milktrader

# this is the data set that will be used
# note: Cl is simply OHLC["Close"]

julia> OHLC
16103x6 TimeArray{Float64,2} 1950-01-03 to 2013-12-31

             Open     High     Low      Close    Volume          Adj Close
1950-01-03 | 16.66    16.66    16.66    16.66    1.26e6          16.66
1950-01-04 | 16.85    16.85    16.85    16.85    1.89e6          16.85
1950-01-05 | 16.93    16.93    16.93    16.93    2.55e6          16.93

milktrader

505x3 MarketSignal 1980-01-03 to 1981-12-31

             signal  supersignal  sig
1980-01-03 | false   true         true
1980-01-04 | true    false        true
1980-01-07 | true    false        true
1980-01-08 | true    false        true
⋮
1981-12-28 | false   true         true
1981-12-29 | false   true         true

milktrader

julia> @> Cl sma(50) x->merge(x,sma(Cl,200)) x->x["sma50"] .> x["sma200"] discretesignal
65x1 TimeArray{Int64,1} 1950-10-18 to 2012-01-31

             signals
1950-10-18 | 1.0
1953-05-11 | 0.0
1953-12-21 | 1.0
1956-10-26 | 0.0
⋮
2010-07-02 | 0.0

milktrader

function macd{T}(ta::TimeArray{T,1}, fast::Int, slow::Int, signal::Int)
 
  fastma = ema(ta, fast)
  slowma = ema(ta, slow)
  mcdval = fastma - slowma
  sigval = ema(mcdval, signal)

  merge(mcdval, sigval, ["macd", "signal"])
end

milktrader

julia> using TimeSeries, MarketTechnicals, MarketData, Lazy

julia> @> OHLC doji findall x->OHLC[x] x->x.timestamp
166-element Array{Date{ISOCalendar},1}:
 1962-03-02
 1962-04-13
 1962-07-16
 1962-10-08
 1963-02-08
 1963-05-22

milktrader

julia> using TradeModels, MarketData

julia>  @long cl rsi (.>) 50 nextday op

0.3999243140318183

milktrader

julia> using Series, MarketData, FactCheck

julia> @time fast = fastmoving(Cl, mean, 60);
elapsed time: 0.305857977 seconds (72646744 bytes allocated)

julia> @time slow = moving(Cl, mean, 60);
elapsed time: 4.925385985 seconds (2079575504 bytes allocated)

julia> @fact fast[end].value => roughly(slow[end].value)
Success :: :(fast[end].value) => :(roughly(slow[end].value))

milktrader

julia> using Series, MarketData, Lazy

julia> d1 = date(1999,1,1);

julia> d2 = date(1999,2,15);

julia> @> Op percentchange x->x[[d1:d2]] value sum expm1
0.017947448312809502

milktrader

julia> using Lazy, Series, MarketData

julia> head(cl)
1-element Array{SeriesPair{Date{ISOCalendar},Float64},1}:
 1980-01-03  105.220

julia> @> cl value log diff cumsum expm1 x -> x+1 x -> x[size(x,1)]
1.1647025280364955

milktrader

julia> plot(cumsum(value(when(lead(percentchange(Op, method="log"), 2), index(istrue(sma(Cl,10) .> sma(Cl,30)))))))