Where in the World is MarketSci?
It’s been eerily quiet around the MarketSci blog the last month or so.
I appreciate all of the emails asking if we’ve given up on this blogging thingamajig or if we got hit by a milk truck. Luckily, it’s nothing that sinister.
I’ve been going to extremes lately.
On one hand I’ve been very focused on some serious for-profit issues that have been on my to-do list for a while. And on the other I’ve been getting a bit of very much not serious R&R in – mostly training the new Lab-mix puppy to be a running/hiking machine (and not eat my shoes).
Unfortunately, that hasn’t left much time for everything in the middle (like this blog), but I’m starting to feel the creative juices flowing again, so expect more geekery in the near future.
P.S. there are now two of us in the investment blogging world: checkout Michael Stokes, President of the Financial Coaching Group [not me]. Damn I hope this guy makes it big so I can ride the coattails of all his Google searches =)
Happy Trading,
ms
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Filed under: Random Stuff | 13 Comments
All of the results below have been independently-audited in real-time by at least one third-party. Visit MarketSci.com for links to third-party audits and to learn more about accessing our strategies via a managed account or subscription.
Note to YK managed accounts: per Scott Daly, you returned a higher -0.4% (gross) for the month. There was a trading error in our tracking account that led to the -3.1% reported here. For consistency, I’m using the lower figure moving forward.
Performance has been tepid the last few months – we’ve been spinning our wheels not going forward or backwards as this market grinds up. I’m bored to no end with recent performance, but confident that all will be good and right in the world as this market settles in.
For a more detailed look at the breakdown in short-term mean-reversion the last few months (something we lean on heavily), refer to our most recent State of Short-term Mean-Reversion report.
One small update: we’re entering a new strategy niche this month with our Enhanced S&P 500 Index:
Most of our strategies target absolute returns, meaning they have little correlation to the broader market and are designed to profit regardless of market conditions.
The Enhanced S&P 500 Index is something very different. This program is designed to move like the market, but to do it with about half the downside risk. Put another way, we’re attempting to build a better, smoother S&P 500.
Specifically, we have four goals over the life of the program: (1) outperform the S&P 500, (2) reduce S&P 500 volatility by half (annualized based on monthly returns), (3) reduce average and peak S&P 500 drawdowns by half, and (4) exhibit greater than 80% correlation to the S&P 500 (based on monthly returns). [read more]
I’m not sure how much I’ll talk about enhanced indexes on this blog – this is really targeted towards institutional money and my readers tend to be high-vol. absolute-return types. But it’s out there and we’ll be updating stats monthly. Note that because this is not an absolute-return program, we will not be including it in our combined performance graph.
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The equity curve below shows our combined real-time monthly performance vs the S&P 500, assuming an equal investment in each family’s flagship program: MarketSci ProFunds (through 08/2009), RH S&P 500, YK (A and B), and Scotty.
COMBINED REAL-TIME PERFORMANCE vs S&P 500
SUMMARY OF ALL PORTFOLIOS SINCE INCEPTION
SORTED FROM MOST TO LEAST AGGRESSIVE *
Notes: (1) results account for transaction costs, but not subscription or managed account fees, (2) YK(B) returns reflect performance after addition of “abnormal market filter” in late October, 2008 (read more), (3) table sorted from highest to lowest measured volatility and may not reflect future performance.
* * *
One of the ways I justify spending my time on this blog is it gives me an opportunity once a month to share these independently-audited trading results. I really hope you enjoy my ramblings each week, but developing these proprietary strategies is really what I do, and I invite you to find out more about accessing our strategies via a subscription or managed account.
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, or following us on Twitter.
Filed under: My Performance | 14 Comments
*** CLICK TO ZOOM ***
This is our monthly health check of short-term mean-reversion in the US market.
Why a health check? Because short-term MR (by “short-term”, think for example RSI(2)) is so important to what we index swing-traders are doing right now because at this moment in history, it’s the most effective directional trade.
See the July and August reports for details re: how this report is calculated. In a nutshell, we’re using both daily mean-reversion (the likelihood that down days follow up days, and vice-versa) and RSI(2) as simple proxies for all other short-term strategies. I would never recommend anyone actually trade either as I’ve defined them here, but I think they make a good proxy because this tendency for the market to retrace very recent gains is exactly why all of these short-term indicators work the way they do.
What is the state of short-term mean-reversion?
Very much under the weather.
3-month averages for the two metrics I think best capture short-term MR, “Return vs Vol” and “RSI(2) Stretch” (upper right and lower right graphs), are hovering near their lowest levels since short-term mean-reversion became the play du jour around the turn of the century. Both metrics have reached much lower points in individual months, but have rarely failed this consistently for this long.
Back in the real-world, I’ve seen a number of alt.-investment programs, that I know are trading short-term MR in some form, go off the rails the last few months. We’ve been fortunate that, despite leaning heavily on short-term MR in our own programs, our combined performance has been more or less flat.
Do I think short-term MR will stage a comeback? Yes. I think the breakdown over the last few months is tied to the strong protracted rally, but that this slow grind up will come to an end and that short-term MR will again be the play du jour once we get to the other side. Do I know that with any certainty? Absolutely not.
More to follow.
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, or following us on Twitter.
Filed under: State of Short-term MR | 7 Comments
All of the results below have been independently-audited in real-time by at least one third-party. Visit MarketSci.com for links to third-party audits and to learn more about accessing our strategies via a managed account or subscription.
Apologies for the late report this month…been buried.
