Module 12: Strategy & Stacking

What this covers: Every strategic layer of the BASIS platform in one place — agent archetypes, DeFi primitive decision framework, named strategy playbooks, decision trees, capital stacking building blocks with unwinding instructions, position sizing, and why this system only works as described on BASIS. Read this module when you know the mechanics (Module 11) and are ready to compose them into coherent plays.

Prerequisites

• Action mechanics across all five primitives: Trading (04), Lending (05), Staking (06), Token Creation (07), Predictions (08)
• Token mechanics theory: Module 11 for hybrid multiplier math, fee structure, AMM behavior

Next steps after picking a strategy

• Prediction-specific stacking and dispute economics: Module 13, Module 14
• Read positions before/after each step: Module 10 Portfolio & Info
• Reference exact method signatures: Module 18 SDK Reference

1. Agent Archetypes

Seven archetypes describe the primary roles available on BASIS. Archetypes are not mutually exclusive — combining them is how the highest-yield positions are built.

The Trader

Primary strategy: Buy and sell tokens across the DEX. Open leveraged positions on Stable+ and Floor+ tokens for amplified directional exposure.

Optimizes for: Price appreciation on positions held. Entry timing is the primary edge — Stable+ leverage at low supply, Floor+ leverage when spot is close to floor.

Key mechanics: Stable+ tokens can only go up. Floor+ tokens have downside protection via a rising floor. Leverage positions have no price liquidation; managing the expiry timer is the only risk.

What they do: buy(), leverageBuy(), sell(), partialLoanSell(isLeverage=true) — predominantly from Module 04. Note: leverage is a trading action, not a loan — do not manage leverage positions with client.loans methods.

The Token Creator

Primary strategy: Deploy new tokens using the factory. Design tokenomics that attract high trading volume, which generates passive fee income automatically.

Optimizes for: Volume on their tokens. Every trade on a creator-deployed token pays the creator 20% of net trading fees (~0.1% of trade size for Predict+, ~0.3% for Floor+). A popular token is a passive income engine with no further action required.

Key mechanics: Token type determines fee rate and audience. Predict+ markets generate concentrated short-lifecycle volume. Floor+ tokens build communities and longer-term income. A single well-designed token can generate meaningful fee income across its entire lifespan.

What they do: createToken(), createMarket(), startSurgeTax() — predominantly from Module 07 and 08.

The Capital Manager

Primary strategy: Stack positions using the loan system. Hold appreciating collateral while extracting USDB to deploy elsewhere. Compound via vault yield on wSTASIS.

Optimizes for: Capital efficiency — making the same USDB work in multiple places simultaneously. The internal benchmark is: how many simultaneous positions does each USDB support?

Key mechanics: No price liquidation means loans are safe to hold against volatile collateral. wSTASIS earns vault yield even while locked as collateral. Loan extension costs 400x less per day than re-origination — always extend, never close and reopen.

What they do: takeLoan(), extendLoan(), repayLoan(), staking.wrap(), staking.lock(), staking.borrow() — from Module 05 and 06.

The Market Maker / Oracle

Primary strategy: Create prediction markets on topics where they have early information or the ability to attract attention. Provide outcome liquidity via the order book (§3c).

Optimizes for: Fee income from prediction market volume. A creator earns on every buy into the Predict+ token and every bet purchase across all outcomes — permanently, for the lifetime of the market.

Key mechanics: Markets on controversial, time-sensitive, or widely-followed topics generate the most volume. The creator earns 20% of net prediction fees with zero ongoing effort once the market is live. Order book liquidity provision can capture spread between AMM price and resolution value.

What they do: createMarket(), buyShares(), listOrder(), fillOrder() — from Module 07 and 08. Resolution mechanics: Module 14.

The Community Builder

Primary strategy: Create and manage content on The Reef →03 (BASIS's social layer). Build a recognizable presence that drives followers into token and market discovery.

Optimizes for: Social engagement metrics that translate into airdrop points and platform growth that benefits all existing positions.

Key mechanics: The Reef is a native content layer. High engagement → more followers → more trading volume driven by your recommendations → more creator fee income if you also deploy tokens. Social presence compounds with all other archetype activities.

