aggregate_trend_following_jan2022.py

import matplotlib
matplotlib.use("TkAgg")
from syscore.objects import arg_not_supplied

# from sysdata.sim.csv_futures_sim_data import csvFuturesSimData
from sysdata.sim.db_futures_sim_data import dbFuturesSimData
from sysdata.config.configdata import Config

from systems.basesystem import System
from systems.provided.rob_system.rawdata import myFuturesRawData
from systems.provided.dynamic_small_system_optimise.portfolio_weights_stage import (
    portfolioWeightsStage,
)
from sysquant.estimators.clustering_correlations import *


def futures_system(
    sim_data=arg_not_supplied, config_filename="systems.provided.rob_system.config.yaml"
):

    if sim_data is arg_not_supplied:
        sim_data = dbFuturesSimData()

    config = Config(config_filename)

    system = System(
        [
            portfolioWeightsStage(),
            myFuturesRawData(),
        ],
        sim_data,
        config,
    )
    system.set_logging_level("on")

    return system

import datetime

system = futures_system()
instrument_list = system.get_instrument_list()

system.config.instrument_returns_correlation['cleaning'] = False
system.config.instrument_returns_correlation['shrinkage_parameter'] = 0.0
system.config.instrument_returns_correlation['date_method']='in_sample'
system.config.instrument_returns_correlation['using_exponent'] = False

corr_matrix = system.portfolioWeights.get_correlation_matrix()

def display_clusters(system, clusters):
    for idx, cluster in enumerate(clusters):
        print("Cluster %d" % (idx+1))

        show_cluster(system, cluster)

def show_cluster(system, cluster):
    instruments = cluster
    assets = [system.data.asset_class_for_instrument(code) for code in instruments]
    classes = list(set(assets))
    for aclass in classes:
        subset = [code for (code,asset_class) in zip(instruments, assets)
        if asset_class==aclass]
        print("%s: %s" % (aclass, str(subset)))


N=2
clusters = cluster_correlation_matrix(corr_matrix,N)

show_cluster(system, clusters)