High Frequency Trading (HFTs): Explained

[Music] this is the New York Stock Exchange the largest and most liquid securities market in the world here is where a good portion of the world's largest companies have their stocks traded amongst millions of investors worldwide ranging from small individual investors to major banks and financial institutions and even entire countries through things like sovereign wealth funds this is not the only exchange there are hundreds of similar exchanges around the world that work to raise capital for productive corporations that will design and build the products of the future classic imagery of loud bombastic traders in bright uniforms tends to be the images that come to mind when we think of these kinds of exchanges but the reality today is that most of the action on Wall Street looks like this the age of automated trading machines is upon us most trading today is happening to from and between computers that all have very clever programs to consistently and reliably invest into the stock market better than a human could these computer programs come in all shapes and sizes but the most controversial amongst all of these are high-frequency trading algorithms these machines trade hundreds of thousands of times a second making tiny little slivers of profit over a very tiny sliver of time these machines have been very profitable for a lot of firms that have properly employed this technology but it has to be asked what are the lasting consequences of these types of systems we have effectively handed control over the most important markets in all of our economies around the world to machines that are basically just playing robot wars with each other in this video we will look at the many weird and wonderful ways that algorithms use lightning speed to get an edge over the average participant in these markets and then assess the many weird and wonderful ways this can all go wrong there is an old legend about the Battle of Waterloo but a Nathan Mayer Ross field of the Rothschild banking family had Scouts at the Battle of Waterloo as soon as the battle was over in the bridge were decidedly victorious this scout raced back to London to be the first to deliver the news to Nathan Ross shield himself upon learning of the British victory Nathan knew that British government war bonds would spike in value so in a cunning attempt to take advantage of this he very openly and very publicly started selling off his British government war bonds this sent the market into panic and the British government bonds plummeted in the few hours before sir Wellington could arrive to deliver the true story in secret Nathan Ross shield ordered his agents to buy up these war bonds for pennies on the pound and by the time Wellington did arrive to announce the kingdoms glorious victory over Napoleon forces Nathan had bought up thousands of these government war bonds on the cheap and reaped the massive rewards of the ensuing price spike now this story is actually not true it's a fun little piece of storytelling but most historians today realized that Lord bethis was the first person to deliver the news to London and no such securities manipulation actually took place what does show though is the power of speed in information had Nathan actually had the fastest horse and ship to deliver the news it is very likely that such a scheme could have actually been pulled off the same is true today whoever gets access to information first has a huge advantage in speculative markets the logical extent of this is getting information from insiders in a company before it is released to the general public if you had a friend who worked in the accounting department of Goldman Sachs let's say and they told you that their quarterly earnings report we're going to show huge profits you could then go and buy up that stock wait for the report to be released and massively increase the demand for that stock and then sell at a higher price unfortunately this whole scheme has a name it's called insider trading and it is super illegal like even rich white people go to jail for it levels of illegal what low-latency news bots attempt to do is effectively the same thing adjust in a slightly more legal way say Bloomberg releases a report detailing huge fraudulent activity within a company if that kind of report gets released it tends to create a mass sell-off of the stock all of these people selling increases the supply the stock in the open market and hence reduces the price the average human could take five or so minutes to read the average Bloomberg article digest the information and then decide on how to trade stocks based on that information low latency news BOTS do it in a fraction of a second low latency or high frequency trading bots will scan articles business reports and even tweets to detect positive and negative words these algorithms assign a positive or negative value to words like fraud growth losses layoffs profits sue and scan these articles for the overall weighting of goodness or badness of the news and then either buy or short the stock almost instantly before regular readers have had a chance to react if an article is written about say Johnson & Johnson and is filled with words like cancer allegation class action greed called cover-up and plaintiffs an automated system is going to basically say oh yeah that's bad instantly short the stock and sure enough two seconds after there's breaking news is released boom the market has already been adjusted due to a wave of high-frequency trading BOTS crashing the market the example of Johnson & Johnson's talcum powder scandal was one of the more obvious instances of these kinds of BOTS but realistically they work day in and day out ingesting huge piles of data and very quickly making snap decisions on if this is good or bad before anybody else has had the chance to react what makes this all the more interesting though is that these types of low latency market bots are not limited to just typical financial markets there are low latency news BOTS operating in sporting markets around the world today as well something like the news of an injury of a star football player can massively reduce the odds of a sports team winning an upcoming game these types of news bots can even operate in these markets to very quickly put bets on the opposing side in these instances to profit off the price change caused by the news hitting the mainstream these news bots were the first kind of high-frequency trading algorithms to be released on the world but from this they have grown and adapted into a range of weird and wonderful algorithms high frequency trading turned quickly from reactionary systems making predictable trades into complex machines that ingest hundreds of points of data in real-time run regression analyses on that data and then make microsecond trades to make thousands of tiny little profitable exchanges throughout the day these data points go from simple stuff like order volume current price and price of similar securities to far more obscure data points that are for the most part closely guarded secrets of the firms that trade with these algorithms this has done a few things firstly it has led to a massive arms race in speed high-frequency trading firms were up until recently increasing the value of land around the new york stock exchange center so that their fiber-optic cables would be closer to the exchange server the speed of light through a hundred metres of glass fiber cable could have meant the difference between your firm or a competitive firm getting the trades in to make the profit today these firms just pay to keep their service in the basement of the New York Stock Exchange and every firm gets exactly the same length of fiber-optic cable connecting it to the node itself to make sure that all the servers are operating within a billionth of a second of one another so you know pretty good ping overall all of these algorithms are still for the most part a reactionary algorithm they are simply looking at data interpreting it very quickly and acting on it before anybody else has had the chance to do the same but they get even weirder from that some algorithms have been designed to