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How I Made a 65% ROI with this Boeing Trading Algorithm

by Aaron DeckerJune 10th, 2021

Too Long; Didn't Read

Since the market crashed in March of 2020 the rebound has been swift and irrational. Since the end of March you can just buy every dip and expect a pop, selling the next day. This simple system returned a whopping 65% in two-ish months. The code below is everything you need to try this out. This is not investment advice, nor am I suggesting you actually do this. Nothing in this article constitutes professional investment advice. Please do your own research before making and investment decisions.

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featured image - How I Made a 65% ROI with this Boeing Trading Algorithm

Since the market crashed in March of 2020 the rebound has been swift and irrational.

Boeing, for example, is in many ways worse off than it was in March.
It’s clear air travel has plummeted and that airlines will be impacted for
years. Where will airlines get the money to purchase planes?

An example of one headline in April: .

Buy the dip?

One thing I’ve noticed is that since the end of March you can
basically just buy every dip and expect a pop, selling the next day. I
mentioned this to a friend on Friday and decided to backtest it.

Well, sure enough it works!

I’ll mention I made one modification. Originally I wrote the system like so:

1. Check if Boeing is down more than 3% 15 minutes from close
2. If yes, buy with 100% of portfolio
3. The next day, 15 minutes from open liquidate the portfolio.

This worked OK. Great actually! It returned about 25%. But want to know what really kicked it up a notch?

Instead of just selling the next day, I only sell if the position is
sitting at a realized gain. So e.g. if the next day its flat or drops
another 1%, don’t sell it, just keep holding on until its up and THEN
sell. Of course, this is completely insane and you would have to expect
the market to only go up, but that’s what has been happening.

Guess what? This simple system returned a whopping 65% in two-ish months. Yeah, I know, crazy.

Check out the backtest screenshot:

And here are the raw trading logs for those that want to see the dates the trades were made:

Here is the code!

Before we look at the code, I'll just mention here are the details of the backtest:

- start with 100k in cash
- start at April first and go until last Friday (June 19th 2020)
- end up with about 165k or a 65% return.

I wrote this little script on Quant Connect. The screenshot at the
top of the page is the backtest result, and the code below is everything you need to try this out.

Note the place I mentioned in the code you should comment if you want this to be a little bit less insane.

class BasicTemplateAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020,4,1)  #Set Start Date
        self.SetEndDate(2020,6,12)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash
        self.SetWarmUp(0)
        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage)

        self.AddEquity("SPY", Resolution.Minute)
        self.SetBenchmark("SPY")

        self.targetSymbol = "BA"
        self.openPrice = 0
        self.downPctTrigger = -0.03

        self.AddEquity(self.targetSymbol, Resolution.Minute, Market.USA, True, 1.0)

        self.Schedule.On(self.DateRules.EveryDay(self.targetSymbol), self.TimeRules.AfterMarketOpen(self.targetSymbol, 1), Action(self.onMarketOpen))
        self.Schedule.On(self.DateRules.EveryDay(self.targetSymbol), self.TimeRules.AfterMarketOpen(self.targetSymbol, 15), Action(self.sellItIfHeld))
        self.Schedule.On(self.DateRules.EveryDay(self.targetSymbol), self.TimeRules.BeforeMarketClose(self.targetSymbol, 15), Action(self.buyIfDown))


    def OnData(self, data):
        pass

    def onMarketOpen(self):
        self.openPrice = self.Securities[self.targetSymbol].Open

    def buyIfDown(self):
        currPrice = self.Securities[self.targetSymbol].Price
        openPrice = self.openPrice

        # e.g. (95 - 100) / 100 = -0.05
        pctDiff = (currPrice - openPrice) / openPrice

        # if gt than loss of x
        if pctDiff < self.downPctTrigger:
            self.Debug("Buying at: " + str(currPrice) + " pct down: " + str(pctDiff))
            self.SetHoldings(self.targetSymbol, 1.0)


    def sellItIfHeld(self):
        if self.Portfolio[self.targetSymbol].Quantity > 0:

            # just making this easy to comment out
            # this is the logic that says only sell if you are sitting on a profit
            # otherwise, we just keep holding until the price moves up
            if self.Portfolio[self.targetSymbol].UnrealizedProfit < 0:
                return

            currPrice = self.Securities[self.targetSymbol].Price
            self.Debug("Selling at: " + str(currPrice))
            self.Liquidate(self.targetSymbol)

Obligatory warning and disclaimer

Try the backtest yourself.

And, by the way, I’m just talking about running the backtest. This is not investment advice, nor am I suggesting you actually do this. Nothing in this article constitutes professional investment advice. Please do your own research before making and investment decisions.

There are obvious risks with this, e.g. one day Boeing could just declare bankruptcy and the price goes down and never recovers. This is for
informational purposes only.

And of course, feel free to shoot me an email if want to talk about trading or algorithm ideas!

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