crossover operators

Description

Binary operators which create the upwards or downwards crossover signals.

Usage

x %x>% y

x %x<% y

Arguments

Examples

library(data.table)
library(pedquant)

data("dt_banks")
boc = md_stock_adjust(setDT(dt_banks)[symbol=='601988.SH'])
bocti = pq_addti(boc, x='close_adj', sma=list(n=200), sma=list(n=50))

dtorders = copy(bocti[[1]])[,.(symbol, name, date, close_adj, sma_50, sma_200)
][sma_50 %x>% sma_200, `:=`(
    side = 'buy', prices = close_adj
)][sma_50 %x<% sma_200, `:=`(
    side = 'sell', prices = close_adj
)][, (c('side', 'prices')) := lapply(.SD, shift), .SDcols = c('side', 'prices')]
orders = dtorders[!is.na(side)]
head(orders)

e = pq_plot(boc,  y='close_adj', addti = list(sma=list(n=200), sma=list(n=50)), orders = orders)
e[[1]]

dataset of bank stocks in sse

Description

The daily historical data of bank stocks

Usage

dt_banks

Format

A data frame with 7506 rows and 15 variables:

symbol

stock ticker symbol

name

stock ticker name

date

trade date

open

stock price at the open of trading

high

stock price at the highest point during trading

low

stock price at the lowest point during trading

close

stock price at the close of trading

volume

number of shares traded

amount

monetary value of shares traded

turnover

rate of shares traded over total

close_adj

adjusted stock price at the close of trading

dataset of shanghai composite index

Description

The daily historical Shanghai Composite Index

Usage

dt_ssec

Format

A data frame with 7506 rows and 15 variables:

symbol

stock ticker symbol

name

stock ticker name

date

trade date

open

stock price at the open of trading

high

stock price at the highest point during trading

low

stock price at the lowest point during trading

close

stock price at the close of trading

volume

number of shares traded

amount

monetary value of shares traded

turnover

rate of shares traded over total

close_adj

adjusted stock price at the close of trading

code list by category

Description

ed_code get the code list of country, currency, stock exchange, commodity exchange and administrative district of mainland of China.

Usage

ed_code(cate = NULL)

Arguments

Examples

## Not run: 
# specify the categories
code_list1 = ed_code(cate = c('country', 'currency'))

# interactivly return code list
code_list2 = ed_code()


## End(Not run)

query FRED economic data

Description

ed_fred provides an interface to access the economic data provided by FRED (https://fred.stlouisfed.org)

Usage

ed_fred(symbol = NULL, date_range = "10y", from = NULL,
  to = Sys.Date(), na_rm = FALSE, print_step = 1L)

Arguments

Value

a list of dataframes with columns of symbol, name, date, value, geo, unit. The geo column might be NA according to local internet connection.

Examples

dat = ed_fred(c("A191RL1A225NBEA", "GDPCA"))

symbol of FRED economic data

Description

ed_fred_symbol provides an interface to search symbols of economic data from FRED by category or keywords.

Usage

ed_fred_symbol(category = NULL, keywords = NULL, ...)

Arguments

Examples

## Not run: 
# search symbols by category
# from top categories
symbol_dt1 = ed_fred_symbol()
# specify the initial categories
symbol_dt2 = ed_fred_symbol(category = 1)

# search symbol by keywords
symbol_dt3 = ed_fred_symbol(keywords = "gdp china")


## End(Not run)

query NBS economic data

Description

ed_nbs provides an interface to query economic data from National Bureau of Statistics of China (NBS, https://www.stats.gov.cn/).

Usage

ed_nbs(symbol = NULL, freq = NULL, geo_type = NULL, subregion = NULL,
  date_range = "10y", from = NULL, to = Sys.Date(), na_rm = FALSE,
  eng = FALSE)

Arguments

Examples

## Not run: 
# query NBS data without setting any parameters
dt = ed_nbs()

# specify paratmeters
dt1 = ed_nbs(geo_type='nation', freq='quarterly', symbol='A010101')
# or using 'n'/'q' represents 'nation'/'quarterly'
dt2 = ed_nbs(geo_type='n', freq='q', symbol='A010101')


# query data in one province
dt3 = ed_nbs(geo_type='province', freq='quarterly', 
  symbol='A010101', subregion='110000')
  
# query data in all province
dt4 = ed_nbs(geo_type='province', freq='quarterly', 
  symbol='A010101', subregion='all')

## End(Not run)

subregion code of NBS economic data

Description

ed_nbs_subregion query province or city code from NBS

Usage

ed_nbs_subregion(geo_type = NULL, eng = FALSE)

Arguments

Examples

## Not run: 
# province code 
prov1 = ed_nbs_subregion(geo_type = 'province') 
# or using 'p' represents 'province'
prov2 = ed_nbs_subregion(geo_type = 'p') 

# city code in Chinese
# city = ed_nbs_subregion(geo_type = 'c', eng = FALSE) 
# city code in English
city = ed_nbs_subregion(geo_type = 'c', eng = TRUE) 

## End(Not run)

symbol of NBS economic data

Description

ed_nbs_symbol provides an interface to query symbols of economic indicators from NBS.

