USDTVLSizeRiskModel#

API documentation for tradeexecutor.strategy.tvl_size_risk.USDTVLSizeRiskModel Python class in Trading Strategy framework.

class USDTVLSizeRiskModel[source]#

Bases: BaseTVLSizeRiskModel

Estimate the trade size based historical USD TVL values.

  • Fast as we have preprocessed data available

  • Some tokens may spoof this value and give unrealistic sizes

__init__(pricing_model, per_trade_cap=1.0, per_position_cap=1.0, missing_tvl_placeholder_usd=None)[source]#

Create size-risk model.

Parameters:

  • pricing_model (PricingModel) – Pricing model is used to read TVL data (historical/real time)

  • per_trade_cap (float) – How many % of pool TVL on trade can be

  • per_position_cap (float) – How many % of pool TVL on trade can be

  • missing_tvl_placeholder_usd (float) –

Parma missing_tvl_placeholder_usd:

If we do not have TVL data available, use this value as a fixed US value placeholder.

E.g. set to 250_000 to assume all unknown pools to have 250k TVL at any point of time.

Methods

__init__(pricing_model[, per_trade_cap, ...])

Create size-risk model.

get_acceptable_size_for_buy(timestamp, pair, ...)

get_acceptable_size_for_position(timestamp, ...)

What this the maximum position amount.

get_acceptable_size_for_sell(timestamp, ...)

get_pair_cap(pair, sizing_type)

Get cap for an individual trade for a pair.

get_tvl(timestamp, pair)

Read the TVL from the underlying pricing model.
__init__(pricing_model, per_trade_cap=1.0, per_position_cap=1.0, missing_tvl_placeholder_usd=None)[source]#

Create size-risk model.

Parameters:

  • pricing_model (PricingModel) – Pricing model is used to read TVL data (historical/real time)

  • per_trade_cap (float) – How many % of pool TVL on trade can be

  • per_position_cap (float) – How many % of pool TVL on trade can be

  • missing_tvl_placeholder_usd (float) –

Parma missing_tvl_placeholder_usd:

If we do not have TVL data available, use this value as a fixed US value placeholder.

E.g. set to 250_000 to assume all unknown pools to have 250k TVL at any point of time.

get_tvl(timestamp, pair)[source]#

Read the TVL from the underlying pricing model.

Parameters:
Return type:

float