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optimizer/optimize_sol_extended.toml
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# SOL Extended-Bounds Optimizer # # SOL 15m optimize_vol_calibration.toml run: Sharpe 12.13 (good) but: # - vol_floor = 0.70 (MAX bound hit) → true optimum may want vol_floor > 0.70 # - ev_hold_theo_threshold = 0.35 (MIN bound hit) → true optimum may want < 0.35 # Both params at walls: the PSO swarm could not escape the search boundary. # # This config extends the bounds to find the true optimum for SOL. # ewma_lambda added for completeness — SOL may also benefit from lambda tuning, # though the vol_floor hitting max suggests the raw EWMA vol was also low for SOL. # # If SOL's optimum settles at vol_floor ~1.0+ it means the EWMA underestimates # SOL's realized volatility (possibly due to lookback being too short or lambda # too high). The optimizer can then co-tune ewma_lambda + vol_floor together. replay_dir = "replay_data/15m_live_recording_20260224_223827" slugs = ["sol-up-or-down-15m"] strategy_type = "cryptoprices" template_config = "config/live/live-sol-eth-15m.toml" [parameter_space.strategy] vol_floor = { min = 0.30, max = 1.50 } ev_hold_theo_threshold = { min = 0.10, max = 0.60 } #hold_to_maturity_seconds = { min = 120, max = 600 } #stop_loss_pct = { min = 0.15, max = 0.50 } ewma_lambda = { min = 0.05, max = 0.30 } [parameter_space.global] #stop_loss_timeout = { min = 5, max = 30 } #stop_loss_recovery_buffer = { min = 0.01, max = 0.05 } [objective] function = "sharpe_ratio" [pso] swarm_size = 20 max_iterations = 50 inertia_weight = 0.729 cognitive_coefficient = 1.49445 social_coefficient = 1.49445