I want to shift gears a little this week and discuss a study I just wrapped up looking at the affects volume has on a trading system. We’ve all heard how important volume is but I’ve become increasingly skeptical of conventional wisdom and decided to take a closer look at it myself. We will change our data format a little this week as well to better facilitate an analysis of this. As usual, we will compare the results over three separate portfolios to confirm our results are systemic.
The entry system is the same one we have been using to date with one exception, Pradeep’s volume requirement has been replaced and we will be looking at the volume increase as a percentage over the average 10-day volume. I inevitable get asked about entries after each post and will only refer one to Stockbee for more details on the entry criteria. I do not want to take the liberty of detailing his criteria here.
For our average volume calculations, we could use a different time frame but the results will not vary substantially as this number changes. This is an area that is susceptible to curve fitting and in order to avoid this, I will always use a 10-day period for these types of calculations.
We will also look at the results with two sets of exits. The 8% protective+20% profit target and the 8% protective + 25% trailing profit stop. These exits are discussed in more detail in previous posts here and here. While probably not necessary, I’ve decided to test with multiple exits to confirm the results are independent of a particular exit strategy.
Let’s begin by looking at a chart of the expectancy per dollar risk (Avg. Trade/ Avg. Loss) against our different volume requirements followed up by the raw data.
8% Protective + 2o% Profit Target
8% Protective + 25% Trailing Profit Stop
To borrow an analogy from Quantifiable Edges, myth confirmed - sort of. Strong volume does appear to elevate our expectancy and the affect can be quite substantial. Looking at he 20% profit target with the IBD portfolio, a 200% volume increase raises our expectancy per dollar risked by nearly 36% over a 0% volume increase. The Nasdaq portfolio is even more dramatic with a 110% expectancy increase.
There are some interesting exceptions however. Above about a 250% volume increase, things start to get a little catawampus, particularly with the S&P portfolio. Part of this can perhaps be described by the lower number of trades at the higher volume breakouts which may be increasing the margin of error but does not fully explain why the S&P portfolio performance completely falls off a cliff between 250-300%. I can only speculate to why this is but feel it might be related to the nature of the large-cap stocks that make up the S&P500 and an over-reaction to a positive event or news item that would trigger this high a volume surge and the subsequent correction. This is only speculation however.
As usual, I encourage everyone to spend some time with the data and formulate your own conclusions and strategies for incorporating this data into your trading, if at all. To aid in this, I have posted the raw data in spreadsheet form to the following location for download.
20% profit target
25% trailing profit stop stop