dca-strategy

name	dca-strategy
description	Implement Dollar Cost Averaging for systematic long-term accumulation. Use when building positions over time, reducing timing risk, or accumulating during uncertainty.
license	Apache-2.0
metadata	{"author":"ske-labs","version":"4.0"}

Dollar Cost Averaging (DCA)

Invest new cash on a fixed schedule. Distinguish paycheck-style periodic investing from deliberately delaying a lump sum that is already available.

DCA Mechanics

Each Purchase = Fixed Amount / Current Price
Average Cost  = Total Spent / Total Units Acquired

Example ($100/week):

• Week 1: $100 / $50 = 2.0 units
• Week 2: $100 / $40 = 2.5 units
• Week 3: $100 / $60 = 1.67 units
• Total: 6.17 units for $300 (avg cost: $48.62)

DCA Variants

Variant	Description
Fixed Interval	Same amount every week/month -- simplest
Value Averaging	Adjust amount to hit a target portfolio value
Enhanced DCA	Base amount + bonus when price drops below MA
Lump Sum + DCA	Deploy 50% immediately, DCA the remaining 50%

Asset Eligibility

Candidate	Reject or escalate
Diversified, liquid exposure	Unclear rights or custody
Assets with a documented thesis	Failing liquidity or security
Instruments compatible with the horizon	Position already above its risk cap

Workflow

1. Capture the plan: goal, horizon, target allocation, contribution amount, frequency, funding source, custody, fees, and maximum allocation. Do not change the schedule from short-term price forecasts.

2. Check allocation drift and current price context:

get_candles(symbol="BTC/USD", exchange="binance", interval="1d", count=1)
get_indicators(indicator_code="sma_50", symbol="BTC/USD", exchange="binance", interval="1w")

3. Apply any enhanced-DCA rule only if it was predeclared and validated; a 200-day moving-average rule is optional, not inherent to DCA:

get_indicators(indicator_code="sma_200", symbol="BTC/USD", exchange="binance", interval="1d")

4. Re-underwrite the asset, not the next candle:

get_financial_news(topic="BTC macro outlook accumulation")

5. Report scheduled contribution, post-trade allocation, weighted average cost, fees, custody or concentration flags, and whether a written pause condition was triggered.

When to Stop DCA

• Target position size reached
• Fundamentals have materially deteriorated
• Better risk/reward opportunity identified elsewhere

Evidence and Validation

• Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
• Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
• Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
• Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
• Research basis: Vanguard research found immediate lump-sum investment historically beat temporary cost averaging about two-thirds of the time; DCA is mainly a cash-flow and behavior plan.

Key Rules

• Do not skip or enlarge a scheduled purchase from an improvised price forecast
• Do not confuse DCA with averaging down an invalidated speculative thesis
• Review quarterly, not daily; over-monitoring defeats the purpose
• For cash already available, explicitly compare immediate investment with staged deployment; DCA may reduce short-term regret at the cost of expected time in market

Related Skills

• altcoin-rotation -- DCA into BTC/ETH during accumulation, then rotate when cycle shifts
• on-chain-analysis -- MVRV and realized cap identify macro accumulation zones for enhanced DCA