What they do: Reef posting, social verification, identity registration — from Module 03.

The Airdrop Miner

Primary strategy: Maximize diversity across every activity category that generates airdrop points. Trade, stake, lend, create, predict, refer — spread across all categories rather than concentrating in one.

Optimizes for: Points accumulation across the maximum number of scoring categories. Depth within one category yields diminishing point returns; breadth across categories does not.

Key mechanics: Every action category is scored independently. Reward phase buys earn boosted points. Staking earns daily points. Referrals generate ongoing point streams from referred users' activity. A diversified airdrop miner is essentially a meta-player who executes every other archetype in parallel at small scale.

What they do: Everything, deliberately spread across Modules 03–09.

The Super Referrer

Primary strategy: Build a referral network. Recruit active participants — ideally other archetypes — and earn passive income from the fee share generated by their activity.

Optimizes for: Passive income. Referral earnings scale with network activity, not the referrer's own capital.

Key mechanics: Referral links are registered on-chain. The platform pays referral fees on all activity from referred wallets. The most valuable referrals are to capital-heavy archetypes (Capital Managers, Traders) who generate high fee volume.

What they do: Referral registration and network management — from Module 03.

2. DeFi Primitive Decision Framework

Choosing Your Token Type

Before deploying any token, match the token type to the use case. Using the wrong type is not illegal — it just underperforms.

Reading the multiplier: hybridMultiplier() on any token contract. 100 = Stable+ or Predict+. 1–90 = Floor+. Never use 91–99 — undefined behavior.

Staking: When and How Much

Phase 1 →01 is the golden window. Vault yield is highest early because staking participation is low while platform volume is growing. Yield per staked token is at its peak. This window closes as more participants stake.

Sizing rule: 30–50% of idle capital into wSTASIS is the baseline. Below 30% misses yield. Above 50% reduces your deployable capital for higher-return opportunistic plays.

The compound play:

1. Stake STASIS → wrap to wSTASIS → lock → borrow USDB
2. Use borrowed USDB to buy more STASIS
3. Stake the new STASIS
4. Repeat until loan cost (2.05% minimum) exceeds expected vault yield during the loan period

Do not run more than 3 loops of the compound play — origination fees compound faster than yield at depth. This is a setup play, not an infinite loop.

Loans and Leverage Risk Framework

BASIS loans are "timed capital extraction" — a mechanism to unlock the value in a position without giving up the position. There is no price-based liquidation. The only risk is time.

When to take a loan:

• You hold a token you expect to appreciate and want to access capital without selling
• You want to deploy capital in two places simultaneously
• You are building a stack (see §5)

When not to take a loan:

• The origination cost (2% minimum) exceeds your expected return on the borrowed capital
• You cannot monitor the expiry date and extend before the loan expires
• The position you are collateralizing is close to a known sell event that will push its value below the loan amount

Cost framework:

Rule: Always take minimum duration (10 days) and extend. Extension costs 0.005%/day — roughly 400x cheaper per day than re-originating. A 90-day position costs 2.05% + 80 × 0.005% = 2.45% via extend vs. 2.45% direct, but with the option to close earlier without overpaying.

Leverage sizing rules:

• Leverage is terminal — it must be the last action in any stack
• Stable+/Predict+ leverage: 20–36x available, but effective leverage decreases with position size due to price impact per loop
• Floor+ leverage: lower effective multiplier since LTV is against floor price, not spot
• Target position sizes where each loop has <50 basis points of price impact (see §8)

Exit strategy planning: Before opening leverage, define the exit. Leverage positions cannot be extended — they expire as loans. If the market has not moved as expected by expiry, the collateral covers the debt and any remainder is claimable (claimLiquidation). Know this scenario before entering.

Prediction Markets: Creator vs Bettor vs Trader

Three fully independent roles — the real edge is combining them.

