backtestGraphics: Interactive Backtest Graphics

Description Usage Arguments Details Value Examples

View source: R/backtestGraphics.R

Description

This function takes a data frame and returns an interactive interface for the backtest data. The interface contains drop-down menus for different strategies, portfolios and instruments/sectors. The user can slice her data set according to the strategies for selecting instruments or the portfolio numbers of her individual portfolios. The user can also look at a specific group of instruments according to the sector of instruments. These sectors will be in the same dropdown menu as instruments. The elements in each of the three dropdown menus are generated according to the input data set. The dropdown menus for strategies and portfolio numbers will only contain "Strategy Summary" or "Portfolio Summary" if there's no strategy or portfolio information available in the input data set.

Usage

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backtestGraphics(x, trade.freq = NULL, name.var = "name", id.var = "id",
  date.var = "date", nmv.var = "nmv", gmv.var = "gmv", pnl.var = "pnl",
  contract.var = "contract", capital.num = NULL, sector.var = "sector",
  strategy.var = "strategy", substrategy.var = "substrategy",
  portfolio.var = "portfolio")

Arguments

x

is a data frame that contains the necessary information.

trade.freq

is the trading frequency of the data set, numeric type. The variable uses the number of dates between two trading dates to indicate trading frequency. The default value of this variable is NULL, and in this case the function will automatically calculate the trading period.

name.var

is the column name of the instrument name column in the input data set, character type. The default value of this variable is "name". The user has to specify name.var if she passes in a data frame with a different column name for the instrument name. The input data set must contain either a name column or an ID column.

id.var

is the column name of the instrument ID column, character type. The default value of this variable is "id". If the input data set labels the column of instrument ID's with some other column name, the user has to pass in the column name here. The input data set has to contain either a name column or an ID column.

date.var

is the column name of the date column, character type. The default value of this variable is "date". This column has to exist, and the column name has to be correct in order for the function to process the data set properly.

nmv.var

is the column name of the "net market value" column, character type. The default value of this variable is "nmv". The input data set has to contain either a "net market value" column or a "number of contract" column.

gmv.var

The column name of the "gross market value" column if exists, character type. The default value of this variable is "gmv". Such column will be automatically calculated from the "net market value" column if it does not exist.

pnl.var

The column name of the profit-and-loss column, character type. The default value of this variable is "pnl". The data set has to contain such column so that the function can function properly. If such column is missing, the function will return an error indicating the problem.

contract.var

The column name of the contract number column, character type. The default value of this variable is "contract". If such column is missing, the function will instead use net market value as the contract number for each day.

capital.num

The constant number of allocated capital for the whole portfolio, numeric type. The default value of such variable is NULL. The function will use the number of allocated capital to calculate return rates. If the allocated capital for the portfolio is not specified, the function will use each day's gross market value to calculate the return rate for each day.

sector.var

is the column name of the sector column, character type. The default value of this variable is "sector". The sector column helps the user to group instruments into big groups according to industries. The function will still perform properly if the column name for sector is wrong.

strategy.var

The column name of the strategy column, if any. Character type. The default value of this variable is "strategy". This column can be missing from the input data set.

substrategy.var

The column name of the substrategy column, if any. Character type. The default value of this variable is "substrategy". This column can be missing from the input data set.

portfolio.var

The column name of the portfolio number column, if any. Character type. The default value of this variable is "portfolio". This column can be missing from the input data set.

Details

The user can also slice the data set according to the division of the data set into main strategies, and the division of any main strategy into small substrategies. The "substrategy" column of the data set should indicate the division of main strategies, if there are any substrategies. Note that the structure of substrategies should conform to main strategies. That is, a single substrategy should be under only one main strategy.

Summary statistics are displayed in tables under the drop-down menu. The summary statistics contain data for the backtesting time horizon, profits, returns, volatility, market values, best/worst performers and biggest drawdowns. Different interactive plots for the cumulative P&L, daily P&L, Net Market Value (NMV), Gross Market Value (GMV) and number of contracts are shown in the right panel.

The backtestGraphics function takes in a data set as well as the names of essential columns in the data set, if these names are different from the default ones. The column names should be assigned to the corresponding variables so that the function can recognize these columns. If some essential columns are missing, the function will try to fill in these columns with existing data. If the function fails to do so due to a lack of data, the function will return an error about the missing columns. If a column name is wrong, the function will treat that column as a missing column. The input data set has to contain either a name column or an ID column, a date column, either a net market value column or a number of contract column and a P&L column. The other columns either help the user slice the data set into different pieces to diagnose the data better, or can be calculated from the data inside the input data set.

Value

a Shiny interface. The interactive shiny interface displays P&L and cumulative P&L on one chart, and number of contracts, net market value and gross market value on the other chart. Some summary statistics about return and performances are displayed on the left sidebar as tables.

Examples

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## Not run: 
backtestGraphics(data = credit.bt)

## End(Not run)

backtestGraphics documentation built on May 29, 2017, 3:11 p.m.