Portfolio Optimization is used for risk-averse investors to construct portfolios to optimize or maximize expected return based on a given level of market risk, emphasizing that risk is an inherent part of higher reward
Also, with the pandemic (COVID-19) situation, there are uncertainities linked in each sector. So the brief analysis of how crytpo, commodities and S&P 500 markets are performing and how the various news / events affect the prices.
- API for financial data from Yahoo! Finance
- Bloomberg Stock Market
- Twitter News Feed
- Cointelegraph News
- Crytocurrency - Bitcoin, Bitcoin-Cash & Etherum
- Commodities - Gold & Silver
- Stock - S&P 500
- Analysis shows that BTC-USD was the most volatile across the year
- Due to pandemic situation, all the assets show significant drop starting March 2020.
- Commodities i.e. Gold has grown significantly from around $1300 to $ 1700. But as all other stocks, March 2020 had seen major drop to $1479.
- Performance Analysis
- BTC still has the best returns, while gold is a distant second. Silver and the SP500 track very closely, as do BTCASH and ETH which are near the bottom.
- Correlation between stocks and other assets class
Standard Deviation
Bitcoin_Cash 0.061713
Bitcoin 0.043095
Etherum 0.049667
Gold 0.010216
Silver 0.017035
SP500 0.016209
- Volatility is a statistical measure of the dispersion of returns for a given security or market index. In most cases, the higher the volatility, the riskier the security.
Gold 0.162170
SP500 0.257317
Silver 0.270420
Bitcoin 0.684110
Etherum 0.788435
Bitcoin_Cash 0.979665
- Bitcoin Cash is the most risky investment followed by Etherum.
- Gold is at the least risk.
- High Beta stocks are supposed to be riskier but provide higher return potential
Bitcoin_Cash : 0.89
Bitcoin : 0.71
Etherum : 1.01
Gold : 0.01
Silver : -0.06
SP500 : 1.0
Sharpe Ratio helps to understand the return of an investment compared to its risk.
Bitcoin_Cash 0.778293
Bitcoin 1.156295
Etherum 0.746208
Gold 1.210387
Silver 0.245059
SP500 0.178116
- Bitcoin & Gold have highest return to risk as compared to other assets.
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Pre-defined weights = [0.1, 0.2, 0.1, 0.2, 0.1, 0.3]
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Statistics :
Expected annual return : 35.0%
Annual volatility/standard deviation/risk : 33.0%
Annual variance : 11.0%
Portfolio Optimization is used for risk-averse investors to construct portfolios to optimize or maximize expected return based on a given level of market risk, emphasizing that risk is an inherent part of higher reward.
Single Random Simulation
- Set our weights to a random numpy array
- Rebalance the weights so they add up to one
- Calculate the expected portfolio return
- Calculate the expected portfolio volatility
- Calculate the Sharpe Ratio
Sharpe Ratio
0.9469891810355706
Multiple Random Simulation
Multiple Random Simulation with highest Sharpe Ratio
Max Sharpe Ratio - 1.246
- Calculate Efficient Frontier - Set of optimal portfolios that offer the highest expected return for a defined level of risk or the lowest risk for a given level of expected return.
- Optimal Weights
Bitcoin Cash - 0.00
Bitcoin - 0.19
Etherum - 0.00
Gold - 0.81
Silver - 0.00
SP500 - 0.00
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Use of Scipy library to calculate the results wherein we minimize sharpe ratio, keep the weights within 1 and use Sequential Least Squares Programming (SLSQP) method
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Optimal Results -
Returns - 0.30
Volatility - 0.19
Sharpe Ratio - 1.59