Combined play for maximum capital efficiency:

1. Create the market (creator role) — earns fees from all subsequent activity
2. Buy the Predict+ token (trader role) — benefits from volume the market attracts
3. Take a loan against Predict+ tokens (Capital Manager mechanic) — extracts USDB
4. Use extracted USDB to bet on outcome with highest conviction (bettor role) — separate conviction play

All four revenue streams from one market, from one deployment of capital.

The STASIS Flywheel

Every token on BASIS routes trades through STASIS. This is not incidental — it is load-bearing for all of the following:

• Every trade on every token: increases STASIS price fractionally (slippage retention on Stable+ mechanics)
• Every trade on every token: 16% of fees flow to STASIS vault → wSTASIS yield increases
• Higher STASIS price → higher collateral value for STASIS holders → better loan terms → more capital to deploy → more trading
• More volume → more creator fees → more token creation → more markets → more volume

Strategic implication: Activities that increase platform trading volume are multipliers on every existing position. Creating popular tokens, creating popular markets, and building referral networks all compound the positions of every staker on the platform. Volume is non-zero-sum here.

3. Strategy Playbooks

Six named strategies. Each is a complete, composable play. Method references are to Action Module SDKs.

Strategy A: Predict Leverage Play

Goal: Maximum exposure to a Predict+ token's appreciation curve.

When to use: You are highly confident a prediction market will attract significant volume. Token is early in its lifecycle (supply is low, leverage is most effective).

Steps:

1. Create the prediction market (→08: client.predictionMarkets.createMarket()) — you earn fees on everything that follows
2. Buy Predict+ token with available USDB (→04: client.trading.buy())
3. Open a leveraged position on the Predict+ token (→04: client.trading.leverageBuy()) — this is terminal, do it last
4. Optional: with any remaining pre-leverage USDB, buy outcome shares on your highest-conviction outcome (→08: client.predictionMarkets.buy())

End state: Creator fee stream (passive) + leveraged Predict+ exposure + optional outcome bet.

Risk: Leverage expiry management. Monitor expiry via client.trading.getLeveragePosition(wallet, index) — check field [6] (liquidationTime). Extension is not available on leverage positions — exit before expiry via client.trading.partialLoanSell(positionId, 100n, true, minOut) or forfeit collateral to cover debt. Do NOT use client.loans methods on leverage.

Strategy B: Predict Loan-Bet Play

Goal: Combine Predict+ token holding with a funded bet using extracted loan capital.

When to use: You want exposure to the Predict+ token AND have conviction on a specific outcome but limited free capital.

Steps:

1. Create the prediction market (→08: client.predictionMarkets.createMarket())
2. Buy Predict+ token (→04: client.trading.buy())
3. Take a loan against the Predict+ tokens (→05: client.loans.takeLoan()) — recover ~96.5% of purchase price as USDB
4. Use the borrowed USDB to bet on your target outcome (→08: client.predictionMarkets.buy())

End state: Predict+ token held (locked as collateral) + outcome shares funded by borrowed capital. Loan repayment required before expiry or Predict+ tokens cover the debt.

Risk: If the bet loses and you need to repay the loan, repayment must come from other capital. Plan the repayment source before entering.

Strategy C: Vault Compound

Goal: Set-and-forget yield position that compounds over time via the wSTASIS vault.

When to use: Capital with no immediate deployment opportunity. Phase 1 window specifically — vault yield is at its peak early.

Steps:

1. Buy STASIS (→04: client.trading.buy() with STASIS address)
2. Stake STASIS → wrap to wSTASIS (→06: client.staking.wrap(stasisAddress, amount) wraps STASIS into wSTASIS)
3. Lock wSTASIS (→06: client.staking.lock())
4. Borrow USDB against locked wSTASIS (→06: client.staking.borrow())
5. Use borrowed USDB to buy more STASIS, repeat steps 2–4 (maximum 3 loops before origination fees exceed yield)
6. When loan nears expiry: extend (→05: client.loans.extendLoan()) — do not close and re-originate

End state: Multi-layer wSTASIS position earning vault yield on the full staked amount, including capital-against-which loans are outstanding.

Refinance loop: At each extension, if vault yield has increased the wSTASIS value above the loan amount, the surplus is earned yield. No action needed — it compounds automatically.

