Have you heard of Algo Trading?

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Computers are taking over our jobs and pretty soon, they’ll be taking over our place as significant others but MOST IMPORTANTLY, they’ll be taking over our stock portfolios.


"Common consensus is that by 2030, tens of millions of jobs will be taken over by automation."


Algorithmic trading…what is it? It’s actually nothing new and it’s been around for a long time now. An algorithm is defined as a set of instructions designed to accomplish an end goal. If you’ve ever traded in the stock market, stop losses, limit buying and selling, and stop limits are very basic, primitive forms of this.



You basically tell your brokerage that if X happens, I want you to do something with my money or my shares. For example, I can instruct my brokerage to sell 1000 shares of TSLA if it drops to 5% of its current value. So in essence, there’s a CONDITIONAL (a form of IF THIS THEN THAT) that needs to be satisfied before something happens in your account. Some brokerages don’t go beyond your conventional stop/limit type of automated triggers.


More sophisticated forms of what we just talked about would be to trigger a buy or sell if a COMBINATION of conditions are satisfied. For example, I may only want to buy or sell if the price moves to a certain level ALONG WITH other technical indicators (like RSI, or MACD) to fine tune my moves. This takes algorithmic trading to a whole new level because now, we’re allowing computers to do statistical analysis using different indicators to help with decision making. Such algorithms would look at volatility, moving averages and volume to decide not only which stock positions to open, but which options positions could result in maximized profits.



Chaining conditions is also a strategy traders may make to ensure that they maximize the amount of returns or minimize the amount of loss. For example, let’s say I wanted to buy 10 shares of XYZ for $100 once it hits a certain price using a limit buy; it’s currently trading at $105 but I don’t want to buy it at that price. However, I believe it’s going to close higher within the day. XYZ is also extremely volatile and I don’t plan to hold onto it past a day; I want to exit once it increases 3% higher. The “algorithm” would essentially look like this:


  1. Buy XYZ once it dips to $100 per share (limit buy)

  2. Sell XYZ once it hits $103 per share (limit sell)


This type of strategy is known as an OTO or “one-triggers-other” order. In the above example, once order 1 is fulfilled, order 2 is triggered and pending. You can see how this takes away a part of the process of having to manually observe your positions and make a move once a condition is satisfied

But what if I held a more defensive position, where I have a stop order setup for some 100 shares of a company that I own where if it drops by a certain dollar amount I then cash out? Let’s say in this scenario, while I have the stop loss position already pending, I also want to sell if the shares go up at a profit. I’ll have to cancel my stop loss if my limit sell is triggered. This is known as a OCO or “one-cancels-other” order.


Now you might be thinking, what if I want to open a position, and then set both a stop loss and a limit sell? In other words,


  1. Buy XYZ once it dips to $100 per share (limit buy)

  2. Sell XYZ if it hits $ 103 per share (limit sell)

  3. Sell XYZ if it drops to $98 per share (stop loss)


You can set up what’s known as a OTOCO, or a “one-triggers-order-cancels-other”. Quite wordy, but what this means is once I buy the shares, I’m going to set both a sell limit and a stop loss on the entire position, where if one of the other orders trigger, the remaining order is cancelled.


Again, you see how this can potentially remove a good deal of the human element from making snap decisions. You create a system or a strategy revolved around rigid guidelines and lose the part of the decision making that can sometimes be detrimental to your profits. You’re still making decisions ultimately, but you’re not making SNAP decisions or off the cuff ones. Reactionary decision making is typically what results in a bad situation or outcome. It lets computers handle the work for you while you essentially “set it and forget it”. You in essence eliminate the potential for:


  1. Panic buying/selling

  2. Taking a greed-motivated position

  3. Taking a speculative position


Let’s take this a step further and delve deeper into how this would work at a larger scope where organizations are. Larger organizations/institutions have much more sophisticated algorithms set up by software engineers to conditionally execute trades based on risk tolerance, probability, and other guidelines that are just as rigid if not more so. Think about it, if there are investment analysts who crunch numbers and make decisions for positions based on their analysis day in and day out, how easy is it to just take their set of guidelines/rubric for what makes a viable or worthy trade and just put it through a computer instead? The computer would make calculations much faster than the person and also execute trades in the blink of an eye. These algorithmic triggers are designed to rake in profits once conditions are satisfied, or enact mass-buying if the opposite condition is satisfied. Hedge fund managers with consistently winning strategies would no longer need a team of analysts to make sure their strategy is properly executed.


And if you want to take this another step further, I’m sure you’ve already thought by now: “Well who needs hedge fund managers when I can have a computer test my algorithm and then run with the best ones?” If you're a coder yourself, you can easily design your own strategies and run it live against a brokerage that allows trading through code. Using machine learning, you can even have your algorithms adapt to changes even beyond the markets.


Now before you panic, know that it’s good to have some form of “algorithm” when trading. Keep in mind that when I say “algorithm”, I really mean strategies where once certain conditions are satisfied, you take action. You don’t necessarily have to learn how to code to execute money-making strategies. If you haven’t checked out one of my other videos, I cover a basic form of “algorithm” in buying long term positions when the company you’re looking to invest in, increases by about 5%. It’s a real no-brainer and doesn’t require complex calculations to put through a computer; all it requires is discipline and understanding of how the market moves. So take a peek if you haven’t done so already.



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