In GiuseppeTT/RiskParityBrazil: An analysis of risk parity applied to the Brazilian stock market

```{js desinvert navbar} $('.navbar-inverse').removeClass('navbar-inverse').addClass('navbar-default');

```r
`%>%` <- magrittr::`%>%`

analysis <-
    params %>%
    magrittr::extract2("analysis") %>%
    magrittr::extract2(1)

Summary

Column {.tabset .tabset-fade}

Metrics

analysis %>%
    magrittr::extract2("summary") %>%
    magrittr::extract2("metrics_table") %>%
    gt::gt(rowname_col = "Asset") %>%
    gt::fmt_percent(tidyselect::everything()) %>%
    gt::tab_style(
        style = gt::cell_text(weight = "bold"),
        locations = gt::cells_column_labels(tidyselect::everything())
    ) %>%
    gt::tab_options(
        table.border.top.style = "hidden",
        table.width = "100%"
    )

Gain

Column {.tabset .tabset-fade}

Price

analysis %>%
    magrittr::extract2("gain") %>%
    magrittr::extract2("price_plot") %>%
    plotly::ggplotly()

DCA multiple

analysis %>%
    magrittr::extract2("gain") %>%
    magrittr::extract2("dca_multiple_plot") %>%
    plotly::ggplotly()

Rolling CAGR

analysis %>%
    magrittr::extract2("gain") %>%
    magrittr::extract2("rolling_cagr_plot") %>%
    plotly::ggplotly()

Risk

Column {.tabset .tabset-fade}

Smooth volatility

analysis %>%
    magrittr::extract2("risk") %>%
    magrittr::extract2("smooth_volatility_plot") %>%
    plotly::ggplotly()

Drawdown

analysis %>%
    magrittr::extract2("risk") %>%
    magrittr::extract2("drawdown_plot") %>%
    plotly::ggplotly()

Relation

Column {.tabset .tabset-fade}

Smooth correlation

analysis %>%
    magrittr::extract2("relation") %>%
    magrittr::extract2("smooth_correlation_plot") %>%
    plotly::ggplotly()

Theoretical weight

analysis %>%
    magrittr::extract2("relation") %>%
    magrittr::extract2("theoretical_weight_plot") %>%
    plotly::ggplotly()

GiuseppeTT/RiskParityBrazil documentation built on Dec. 17, 2021, 9:33 p.m.