# set default parameters
number_of_agents = 1000
init_time = 100
max_time = 500
av_return_interval_min = 5
av_return_interval_max = 50 # previously Lmax
fundamental_value = 1000. # previously pf
allowed_price_steps = 0.1 # deltaP
variance_noise_forecast = 0.01 # prev sigmae
order_noise_max = 0.5 # prev kMax
order_expiration_time = 50 # prev tau
runType = 0
if runType == 0:
    fundamental_weight = 0.  # prev sigmaF
    momentum_weight = 0.    # prev sigmaM
    noise_weight = 1.       # prev sigmaN
if runType == 1:
    fundamental_weight = 1.
    momentum_weight = 0.
    noise_weight = 1.
if runType == 2:
    fundamental_weight = 1.
    momentum_weight = 10.
    noise_weight = 1.
ticks_per_day = 100

"""
Explanation: Replication notebook
Using this notebook, we replicate the 2002 model by Ciarelli and Lori (2002).
Based on code from agentFin website by Blake Lebaron.
End of explanation
"""


day_price, day_volume, day_return, price, returns, total_volume = ciarellilori2002(seed, max_time, init_time, number_of_agents, av_return_interval_min, 
                 av_return_interval_max, fundamental_value, allowed_price_steps, variance_noise_forecast,
                 order_noise_max, order_expiration_time, fundamental_weight, momentum_weight, noise_weight, 
                 ticks_per_day):

"""
Explanation: Simulation:
End of explanation
"""


