Trading Bots vs Humans 路 Everything you need to know

Written by janny | Published 2019/08/16
Tech Story Tags: trading | bots | machine-learning | ai | investing | cryptocurrency | latest-tech-stories | hackernoon-top-story

TLDRvia the TL;DR App

Over the past 10 years we've seen the rise and rise of trading bots and Quantitative Funds and we've seen the fall and fall of traditional Asset Managers and Hedge Funds.
There are a number of reasons for this so we're going to explore them here.
When we look at trading bots vs humans, there are four categories we can split this up into:
  1. Trading bots for retail. These are the bots available through all the common bot platforms that you'll find from a quick Google.
  2. Proprietary trading bots. These are the ones that are developed in house by accomplished Hedge Funds, written by extremely smart finance professionals and statisticians.
  3. Professional (Human) Investors. These are the regular fund managers that you see on the finance channels touting their own positions.
  4. Retail (Human) Investors. This is pretty much everyone else. In the U.K. and Australia they'll live on CFD trading platforms.
What we really want to do is understand the differences between these different groups; humans vs bots on both the retail and institutional side.
Let's start with performance because that's the most important factor.
The average Hedge Fund has underperformed buy and hold by 71.7% over the last 10 years (+5.95% per year for Hedge Funds and +13.12% per year for the S&P 500 net returns over the past 10 years).
However, there is a strong outlier; algorithmically traded Funds (aka Quant Funds).
The performance of funds like Renaissance and Citadel create a force to be reckoned with. They have achieved a very impressive annualised net return over the past 10 years are +37.1% and 22.1% respectively.
However, not all have been successful.
The Quantopian "crowdsourced hedge fund" experiment doesn't seem to be going as planned with overfitting prevalent amongst strategies. Another highly regarded Quant, has suffered tremendous outflows and has had pretty shocking performance of -12.11% in the last 12 months.
See,
You can get a trading bot for just about any asset these days; stocks, forex, cryptocurrencies, you name it.
But it's much harder to find a profitable trading bot.
It is trivial to make a working bot, less so to have a profitable one. - Reddit User
And this is really because they start with the same flawed knowledge. Decades of incorrect assumptions floating around in the public knowledge sphere of Github and Google scholar is only the tip of the iceberg.
Furthermore, profitable trading algorithm developers guard their "edge" like pirates hoard treasure.
The unfortunate reality is, you'd struggle to find a single bot available to the public today that's consistently profitable.
This is the exact reason why we're building Credium. Our only focus is on creating profitable crypto trading bots and for retail investors as well as institutional investors. The founding team have a strong background in finance and are the only bot provider that focusses on profitability as the main goal.
When it comes to retail (human) traders, most lose money over time.
We can actually find out exactly how many of them lose vs win by platform; due to a legal requirement, brokers in the U.K. now have to tell you what percentage of their customers lose money.
If you change your VPN to the U.K. and just Google "CFD Trading" you'll see a page like this:
Literally somewhere between 62.9% and 76.4% of retail traders lose money.
Pretty wild huh?
And it's mainly because of the investor Psychology cycle:
This bring us onto our comparison:

Reasons Why Trading Bots Are better than Humans

  1. Potential for greater performance. The best performing trading algorithms have a performance that's significantly greater than the best performing humans. It's worth noting here though that the majority of bots lose money.
  2. Automation. Bots can automatically execute trades when a particular level has been reached at any time of the day. They react with predictability and logic and when it comes to probability theory and statistics, this approach tends to produce more favourable results over time.
  3. Emotionless. Bots can analyse data without emotion or bias. They understand the implications for a wide range of events and typically wont get wed to their positions.
  4. A.I. A.I. & Machine Learning is beating humans across the board, from Go to Poker. We're right at the beginning of the A.I. age with the advent of self-driving cars and healthcare diagnoses. Credium's crypto trading bot utilises A.I. extensively.
  5. Scale. Bots are able to process significantly more data and in much shorter timeframes than humans. This means they won't miss an important announcement on a portfolio company. It also means they can analyse more companies and thus diversify risk better.
  6. Speed. Speed reduces slippage as reaction time isn't needed and opens up arbitrage opportunities too.
  7. Longevity. Bots can be up and running 24/7. In a product like cryptocurrencies this is especially useful. Humans need to eat, sleep, live. A human typically works 40 hours a week however a bot can work 168 hours a week therefore can capture 4.2x more opportunities.
  8. Consistency. Bots by design are consistent. When they engage in a piece of information or an announcement they'll react in the same way over and over again.
  9. Strategy Diversity. Because bots are able to scale and run at speed, they can also work on different time frames and with different strategies that are uncorrelated which reduces their risk. This is because the P&L volatility is lower which would cause your risk adjusted returns to be better.
  10. In-built backtesting. Every strategy can be backtested multiple times and in multiple environments automatically. This gives you more confidence that the particular strategy works and when you should stick with it or not. This also helps you manage risks better.

Reasons Why Humans are better than Trading Bots

  1. Less susceptible to fake news and pump n dump schemes. Tweet manipulation can sometimes send bots into a frenzy chasing after a particular stock or coin to then be left playing hot potato with each other when they realise the news article wasn't real.
  2. Subjective analysis of data. Sometimes a particular piece of information won't have a first-degree-thinking outcome and will need deeper analysis to understand the implications. Bot's are able to look at words and overall sentiment in a multitude of cases but there can be news events that they don't know how to respond to.
  3. Black swan events. Humans are good at rational thinking. Sometimes black swan events cause bots to lose millions because it's a scenario they haven't encountered before. Human traders are better to respond to severe mispricings and take advantage of them. However, granted, these are rare.
  4. Bug free. Bots are susceptible to bugs and errors. There are times when bots have effectively "fat fingered" a trade and ended up causing a huge price movement in the underlying. Bots can in theory also crash leaving them offline for periods of time.
Well that just about wraps things up for now.
If you like the promise of trading bots and want to get started with trading bots, feel free to give Credium a try.
Disclaimer. Financial markets are risky. Unlike stocks which have intrinsic value and are correlated with the global economy, cryptocurrencies unfortunately aren鈥檛 productive assets and they have no intrinsic value. Therefore you should be very conservative if you plan on getting involved with cryptocurrencies; the risks are pretty huge. This post isn鈥檛 intended as investment advice so please do your own research before investing in anything.

Written by janny | working on credium.io
Published by HackerNoon on 2019/08/16