August was a very blah month across the board as most of our strategies had little exposure to the market as a result of the abnormal market filter.
RH was the month’s leader, making a bit of headway chipping away at July’s drawdown, and is up again nicely so far this month. YK gave back a bit of last month’s big gains and is still struggling at the moment.
Two Big Changes to Talk About
First, the original MarketSci strategies…
We’ve been alluding to this coming down the pipe for a while: I officially retired the original MarketSci strategies effective the end of August.
These were my first foray into developing programs professionally, and they’ve had an outstanding run over the last 44 months. The flagship ProFunds program was ranked #1 at Theta Research for risk-adjusted performance in its first two years trading, and we were able to do some real good for folks. I’m happy about that.
But I just don’t feel that these strategies represent our best work today, or are as robust as the strategies I talk about on this blog or those we represent through our Timer Seeds program. Though the loss of revenue is always painful, I can’t accept not putting our best foot forward.
Of course, unlike some less savory characters in this business, we will be carrying the original MarketSci programs indefinitely in our summary stats and combined portfolio graph (ending 08/2009), and independently-verified results will always be available.
And second, to RH…
For the uninitiated, RH is a product of our Timer Seeds program and is the only strategy I talk about on this blog that I didn’t directly develop. Because of that, and the fact that I try not to impose my own thoughts on our Timer Seeds (lest they all start to look the same), RH doesn’t include things like the abnormal market filter.
But July made painfully clear that group-think be damned, some of those concepts needed to be applied to RH, and I’ve worked with the developer to do just that.
A new overlay was applied to RH late in August. By overlay I mean that I’m not changing the developer’s underlying signal (long/short/cash) so RH’s success or failure is still squarely on the shoulders of RH. But we’ll be reducing exposure at times to reduce downside volatility (hopefully without sacrificing return). Managed account holders will have already noticed drastically reduced position sizing.
* * *
The equity curve below shows our combined real-time monthly performance vs the S&P 500, assuming an equal investment in each family’s flagship program: MarketSci ProFunds (through 08/2009), RH S&P 500, YK (A and B), and Scotty.
COMBINED REAL-TIME PERFORMANCE vs S&P 500
SUMMARY OF ALL PORTFOLIOS SINCE INCEPTION
SORTED FROM MOST TO LEAST AGGRESSIVE *
Notes: (1) results account for transaction costs, but not subscription or managed account fees, (2) YK(B) returns reflect performance after addition of “abnormal market filter” in late October, 2008 (read more), (3) table sorted from highest to lowest measured volatility and may not reflect future performance.
* * *
One of the ways I justify spending my time on this blog is it gives me an opportunity once a month to share these independently-audited trading results. I really hope you enjoy my ramblings each week, but developing these proprietary strategies is really what I do, and I invite you to find out more about accessing our strategies via a subscription or managed account.
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, or following us on Twitter.
Filed under: My Performance | 8 Comments
*** CLICK TO ZOOM ***
This is our monthly health check of short-term mean-reversion in the US market.
Why a health check? Because short-term MR (by “short-term”, think for example RSI(2)) is so important to what we swing-traders are doing right now, because at this moment in history, it’s the most effective directional trade.
See the July report for details re: how this report is calculated, but in a nutshell, we’re using daily mean-reversion as a simple proxy for all other short-term strategies. Put another way, we assume a trader went long the S&P 500 at the close if the market closed down, and short if it closed up, and look at the results each month in terms of (a) average daily return, (b) average return relative to volatility (daily SD), and (c) win percentage.
I would of course never recommend anyone actually trade this strategy, but I think it makes a good proxy, because this tendency for the market to retrace very recent gains is exactly why all of these short-term indicators work the way they do.
A New Addition: RSI(2) Stretch
Note that I’ve also added a fourth metric: RSI(2) Stretch.
The problem with looking at short-term MR in a purely binary sense (up days and down days) is that it doesn’t capture the fact that at this moment in history the more the market becomes stretched, the more likely it is to retrace (like a rubber band).
For example, consider four fictional daily returns: -0.3%, -0.3%, -0.3%, +0.5%.
Binary daily mean-reversion would see that sequence as a failure because it would have been equally long on days 2, 3, and 4, resulting in a negative total return. But an indicator based on the stretch of the market (like scaling in/out of RSI(2)) might not have ratcheted up exposure until day 4 (if at all), meaning that that sequence might have been profitable.
The RSI(2) Stretch graph tries to capture this by looking at the return vs. vol. of a strategy that goes long or short based on how close RSI(2) is to its extremes. An RSI(2) reading of 0 would equal 100% long exposure, a reading of 25 = 50% long exposure, 50 = no exposure, 75 = 50% short exposure, 100 = 100% short exposure, etc (and all points in between).
So what is the current state of short-term mean-reversion?
Depending on how you play it, it’s been under the weather the last two months.
July performed well in a binary sense, but very poorly in terms of stretch. Interestingly, I saw this same disparity in my own strategies. YK approaches daily MR in a more binary sense and performed very well last month (+13.0%), while Scotty looks at daily MR in a more stretched sense and performed poorly (-1.4%).
This month, it was binary MR that performed poorly, while stretched MR was neutral. And more importantly, 1-year averages for the metrics that matter most have fallen very close to 5-year averages.
Short-term MR has clearly lost some of its steam relatively to its peak about a year ago. I’m not going to get too excited about these results just yet, but it’ll be very interesting to see if this trend continues over the coming months.
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, or following us on Twitter.
Filed under: State of Short-term MR | 11 Comments