Strategy D: Prediction Market Mirror

Goal: Create BASIS prediction markets that mirror high-volume markets on Polymarket or Kalshi, capturing better economics.

Why BASIS economics are better:

• Polymarket: fixed $1 payout cap. BASIS: uncapped merged pot payout
• Polymarket: creator earns nothing. BASIS: creator earns 20% of net fees forever
• Polymarket: needs counterparty liquidity. BASIS: AMM fills instantly with virtual liquidity

Steps:

1. Identify an active Polymarket/Kalshi market with high volume on a broadly verifiable question
2. Create a matching market on BASIS (→08: client.predictionMarkets.createMarket()) — match the outcomes exactly for cross-pollination
3. Promote the market through social channels and referrals to drive participants
4. Collect creator fees passively for the market's lifetime
5. Optional: bet on your own market if you have higher information than the crowd

Structural edge: A participant familiar with a Polymarket market can immediately engage with its BASIS equivalent. The question is already understood. The only friction is the new platform — remove it with clear market descriptions.

Strategy E: Capital Recycler

Goal: Keep USDB continuously deployed across multiple revenue streams with a perpetual refinance loop.

When to use: Active capital management. Suitable for agents running autonomously on a recurring cycle.

Cycle (repeat on each pass):

1. Earn: Collect any outstanding vault yield, creator fees, loan remainders, or resolved outcome payouts
2. Lend: Deploy earned capital into a new position (buy token → take loan)
3. Deploy: Use extracted USDB to buy into a new market or token
4. Refinance: On each loan approaching expiry, extend (do not re-originate) unless a better opportunity justifies closing

Key principle: Capital should never sit idle. Idle USDB in a wallet earns nothing. Idle USDB in a wSTASIS vault earns platform fees. Idle USDB as a bet earns outcome payout. Every idle USDB has a deployment option.

Agent implementation: Schedule a recurring check every 24–48 hours. Collect any matured positions, extend approaching loan expirations, and deploy collected USDB into the highest-current-yield option from the decision trees in §4.

Strategy F: Network Multiplier

Goal: Amplify any primary strategy with a referral network that generates passive fee income from other participants' activity.

How to layer it onto any other strategy:

1. Register referral link on-chain (→03: identity module)
2. Recruit participants who fit the highest-fee archetypes: Capital Managers (high loan volume), Traders (high trade volume), Token Creators (sustained fee streams)
3. Earn referral fee share on every action from referred wallets — permanently
4. Re-deploy referral income using Strategy E (Capital Recycler)

Compounding dynamic: A referral network turns your social capital into on-chain yield. The more active your referred network, the more the network multiplier amplifies every other position you hold. A Super Referrer running Strategy E with 50 active referred Capital Managers is earning on both their own positions and every loan their network takes.

4. Decision Trees

"I have idle USDB — what should I do?"

"I want exposure to token X — how much conviction do I have?"

"I need liquidity but don't want to sell"

"I want to start a business on BASIS"

"Do I want to build a referral network?"

5. Stacking Strategies

Core Concept

Stacking is the technique of building multiple simultaneous positions from one starting pool of USDB, using loans to extract capital from each layer before deploying into the next.

Three properties make deep stacking viable on BASIS that would be dangerous on other platforms:

1. Shared collateral system. A single token position backs a loan. That loan's proceeds buy another position. The positions are independent — a move in one does not margin-call the other.
2. Buying does not lock capital. When you buy a token, you can immediately take a loan against it. The capital is not locked — it returns in a slightly smaller form.
3. No price liquidation. The floor price never decreases on Floor+ tokens. STASIS and Predict+ prices can only go up. No mid-stack market crash triggers a liquidation cascade. The only failure mode is time: missing a loan expiry.

The 5 Building Blocks (Paths A–E)

Every stack is built from these five paths. Each path starts with USDB and either returns USDB (allowing further stacking) or terminates.

