 Hey guys, welcome back to the Amplify Trading YouTube channel. My name is Milindy Basi, and I'm a technology analyst for Amplify Trading. In today's video, we're going to be looking at algorithmic versus discretionary trading. What are the pros and cons of each, and is there a reason someone might choose to be an algorithmic or discretionary trader? Is one better than the other? These are the kind of questions we'll be answering in today's video. So as usual, guys, please do like and subscribe down below to stay up to date with the latest content from Amplify Trading, relating to markets every day, every morning, straight into your inbox. So do hit that bell button to stay up to date. Algorithmic trading is all about traders who use algorithms, machine learning, AI, or anything like that to make trading decisions for them. They have systems in place that usually have a fixed set of rules, or in the case of machine learning or AI, adapt to market conditions to decide what is the best trade or plan for the day. These rules will then allow the system to trigger a short or long position, so that basically means to either buy or sell. These algorithmic trading systems will then also automatically exit the position normally, either at a take profit or a target price determined by the algorithm. In the scenario of algorithmic trading, what usually happens is the trader isn't making decisions. Instead, the trader is actually monitoring the system to make sure there are no malfunctions or unexpected trades being placed. Algorithmic trading, on the other hand, is all about a trader who makes decisions live in markets real time. This trader may have a set of rules that they've determined themselves, a strategy if you must, and they usually stick to this or at least try to. A set of rules that they stick to are then used to make the decisions of if they should enter long or short. And unlike algorithmic trading, these rules might be a bit loose, so they often are changed to fit market conditions, depending on if we're having a volatile or non-volatile day. Discretionary trading at the end of it is usually based around signals, so this can be from your technical analysis or a signal maybe in the form of any fundamental news that comes out, like a drawdown or a buildup in weekly oil inventories. So let's look at the most obvious downside with discretionary traders. The big one that everyone always thinks of the first time they compare discretionary versus algorithmic trading, emotions. With emotions, as you can see in the last like 30 seconds or whatever, I've gone all over the place with my emotions as well, and that can happen in trading easily. You can easily go from being a calm, logical person to being completely irrational and doing things that you wouldn't normally do. The impact of human emotions is something everyone always deals with, so it's not like it's a unique case for some discretionary traders. Human emotions is a part of life, and it's something that every trader must overcome to become a successful one usually. As with anything, human emotions can actually lead to the trader becoming irrational and prone to more errors. This is obviously not an issue in algorithmic trading, where a computer system that usually takes in strict, fixed rules doesn't have to deal with these emotions. They usually either take the signal, go long or short, and they aren't phased by anything if that happens in the news or anything like that. This mathematical model that might be adapted by algorithmic traders also allows for the system to avoid any emotions such as fear or greed. This means that when there is a take profit at, say, 20 or 30 ticks, well, that take profit will always be hit at 20 or 30 ticks. This algorithmic trading bot may not, unlike a human trader, get greedy and move this take profit higher and higher to the point where markets never reach there, and next thing you know, they're not making as much as they potentially could have. Likewise, the opposite happens. A algorithmic trading bot might have a target at 50 ticks or something like that, and the human trader actually feels fear and takes out this position a lot earlier. So building on that, discretionary traders may have the potential to close positions earlier. They may let their losers run longer they need to, and let the winners actually run really short. As a human making many decisions in a few seconds, or even a couple of minutes, or even an hour, these decisions that are based around your trades can be a lot of overwhelming thoughts, and eventually can lead to a lot of confusion. As a result, algorithmic trading actually stands out here incredibly well. There is defined risk, and you know what you're getting into when you get into a trade. The algorithm takes all the decision making away from the trader. Okay, so I said a lot of things hating on discretionary traders, but it's not all doom and gloom for discretionary traders. There's actually a lot of benefits. One of the key benefits discretionary traders have over algorithmic traders is that they're able to adapt to market conditions a lot faster and a lot quicker than an algorithm can. You know, if Donald Trump tweets something, the algorithm might not even be looking at that at all, while a discretionary trader may hear this in the news or through a squawk. And the next thing you know, they'll be able to adapt their trading style to whatever's happening in markets instantly. And, you know, that all sounds good in theory. And the best thing is this actually happened this year. During March, we found that a lot of quant hedge funds actually performed a lot worse than the traditional counterparts. According to a numerous strategists, actually what we found was 17% of all quant funds actually outperformed the benchmarks compared to traditional funds. With the fundamental driven funds or traditional funds, as you want to call them, we actually found that more than half of all of those actually outperformed