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In this article we analyse 2017 performance for quant funds which tended to underperform, the number one cause merely is – the lack of volatility. No movement means no range which in turn means far fewer opportunities.

 

For more significant quant funds, with the positive attention they received over the last decade we find they attracted too much money too quickly and more people who use the same strategy will ultimately see a deterioration of its edge over time. The markets over the last decade have been a machine utopia but, as the competition has increased the machines are starting to skirmish with each other. Robots trading against robots is what the future of quant funds has become, and the prize has been getting smaller with each subsequent year.

 

Putting the big quant firms aside, how do the small algo trading systems hold up?

The smaller companies often are far nimbler than the substantial quant funds; they utilise strategies which revolve around liquidity and usually will have a maximum ceiling on the total capital which can be utilised. Still, 2017 was deemed to be a challenging year, again mostly attributed to the low volatility.

From our own experience, we utilise a portfolio of systems which are in turn market neutral. In a day trading setting where volume is highest, our robots can get in without creating so much as a splash and get out unseen from the prying eyes of other much more prominent robots.

 

A case study to find reasons why so many funds might have struggled in 2017.

We will base this on systems which trade one of the most liquid markets on earth, the Emini S&P 500 Futures market (ES) – which trades on the Chicago Mercantile Exchange. In all this analysis we have the following criteria:

  • -Day trading only and never holding positions overnight
  • -Data is based on the day trading session only from 830am Central time to 315pm central.
  • -We cannot take overnight moves into account as we cannot trade them.

Our results show data for the ES futures markets.

  • -Only 11 days this year with over 1%-day trading range in 2017.
  • -To put this in perspective in 2016 which was still not a volatile year (except Jan and Feb) we had 86 days with over a 1% move.
  • -11 days 2017 with 1% range compared to 86 days with 1% range 2016 – this is a large variance.
  • -To put things in perspective further, just looking at a moderately volatile year like 2011 there were 168 days of the trading year with higher than a 1% range.

Table 1: Days with over 1% range:  

Year       2017       2016       2015       2014       2013       2012       2011       2010       2009       2008
1% Rng       11       87       124       77       69       97       168       158       216       228

        Mean: 2008-2016 - 136

Average from 2008 to 2016 is 136 trading days in a year with a range over 1%. Hence, 2017 is an outlier; it is statistically -2.097 standard deviations away from the mean (2016-2008).

 

 Low Volatility setting continual records in 2017

                                                                                                                              Chart 1: VIX Index

                                         VIX (volatility index): 2017 the whole year was nearly below all-time volatility lows.

 

The VIX chart above shows another record for 2017 by setting the lowest volatility ever recorded.

All-time lowest VIX close was 9.14 on Friday 3 November 2017.

The 20 lowest VIX closes have been the following:

Fri 03 Nov 2017 = 9.14

Thu 05 Oct 2017 = 9.19

Wed 22 Dec 1993 = 9.31

Mon 11 Dec 2017 = 9.34

Fri 21 Jul 2017 = 9.36

Mon 06 Nov 2017 = 9.40

Tue 25 Jul 2017 = 9.43

Mon 24 Jul 2017 = 9.43

Mon 02 Oct 2017 = 9.45

Thu 23 Dec 1993 = 9.48

Tue 03 Oct 2017 = 9.51

Fri 29 Sep 2017 = 9.51

Fri 14 Jul 2017 = 9.51

Thu 28 Sep 2017 = 9.55

Fri 08 Dec 2017 = 9.58

Thu 20 Jul 2017 = 9.58

Fri 22 Sep 2017 = 9.59

Wed 26 Jul 2017 = 9.60

Fri 13 Oct 2017 = 9.61

Wed 04 Oct 2017 = 9.63

 

Almost all 20 all-time lowest VIX closes occurred in 2017, except two consecutive days 22-23 December 1993 – just before the holidays.

Further statistics show that sub-10 VIX closes in 2017 were 79 days, this compared to sub-10 VIX closes before 2017 running from 1990 to 2016 we had only 18 days. Truly shocking that there were four times as many sub-10 closes in 2017 than the previous 27 years combined.

With this data at hand, one strategy for smaller investors would be to buy volatility; this strategy can be achieved via VIX Futures, VIX Call options or VIX ETF.

 

Identifying other causes for the problematic year?

Algo trading systems had a challenging year, first as mentioned above the volatility is perhaps the dominant factor. Another reason is the number of down days which stayed down, also known as trend days down. Many Short (make money from downside moves) only systems catch big moves down historically but in 2017 we have seen that time, and time again there were constant rebounds for any potential down day. Any human day trader could adjust quickly to recognise this pattern, and dip buying ensued. See the following data:

Table 2: Trend days down (a day which opened near the high of the day and closed near low of day)

Year      2017      2016      2015      2014      2013      2012      2011      2010      2009      2008
Trend Down       16      21      36      30      23      35      33      33      34      50

                              Mean: 2008-2016 – 32.7

2017 shows only 16 such trending down days.

Next factor is trend days up, considering the market has been one of the most one-sided in history we would assume many Long only systems would have performed exceptionally:

 

Table 3: Trend days up (a day which opened near the low of the day and closed near high of day)

Year    2017      2016      2015       2014      2013      2012      2011      2010      2009      2008
Trend Up    34      42      47      49      50      52      41      43      42      47

                  Mean: 2008-2016 – 45.8

Strangely enough, we find 2017 has the least trend days up in the last decade, this is peculiar considering the market theme. The fundamental reason for this is many days the moves were stolen overnight in which the market gapped up.

Liquidity and Volume for 2017 were extraordinarily low. Low volume causes more slippage and indicates the lack of range and movement. 2017 the underlying market theme was dominated by a consistent daily chop. See the following data:

 

Table 4: Volume

Year      2017      2016      2015      2014      2013      2012      2011      2010      2009      2008
Volume (millions)      268      362      364      324      347      355      477        433      460         523

Mean: 2008-2016 – 405 million

 

2017 indeed was a bizarre year, one which I have never seen in my long tenure trading futures markets. Most days were like watching paint dry and therefore many day traders and quants I know went days barely glancing at the stale quotes. Whereas the longer-term charts we have almost a parabolic move up in nearly all equity markets, there is yet to be any real down moves for nearly a decade now! Is this what the massive intervention of Central Banks has caused and what is the end game?

Statistically, we find it hard for this type of year with all its extremes to transpire again. Our recommendation for both larger and smaller firms alike is to view this very much as an outlier. The historical low volatility has very little chance of being replicated, particularly the 11 down days with over 1%-day trading range – that is so far from the mean it boggles the mind.

Some day traders or quants are diverting their skills to cryptocurrency trading. With these markets now available to trade at futures exchanges can only mean a pick-up volume for these new types of asset classes.

All data suggests that 2017 was a record-setting year and in the wrong areas for day traders.

You might also like: 

 

Algorithmic Trading During Volatility Spike

 

Drawdown is Misleading Metric in Futures Trading


 


 

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