Path A: Stable+ (STASIS wSTASIS loop)

This path is always Stack 1. It is the foundational layer:

• wSTASIS earns vault yield on the full position while locked as collateral
• STASIS price can only go up — the collateral appreciates without price risk
• No liquidation risk — collateral value never decreases
• The extracted USDB funds all subsequent paths

Path B: Floor+

LTV is against the floor price, not spot. If you buy at launch when floor is close to spot, LTV is near 100% of your purchase. If you buy after large appreciation when spot is 3x the floor, your LTV is roughly 33% of spot — you recover only ~33% × (100% − fees) of your USDB.

Path C: Predict+

LTV is at spot price (same as Stable+). Works identically to Path A but with Predict+ collateral. Use across multiple markets to maintain diversified exposure.

Path D: Outcome Bet

Path D is a terminal path. It does not return USDB to feed the next layer. It is deployed at the end of a stack when you want conviction-based directional exposure funded by loan proceeds from earlier layers. (See Module 08 §3b for bet mechanics and Module 14 for payout mechanics.)

Path E: Leverage

Path E is always terminal. No USDB returns from this path. It amplifies the position in one token with no remaining capital to deploy elsewhere. Use it last in any strategy. Best deployed on Floor+ tokens at launch (when floor ≈ spot, maximizing each loop's effective LTV) or on Stable+/Predict+ tokens for highest leverage multiplier. Mechanics reference: Module 04 §3c.

Fee Reality Check

After each path from a $1,000 starting position:

Every non-terminal path loses 2.05%–3.5% in fees per layer. Deeper stacks have proportionally less capital at each step. Build stacks where each layer's expected return exceeds its all-in cost.

4 Example Strategies

Conservative Stack

Profile: Risk-averse, yield focus, minimal monitoring required.

End state: Three layers of wSTASIS, all earning vault yield. Total staked: ~$29,756 in wSTASIS value. Total USDB borrowed: ~$19,256. Net cost: ~$494 in loan fees. Annual vault yield on $29,756 >> $494 in most fee environments.

Yield Maximizer

Profile: Moderate risk tolerance, active management, best Phase 1 strategy.

Deep Stack

Profile: Active agent, high frequency, maximum capital utilization.

End state: wSTASIS position (earning yield), Predict+ tokens in three markets (locked as collateral, earning from their own volume), outcome bet in a fourth market. Five concurrent positions from $5,000.

Monitoring requirement: Four loan expiry dates to track. All must be extended or repaid before expiry or the respective collateral covers the debt.

Creator's Edge

Profile: Token creator who wants to stack passive income streams.

Key Rules for Agents (Stacking)

1. Path A is always Stack 1. It is the safest path with the best LTV. Build wSTASIS first, everything else builds on top.

   Price impact on shallow pools: Capital recovery percentages (97.5%, 96.5%) assume negligible price impact. On pools with less than ~$5,000 liquidityUSD, price impact can exceed fees significantly. Always call getToken(address) to check pool depth, and probe with getAmountsOut() →04 before each stack. If your trade exceeds 10% of liquidityUSD, split into smaller buys.

2. Path E is always last. Never put leverage in the middle of a stack. Nothing can follow it.
3. Path D is terminal. Do not plan on extracting capital from an outcome bet before resolution.
4. Track every loan expiry. A missed expiry is a forced liquidation. Set alerts or use a monitoring loop. Check: client.loans.getUserLoanDetails() →05.
5. Extend, never re-originate. Extension is 400x cheaper per day. Closing and reopening a loan wastes 2% each time.
6. Buy Floor+ for stacking at or near launch. The floor-spot gap widens over time, reducing effective LTV. Early entry captures near-100% LTV.
7. Limit depth to what you can monitor. A 6-layer stack has 5 active loans. If any expires unmanaged, one position is liquidated. Depth is only safe if monitoring is reliable.
8. Do not stack across loans with different expiry windows without a rollover plan. Mismatched expiries create management complexity that causes missed extensions.

6. Unwinding Stacks

Sell vs Borrow Decision

The choice between selling a position and borrowing against it determines the character of your exit.

Good active managers use both. Selling reduces complexity. Borrowing preserves upside exposure. Neither is universally correct.

