SnapshotL1(...)

Structure containing the L1 snapshots.

SnapshotL2(...)

Structure containing the L2 snapshots.

adjust_L2_snapshots(X::Union{Array{Float64, 3}, Array{Int64, 3}})
adjust_L2_snapshots(Union{JArray{Float64, 3}, JArray{Int64, 3}})

Adjust inconsistent use of zeros at source to indicate missing observations in bids/asks.

aggregate_L2_snapshot_eop(X::SnapshotL2, time_step::Period)

Take the last bids and asks in X approximately every time_step.

aggregate_LOB_measurement(X::Union{Vector{Float64}, JVector{Float64}}, times::Vector{Time}, time_step::Period, f::Function; f_args::Tuple=(), f_kwargs::NamedTuple=NamedTuple())

Aggregate X by taking its f transformation at the specified time_step.

aggregate_LOB_measurement_avg(X::Union{Vector{Float64}, JVector{Float64}}, times::Vector{Time}, time_step::Period)

Aggregate X by returing the average (non-overlapping) measurement taken at the specified time_step.

aggregate_LOB_measurement_eop(X::Union{Vector{Float64}, JVector{Float64}}, times::Vector{Time}, time_step::Period)

Aggregate X by returing the EOP measurement taken at the specified time_step.

build_config(config_suffix::String, kwargs::NamedTuple)

Build a configuration starting from the one of the official rmscXX templates.

Notes

• More information on the templates is available at https://github.com/jpmorganchase/abides-jpmc-public.

compare_aggregated_LOB_measurements(X::JMatrix{Float64}, Y::JMatrix{Float64}, f_ticks::Function, f_time::Function)

Compare two vectors of aggregated LOB measurements.

Each column of X and Y denotes a different point in time, while each row is a different entry (perhaps different levels).

compare_aggregated_LOB_measurements_mse(X::JMatrix{Float64}, Y::JMatrix{Float64})

Compare two vectors of aggregated LOB measurements through the MSE.

get_L1_snapshots(order_book::PyObject)

Get the L1 snapshots from the order book in an ad-hoc Julia structure.

get_L2_snapshots(order_book::PyObject, nlevels::Int64)

Get the L2 snapshots from the order book in an ad-hoc Julia structure.

ndarray_to_matrix(X::Matrix{PyCall.PyObject})

Converts X into a JMatrix{Float64} handling None appropriately.

ndarray_to_matrix(X::Matrix{Float64})

Converts X into a JMatrix{Float64} for internal consistency.

parse_logs_df(end_state::Dict)

Takes the end_state dictionary returned by an ABIDES simulation, goes through all the agents, extracts their log, and un-nest them returns a single dataframe with the logs from all the agents warning.

run(config::Dict)

Run simulation using the configuration in config.