Seeing something in nothing

My brain has been constantly whirring over the past day or so, desperate to find an idea for a blog article. The problem is that my brain is invariably focused on topics for a blog, which have nothing to do with finance like burgers. Yes, I could write about burgers and somehow skew the end of the article to finance. But I've probably done that more than enough times by now (and want to leave that opportunity for a week when I really do not have any ideas). Alternatively, I could just take a break from writing something financial, and focus on more important subjects (despite being in currency markets for a decade, even I recognise, that where EUR/USD is trading, is perhaps not the biggest concern of most people). Possibly, although, I do quite enough of that already on my Twitter feed (@thalesians if you're interested in following!)

The whole exercise has however, got me thinking. Maybe sometimes doing nothing, tinkering with your thoughts and engaging only in that thing called idleness can sometimes be the best course of action. Always wanting a positive result from what you do, is not always possible.

I'm not for a moment suggesting that doing nothing all the time is a solution for success, merely that it has its time and place. Working hard has an element of usefulness, if it's on a project where the outcome could yield a tangible benefit.

I recently went to a conference organised by the London Quant Group, which featured a myriad of exciting talks, one of which was on the subject of data mining by Mark Salmon, which I enjoyed very much (I also gave a talk, although I must confess I probably should have avoided telling any jokes - my subject of the Impact of Scheduled Events on FX Implied Vol was perhaps not the best avenue for my brand of humour!)

However, returning to the narrative about Mark's talk, the crux of data mining can be simplified into the problem of spending too much time finding "value" in a dataset where there is nothing to be found. He outlined a number of different methods to try to avoid data mining.

In the context of a systematic trading strategy, excessive data mining can result in a strategy which might work fantastically on historical data, but potentially awfully when you run it live with real cash. Doing nothing, rather than endlessly searching for something which isn't there would have perversely been more productive.

In a different context, even with discretionary trading, sometimes doing nothing can be the answer. Trading for the sake of it, when you have no conviction in any market view at that time, is worse than doing nothing. Overtrading your book, is one thing to avoid, and is the bane of many traders. Only your broker will make money from overtrading!

So perhaps sometimes, doing nothing might well be better than doing something. In the next blog, I promise to discuss a bit more than simply, well... nothing.

(as an aside, I'll be in Amsterdam next week speaking at Global Derivatives on Big Data based trading and impact of scheduled events on FX implied vol. Let me know if you'll be around!)

Like my writing? Have a look at my book Trading Thalesians - What the ancient world can teach us about trading today is on Palgrave Macmillan. You can order the book on Amazon. Drop me a message if you're interesting in me writing something for you or creating a systematic trading strategy for you! Please also come to our regular finance talks in London, New York and Budapest - join our Meetup.com group for more details here (Thalesians calendar below)

27 May - London - Gaining the alpha advantage in vol trading - Artur Sepp
29 May - Prague - Trading Thalesians book talk / Interactive FX intraday demo - Saeed Amen / The Thalesians (tickets here)
03 Jun - Frankfurt - Trading Thalesians book talk / Python FX intraday demo - Saeed Amen / The Thalesians (tickets here)
17 Jun - London - Using Python to build trading strategies - Man-AHL & Saeed Amen
18 Jun - New York - Dr. Tim Leung - Exchange-Traded Funds and Related Trading Strategies - IAQF-Thalesians