Trading and Rebalancing Financial Instruments

Description

The Rmetrics "fTrading" package is a collection of functions for trading and rebalancing financial instruments.

Details

Content

Utility Functions:

    emaTA           Exponential Moving Average
    biasTA          Bias Indicator
    medpriceTA      Medium Price Indicator
    typicalpriceTA  Typical Price Indicator
    wcloseTA        Weighted Close Indicator
    rocTA           Rate of Change
    oscTA           Oscillator Indicator
    

Oscillator Indicators:

    momTA           Momentum Indicator
    macdTA          MACD Indicator
    cdsTA           MACD Signal Line
    cdoTA           MACD Oscillator
    vohlTA          High/Low Volatility
    vorTA           Volatility Ratio
    

    stochasticTA    Stochastics Oscillator
    fpkTA           Fast Percent K
    fpdTA           Fast Percent D
    spdTA           Slow Percent D
    apdTA           Averaged Percent D
    wprTA           William's Percent R
    rsiTA           Relative Strength Index
    

S-Plus Like Moving Averages:

    SMA             Simple Moving Average
    EWMA            Exponentially Weighted  Moving Average
    

About Rmetrics:

The fTrading Rmetrics package is written for educational support in teaching "Computational Finance and Financial Engineering" and licensed under the GPL.

Utilities and Benchmark Analysis

Description

A collection and description of utility and benchmark functions for the analysis of financial markets. The collection provides a set of functions for the computation of returns, for the display of price charts, and for benchmark measurements.

The functions are:

Usage

ohlcPlot(x, xlim = NULL, ylim = NULL, xlab = "Time", ylab, col = par("col"),
    bg = par("bg"), axes = TRUE, frame.plot = axes, ann = par("ann"),
    main = NULL, date = c("calendar", "julian"), format = "%Y-%m-%d",
    origin = "1899-12-30", ...)
    
sharpeRatio(x, r = 0, scale = sqrt(250))
sterlingRatio(x)

maxDrawDown(x)

Arguments

Details

Open–High–Low–Close Chart:

Within an open–high–low–close bar chart, each bar represents price information for the time interval between the open and the close price. The left tick for each bar indicates the open price for the time interval. The right tick indicates the closing price for the time interval. The vertical length of the bar represents the price range for the time interval. The time scale of x must be in Julian dates (days since the origin).
[tseries:plotOHLC]

Sharpe and Sterling Ratios:

The Sharpe ratio is defined as a portfolio's mean return in excess of the riskless return divided by the portfolio's standard deviation. In finance the Sharpe Ratio represents a measure of the portfolio's risk-adjusted (excess) return. The Sterling ratio is defined as a portfolio's overall return divided by the portfolio's maximum drawdown statistic. In finance the Sterling Ratio represents a measure of the portfolio's risk-adjusted return.
[tseries:sharpe]

Maximum Drawdown:

The maximum drawdown or maximum loss statistic is defined as the maximum value drop after one of the peaks of x. For financial instruments the maximum drawdown represents the worst investment loss for a buy–and–hold strategy invested in x.
[tseries:maxdrawdown]

Get Returns:

The function computes the return series given a financial security price series. The price series may be an object of class numeric or a time series object. This includes objects of classes "ts", "its" and/or "timeSeries".

Value

ohlcPlot
creates an Open–High–Low–Close chart.

sharpeRatio
sterlingRatio
return the Sharpe or Sterling ratio, a numeric value.

maxDrawDown
returns a list containing the following three components: maxDrawDown, double representing the max drawdown or max loss statistic; from, the index (or vector of indices) where the maximum drawdown period starts; to, the index (or vector of indices) where the max drawdown period ends.

Author(s)

Adrian Trapletti for the ohlcPlot,*Ratio and maxDrawDown functions,
Diethelm Wuertz for the Rmetrics R-port.

Examples

## ohlcPlot -
   # Plot OHLC for SP500
   # ohlcPlot(x, ylab = "price", main = instrument)
   
## sharpeRatio -
   # Sharpe Ratio for DAX and FTSE:
   data(EuStockMarkets)
   dax = log(EuStockMarkets[, "DAX"])
   ftse = log(EuStockMarkets[, "FTSE"])
   # Ratios:
   sharpeRatio(dax)
   sharpeRatio(ftse)
   
## maxDrawDown -
   data(EuStockMarkets)
   dax = log(EuStockMarkets[, "DAX"])
   mdd = maxDrawDown(dax)
   mdd
   # Plot DAX:
   plot(dax)
   grid()
   segments(time(dax)[mdd$from], dax[mdd$from],
     time(dax)[mdd$to], dax[mdd$from])
   segments(time(dax)[mdd$from], dax[mdd$to],
     time(dax)[mdd$to], dax[mdd$to])
   mid = time(dax)[(mdd$from + mdd$to)/2]
   arrows(mid, dax[mdd$from], mid, dax[mdd$to], col = 2)
   title(main = "DAX: Max Drawdown")

Rolling Analysis

Description

A collection and description of functions to perform a rolling analysis. A rolling analysis is often required in building trading models.

