## Loading stock data from local file /cloud/project/stockdata_from_2019-01-01_to_2023-05-31_(0f9cf120d38e5ba793ee9b2a12c3efc1).RData
In this section we assign our riskParity & max_sharpe_ratio portfolio functions. The functions will get passed into out optimization to find the weights at each period.
## Backtesting 2 portfolios over 1 datasets (periodicity = monthly data)...
## Backtesting benchmarks...
Get rebalanced dates along with the table of stats for each portfolio.
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## Rebalanced:
## [1] "Jun 2019" "Jul 2019" "Aug 2019" "Sep 2019" "Oct 2019" "Nov 2019"
## [7] "Dec 2019" "Jan 2020" "Feb 2020" "Mar 2020" "Apr 2020" "May 2020"
## [13] "Jun 2020" "Jul 2020" "Aug 2020" "Sep 2020" "Oct 2020" "Nov 2020"
## [19] "Dec 2020" "Jan 2021" "Feb 2021" "Mar 2021" "Apr 2021" "May 2021"
## [25] "Jun 2021" "Jul 2021" "Aug 2021" "Sep 2021" "Oct 2021" "Nov 2021"
## [31] "Dec 2021" "Jan 2022" "Feb 2022" "Mar 2022" "Apr 2022" "May 2022"
## [37] "Jun 2022" "Jul 2022" "Aug 2022" "Sep 2022" "Oct 2022" "Nov 2022"
## [43] "Dec 2022" "Jan 2023" "Feb 2023" "Mar 2023"
## risk parity portfolio tangency portfolio 1/N
## Sharpe ratio 5.1805 4.9795 5.8403
## max drawdown 0.2098 0.2226 0.2057
## annual return 5.0913 5.1154 5.4966
## annual volatility 0.9828 1.0273 0.9411
## Sortino ratio 8.9534 9.2195 10.9557
## downside deviation 0.5686 0.5548 0.5017
## Sterling ratio 24.2708 22.9820 26.7218
## Omega ratio 2.1958 2.1866 2.3825
## VaR (0.95) 0.0846 0.0918 0.0782
## CVaR (0.95) 0.1087 0.0984 0.0827
## rebalancing period 1.0217 1.0217 1.0217
## turnover 0.2899 0.5199 0.0530
## ROT (bps) 688.6823 376.1237 4072.5261
## cpu time 0.0050 0.0258 0.0039
## failure rate 0.0000 0.0000 0.0000
Plot the returns for all the portfolios.
Plots the weigjt changes at each interval.