Hack the market

This weekend I read Jason Zweig’s “Will leveraged ETFs Put Cracks in Market Close?” which references a paper by Minder Cheng and Ananth Madhaven at Barclay’s.   I tried, but couldn’t find their original paper over the weekend.  As luck would have it from across the internets Paul Kedrosky came to the rescue with a post referencing that paper, “The Dynamics of Leveraged and Inverse Exchange-Traded Funds“.

If you have any interest in ETFs, then you should read this paper carefully as it provides a very nice and accessible mathematical treatment of leveraged and inverse ETFs.

I’ve had success using ETFs in portfolio-oriented strategies to conveniently provide specific exposures, eg, to emerging markets.  I’ve also explored strategies that pit ETFs against futures and similar arbs that take advantage of contract rolls or other anomalous behaviors across the markets.  But I’ve never looked at ETFs the way they really should be understood: as structured products that should have well-defined (if not necessarily obvious) properties.

Like many structured products, some of these characteristics are not obvious and may be quite unintuitive but are always important to understand.  For instance, the hedging required to implement these funds is both non-linear and asymmetric.

Specifically, leveraged ETFs must re-balance their exposures on a daily basis to produce the promised leveraged returns. What may seem counterintuitive is that irrespective of whether the ETFs are leveraged, inverse or leveraged inverse, their re-balancing activity is always in the same direction as the underlying index’s daily performance. The hedging flows from equivalent long and short leveraged ETFs thus do not “offset” each other. [...]

The impact is particularly significant for inverse ETFs. For example, a double-inverse ETF promising -2X the index return requires a hedge equal to 6X the day’s change in the fund’s Net Asset Value (NAV), whereas a double-leveraged ETF requires only 2X the day’s change. This daily re-leveraging has profound microstructure effects, exacerbating the volatility of the underlying index and the securities comprising the index.

Hence Mr Zweig’s concern that these ETFs feed the volatility we’ve seen for the last 8 months or so near the market close.  If the day has been up then both “bull” and “bear” levered ETFs will need to buy in order to stay hedged – reinforcing the trend and effectively supporting serial correlation of returns.

Read more…

Competition has forever been fierce and at times may not be entirely fair.  Thus, a student of the market must be ever aware of the trends around them so they can promptly identify growing areas of opportunity which haven’t yet been revealed to the majority.  Mr Madoff made a very good living (while it lasted) offering clients a steady ~10% return on their investment.  Bush league stuff, it turns out.  The real maestros of money are doing rather better.

Accounting and legal researchers at the University of Kansas have identified a bull market in influence-peddling: returns on the order of 22,000% for firms who “invested” in lobbying efforts to favorably modify the tax code.  These people obviously learned that it’s important to play by the rules.

I’ve written some decent strategies and have been blessed with moments of great luck, but I’m ashamed to note that I’ve never gotten remotely close to these kinds of returns.  Can you imagine the sharpe ratio these guys can claim?  And it’s a repeatable process.  Although the Kansas researchers don’t mention it, there are many other cases of such legal arbitrage as pointed out in an AP piece on the subject:

The nonpartisan group recently released a study comparing the amount spent by bailed-out banks on political contributions and lobbying with the amount of money they got from the Wall Street rescue fund, known as the Troubled Asset Relief Program. The results produced eye-popping rates of return, an overall 258,449 percent for the $114 million they spent on campaign donations and lobbying.

Now this number – ~260,000% ROI – is clearly a bit inflated as $114M barely covers what Citi paid out to Mr Rubin for his services over the relevant period, but we’re probably in the ballpark.  Perhaps the banks only made 100,000% on their investment, but we can still see why they’re “the pros.”

I’m wracking my brains trying to figure out how to shoe-horn this marvelous alpha-generator into my trading algorithms.  I confess that I haven’t yet figured it out.  But I take solace in the knowledge that, as an American, I have the best government money can buy!