BTC - DCA vs HODL Calculator Matrix

BTC - DCA vs. HODL Calculator Matrix | RM

Overview
The BTC - DCA vs. HODL Calculator Matrix is a high-performance telemetry laboratory designed to settle the ultimate debate in Bitcoin accumulation: Is it more efficient to deploy all capital at once (Lump Sum & HODL) or utilize a recurring purchase strategy (DCA)? More importantly, if DCA is the choice, which exact frequency and weekday provides the mathematical edge?

The Calculator Matrix was engineered to solve a critical limitation in the current script ecosystem (at least I couldnt find such an indicator): the inability to compare multiple DCA frequencies and specific calendar days simultaneously within a single dashboard. While developing this tool, I found that existing calculators typically only permit testing one strategy at a time (e.g., a generic "Weekly" buy). This script fills that gap by utilizing a high-performance array-based "Telemetry Engine" to rank dozens of variables—including every individual weekday and specific monthly dates—against a HODL benchmark in real-time. This unique simultaneous comparison allows investors to mathematically identify "Weekday Alpha" across any user-defined timeframe.

Core Philosophy
The script utilizes a Normalized Capital Model. To ensure a true "apples-to-apples" comparison, your total capital (e.g., $10,000) is distributed with mathematical precision across the exact number of entries for each specific strategy. This eliminates the ROI skewing commonly found in basic scripts, ensuring that every strategy is judged on the same total dollar expenditure over the same "Race Track."

Key Features & Analytics
• The Podium System: An automated ranking algorithm that awards 🥇 Gold, 🥈 Silver, and 🥉 Bronze medals to the top three performing strategies. Spoiler: Regular Winner: 1-time HODL (Lump Sum)
• Simultaneous Strategy Testing: Compare Daily, 7 different Weekly days (Mon-Sun), and Monthly dates (1st–28th) all at once.
• Risk Telemetry: Integrated Max Drawdown (MDD) sensors for every strategy, revealing the "Emotional Cost" of your accumulation path.
• Race Track Visuals: Blue dashed "Green Flag" and "Checkered Flag" lines visually define the boundaries of your backtest.
• Dashboard Customization: Use the "Odd/Even" filter to keep the matrix sleek and readable on (nearly) any screen resolution.

The Strategies Tested
• 1-TIME HODL: The benchmark (Lump sum entry on Day 1 - meaning all the capital is deployed at the start date).
• DAILY DCA: High-frequency, day-by-day accumulation (the capital is split amongst the different entries).
• WEEKLY (SUN-SAT): Evaluates which specific day of the week historically captures the best entries (e.g., "Weekend Dips").(The capital is split amongst the different entries).
• MONTHLY (1-28 + END): Tests monthly date performance to optimize for beginning-of-month or end-of-month cycles. (The capital is split amongst the different entries).

Monte Carlo Simulation & Python Research
While this tool allows you to manually check any specific timeframe, manual testing is limited by "Start Date Bias." To find the Universal Winner, I have conducted a Monte Carlo Simulation using 100 random entry dates over the last 5 years via Python/Colab. This research reveals the statistical probability of a day (like Saturday) winning the Gold medal across all market conditions.
Access the Python Heatmap Research in my substack article (link for substack in Bio).

How to Use
1. Set the Race Track: Input Start and End dates in the settings.
2. Fuel the Engine: Set your Total Capital ($).
3. Analyze the Matrix: Compare ROI vs. MAX DD. The goal is not just the highest return, but the best Risk-Adjusted return.

Technical Implementation
This script utilizes an array-based telemetry engine to handle the simultaneous calculation of 30+ independent investment strategies. To ensure computational efficiency and bypass the limitations of standard security-based backtesting, I implemented a custom-built accumulator logic using array.new_float() and array.set(). The core calculation loop (if in_race and is_new_day) processes capital deployment on a per-bar basis, utilizing ta.change(time("D")) to ensure entry synchronization with the Daily UTC close. By decoupling the unit accumulation (u_weekly, u_monthly) from the final valuation logic (f_get_stats), the script maintains a Normalized Capital Model. This ensures that even with complex comparative logic across varying frequencies, the script provides a mathematically rigorous, reproducible result that matches real-world execution at the Daily UTC Midnight close.

Note: All calculations are made on the "close" bar, which means UTC 00:00. By creating a strategy or using the research, make sure to be aware of your time zone

Disclaimer: Past performance is not indicative of future results. This tool is for educational and research purposes only. Rob Maths is not liable for any financial losses.

Tags:
robmaths, Rob Maths, DCA, HODL, Bitcoin, BTC, Backtest, RiskManagement, Investment, Strategy, Statistics