basically prey on other algorithms detecting the data points that they look for feeding them false data points like bogus bids or low value high-volume trades to get them to react in such a way as to offer a security for less than it should have otherwise been created for and then selling it back to the regular market and a markup all within a millionth of a second the basic techniques of these aggressive predator style bots are spoofing putting orders into the market to give a false impression of demand and then canceling them a billionth of a second later before they are filled and quote stuffing which is basically very quickly throwing up a whole lot of crappy low value buy or sell offers really really quickly they won't get filled but they will slow down other high-frequency trading algorithms that now have to analyze all of these new crappy orders while your algorithm can ignore them and gain a significant speed advantage these aggressive techniques have since been made illegal in most markets around the world as it has been determined that they effectively amount to stock manipulation which is again super illegal but it doesn't mean that high-frequency trading firms aren't experimenting with new and similarly aggressive techniques because if you can be sure of something it is that laws will struggle to keep up with technology especially if there is money to be made otherwise regular reactionary high-frequency trading algorithms remain at large throughout most markets today which begs a pretty big question what does this actually mean for the foundational purpose of most of these markets all of these kinds of high-frequency trading techniques are all very fun to explore and certainly have been very profitable for the firms that have utilized them well but what does it mean for the greater economy at the end of the day stock exchanges are basically the markets for companies to trade their stock with the general population in order to raise capital to build factories or develop technologies or research life-saving medication or whatever what happens when these markets a cornerstone of modern world finance get turned into the most boring episode of BattleBots ever well the first major drawback are flash crashes effectively high-frequency trading algorithms are just computer scripts a set of instructions if x and y equals z do this now of course modern algorithms are extremely complex but it doesn't mean that they can't fall into the same kinds of problems that any other computer program does most notably endless recursions let's say one high-frequency trading bot is programmed to short shares for Citibank every time that there is a new sell order for Citibank this is called front-running it is a super common strategy basically the bots will short shares and get its order filled microseconds before a larger sell order comes along to the market and pushes the whole market price down the bot then buys out its short position and turns a tidy little profit the problem arises when another high-frequency trading bot decides that this front running business is a good idea some average trader will sell their Citibank shares and bot one will see that order and front run it shorting Citibank - does the same and then suddenly but one sees that there is another cell order and shorts of shares again but to seize a cell order that bought one place and shorts the stock billions of times over in a fraction of a second this is obviously an extremely simple example of a recursion loop and in reality most decent trading algorithms have checks in place to stop something as simple as this happening but it is impossible to create a system that will react perfectly to everything all of the time and you can ask anybody that works in development or software recursions happen all the damn time only in this case you aren't control-alt-delete in your python script your control of deleting the Chicago Mercantile Exchange these flash crashes have hit many markets all over the world as high frequency trading becomes more prominent and it was kind of a big red flag that said to investors hey you know this securities market here the market that is supposed to be will up secure yeah well it's actually just a playground for software nerds who got bored of writing PI or GUI runescape scripts I have said it over and over again on this channel that confidence is the basis of any market or economy and it is difficult to have confidence in a market that could literally fall apart in a billionth of a second in response to this many exchanges around the world have put strict limitations on these kinds of trading patterns but when there's a will there is a way and if there's a dollar to be made it will be made [Music] this is Robin Hood a stock trading platform that services billions of dollars worth of trade in any given day the darling of Wall Street bets and it seemingly does all of this for a far lower price than traditional brokers how do they do this well they operate as what is called a dark pool most of the fun stuff that high-frequency traders try to pull is not really feasible and major exchanges anymore due to regulation minimum latency restrictions or straight-up competition but a platform like Robin Hood is big enough that it kind of exists in its own little ecosystem judical stockbrokers will pass along their clients orders to the primary market in this case let's say the New York Stock Exchange but Robin Hood has enough clients that it can just keep the trades internal passing the cash and securities from one client to the other without the need to go through the main market this is known as a dark pool which is just a scary way of saying a stock market that forms separate to the primary stock market a market like Robin Hood though does not have the same kind of regulations around high-frequency trading so for a price they will let high-frequency trading firms plug their software into the back end of the exchange and front-run and news reactants smooth to their heart's content a market filled with average non institutional investors with high liquidity is fertile ground for high-frequency trading firms and they will pay big premium to facilitators like Robin Hood which means that firms like Robin Hood don't need to charge their regular clients as much if anything at all which is yet again another example of a solid business saying if you are not paying for a product you are using chances are you are the product now a huge disclaimer here is that this isn't to say that there is no money to be made investing through Robin Hood just keep in mind that every time you do chances are you are making a high-frequency trading firm somewhere out there just a little bit richer high-frequency trading is the modern incarnation of the race to be the first to the market it is a battle that has been going on for as long as economics has been studied is it healthy well no probably not it does severely throw the stability of major world markets into question but as always it's likely to be around until regulation has a chance to make sense of this new reality and catch up with innovation hi guys thanks for watching my latest video we will be live-streaming the Q&A session for this video half an hour after it goes up if you want to ask questions I would encourage joining that YouTube stream or joining our discord server otherwise if you did enjoy please consider liking and subscribing thanks guys bye

Channel: Economics Explained

Views: 347,821

Rating: 4.921854 out of 5

Keywords: the economy of high frequency trading, the economics of high frequency trading, the economy of high frequency trading explained, the economics of high frequency trading explained, high frequency trading economics explained, economics explained high frequency trading, high frequency trading economy explained, high frequency trading economy, high frequency trading economy economics explained, high frequency trading economics, how high frequency trading works, economics explained

Id: oUVchh37AO8

Length: 14min 41sec (881 seconds)

Published: Thu Nov 28 2019

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[u/StreetSquatch]

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