Usage

ed_nbs_symbol(symbol = NULL, geo_type = NULL, freq = NULL, eng = FALSE)

Arguments

Examples

# query symbol interactively
## Not run: 
sym = ed_nbs_symbol()
## End(Not run)

query bond data

Description

md_bond query bond market data from FRED and ChinaBond.

Usage

md_bond(symbol = NULL, type = "history", date_range = "3y",
  from = NULL, to = Sys.Date(), print_step = 1L, ...)

Arguments

query forex data

Description

md_forex query forex market data from FRED (history data) or sina (real data).

Usage

md_forex(symbol, type = "history", date_range = "3y", from = NULL,
  to = Sys.Date(), print_step = 1L, ...)

Arguments

Examples

## Not run: 
# history data
dtfx_hist1 = md_forex(c('usdcny', 'usdjpy'))

# real data
dtfx_real = md_forex(c('eurusd', 'usdcny', 'usdjpy'), type = 'real')


## End(Not run)

query future market data

Description

md_future query future market data from sina finance, https://finance.sina.com.cn/futuremarket/.

Usage

md_future(symbol, type = "history", date_range = "max", from = NULL,
  to = Sys.Date(), freq = "daily", print_step = 1L, ...)

Arguments

Examples

## Not run: 
# history data
df_hist = md_future(symbol = c('IF0', 'A0', 'CU0', 'CF0', 'XAU'))

# real data
df_real = md_future(symbol = c('IF0', 'A0', 'CU0', 'CF0', 'XAU'), 
                    type = 'real')

## End(Not run)

symbol of future market data

Description

md_future_symbol returns all future symbols that provided by sina finance, see details on http://vip.stock.finance.sina.com.cn/quotes_service/view/qihuohangqing.html or http://vip.stock.finance.sina.com.cn/mkt/#global_qh)

Usage

md_future_symbol(...)

Arguments

Examples

## Not run: 
sybs = md_future_symbol()

## End(Not run)

query interbank offered rate

Description

md_money query libor from FRED or shibor from chinamoney.

Usage

md_money(symbol = NULL, date_range = "3y", from = NULL,
  to = Sys.Date(), print_step = 1L)

Arguments

query chinese benchmark rates

Description

md_moneycn query benchmark rates from chinamoney.com.cn.

Usage

md_moneycn(symbol = NULL, date_range = "3y", from = NULL,
  to = Sys.Date(), print_step = 1L)

Arguments

query stock market data

Description

md_stock provides an interface to query stock or fund data.

Usage

md_stock(symbol, type = "history", date_range = "3y", from = NULL,
  to = Sys.Date(), forward = NULL, print_step = 1L, ...)

Arguments

Examples

## Not run: 
# Example I: query history data
# us
FAANG = md_stock(c('META', 'AMZN', 'AAPL', 'NFLX', 'GOOG'))

# hkex
TMX = md_stock(c('00700.hk', '03690.hk', '01810.hk'))

# sse/szse
## the symbol without suffix
dt_cn1 = md_stock(c("000001", "^000001", "512510"))
## the symbol with suffix
dt_cn2 = md_stock(c("000001.sz", "000001.ss", '512510.ss'))

             
# Example III: query real prices
# real price for equities
dt_real1 = md_stock(c('META', 'AMZN', 'AAPL', 'NFLX', 'GOOG',
                     '00700.hk', '03690.hk', '01810.hk',
                     "000001", "^000001", "512510"), type = 'real')
               
               
# query company information 
dt_info1 = md_stock('600036', type = 'info')

## End(Not run)

adjust stock prices

Description

md_stock_adjust adjusts the open, high, low and close stock prices.

Usage

md_stock_adjust(dt, forward = FALSE, ...)

Arguments

Examples

data("dt_banks")

dtadj1 = md_stock_adjust(dt_banks, adjust = FALSE)
dtadj2 = md_stock_adjust(dt_banks, adjust = TRUE)

query financial statements

Description

md_stock_financials provides an interface to query financial statements for all listed companies in SSE and SZSE by specified report date.

Usage

md_stock_financials(type = NULL, date_range = "1q", from = NULL,
  to = Sys.Date(), print_step = 1L, ...)

