mpo_* tool: single- and multi-period optimisation policies (expected return against full, diagonal, factor or worst-case risk, transaction and holding costs) with a planning horizon and about thirty constraint types (long-only, leverage, weight, trade and holding limits, turnover, participation rate, market, dollar and factor neutrality, cash, volatility target, soft constraints); rule-based policies (hold, cash, equal weight, fixed weights, periodic, proportional and adaptive rebalancing, rank long-short, volume-weighted market portfolio); a market simulator charging spreads, market impact, per-share fees, borrow and holding costs, with whole-share rounding and liquidity caps; today’s optimal trades and planned trajectory; pre-trade cost, risk and constraint checks; return, risk, factor and volume forecasts; and risk and trade-aversion sweeps and searches. It never fetches market data itself: pass a table or a $fincept reference. It runs on Fincept’s servers; your agent sends numbers or data references and gets back a result envelope with tables and charts.
Fincept Multi-Period tools are free. They count toward the rate limit only; a
$fincept reference inside a call is charged like a direct call to that tool.Modules
Tools are grouped in modules. Each module is a toolset namedmpo_<module>, so you can list it or search within it. The Fincept Multi-Period reference lists every module and tool.
mpo_catalog returns the live list of modules and tools from inside your agent.
Inputs
Limits
A computation that runs past its time limit answers
timeout; a busy engine answers busy and the call can be retried a few seconds later.
Outputs
Back-tests return every metric (return, volatility, excess and active return, Sharpe ratio, information ratio, growth rate, drawdown, turnover, leverage and the cost breakdown), per-period paths and weights over time as series with charts;mpo_backtest_rules adds a comparison table and value curves of every policy. mpo_optimize and mpo_rule_trades return current, target and trade weights and trades in value and in whole shares; mpo_evaluate_trade returns each objective term and whether every constraint holds. mpo_gamma_sweep returns the realized risk-return frontier and the best aversions by Sharpe ratio.
Example
Prompt
multi-period backtest, finds mpo_backtest and mpo_optimize, and passes each stock’s closes as a $fincept reference to market_get_candles, one prices column per stock, with the dates from candles.time as the date column.