With all the allegations of Mt. Gox’s automated trading bot, which has been dubbed “Willy”, algorithmic trading is getting a bad rap. However, using bots to trade on the financial markets is a long-established and legitimate activity – and it’s easier than anywhere in the cryptocurrency markets.

So, how do these bots work, and can they really make you money?

Trading bots are software programs that talk directly to financial exchanges, and place buy and sell orders on your behalf. They make those decisions by watching the market’s price movements, and reacting according to a set of predefined rules.

Joseph Lee is living proof that they can make money. Lee, who founded derivatives exchange BTC.sx, based its trading engine on algorithmic trading bots that he wrote himself, and used between 2011 and 2013.

He claims to have turned a simple $100 buy order into $200,000 in profits using his private software army. While that seems astonishing, the devil is in the detail, of course: a lot of that price increase stems from the massive price increase in bitcoin late last year.

In fact, the real profits are far more marginal, he has said, so don’t expect to install a plug-in and write your own rags-to-riches story.

Lee, who claims that his bots shifted 10% of the market’s entire volume in the early days, started using his methods when the price sat at $2-$4 per bitcoin.

Market maker

Lee’s first trading bot used inter-exchange arbitrage, noticing differences in prices between orders on different exchanges, and buying on some exchanges while selling on others.

“I was essentially taking liquidity from a market where there was some and injecting it into a market where there wasn’t,” he explained. Back then, Mt. Gox dominated the market, and other exchanges had poor pricing because their supply of bitcoins was limited.

“So, I bought for cheap on Mt. Gox and sold them to other markets. I bought a lot of bitcoin into tertiary markets.”

In short, he acted as a market maker on less-established exchanges.

Established practice

Lee may have written his own bots, but today, the bitcoin trading bot market is far more established, with several available off the shelf.

Examples include Butter Bot, which offers an online trading bot accessed via a Google Chrome plug-in, and Haas Online, which sells a Windows-based personal trading server. CryptoTrader offers a trading bot marketplace, which allows people to develop bots using different trading strategies, and then rent them to others.

Trading by algorithm isn’t new in the financial world: companies in the conventional financial markets have been using the method for years. Lee said, however, that the bitcoin exchange community is one of the first where exchanges grant customers’ computers direct market access (DMA).

This enables individual traders to have their computer access the exchange’s electronic order books directly. That’s a service normally only available to brokers and investment houses in the conventional markets.

“In the past, it was the people who had the means to pay for a $10,000-plus a year Bloomberg terminal with an API connection who could try their hand at bot trading,” Lee explained.

So, why isn’t everyone doing it?

Pablo Lema, founder of Butter Bot, says that bots aren’t a ‘fire and forget’ technology that enable dilettantes to make money without trying:

“Trading bots require users to have at least a basic understanding of the market, need to be modified and tweaked by the user according to the predominant market conditions, and also according to their own risk profile.”

Trading bot strategy

Lee started off capitalising in a highly inefficient market, where exchanges with sufficient liquidity could be counted on one hand.

The situation – while still needing improvement – is at least a little better now. Opportunities for inter-exchange arbitrage still exist, but he recommends using technical analysis bots.

But trading isn’t necessarily based on technical analysis alone. It’s difficult to program a computer to react to fundamental market conditions such as, say, rumours about the Chinese government taking a new stance on bitcoin, or the latest bitcoin-based black market trading site shutting down.

Many bots will use an exponential moving average (EMA) as a starting point. These averages track market prices over a set time span, and bots can be programmed to react to what that price does – such as moving beyond certain thresholds.

“If you have a conservative appetite, choose to trade on a slower basis,” Lee advised. “If you picked daily rather than hourly periods, it’s generally seen as a safe bet to get involved in the basics of trading, let alone bot trading.”

Others suggest tweaks to the EMA approach.

“If you look to the biggest downside of an EMA then you see it’s almost always to late. And this is the part that can be improved,” said Stephan de Haas, founder of the Haas Online trading bot company, adding.

“This improvement could be done by using a DEMA [double exponential moving average] or TEMA [triple exponential moving average] instead. Those have the ability to respond faster then the EMA and their calculation is EMA-related, so it looks the same while it gives off better momentum.”

There are still other methods, he pointed out, such as relative strength indicators and regression analysis.

“This type of analysis works perfectly for processes (in this case a price market) that are unstable,” he says, in a description which seems to sum up the roller-coaster world of bitcoin.

“Using that data, it can make good sense of what’s to be expected in the […] future.”

Secret strategies

However, technical analysis is a discipline, and these things are indicators, not strategies. You’re still going to have to come up with your own set of trading rules, if you’re going to tell a bot how to make decisions.

“The really good strategies are kept secret and closed source,” says Lema. “That’s done by everyone: the mid [and] high level [traders] and clearing houses. It’s hard for a trader who’s new to understand the market.”

BTC or Bust, the creator of the Crackin’ Kraken bot found on Cryptotrader, points to a set of algorithms in a library of technical analysis algorithms known as TA-Lib, along with custom indicators developed by the bot author. These are typically combined to find buy and sell signals in the market, BTC or Bust told CoinDesk.

Bots can be programmed to be predictive or reactive, or a combination of both, using these combined algorithms, it said, explaining:

“For example, let’s say the bitcoin price is crashing. A predictive algorithm might start buying as it expects the price will quickly rebound, while a reactive algorithm might start selling as it sees the price is dropping. Both types have their advantages and disadvantages – the challenge is to have the bot employ the correct strategy at the correct time.”

The ability to set these strategies is one of things that will stop bots from unbalancing the market. Even if lots of people use them, the theory goes that the different strategies they employ would stop them all moving the market in one direction and creating an artificial bubble – or worse, a ‘flash crash‘.

Not for everyone

Is bot trading for you? Possibly. They offer a variety of advantages, not least of which is the ability to diligently trade on your behalf, 24/7, and the ability to remove all of the emotion from trading (assuming you don’t barge in and terminate them when you’re feeling irrationally antsy).

On the other hand, if you don’t have the financial smarts to put together a trading strategy, then bots could simply end up automating a set of poor market trading decisions.

For many, then, who believe in bitcoin’s long-term potential, the most basic trading strategy could be buy-and-hold.

Whether or not you decide to automate your trades, the basic rules apply: don’t trade more than you can afford to lose, and don’t go into any investment without at least a basic understanding of what you’re doing.

Disclaimer: Statements in this article should not be considered investment advice, which is best sought directly from a qualified professional.

Robot image via Shutterstock