the benchmark during the sell-off in March. So algorithmic versus discretionary trading. There's a lot of benefits and a lot of cons. One system might not work all the time, and there's a reason that we still have discretionary traders to this day. Even though algorithms might seem like the future, I feel personally there's always going to be a space for discretionary traders. There are a few other things to look at as well with discretionary versus algorithmic trading. Algorithmic traders have a lot higher skill set required, I guess, in terms of developing algorithms, understanding programming, while also understanding how markets work. I don't think that an algorithmic trader can create the correct algorithm to trade in markets without a good understanding of how financial markets operate. And this can only be really achieved from being a discretionary trader first. Understanding firsthand in real time, what is it like to trade? What kind of thoughts and decisions might a discretionary trader actually have? And then these can be later applied to algorithmic trading. While on the other hand, a discretionary trader actually might be someone who is very in tone with their emotions and actually able to control them very well. Being able to understand why you're thinking in a certain way and being able to reflect these changes in your trading without going out of control and not really becoming irrational is something that might make a discretionary trader actually outperform and excel. And these are the skills that you might be looking at when deciding, am I an algorithmic or discretionary trader? Do you have all the skills required in the time to develop an algorithmic trading system? Or are you someone who's actually very at tone with their emotions or the decision-making process in having quick reactions to what markets are doing to the point where you can also be a discretionary trader? So just to fire through the pros and cons again for algorithmic training. Well, algorithmic training pros, I guess, there is no emotional impact as the machine listens to a set fixed rules. There was also fixed position and risk management. The machine is told to do X number of trades or go X number of ticks before exiting a position while a human trader might not necessarily stick to these rules exactly. Some of the cons with algorithmic trading, well, obviously you need a very high skill set. You need to be able to understand financial markets, be able to code and most of all, you need to have the high maintenance availability. You can't just let this algorithmic trading bot go into the wild and just trade without you not looking at it. You need to be able to be there to monitor it and fix any faults that may occur during a trading session. Algorithmic trading is also slow to adapt to Black Swan events. So like March in our example, these algorithms and systems aren't designed for that and they cannot predict the future. And as a result of being unable to adapt very fast, they actually lag behind the discretionary counterpart. So what are the benefits of a discretionary trader? Well, like I said, they're able to adapt to these Black Swan events. March was a time where in my opinion, algorithms went out the window and it was much more down to how were people feeling, what was the current sentiment in the market. And as a result there, you would have excelled rather than an algorithm that would have been looking at just numbers. On top of that, a discretionary trader is actually able to adapt to market conditions live and real-time. And that gives you that edge of knowing and being able to respond to events happening in real-time that an algorithm might not be able to do. Well, a basic one anyways. What are the cons of a discretionary trader? Well, the biggest outlying one is the emotional impact of trading, the irrationality and the ability to potentially go off the rails, I guess, when a trade goes sideways. There is obviously also the potential poor trade management. So this includes entries, getting out of positions, letting your losers run and your winners cutting them short. These are all the things that could potentially prohibit and make a discretionary trader perform worse than the algorithmic counterpart. So guys, thank you for watching this video. I know it was a very quick one, but we were just looking at algorithmic versus discretionary trading. If you're interested in algorithmic trading or discretionary trading, please do check out the services provided by Amplified Trading. In the algorithmic side, since that's where I specialize, well, we have a algorithmic trading simulation. And this simulation is run for students. We've run it all summer for the students in the Amplified Trading internship. And what we do in the simulation is use Python to back test three stocks with a simple moving average strategy. And in the space of one day, you should be able to have a good understanding of the fundamentals of Python and be able to actually have something to show at the end of it with a benchmark and a graph showing how your algorithm has performed in a one year period. So if that is something that interests you, please do check the description for a link to the Amplified Trading website where you'll be able to find out more about the algorithmic trading simulation. Likewise, for anyone interested in discretionary trading, please do check out the Amplified Trading website for the trader program. Or if you have any questions about discretionary or algorithmic trading, please do feel free to comment down below while you're down there, please do subscribe as well. And I'll be in the comments for the first few hours, at least anyways, replying to any questions you guys might have. So as usual, everyone, thank you very much for watching this video. I hope you've learned something today. And if you have likewise again, please do let me know in the comments down below. And as usual, everyone, please stay safe and have a great one.