Today I would like to share about the strategy I am applying for trading bots; it will be somewhat technical, and I hope to receive more shares and suggestions from you all to improve further.
Nash Equilibrium, this is a strategy that few people mention, but based on my personal experience, it works quite effectively for Spot and Futures with low leverage. I have been applying it continuously over the past month and the profits are relatively stable (NFA).
Core idea:
In game theory, Nash Equilibrium is the state where all players are 'rational' and have no incentive to change strategies. The crypto market rarely stays balanced for long — it continuously deviates due to funding, crowd psychology, basis, OI volatility...
👉 My goal: quantify the level of 'equilibrium deviation' and exploit it in 2 modes:
Contrarian: Too large a deviation on one side → enter a reverse position to profit from a mean-revert.
Momentum: Moderate deviation but with a trend → go with the momentum, maintain risk management discipline.
EDI (Equilibrium Deviation Index)
I aggregated many sources to create a single measure:
8-hour funding (z-score) & Long/Short account ratio (z-score): measures crowd psychology & leverage.
Open Interest change (z-score): measures sudden market heat.
Orderbook imbalance (micro): supply/demand deviation at the top of the order book.
Basis & basis slope: difference between mark-index and slope over time.
(Optional) Wick/Liquidation signal + BTC momentum to adjust noise.
From there create EDI:
High EDI + crowd heavily leaning one side → prioritize Contrarian.
Average EDI + clear momentum → prioritize Momentum.
Entry/exit rules (abbreviated):
Entry: place limit post-only with offset (to reduce slippage), only scale-in when there is a pullback and EDI improves (no FOMO).
SL/TP according to ATR:
SL ≈ ATR_MULT_SL × ATR, TP ≈ ATR_MULT_TP × ATR (depending on volatility & mode).
SOFT Trailing Stop: follows the anchor, adjusts according to ATR & price momentum.
Break-even: when profit goes far enough, pull SL back to positive with a cushion (bp).
Partial TP when the market is 'FLAT': if it stays sideways long enough, close some positions to lock in profits.
Disaster Stop: always have a STOP_MARKET insurance (according to liquidation price or large ATR).
Risk management & sizing
Low leverage priority (reduce stress & tail-risk).
Risk per trade is about 10–15% of the risk budget (not account capital).
Hedge mode allows independent LONG/SHORT management, avoiding conflict.
Notional/margin cap limits to prevent capital abuse during unusual volatility.
Crypto easily goes out of balance → EDI captures many mean-revert & clean breakout phases.
Low leverage helps when EDI is noisy, while optimizing RR with flexible trailing.
Last month, I ran a trading bot using this strategy and the profit was quite stable (3% for Spot and 20% for features). Since my capital is not much, I chose the least risky path. You can refer to the positions in my leader profile here:
SOCO
NFA. Do your own research. Manage risk first, profits will follow.
