I not done any spread betting, but isn't pay outs the same of what you betting? Whereas in long term trading most of those that do well can make 8 to over 100 times what the initial risk was on one trade after rollovers. Flipping a coin is very poor return.
Right you were, the very subtle bug of multiplying the something thing by today's price instead of yesterday's price. Goes to show how careful you have to be building these things. Just for completeness, it looks like this now, which looks good to me. Interesting how the distribution of the weights is a bit like a frequency response curve: Thanks for your help!
IMO, you're missing out on WAY more than 120$ in opportunity by not including ICE energies, softs, interest rates, and financials markets. Why even sweat 120$ a month anyway?
$120 a month is $7200 a year, or about 1.5% of my capital. That's roughly what I spend on slippage and commissions in a year already. To me that's a lot. I can't control my performance pre costs, but I can control my costs. I run at 25% annualised vol so I'd have to gain 0.06 SR units to compensate. If I added say Gilts I'd have to remove a market - I'm at capacity http://qoppac.blogspot.co.uk/2016/03/diversification-and-small-account-size.html Do I think that trading Gilts instead of say US 5 year is going to improve my performance at all? Maybe very slightly, but not enough to compensate for the extra cost. Or I'd have to deploy more capital. But if I was to do that I'd probably use it to trade other strategies - options or spreads. GAT
Oh yeah, maths isn't my strong point I wouldn't backtest this since the result wouldn't be statistically different, but what I would do is look at the correlations and work out how much benefit I'd expect to get. Another thing I could do is compare the slippage cost of trading blind (assuming I could get daily data for free) and issuing market orders. Bid / ask on Gilts is £10; half that is £5. I normally cut slippage by 80% if I execute intelligently; so that's £4 per order. So I'd need to trade 250 Gilts a year to make it worth buying the data. That's much more than I would trade, so I'd certainly need to be using other ICE markets to make it worthwhile. Assessing my market list is on my "to do" list since I'm thinking about carving out different markets for some new strategies at some point. At this point I'll do the analysis properly. GAT
No worry, a year indeed feels like 60 months sometimes I understand your first point. Low correlation instruments would boost overall sharpe much more than high correlation instruments. However, I am not understanding the second point of comparing the cost of the data against the slippage cost of trading blind. Would that mean you would not trade any instrument where the transaction cost is 0 (i.e. trading at the mid)?
Er no I've explained it wrong. What I'm saying let's suppose I had to trade Gilts. I can trade them using end of day data to calculate my position (from something like quandl.com although I haven't checked to see if they have Gilts specifically), then submit a market order during the following day. That will cost me on average £5 in slippage per contract (mid to bid/ask assuming a 1 tick = £10 spread). I'd guesstimate that I'd probably trade around 50 lots a year of Gilts, costing me £250. Alternatively I could pay for data, in which case I'd be able to use a smart execution algo like I currently do for all the markets I trade. I know from experience that will cut my slippage by around 80% to something like £1 a lot. So I'd save 50 lots x £4 = £200. If I have to pay more than £200 for the data, then this isn't worth doing. GAT
GAT, first of all thanks for a really interesting book which I owe you an Amazon review for. A properly eye opening take for me on what I've always seen as the issue with mechanical systems in the past (that a small edge is possible but it never seems to make enough sense when you're trying to look at a single market). Also the first thing I've really come across to convince me that "volatility" can appropriately be called "risk" in some circumstances. The python stuff is also really interesting and has convinced me to learn a bit more beyond the very limited scripting stuff I've picked up in the past (for my home automation system). On a philosophical level the quote above struck me. Is there an element of this being the constant urge to tinker that accuse the big players of? Statistically you presumably don't expect to generate anything to suggest that the results are sufficiently better than your current system to abandon that, do you? So is it ultimately just a question of further diversification? Or is there more to it than that?