POST #6

I've attached the spreadsheet which, once you populate with the data referred to below, will output the figures shown on the attached pdf (I've had to zip the spreadsheet to enable upload as it's around 5 megabytes in xls format). The most critical figures are shown in the table above the first graph, and draw from those outputs boxed in red. The graphs are provided for quick glance and not primary reference, hence lack of labelling and general draft form.

To insert the data, go to Yahoo Finance and download the daily prices for the S&P500 from 1 January 2000 to 31 December 2010. Sort the data into ascending date order, and copy and paste the high, low and close prices into columns C, D & E, rows 4 to 2770.

Once done, the bottommost section of outputs should be identical to the pdf print. The accumulation factor in cell AT2778 can be adjusted to arrive at its respective outputs. Let me know if you find it different or some steps seem to be missing, and I'll help fill in the gaps.

The spreadsheet is still in its formative stages so apologise if it seems a little cluttered at the moment. I'll run through the most important outputs below so you can go straight to the information.

First off, the S&P500 is 'tradeable' on the face of it, as it's generating positive outcomes across most of the accumulation factors, generally peaking around the 8-13 mark, wavering around 1,000. This amount is adjusted for Pertinent Outside Days (PODs) which, at an accumulation factor of 8, reduces the unadjusted amount by 499.4, from 1,627.66 down to 1,128.26.

I should mention at this stage that the numbers quoted above are based on an equivalent of trading £1 per point. In other words, if you traded the S&P500 at £1 per point since 1 January 2000, at an accumulation factor of 8 and spread of 0.4, then the outcome by 31 December 2010 will be approximately £1,128.26.

Keeping on the theme of an accumulation factor of 8, we can see the following:

1. CUMULATIVE PROFIT OR LOSS. As noted in the above paragraph, we are looking at a positive outcome using a middle-of-the-road price indicator (INDE). Not a bad start.

2. PROFIT TO LOSS RATIO. This is 1.37:1, the cumulative profit being made up of the difference between a 3944.6 profit and a 2872.2 loss. Things are looking a little less rosy. Remember, I'm showing some of the challenges of trading so, once these are known, you can make more informed decisions. It's interesting to note that this ratio holds a pretty steady state over a broad range of accumulation factors.

3. AVERAGE RETURN TO SPREAD RATIO. The average amount of net profit made relative to the spread is 8.25:1. Not bad going.

4. PROFIT TO LOSS NUMBER OF TRADES RATIO. This is a most interesting one. At a ratio of 0.49:1, there are 113 profit making trades compared to 229 loss making trades! So for every profit making trade there are at least two loss making ones. This seems a bit odd given we have a overall profit outcome, but it is because the average profit making trade is 34.91 compared to 12.54 for the average loss making trade.

5. AVERAGE NUMBER OF PERIODS PASSING BETWEEN TRADES. This is 8.1 days, which remember is an average and will actually see some intensive clustering and contrasting quiet periods. As expected across the accumulation factors, this output produces a smooth rising curve which is proportional to the 'length' of the accumulation factor. I've also plotted the number of trades (row 7 on table), which is naturally inversely proportional across the accumulation factors.

6. INCIDENCE OF 'PERTINENT' OUTSIDE DAYS (PODs). This is 0.51% across the whole time range (14 incidents over 2767 days), and comprises 8.2% of all trades made. This factor will be better understood when different markets (and timeframes) are compared relative to each other, as I'll do in the next post with a forex market.

Interesting times.