Markets are efficient if new information is incorporate instantly and essentially without any trading, i.e. price jumps to the correct level that represents all available information at the time. If you believe markets are indeed perfectly efficient, there seems to be no point in using news as a source of alpha in trading. However it is unlikely that information can be incorporated instantaneously as there are plenty of frictions. Markets participants who provide the market with a useful service, for example you are smart(er) at processing new information and/or you are fastest at processing information and executing trades. In this short article I consider the speed of simple news strategy and abstract from the smartness.
US Employment report is considered the most important piece of economic news. Traders especially wait for the non-farm payrolls (NFP) number. For example June 3 report indicated that in May 38,000 new jobs have been created. Is that good or bad economic news for assets? In theory price reaction depends on two things:
(1) which part of the report is actually news and
(2) what this news means to an asset?
News can be estimated as the unexpected part of announcement: subtract expected part from actual announced figure. The expectation of economists was around 160,000 new jobs, therefore 38,000 is quite below the expectations. It is bad for economic growth, as less new jobs indicate less economic growth. What would this mean to USDJPY pair? In simple terms, this is bad news for US economy, thus USD is expected to depreciate vs. JPY in reaction to the news.
If you knew the news, how would much profit could you expect make? How fast do you need to be? Below is cumulative average return, assuming you are able to trade NFP at USDJPY prices available at 8.30 EST (US Employment report release time):
Almost 5 bps negative return at the beginning is bid-ask spread cost. It takes 1.5 seconds to reach breakeven point, and there is little systematic move of the price beyond 8 seconds. In total one could expect to make around 25 basis points net per trade. Since foreign exchange market allows for easy leverage, these 25 bps can easily turn into 2.5% per trade. There are 12 monthly announcements, thus 30% annual return. If we assume 10 seconds holding time per trade, that would make 2 minutes exposure time per annum for 30% return.
Of course this is too good to be truth. In reality it not possible to trade with zero latency. How much latency could we tolerate? The plot below shows returns assuming opening position with 0 to 30 second delay and closing position 30 second after announcement. Expected return drops sharply until 4 seconds after announcement, and at 6 there is no money to be made.
This seems like a good trading strategy, even being 2 seconds late can make 10 bps per trade! However, the data that I used is from 2003 till now. Over the last 5 years technology improved quite a bit, and more participants entered news trading. Did it make news trading extremely competitive business?The same latency robustness figure for 2015-2016 looks a bit different (see below) compare to the one above. There is no profit to be made after just 2 seconds.
And now the caveats. Could you trade on the information I have just provided? Yes, if you believe assumptions I make hold in reality:
- News is actually available at 8.30 EST for you. This is usually not the case, there is a slight delay as the announcement dispatched from Bureau of Labor Statistics travels to you. When processed by you it has to travel to the trade engine. This all takes time.
- In addition, we assumed that tick data time is in sync with BLS announcement data. The last plot could suggest that BLS server time is 1 second behind our price server data.
- There is plenty of liquidity to trade. In reality around important news liquidity dries up significantly, thus even if you were the first to send you trade order, you might end up moving the market to much.
From my experience, the higher the frequency of a trading strategy the more precision in data you need. And often higher frequency means assumptions on data quality and speed of execution will make or break a trading strategy once it goes live.