at https://www.itrade.icu. Visit for more benefits.

πŸ“’ Final Summary

This strategy has been tested with real market data over an extended period, delivering high frequency, stability, controlled risk, and strong profitability. It’s ideal for small to medium capital quantitative traders, especially for short-term BTC/ETH trades. It also serves as a great reference case for crypto quant enthusiasts and strategy developers.


Keywords: Whale Strategy, Crypto Quant Strategy, BTC Quant, ETH Quant, Short-term Trading, Backtest, Automated Trading, Low Drawdown Strategy, High-Frequency Crypto Trading

Last updated