onekenosi/African-Risk-Market-Dashboard
Domain:
socioeconomicCreator:
one
Host:
# African-Risk-Market-Dashboard
import streamlit as st
import pandas as pd
import numpy as np
import plotly.graph_objects as go
import plotly.express as px
from datetime import datetime, timedelta
import yfinance as yf
st.set_page_config(
page_title="African Markets Risk Dashboard",
page_icon="📊",
layout="wide"
)
st.title("📊 African Markets Risk Dashboard")
st.markdown("""
Explore financial risk metrics across African stock markets and currencies.
This dashboard provides real-time analysis of volatility, returns, and comparative performance.
""")
st.sidebar.header("Configuration")
AFRICAN_MARKETS = {
"South Africa (JSE Top 40)": "^J203.JO",
"Nigeria (NGX All-Share)": "NGSEINDEX",
"Egypt (EGX 30)": "^CASE30",
"Kenya (NSE 20)": "^NSEI",
"Morocco (MASI)": "^MASI.CS"
}
CURRENCIES = {
"ZAR/USD (South African Rand)": "ZARUSD=X",
"NGN/USD (Nigerian Naira)": "NGN=X",
"EGP/USD (Egyptian Pound)": "EGP=X",
"KES/USD (Kenyan Shilling)": "KES=X",
"MAD/USD (Moroccan Dirham)": "MAD=X"
}
BENCHMARK_MARKETS = {
"S&P 500": "^GSPC",
"FTSE 100": "^FTSE",
"Shanghai Composite": "000001.SS"
}
selected_market = st.sidebar.selectbox(
"Select African Market",
list(AFRICAN_MARKETS.keys())
)
selected_currency = st.sidebar.selectbox(
"Select Currency Pair",
list(CURRENCIES.keys())
)
time_period = st.sidebar.selectbox(
"Time Period",
["1mo", "3mo", "6mo", "1y", "2y"],
index=2
)
risk_free_rate = st.sidebar.slider(
"Risk-Free Rate (%)",
min_value=0.0,
max_value=10.0,
value=4.5,
step=0.1
) / 100
@st.cache_data(ttl=3600)
def fetch_data(ticker, period):
"""Fetch historical data from Yahoo Finance"""
try:
data = yf.download(ticker, period=period, progress=False)
return data
except:
return None
def calculate_returns(data):
"""Calculate daily returns"""
return data['Close'].pct_change().dropna()
def calculate_volatility(returns, annualize=True):
"""Calculate volatility (standard deviation of returns)"""
vol = returns.std()
if annualize:
vol = vol * np.sqrt(252) # Annualize assuming 252 trading day …