sharavsambuu

sharavsambuu

Risk Parity & Budgeting

With Python

Dr. Yves J. Hilpisch | The Python Quants & The AI Machine

Python for Quant Finance Meetup, London, 16. November 2022

(short link to this Gist: http://bit.ly/pqf_risk)

sharavsambuu

#include <glm/matrix.hpp>

class Frustum
{
public:
	Frustum() {}

	// m = ProjectionMatrix * ViewMatrix 
	Frustum(glm::mat4 m);

sharavsambuu

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

sharavsambuu

sharavsambuu

sharavsambuu

import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import timedelta


def generate_stock_equity(start_date, end_date):
    num_days   = (end_date - start_date).days + 1
    changes    = np.random.randint(low=-150, high=150, size=num_days)

sharavsambuu

#%%
import random
import numpy as np
from pymoo.core.problem            import ElementwiseProblem
from pymoo.algorithms.moo.nsga2    import NSGA2
from pymoo.algorithms.moo.nsga3    import NSGA3
from pymoo.optimize                import minimize
from pymoo.util.ref_dirs           import get_reference_directions

from pymoo.operators.sampling.rnd  import FloatRandomSampling

sharavsambuu

#%%
import random
import numpy as np
from pymoo.core.problem            import ElementwiseProblem
from pymoo.algorithms.moo.nsga2    import NSGA2
from pymoo.optimize                import minimize

from pymoo.operators.sampling.rnd  import FloatRandomSampling
from pymoo.operators.crossover.sbx import SBX
from pymoo.operators.mutation.pm   import PM

sharavsambuu

#%%
import warnings
warnings.filterwarnings("ignore")
def action_with_warnings():
    warnings.warn("should not appear")
with warnings.catch_warnings(record=True):
    action_with_warnings()
import sys
sys.path.insert(0, '.')
import os