LIFO Unwind Order

Unwind stacks last-in, first-out. The outermost position must be closed before the loan that funded it can be repaid, and that loan repayment releases the collateral from the layer below it.

Skipping to a middle layer is not possible — the loans must be repaid in sequence from the outside in.

Closing Each Path Type

Path A (wSTASIS):

Before borrowing in Path A, check getUserStakeDetails() — if a vault loan is already active, use addToLoan() instead of borrow(). Only one vault loan per wallet.

1. Repay vault loan: client.staking.repay()
2. Unlock wSTASIS: client.staking.unlock(amount)
3. Unwrap wSTASIS to STASIS: client.staking.sell(shares, false)
4. Sell STASIS if needed: client.trading.sell(STASIS_ADDRESS, amount, minOut)

Or use the quick exit: client.staking.sell(shares, claimUSDB=true) — atomic unwrap-to-USDB in one transaction.

Path B (Floor+):

1. Repay loan: client.loans.repayLoan(loanId)
2. Retrieve collateral (token is released back to wallet)
3. Choose exit: sell via client.trading.sell() or hold for further appreciation

Path C (Predict+):

1. Repay loan: client.loans.repayLoan(loanId)
2. Retrieve Predict+ token
3. Sell before resolution: client.trading.sell() — may be suboptimal (see post-resolution timing below)
4. Or hold through resolution for post-resolution sell wave (price rises as holders sell)

Path D (Outcome shares):

• Cannot exit before resolution via loan — shares are terminal
• Sell on P2P order book if early exit is needed: client.orderBook.listOrder()
• After resolution: client.predictionMarkets.redeem(marketToken) if outcome won

Path E (Leverage):

1. Leverage positions are loan-backed — they expire by time, not by market action
2. At expiry: collateral automatically covers debt. Remainder (if any) claimable via client.loans.claimLiquidation() →05
3. To exit early: client.loans.partialSell() in 10% increments to reduce the position before expiry

Floor+ Profit Scenarios

Floor+ position never creates a loss beyond the initial loan fees — the floor guarantee means the collateral always has recoverable value at the floor price.

Leverage Unwinding Math

On leverage positions (Path E), the math at expiry:

Partial Close in 10% Increments

When reducing a position before full exit, partial close allows proportional exits without closing the entire position. The method differs depending on whether you're closing a loan or leverage:

// JS — regular loan: use client.loans
const result = await client.loans.hubPartialLoanSell(hubId, 20n, false, 0n); // isLeverage=false

// JS — leverage position: use client.trading (different contract!)
const result = await client.trading.partialLoanSell(positionId, 20n, true, minOut); // isLeverage=true

// Python — regular loan
result = client.loans.hub_partial_loan_sell(hub_id, 20, False, 0)

// Python — leverage position
result = client.trading.partial_loan_sell(position_id, 20, True, min_out)

Rule: The percentage argument must be a multiple of 10. Valid: 10, 20, 30, 40, 50, 60, 70, 80, 90, 100. 100 = full close. Invalid: any other number (silently reverts).

Use case: You hold a leveraged Floor+ position. Token has appreciated significantly. Rather than letting it ride to expiry, sell 30% now to lock in gains while keeping 70% exposed to further upside.

Exit Timing Guidance

Five rules that govern when to exit:

1. Exit Predict+ after resolution, not before. Post-resolution, sellers burn tokens pushing the price up. The last seller exits at the highest price. Early exits sacrifice post-resolution appreciation.

2. Exit Floor+ before the floor closes the gap with spot. When spot has risen far above floor, per-loop yield on any new position shrinks. But for existing holders, the higher spot means higher exit value — sell into strength.

3. Exit leverage positions before expiry if the market has moved in your favor. A leverage position that has 3x'd should exit via partial sells or full sell before expiry rather than waiting for the loan clock to force liquidation.

4. Extend rather than exit when costs are favorable. If the position still has expected upside and the extension fee (0.005%/day) is less than expected daily return, extend and stay.

5. Unwind from outermost layer inward (LIFO). Do not attempt to repay a middle-layer loan before clearing the outer layer — the outer loan's capital must be freed first to fund repayment.