Arguments

Examples

## Not run: 
# interactively specify type of financial table 
dtfs1 = md_stock_financials(type="fs0_summary", to = '2022-12-31')
dtfs2 = md_stock_financials(type="fs0_summary", to = c('2022-12-31', '2023-03-31'))
dtfs3 = md_stock_financials(type="fs0_summary", from = '2022-12-31', to = Sys.Date())

# all statements
dtfs4 = md_stock_financials(type = "fs", to = '2022-12-31')

# setting column names to Chinese
dtfs5 = md_stock_financials(type="fs0_summary", to = '2022-12-31', colnam_chn = TRUE)


## End(Not run)

symbol components of exchange

Description

md_stock_symbol returns all stock symbols by exchange

Usage

md_stock_symbol(exchange = NULL, ...)

Arguments

Examples

## Not run: 
# get stock symbols in a stock exchange
## specify the exchanges
ex_syb1 = md_stock_symbol(exchange = c('sse', 'szse'))

## choose exchanges interactivly
ex_syb2 = md_stock_symbol()


## End(Not run)

symbol of market data

Description

md_stock_symbol returns all symbols by market category, including forex, money, bond, stock, future.

Usage

md_symbol(market = NULL, ...)

Arguments

Examples

## Not run: 
syblst = md_symbol()

## End(Not run)

adding technical indicators

Description

pq_addti creates technical indicators using the functions provided in TTR package.

Usage

pq_addti(dt, ...)

Arguments

Examples

# load data
data('dt_ssec')

# add technical indicators
dt_ti1 = pq_addti(dt_ssec, sma=list(n=20), sma=list(n=50), macd = list())

# specify the price column x
dt_ti11 = pq_addti(dt_ssec, sma=list(n=20, x='open'), sma=list(n=50, x='open'))
dt_ti12 = pq_addti(dt_ssec, x='open', sma=list(n=20), sma=list(n=50))

# only technical indicators
dt_ti2 = pq_addti(
  dt_ssec, sma=list(n=20), sma=list(n=50), macd = list(), 
  col_kp = c('symbol', 'name')
)

dt_ti3 = pq_addti(
  dt_ssec, sma=list(n=20), sma=list(n=50), macd = list(), 
  col_kp = NULL
)

# self-defined technical indicators
bias = function(x, n=50, maType='SMA') {
    library(TTR)
    (x/do.call(maType, list(x=x, n=n))-1)*100
}

dt_ti3 = pq_addti(dt_ssec, bias = list(n = 200))

technical functions

Description

Technical functions provided in TTR package.

Usage

pq_addti_funs()

converting frequency of daily data

Description

pq_freq convert a daily OHLC dataframe into a specified frequency.

Usage

pq_freq(dt, freq = "monthly", date_type = "eop")

Arguments

Examples

## Not run: 
data(dt_ssec)
dat1_weekly = pq_freq(dt_ssec, "weekly")

data(dt_banks)
dat2_weekly = pq_freq(dt_banks, "monthly")

## End(Not run)

dataframe operation

Description

It performs arithmetic operation on numeric columns on multiple series.

Usage

pq_opr(dt, opr, x = "close", rm_na = FALSE, ...)

Arguments

Examples

data("dt_banks")

dt1 = pq_opr(dt_banks, '601288.SH/601988.SH')
print(dt1)

dt2 = pq_opr(dt_banks, c('(601288.SH+601988.SH)/2', '(601288.SH*601988.SH)^0.5'))
print(dt2)

calculating performance metrics

Description

pq_performance calculates performance metrics based on returns of market price or portfolio. The performance analysis functions are calling from PerformanceAnalytics package, which includes many widely used performance metrics.

Usage

pq_performance(dt, Ra, Rb = NULL, perf_fun, ...)

Arguments

Examples

 
## Not run: 
library(pedquant) 
library(data.table)

# load data
data(dt_banks)
data(dt_ssec)

# calculate returns
datret1 = pq_return(dt_banks, 'close', freq = 'monthly', rcol_name = 'Ra')
datret2 = pq_return(dt_ssec, 'close', freq = 'monthly', rcol_name = 'Rb')

# merge returns of assets and baseline
datRaRb = merge(
    rbindlist(datret1)[, .(date, symbol, Ra)], 
    rbindlist(datret2)[, .(date, Rb)],
    by = 'date', all.x = TRUE
)

# claculate table.CAPM metrics
perf_capm = pq_performance(datRaRb, Ra = 'Ra', Rb = 'Rb', perf_fun = 'table.CAPM')
rbindlist(perf_capm, idcol = 'symbol')

## End(Not run)

performance functions

Description

A complete list of performance functions from PerformanceAnalytics package.

Usage

pq_performance_funs()

creating charts for time series

Description

pq_plot provides an easy way to create interactive charts for time series dataset based on predefined formats.

