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Idea Generation

Another, perhaps more standard, way to try and come up with new strategies before implementing them as a system is to manipulate data in TimeArrays. Due to the way that the BackTester tries to mimic a true trading situation, it sacrifices a bit of outright speed. This may be fine in most cases, but for true big data it is often faster to work with a TimeArray. Most of this functionality is present in the brilliant TimeSeries and MarketTechnicals packages.

We here discuss the [slow fast](@ref slow_fast_id) again from this point of view.

Slow Fast with TimeArrays

As usual, we define a [Broker](@ref Brokers), and proceed with acquiring the historical data with bars.

using Trading#hide
using Plots#hide
using MarketTechnicals

broker = AlpacaBroker(ENV["ALPACA_KEY_ID"], ENV["ALPACA_SECRET"])

start_day = DateTime("2015-01-01T00:00:00")
stop_day  = DateTime("2020-01-01T00:00:00")
full_bars = bars(broker, Stock("AAPL"), start_day, stop_day, timeframe=Day(1))
df        = rename(merge(full_bars[:c], full_bars[:o]), [:AAPL_Close, :AAPL_Open])

Next, we calculate the two moving averages that we will use in our strategy:

sma_ta = merge(sma(df, 20), sma(df, 120))

To find crossovers we do:

diffs  = rename(sma_ta[:AAPL_Close_sma_20] .- sma_ta[:AAPL_Close_sma_120], :diff)
signal = TimeArray(timestamp(diffs), zeros(length(diffs)), [:signal])
diffs  = merge(diffs, rename(sign.(diffs), :sign), rename(sign.(lag(diffs,1)), :lagged_sign), signal)

diffs = map(diffs) do timestamp, vals
    if vals[2] != vals[3]
        if vals[1] < 0
            vals[4] = 1
        elseif vals[1] > 0
            vals[4] = -1
        end
    end
    return timestamp, vals
end
diffs[diffs[:signal] .!= 0]

Then we fill in our positions and cash balance, and calculate the total position value:

signal   = lag(diffs[:signal], 1) # because we buy at open next period
position       = rename(cumsum(signal), :position)
position_value = rename(df[:AAPL_Close] .* position, :position_value)
cash           = rename(cumsum(signal .* -1 .* df[:AAPL_Open]), :cash)
total = rename(cash .+ position_value, :total)
df = merge(df, position_value, cash, total)

plot([df[:AAPL_Close] df[:total]])

We find similar horrible results as in [slow fast](@ref slow_fast_id) before.