Full Cycle Example

Week 1: Build

Weeks 2–4: Hold and Monitor

• Day 8: Extend all three loans (cost: 0.005%/day each, negligible vs positions)
• Day 14: Market X resolves. Predict+ X loan: repay → claim Predict+ → sell at post-resolution peak
• Day 14: Proceeds ($5,200) redeploy into new Predict+ market via Path C

Week 4: Unwind

7. Position Sizing Guidance

Reading Token Depth Before Entering

Pull token data before sizing any position:

// JS
const tokenData = await client.api.getToken(tokenAddress);
const liquidityUSD = tokenData.liquidityUSD;         // current pool depth
const startingLiquidity = tokenData.startingLiquidityUSD; // startLP equivalent in USD

// Python
token_data = client.api.get_token(token_address)
liquidity_usd = token_data['liquidityUSD']
starting_liquidity = token_data['startingLiquidityUSD']

liquidityUSD tells you how deep the current pool is. A $100 trade into a $500 pool moves the price dramatically. A $100 trade into a $50,000 pool moves it negligibly.

Price Impact Calculation

Before entering any position, simulate the trade and calculate slippage:

// JS — calculate price impact for a proposed buy
const path = [USDB_ADDRESS, STASIS_ADDRESS, tokenAddress];
const amountIn = parseUnits("1000", 18); // $1,000 proposed buy

const amountOut = await client.trading.getAmountsOut(amountIn, path);

// Get current price (per single token)
const currentPrice = await client.api.getTokenPrice(tokenAddress);

// Expected output at zero slippage
const expectedOut = amountIn / currentPrice;

// Slippage in basis points
const slippageBP = ((expectedOut - amountOut) * 10000n) / expectedOut;

console.log(`Price impact: ${slippageBP} basis points`);

# Python
path = [USDB_ADDRESS, STASIS_ADDRESS, token_address]
amount_in = 1000 * 10**18  # $1,000 proposed buy

amount_out = client.trading.get_amounts_out(amount_in, path)

current_price = client.api.get_token_price(token_address)
expected_out = amount_in // current_price

slippage_bp = ((expected_out - amount_out) * 10000) // expected_out
print(f"Price impact: {slippage_bp} basis points")

Thresholds

Splitting large positions: If a $10,000 buy produces 300 BP of slippage, split into 10 × $1,000 trades. Slippage on each is lower, total impact across all 10 is usually less than the single large trade due to the constant-product curve shape. Alternatively, spread across 10 different Predict+ markets in parallel — the multi-market stacking approach naturally solves the slippage problem.

Leverage position sizing: Each leverage loop adds price impact. The effective leverage (number of loops) decreases as position size increases. A $100 starting leverage position on a $10,000 LP token achieves more loops — and higher leverage — than a $10,000 starting position. Small positions on deep pools unlock maximum leverage.

8. Why This Only Works on BASIS

Every element of the stacking strategies above depends on structural properties of the BASIS platform. Standard DeFi replication is not possible.

The architectural dependency is total. A strategy like the Conservative Stack (§5) requires:

• Borrowing against a Stable+ token at 100% LTV (only possible because the floor price = spot, guaranteed by the AMM mechanics)
• No liquidation risk on the borrowed position (only possible with time-based expiry model)
• Vault yield on locked collateral (only possible with wSTASIS ERC4626 design that accrues yield to locked shares)

Remove any of these three properties and the Conservative Stack becomes either impossible or dangerous. The same dependency holds for every strategy in this module.

Gas sponsorship →01 note: 0.001 BNB per wallet per day is sponsored. Small individual position entries (multi-market stacking with smaller per-trade sizes) are effectively free for gas. This sponsorship makes the multi-prong approach economically viable even at small position sizes.

Quick Reference

→ Prerequisite modules: 04-trading.md · 05-lending.md · 06-staking.md · 07-token-creation.md · 08-predictions.md → Deep mechanics: 11-token-mechanics.md (AMM math, multiplier system, token type reference) → Advanced prediction plays: 13-prediction-strategies.md · 14-resolution-deepdive.md