sum_data

This function takes in a data set and returns the summary for each day's
net market value, profit and loss, contract number and return rate.

Creates an interactive graphics
interface to visualize backtest results of different financial
instruments, such as equities, futures, and credit default swaps.
The package does not run backtests on the given data set but
displays a graphical explanation of the backtest results. Users can
look at backtest graphics for different instruments, investment
strategies, and portfolios. Summary statistics of different
portfolio holdings are shown in the left panel, and interactive
plots of profit and loss (P&L), net market value (NMV) and
gross market value (GMV) are displayed in the right panel.

Yanrong Song

backtestGraphics

Interactive Graphics for Portfolio Data

Zijie Zhu

David Kane

Ziqi Lu

Karan Tibrewal

Fan Zhang

sum_data function

<dl><dt>x</dt>
<dd>A data frame that contains data for individual commodities.</dd>
<dt>sector.selected</dt>
<dd>The sector that the function is doing summarization
for. When "sector.selected = NULL", the function performs summarization across
the whole data set.</dd>
<dt>capital.num</dt>
<dd>The constant number of allocated capital to calculate return, 
number. Default value is NULL. When "capital.num = NULL", the function uses
gross market value to calculate return rates for each row.</dd></dl>

Arguments

Summarize data for the overall portfolio — sum_data

<dl>

<dt>x</dt>
<dd>A data frame that contains data for individual commodities.</dd>


<dt>sector.selected</dt>
<dd>The sector that the function is doing summarization
for. When "sector.selected = NULL", the function performs summarization across
the whole data set.</dd>


<dt>capital.num</dt>
<dd>The constant number of allocated capital to calculate return, 
number. Default value is NULL. When "capital.num = NULL", the function uses
gross market value to calculate return rates for each row.</dd>

</dl>

sum_data: Summarize data for the overall portfolio

Description

Usage

Value

Arguments