Back in 2012, I penned a friendly debunking of TradingMarkets.com’s RSI(2) mean-reversion strategy for trading the volatility ETN XIV.

The thrust of the post was that TM only tested the strategy back to the launch of XIV, which led them to write “they had never seen numbers like this in equity trading”, but had they tested the strategy back to 2004 (which we can do, and so can you), they would have found the strategy wasn’t nearly as solid as it first appeared.

Volatility Made Simple has posted a further follow up showing that TM’s strategy would have greatly improved if we only took those trades that agreed with the state of the VIX futures term-structure. From VMS:

20140318.01

I love this type of vertical blogging and thought I would repost here.

I would note however that this strategy has only begun to become successful in very recent history, most of which coincides with a tidy bull market when dip-buying strategies inherently do well.

For that reason, and just my general dislike for Martingaling such a potentially portfolio vaporizing instrument like XIV or VXX, I would still stay away from putting too much faith in this strategy.

Happy Trading,
ms

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As previously mentioned, I’ll no longer be issuing day-of-month seasonality maps each month.

I worried that MarketSci was becoming the “DOM Seasonality Blog” when it’s not really a big contributor to where my trading has gone the last couple of years (volatility ETPs are the play du jour, and the forces that drive them are more complicated than equities, meaning DOM seasonality is less impactful).

For those still interested in the subject, I’ve previously shown more or less how I generated the maps here, here, and here, including an Excel workbook so readers could generate the map on their own. Note that I tweaked the method a bit in the posts I’ve done over the last 17 months, but the workbook will get you very, very close.

Happy Trading,
ms

* * * * *

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I’m considering whether to discontinue these monthly day-of-month seasonality posts. I’ve been doing these for 16 months now with excellent results: the S&P 500 on the best half of days has returned more than double the worst half of days (26% versus 10% annualized). Those numbers are real-time, not backtested.

But I worry that MarketSci is becoming the “DOM Seasonality Blog” when it’s not really a big contributor to where my trading has gone the last couple of years (volatility ETPs are the play du jour, and the forces that drive them are more complicated than equities, meaning DOM seasonality is less impactful).

In the meantime, enjoy the DOM seasonality calendar for February. Quartile 1 indicates the strongest of days and quartile 4 the weakest.

20140129.01

Geek note: the calendars I post here are based on a more robust version of the approach used in the posts here, here, and here in which, using a simple walk-forward test to minimize hindsight bias, I showed that trading the days of the month that have been strong historically has consistently led to much stronger future returns.

As I stressed when I introduced the concept, day-of-month seasonality never justifies a trade all by itself, but I do think it deserves to be one of many tools in the trader’s toolbox.

Happy Trading,
ms

. . . . .

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Last year, using a simple walk-forward test to minimize hindsight bias, I showed that trading the days of the month that have been strong historically has consistently led to much stronger future returns. That’s as true today as it was in 1950. Read more, more, and more.

Below are seasonally strong/weak days of the month for January, broken out by quartiles. Quartile 1 indicates the strongest days and quartile 4 the weakest.

20140104.01

Real-time results since I began sharing the calendar in late 2012 have run inline with the historical test.

The S&P 500 has averaged 0.11% (31% annualized) on the best half of days versus 0.06% (16% annualized) on the worst half.

Quartile 4 days (the worst of days) have been particularly bad, with an average return of -0.06% (-14% annualized).

As I stressed when I introduced the concept, day-of-month seasonality never justifies a trade all by itself, but I do think it deserves to be one of many tools in the trader’s toolbox.

On a personal note, my blogging has been light as of late. I’ve been away working on other projects, for-profit and otherwise (but mostly otherwise). Eventually my drive to post often will return as it always does, but in the meantime, my trading (actual, real-time, and verifiable) continues to shine. To stay up to date on the performance of our strategies, visit MarketSci.com.

Happy Trading,
ms

. . . . .

To stay up to date with what’s happening at the MarketSci Blog, we recommend subscribing to our RSS Feed or Email Feed.


Last year, using a simple walk-forward test to minimize hindsight bias, I showed that trading the days of the month that have been strong historically has consistently led to much stronger future returns. That’s as true today as it was in 1950. Read more, more, and more.

Below are seasonally strong/weak days of the month for December, broken out by quartiles. Quartile 1 indicates the strongest days and quartile 4 the weakest.

20131202.01

Real-time results since I began sharing the calendar in October, 2012 have run inline with the historical test.

The S&P 500 has averaged 0.11% (33% annualized) on the best half of days versus 0.05% (12% annualized) on the worst half.

Quartile 4 days (the worst of days) have been particularly bad, with an average return of -0.08% (-19% annualized).

As I stressed when I introduced the concept, day-of-month seasonality never justifies a trade all by itself, but I do think it deserves to be one of many tools in the trader’s toolbox.

On a personal note, my blogging has been light as of late. I’ve been away working on other projects, for-profit and otherwise (but mostly otherwise). Eventually my drive to post often will return as it always does, but in the meantime, my trading (actual, real-time, and verifiable) continues to shine. To stay up to date on the performance of our strategies, visit MarketSci.com.

Happy Trading,
ms

. . . . .

To stay up to date with what’s happening at the MarketSci Blog, we recommend subscribing to our RSS Feed or Email Feed.




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