2013: Lessons Learned and Revisiting Some Studies

The year is over in a few hours and I thought it would be nice to do a quick review of the year, revisit some studies and the most popular posts of the year, as well as share some thoughts on my performance in 2013 and my goals for 2014.

Revisiting Old Studies

IBS

IBS did pretty badly in 2012, and didn’t manage to reach the amazing performance of 2007-2010 this year either. However, it still worked reasonably well: IBS < 0.5 led to far higher returns than IBS > 0.5, and the highest quarter had negative returns. It still works amazingly well as a filter. Most importantly the magnitude of the effect has diminished. This is partly due to the low volatility we’ve seen this year. After all IBS does best when movements are large, and SPY’s 10-day realized volatility never even broke 20% this year. Here are the stats:

ibs

UDIDSRI

The original post can be found here. Performance in 2013 hasn’t been as good as in the past, but was still reasonably OK. I think the results are, again, at least partially due to the low volatility environment in equities this year.

UDIDSRI performance, close-to-close returns after an zero reading.

UDIDSRI performance, close-to-close returns after a zero reading.

DOTM seasonality

I’ve done 3 posts on day of the month seasonality (US, EU, Asia), and on average the DOTM effect did its job this year. There are some cases where the top quarter does not have the top returns, but a single year is a relatively small sample so I doubt this has any long-term implications. Here are the stats for 9 major indices:

dotm

Day of the month seasonality in 2013

VIX:VXV Ratio

My studies on the implied volatility indices ratio turned out to work pretty badly. Returns when the VIX:VXV ratio was 5% above the 10-day SMA were -0.03%. There were no 200-day highs in the ratio in 2013!

 

Performance

Overall I would say it was a mixed bag for me this year. Returns were reasonably good, but a bit below my long-term expectations. It was a very good year for equities, and my results can’t compete with SPY’s 5.12 MAR ratio, which makes me feel pretty bad. Of course I understand that years like this one don’t represent the long-term, but it’s annoying to get beaten by b&h nonetheless.

Some strategies did really well:

stratgoodOthers did really poorly:
stratbad

The Good

Risk was kept under control and entirely within my target range, both in terms of volatility and maximum drawdown. Even when I was at the year’s maximum drawdown I felt comfortable…there is still “psychological room” for more leverage. Daily returns were positively skewed. My biggest success was diversifying across strategies and asset classes. A year ago I was trading few instruments (almost exclusively US equity ETFs) with a limited number of strategies. Combine that with a pretty heavy equity tilt in the GTAA allocation, and my portfolio returns were moving almost in lockstep with the indices (there were very few shorting opportunities in this year’s environment, so the choice was almost always between being long or in cash). Widening my asset universe combined with research into new strategies made a gigantic difference:

beta

The Bad

I made a series of mistakes that significantly hurt my performance figures this year. Small mistakes pile on top of each other and in the end have a pretty large effect. All in all I lost several hundred bp on these screw-ups. Hopefully you can learn from my errors:

  • Back in March I forgot the US daylight savings time kicks in earlier than it does here in Europe. I had positions to exit at the open and I got there 45 minutes late. Naturally the market had moved against me.
  • A bug in my software led to incorrectly handling dividends, which led to signals being calculated using incorrect prices, which led to a long position when I should have taken a short. Taught me the importance of testing with extreme caution.
  • Problems with reporting trade executions at an exchange led to an error where I sent the same order twice and it took me a few minutes to close out the position I had inadvertently created.
  • I took delivery on some FX futures when I didn’t want to, cost me commissions and spread to unwind the position.
  • Order entry, sent a buy order when I was trying to sell. Caught it immediately so the cost was only commissions + spread.
  • And of course the biggest one: not following my systems to the letter. A combination of fear, cowardice, over-confidence in my discretion, and under-confidence in my modeling skills led to some instances where I didn’t take trades that I should have. This is the most shameful mistake of all because of its banality. I don’t plan on repeating it in 2014.

Goals for 2014

  • Beat my 2013 risk-adjusted returns.
  • Don’t repeat any mistakes.
  • Make new mistakes! But minimize their impact. Every error is a valuable learning experience.
  • Continue on the same path in terms of research.
  • Minimize model implementation risk through better unit testing.

 

Most Popular

Finally, the most popular posts of the year:

  1. The original IBS post. Read the paper instead.
  2. Doing the Jaffray Woodriff Thing. I still need to follow up on that…
  3. Mining for Three Day Candlestick Patterns, which also spawned a short series of posts.

 

I want to wish you all a happy and profitable 2014!

The VIX:VXV Ratio

The VXV is the VIX’s longer-term brother; it measures implied volatility 3 months out instead of 30 days out. The ratio between the VIX and the VXV captures the differential between short-term and medium-term implied volatility. Naturally, the ratio spends most of its time below 1, typically only spiking up during highly volatile times.

VIX VXV Ratio Chart

It is immediately obvious by visual inspection that, just like the VIX itself, the VIX:VXV ratio exhibits strong mean reverting tendencies on multiple timescales. It turns out that it can be quite useful in forecasting SPY, VIX, and VIX futures changes.

Short-term extremes

A simplistic method of evaluating short-term extremes is the distance of the VIX:VXV ratio from its 10-day simple moving average. When the ratio is at least 5% above the 10SMA, next-day SPY returns are, on average, 0.303% (front month VIX futures drop by -0.101%). Days when the ratio is more than 5% below the 10SMA are followed by -0.162% returns for SPY. The equity curve shows the returns on the long side:

short term EC

Long-term extremes

When the ratio hits a 200-day high, next-day SPY returns have been 0.736% on average. Implied volatility does not fall as one might expect, however.

More interestingly, the picture is reversed if we look at slightly longer time frames. 200-day VIX:VXV ratio extremes can predict pullbacks in SPY quite well. The average daily SPY return for the 10 days following a 200-day high is -0.330%. This is naturally accompanied by increases in the VIX of 1.478% per day (the front month futures show returns of 1.814% per day in the same period). It’s not a fail-proof indicator (it picked the bottom in March 2011), but I like it as a sign that things could get ugly in the near future. We recently saw a new 200-day high on the 19th of December: since then SPY is down approximately 1%.

200d high cumulative

 

This is my last post for the year, so I leave you with wishes for a happy new year! May your trading be fun and profitable in 2013.