The functions are:

Usage

rollFun(x, n, trim = TRUE, na.rm = FALSE, FUN, ...)
rollVar(x, n = 9, trim = TRUE, unbiased = TRUE, na.rm = FALSE)

Arguments

Value

The functions return a timeSeries object or a numeric vector, depending on the argument x.

rollMax returns the rolling sample maximum,
rollMin returns the rolling sample minimum,
rollMean returns the rolling sample mean, and
rollVar returns the biased/unbiased rolling sample variance.

Note, that the function rollFun always returns a numeric vector, independent of the argument x.

If you like to operate for x with rectangular objects, you have to call the functions columnwise within a loop.

Author(s)

Diethelm Wuertz for the Rmetrics R-port.

See Also

var.

Examples

## Rolling Analysis:
   x = (1:10)^2
   x
   trim =  c(TRUE, TRUE, FALSE, FALSE)
   na.rm = c(TRUE, FALSE, TRUE, FALSE)
   for (i in 1:4)
     rollFun(x, 5, trim[i], na.rm[i], FUN = min)
   for (i in 1:4)
     rollFun(x, 5, trim[i], na.rm[i], FUN = max)
   for (i in 1:4)
     rollVar(x, 5, trim[i], unbiased = TRUE, na.rm[i])
   for (i in 1:4)
     rollVar(x, 5, trim[i], unbiased = FALSE, na.rm[i])

Tools for the Technical Analysis

Description

A collection and description of functions for the technical analysis of stock markets. The collection provides a set of the most common technical indicators.

Utility Functions:

Oscillator Indicators:

S-Plus Like Moving Averages:

Usage

emaTA(x, lambda, startup = 0)
biasTA(x, lag)
medpriceTA(high, low)
typicalpriceTA(high, low, close)
wcloseTA(high, low, close)
rocTA(x, lag)
oscTA(x, lag1 = 25, lag2 = 65)

momTA(x, lag)
macdTA(x, lag1, lag2)
cdsTA(x, lag1 = 12, lag2 = 26, lag3 = 9)
cdoTA(x, lag1 = 12, lag2 = 26, lag3 = 9)
vohlTA(high, low)
vorTA(high, low)

stochasticTA(close, high, low, lag1 = 5, lag2 = 3, lag3 = 5, 
    type = c("fast", "slow")) 
fpkTA(close, high, low, lag)
fpdTA(close, high, low, lag1, lag2)
spdTA(close, high, low, lag1, lag2, lag3)
apdTA(close, high, low, lag1, lag2, lag3, lag4)
wprTA(close, high, low, lag)
rsiTA(close, lag)

SMA(x, n = 5)
EWMA(x, lambda, startup = 0)

Arguments

Value

*TA
The technical Indicators return the following numeric vectors (or matrix):

emaTA returns the Exponential Moving Average, EMA
biasTA returns the EMA-Bias,
medpriceTA returns the Medium Price,
typicalpriceTA returns the Typical Price,
wcloseTA returns the Weighted Closing Price,
rocTA returns the Rate of Change Indicator,
oscTA returns the EMA Oscillator Indicator,
momTA returns the Momentum Oscillator,

macdTA returns the MACD Oscillator,
cdsTA returns the MACD Signal Line,
cdo returns the MACD Oscillator,
vohlTA returns the High/Low Volatility Oscillator,
vorTA returns Volatility Ratio Oscillator,

stochasticTA returns a 2-column matrix with percent K and D Indicator,
fpkTA returns the Fast Percent-K Stochastics Indicator,
fpdTA returns the Fast Percent-D Stochastics Indicator,
spdTA returns the Slow Percent-D Stochastics Indicator,
apdTA returns the Averaged Percent-D Stochastics Indicator,
wprTA returns the Williams Percent-R Stochastics Indicator,
rsiTA returns the Relative Strength Index Stochastics Indicator.

Author(s)

Diethelm Wuertz for the Rmetrics R-port.

Examples

## data -
   # Load MSFT Data:
   x = MSFT
   colnames(x)
   x = x[, "Close"]
   head(x)
   
## emaTA -
   # Exponential Moving Average:
   y = emaTA(x, lambda = 9)   
   seriesPlot(x)
   lines(y, col = "red")