Jan

28

 Algorithmic trading developed impressively during the past years. Up to 60% of trading in equity markets is computer-driven. Some say that the increasing dominance of algorithmic trading could cause "tiny price changes to snowball, rolling down the hill at exponentially increasing speed". There is the possibility for a crash to happen also because too many funds are trading in the same style. What is the human control on these machines? How long will it take before a mistake is recognized as such? Is there a way to prevent "algos gone wild"? Can regulation help or would it make it worse? In practice, there is a risk of systemic imbalance. On the other side there are those who believe that high frequency traders deliver a service: liquidity and their systems are the most efficient way to match buyers and sellers.

In the paper "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market", Alain Chaboud Benjamin Chiquoine Erik Hjalmarsson Clara Vega find that:

- algorithmic trades tend to be correlated, suggesting that the algorithmic strategies used in the market are not as diverse as those used by non-algorithmic traders

- there is no evident causal relationship between algorithmic trading and increased exchange rate volatility

- even though some algorithmic traders appear to restrict their activity in the minute following macroeconomic data releases, algorithmic traders increase their provision of liquidity over the hour following each release

- non-algorithmic order flow accounts for a larger share of the variance in exchange rate returns than does
algorithmic order flow

- there is evidence that supports the recent literature that proposes to depart from the prevalent assumption that liquidity providers in limit order books are passive.

Among the most recent developments in algorithmic trading, some algorithms now automatically read and interpret economic data releases, generating trading orders before economists have begun to read the first line. They allow trading to take place automatically in response to market data and news, deciding when and how much to trade. There are services that allow to react more quickly to breaking news events, providing a quantifiable measure of qualitative information present in news articles. The result is that computers can place orders more strategically than humans.

In the paper, it emerges that there is no positive correlation between algorithmic trading and the level of volatility. The evidence points towards a negative relationship, suggesting that the presence of algorithmic trading reduces volatility. Computer trading provides liquidity in period of stress (after the release of news). From the data analysed, the growth of algorithmic trading has not caused lower market quality.

George Parkanyi writes:

I don't see them being a problem unless everyone is automatically increasing trade size and leverage with the trend. The associated risk-management is fairly sophisticated. That they would do this in a highly-correlated, invisible way is highly unlikely. And high-frequency trading is by definition short-term, so there is constant buying and selling in the market. A lot of these strategies may not hold a position overnight. Markets that are up a lot or down a lot as one-way sure-bet trades are pretty highly publicized. You'll eventually get a sudden reversal, and a lot of haircuts, but these overextensions most savvy players can see coming (though you don't know where or when the turn is going to happen). Wouldn't worry about it - enjoy the liquidity.


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