Trading like a robot: looking at spread betting algorithms

Spread trading robot. Trading Bots: the Holy Grail?

What is automated trading?

Its exponential rise in price is pushing it further into mainstream consciousness each week, attracting even more investors, pushing the price further up. Both of spread trading robot friends had invested not insignificant amounts of their own money into Bitcoin, and were profiting off of the rising price. To understand what a spread is, and why this is significant, we need to look at some basics about how an exchange works.

Typically when we think of an exchange-traded asset, like a stock, we think of it as having a fixed price which we can buy or sell it at. Most buyers are willing to pay less than sellers are willing to sell for, and so the bid price of an asset will always be below the ask price. In the case of the Apple stock, these two prices are likely to be very close together.

How does automated trading work?

The spread is small on a popular, stable stock like Apple. This is because there are always plenty of people willing to buy the stock, which causes the bid price to rise, and plenty willing to sell, which pushes down the ask price. Competition amongst both buyers and sellers pushes the bid and ask prices close to one another.

The size of the spread on Bitcoin was a consequence of the market chaos that was emerging in December Retail investors — you, me, the average person on the street — were flooding into the market.

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Prices were so volatile as a result, that the spreads could never stabilise. Large spreads might sound like a bad thing, and to an extent they are, but they also present an opportunity to profit. To see how fees fit into this, we have to take another slight detour into how exchanges work.

What is automated trading?

This could happen milliseconds or days later, depending on how high your price is and the volume on the exchange. Naturally, this will be at the ask price, because this is the lowest that anyone is willing to sell for. This last point is crucial, because it helps to explain the fee structure that most exchanges have.

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Back to our earlier example. There is one final problem however, which presented the biggest challenge to making an algorithm which could do this programmatically.

In practice however, in the time between checking the bid price and submitting your order, the bid price will often change.

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We check the current ask price, and bid several cents below that. This ensures that if a taker buy order comes in, it gets matched against our maker sell order.

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The most obvious example of this can be seen by looking at the competition created by market-makers jostling amongst one another to set the bid price.

Often it would only increase by one or two cents, as traders fought amongst each other to maximise the amount of time they set the bid price, whilst also wanting to offer as low a price as possible. Sensible as this first seemed, I found that by the time my order went through I would often be several cents below the constantly changing bid price.

To get around this, and to ensure that as many as possible of my orders would beat the current bid price, I took measurements of how much the bid price would typically forward and option comparison every ms.

Sunday 12 June pm Trading like a robot: looking at spread betting algorithms KCS-content WHEN spread betting, there is always the temptation to break your own rules. So maybe algorithmic trading programs are the answer to this problem. Having attended a trading seminar where the speaker said that in an ideal world, he would be shut off from all news sources and trade only from charts, surely a robot could be a better technical trader than a human?

I also began to consider how the size of the spread would affect how much I was willing to offer over the current bid price. As we saw earlier, profit from any trade is directly proportional to the size of the spread.

Trading Bots: the Holy Grail?

I assumed at spread trading robot time that this was because of there being more demand than supply for Bitcoin, explaining spread trading robot there was more competition amongst buyers than sellers. Market Manipulation Market manipulation refers to a variety of malevolent tactics that traders employ in markets in order to gain an unfair advantage.

As an unregulated market, cryptocurrency exchanges were and still are ripe with market manipulation. With a spread so small, it appears impossible to profit off of market making, and all activity grinds to a halt. The issue however was that whenever these buy orders appeared, they would typically be for the smallest amount possible; 0. The reason another market maker might place such a small buy order, right below the ask price, is genius.

If another market maker has just been able to buy Bitcoin at the bid price, they then have an incentive to sell it at the ask price as soon as possible.

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This latter order will have as small an order size as possible 0. The first 0.

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The next 0. Though bad for investors, this provided huge opportunity for market makers. The high levels of volume on both the buy and sell side which meant more taker spread trading robot coming in massively increased the amount of trades per day that an efficient market maker could execute. This period of opportunity was relatively short-lived though.

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After the frenzy of January and February, volumes started to dry up, meaning fewer opportunities to profit. Despite the falling trade volumes, the number of market-makers kept increasing, as new bots entered the exchange.

Forex Robots - Does Automated Forex Trading Work?

More market makers on exchanges led to more competition on bid and ask prices, in turn narrowing the spreads. The additional competitors also meant that orders would typically be at the bid price for a shorter period of time, as there were more competitors ready to outbid you as soon as your order had been submitted.

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