Split-second mental maths, excellent communication skills and an appetite for finance: all traditional ‘must-haves’ for any successful Wall Street stock trader. Indeed, for much of the past century, these were three core values for traders employed by investment banks as well as the market makers who kept the markets running by providing liquidity.
And then technology changed everything. While decision-making under pressure is just as important as ever, quantitative skills have raced up the wish list for trading houses. In today’s financial markets, bright graduates from an engineering, mathematics or computer science background, all have ample opportunity to apply their skills in a highly competitive and challenging environment.
Trading firms: what do they actually do?
Companies running trading strategies typically fall under one of two sectors. On one side of the street, proprietary trading firms such as market makers trade financial products, often stocks and options, for their own account and at their own risk. Over the road, banks and pension funds trade to invest their clients’ capital in the hope prices and yields will increase in the future. The latter has the longer-term trade horizon.
Market makers – essential liquidity providers
Proprietary traders often run market making strategies. The simplest example of a market maker is a currency exchange counter at the airport: imagine you wanted to convert EUR 100 euros (EUR) into US dollars (US$) for a weekend trip to New York. The person behind the counter might offer you US$ 110 – this is a price quote. However, coming back from the weekend – assuming for a second you spent nothing and the exchange rate stayed the same – the counter will likely return you only EUR 97. The exchange counter played the role of market maker and pocketed EUR 3 for their troubles.
This sounds like an easy way to make a quick buck – or three – but the market maker runs the risk that the exchange rate might move adversely during the weekend while you are out enjoying the sights. In fact, the counter has an inventory of euros, which might depreciate overnight.
Even though you didn’t get your full EUR 100 back, the desk did allow you to trade your currency back and forth with ease – no questions asked. During periods of uncertainty, you are probably lucky if you get to exchange your cash at all.
The more widely traded the currency, the more likely you, as the customer, are to walk away with a reasonable deal. This is where competition between these counters (read: market makers), is extremely valuable: if a second desk opens and offers everyone a better price – say, EUR 98 or even EUR 99 – the first shop is out of business quickly, and all clients benefit.
Wanted: quantitative skills
It stands to reason: the market maker offering the best deal will get most of the business. But this comes at the cost of inventory risk – namely the risk that the price of the euros (the exchange rate) will fall after buying them from the traveller. Market makers like to unwind this risk, and the simplest way to do this is to find someone who would like to trade the opposite side. To take our example: someone travelling in the opposite direction from New York to Amsterdam. This way, the hard-working currency counter clerk at Schiphol can offload some of their inventory to our American friend – fresh off the plane and hungry for euros.
However, this isn’t always possible. If no one wants euros, the counter could swap their euro inventory for British pounds (GBP). This isn’t a like-for-like exchange, but the price of pounds and dollars tend to move together quite closely. Calculating these cross-correlations and understanding how to mitigate (this is known as hedging) inventory risk, requires a whip-smart mathematical brain. Globalisation connected all pools of financial products, from stocks to derivatives and everything in between – and finding a proper hedge has become easier over time.
Algorithms in market making
Now, imagine a market maker can offer the best possible deal to the market – i.e. they are able to return EUR 99.99, since exchange rates are somehow unusually stable. Also, picture all competitors being able to offer EUR 99.99. In this scenario, customers are indifferent about whom they give the trade. According to exchange ruling, the market maker that makes their offer first will typically get the deal. Speed is of the essence, and this is where algorithmic skills come in. Market makers must act quickly while sending as little information to the wider marketplace as possible. And this can only be done using high-frequency strategies.
Do you see yourself as a trader?
As you can see, today’s financial markets are a highly competitive and efficient field. If you want to be successful in trading, you need a set of skills that goes beyond a standard technical profile: market makers like IMC need good communicators with an entrepreneurial spirit, a technical background and a strong, flexible mindset. This final attribute is especially important, since market circumstances can change overnight which requires traders to adapt their strategies daily.
Think you’ve got what it takes to work in high-frequency trading? Learn about the opportunities on offer at IMC via our graduate careers site.