Usage

pq_plot(dt, chart_type = "line", x = "date", y = "close", yb = NULL,
  date_range = "max", yaxis_log = FALSE, title = NULL, addti = NULL,
  nsd_lm = NULL, markline = TRUE, orders = NULL, arrange = list(rows =
  NULL, cols = NULL), theme = "default", ...)

Arguments

Examples

# single serie
library(data.table)
library(pedquant)
data(dt_ssec)

# line chart (default)
e1 = pq_plot(dt_ssec, chart_type = 'line') # line chart (default)
e1[[1]]

# add technical indicators
e2 = pq_plot(dt_ssec, addti = list(
        sma = list(n = 200), 
        sma = list(n = 50), 
        volume = list(),
        macd = list()
))
e2[[1]]

# linear trend with yaxis in log
e3 = pq_plot(dt_ssec, nsd_lm = c(-0.8, 0, 0.8), markline=FALSE)
e3[[1]]

# multiple series
data(dt_banks)
setDT(dt_banks)
dt_banksadj = md_stock_adjust(dt_banks)

# linear trend
elist = pq_plot(dt_banksadj)
e4 = pq_plot(dt_banksadj, arrange = list(rows=1, cols=1))
e4[[1]]

# orders 
b2 = dt_banks[symbol %in% c('601988.SH', '601398.SH')]
b2orders = b2[sample(.N, 10), .(symbol, date, prices=close, 
              side=sample(c(-1, 1), 10, replace=TRUE))]
                
e5 = pq_plot(b2, orders=b2orders)
e5[[1]]

e6 = pq_plot(b2, orders=b2orders, arrange = list(rows=1, cols=1))
e6[[1]]

calculating returns/equity of portfolio

Description

pq_portfolio calculates the weighted returns or the equity of a portfolio assets.

Usage

pq_portfolio(dt, orders, x = "close", dtb = NULL, init_fund = NULL,
  method = "arithmetic", cols_keep = NULL, ...)

Arguments

Examples

library(pedquant)

data(dt_banks)
datadj = md_stock_adjust(dt_banks)


# example I 
orders = data.frame(
    symbol = c("601288.SH","601328.SH","601398.SH","601939.SH","601988.SH"), 
    quantity = c(100, 200, 300, 300, 100)
)
dtRa = pq_portfolio(datadj, orders=orders) 

e1 = pq_plot(dtRa, y = 'cumreturns')
e1[[1]]


# example II 
data(dt_ssec)
orders = data.frame(
    symbol = rep(c("601288.SH","601328.SH","601398.SH","601939.SH","601988.SH"), 3), 
    date = rep(c('2009-03-02', '2010-01-04', '2014-09-01'), each = 5), 
    quantity = rep(c(100, 200, 300, 300, 100), 3) * rep(c(1, -1, 2), each = 5)
)
dtRab = pq_portfolio(datadj, orders=orders, dtb = dt_ssec, init_fund = 10000) 

e2 = pq_plot(dtRab, y = 'cumreturns', yb = 'cumreturns_000001.SH', addti = list(portfolio=list()))
e2[[1]]


# example III
orders = data.frame(symbol = "000001.SH", 
     date = c("2009-04-13", "2010-03-24", "2014-08-13", "2015-09-10"), 
     quantity = c(400, -400, 300, -300))
dtRa2 = pq_portfolio(dt_ssec, orders=orders, cols_keep = 'all')

e3 = pq_plot(dtRa2, y = 'close', addti = list(cumreturns=list(), portfolio=list()))
e3[[1]]

calculating returns by frequency

Description

pq_return calculates returns for daily series based on specified column, frequency and method type.

Usage

pq_return(dt, x, freq = "daily", n = 1, date_type = "eop",
  method = "arithmetic", cumreturns = FALSE, rcol_name = NULL,
  cols_keep = NULL, date_range = "max", from = NULL, to = Sys.Date(),
  ...)

Arguments

Examples

# load data and adjust
data(dt_banks)
datadj = md_stock_adjust(dt_banks)

# set freq
dts_returns1 = pq_return(datadj, x = 'close_adj', freq = 'all')

# set method
dts_returns2 = pq_return(datadj, x = 'close_adj', method = 'log')

# set cols_keep
dts_returns3 = pq_return(datadj, x = 'close_adj', cols_keep = 'cap_total')

# cumulative returns
dts_cumreturns = pq_return(datadj, x = 'close_adj', from = '2012-01-01', cumreturns = TRUE)
e1 = pq_plot(dts_cumreturns, y = 'cumreturns.daily', title='cumreturns', 
        arrange = list(rows=1, cols=1))
e1[[1]]