The Deposit Optimizer: How We Decide Which Shares to Buy

The Problem

You've just deposited your paycheck into your brokerage account. You hold 20 different high-yield ETFs. Which ones do you buy more of?

Most investors go with gut feel: "JEPQ looks cheap" or "CONY has the highest yield." But gut feel doesn't account for the dozen competing factors that determine the optimal allocation. That's what the deposit optimizer solves.

The 15-Factor Scoring Algorithm

Every ticker in your portfolio receives a composite score based on these factors, each with a configurable weight:

Price-Based Factors

1. Cost Basis Opportunity (costBase): How far is the current price from your average cost basis? Buying below your cost basis lowers your average and amplifies future gains. The further below cost, the higher the score.

2. 52-Week Range Position: Where does the current price sit within the 52-week high/low range? A ticker near its 52-week low scores higher — you're buying at a relative discount.

3. NAV Discount (for CEFs): Closed-end funds trade at premiums or discounts to their net asset value. A fund trading at a 10% discount to NAV is objectively cheaper than one at a 5% premium.

Income Factors

4. Yield Boost (yieldBoost): Higher-yielding tickers score higher, but with diminishing returns. A jump from 5% to 10% yield is worth more than a jump from 25% to 30%. The scoring uses configurable thresholds to prevent chasing extreme yields blindly.

5. Ex-Dividend Proximity (exBoost): Is the ticker's ex-dividend date coming up? Buying before the ex-date means you capture the next distribution. The closer the ex-date, the higher the boost — but only if you're buying at least a few days before to ensure settlement.

6. Dividend Growth Rate: Has the fund been increasing its distribution over the past 6-12 months? Growing distributions are a sign of sustainability and compound more aggressively.

Risk Factors

7. Maintenance Requirement (maintBoost): Lower maintenance requirements mean more margin efficiency. A ticker requiring only 25% maintenance gives you more borrowing capacity than one requiring 75%.

8. Volatility Penalty: Higher historical volatility means larger potential drawdowns. In a margin strategy, volatility is the enemy — it's what triggers margin calls. More volatile tickers receive a penalty.

9. Sharpe-Adjusted Yield (sharpeYield): Raw yield doesn't account for risk. The Sharpe-adjusted yield divides yield by volatility, rewarding tickers that deliver high income per unit of risk taken.

Portfolio Construction Factors

10. Diversification Score: If one ticker already represents 15% of your portfolio, buying more concentrates risk. This factor penalizes overweight positions and rewards adding to underweight ones, pulling toward target allocations.

11. Sector/Strategy Balance: Owning 10 covered-call ETFs on the Nasdaq creates hidden correlation. This factor encourages diversification across underlying strategies and market exposures.

12. Manual Boost: Sometimes you have conviction about a ticker that the algorithm can't capture — maybe you've done deep research on a fund's strategy change. A per-ticker manual boost lets you express that view.

Momentum Factors

13. Price Momentum: Is the ticker trending up or down over the past 1-3 months? Mild positive momentum is rewarded (trend-following), while extreme negative momentum gets a penalty (catching falling knives).

14. Growth-Adjusted Yield: This combines current yield with price appreciation to get a total-return estimate. A 10% yielder that's also appreciating 8% is more attractive than a 12% yielder declining 5%.

Operational Factors

15. Mode Boost (CORE vs SCORE): The optimizer runs in two modes. CORE mode prioritizes a curated list of blue-chip high-yield tickers — the "sleep at night" holdings. SCORE mode uses the full algorithm without favorites. In CORE mode, core tickers get a substantial boost.

How Scoring Works

Each factor produces a normalized score (typically 0 to 10). These scores are multiplied by their respective weights and summed to produce a raw composite score. The weights are fully configurable — you can emphasize yield over momentum, or prioritize diversification over cost basis.

The algorithm then runs in phases:

Phase 1 - Score: Calculate composite scores for all tickers.

Phase 2 - Rank: Sort tickers by score, highest first.

Phase 3 - Allocate: Starting from the top-ranked ticker, allocate shares in round lots. The deposit amount is distributed across the top-scoring tickers, with higher-scoring tickers receiving proportionally more capital.

Phase 4 - Decide: Each ticker receives a decision: BUY (allocated shares), EVAL (scored well but didn't make the cut due to limited capital), or SKIP (scored too low or eliminated by a hard filter).

A Sample Optimization

Let's say you're depositing $2,000 and hold these five tickers:

JEPQ scored highest because it was below cost basis, had an ex-date in 4 days, and had low volatility. SVOL's massive yield and low price gave it a strong yield-adjusted score. JEPI rounded out the allocation with its stability.

CONY scored in the middle — decent yield but high volatility penalty and already overweight in the portfolio. MSTY was skipped entirely: extreme yield but extreme volatility, high maintenance requirement, and negative momentum.

The optimizer allocated $1,956 of the $2,000 deposit (the remaining $44 wasn't enough for a full share of any top-ranked ticker).

Why This Matters

Without the optimizer, you might have bought MSTY because "95% yield." The algorithm sees what gut feel misses: the volatility, the concentration risk, the momentum, and the maintenance cost of that position.

Over hundreds of deposits across years, the optimizer's disciplined scoring compounds into a meaningful edge. It removes emotion, enforces diversification, and captures income opportunities that a manual review would miss.

Every paycheck becomes a precision-targeted deployment of capital. That's the deposit optimizer.