This note was originally published at 8am on October 29, 2013 for Hedgeye subscribers.
“The new coins helped to wash away the old aristocratic order.”
That, of course, is not what the 16th century European aristocracy had in mind. As my man Jack Weatherford explains in an excellent chapter of Indian Givers, “Silver and Money Capitalism”, “the silver coins at first promised to strengthen the feudal order…” (pg 19). Never blindly believe what the government promises you.
Weatherford first penned Indian Givers in 1988 (then updated it in 2010) after writing about the history of porn in Japan in 1986. His writings are some of my favorites in economic history because his narratives are fully loaded with the inconvenient truths about government plans versus outcomes.
You can only lie to The People about policies that aren’t working for so long. In the end, the history of markets, money, and businesses are marked-to-market. And even though it may take a long-time for bad policy (like burning your currency) to fail, I thoroughly enjoy the thought of my son or daughter reading about how the 2013 Fed sucked in so many group-thinkers.
Back to the Global Macro Grind…
There’s another Indian Giver making headlines this morning:
BREAKING: Rajan Raises Key Rate to Fight Inflation –Bloomberg
Booyah! That’s right, yo. India’s got a new central banker in the house- and he goes both ways (on rates). This is the 2nd interest rate HIKE in 2 months for Governor Raghuram Rajan. And the Indian stock market absolutely loved it, closing up +1.65%!
Huh? I thought that the other 90% of Bloomberg/CNBC headlines have been implying that if the US, Europe, or any country were to raise rates that the world as we know it would end?
Newsflash: it would.
But like during the 17th century enlightenment, it would end for the better! #EndofBackwardness
Indian Giver giveth to The People of India the following via a rate hike:
2. Lower currency adjusted inflation
3. Breakout in Indian stock market
And yes, everything in the land of causal currency policy action is relative, but consider the alternative model (which Bernanke, Yellen, and most French Bureaucrats are begging for – Down Currency, Down Rates):
Then, Rajan raised rates (twice) and:
The Keynesian-anti-dog-eat-dog-currency-debauchery-department at Dartmouth better get on this. This Indian Giver is going off the reservation versus what they’re teaching undergrads for $63,282/yr.
It’s hockey season, so it’s a good time to take a shot at Dartmouth’s Big Green Keynesian mouthpiece-in-chief, dogmatic Danny Blanchflower. He’s the guy you may have seen recently on Twitter with his jersey yanked over his head by @HedgeyeSnakeye and @DanHannanMEP (Todd Jordan and Hedgeye fav Daniel Hannan).
Blanchflower was the guy who warned that British austerity was going to mean #EOW (end of the world) for the UK economy a few years back. He’s also of the ideology that a #StrongEuro and #StrongPound is bad for “exports”, or something like that.
In other news…
The slope of UK economic growth just clocked a 3-year high and both the British Pound and British stock market (FTSE) are breaking out to new highs as the world comes to realize that ending Mervyn King’s QE Pound Getting Pounded experiment hath ended.
No, I’m not saying that India and the UK are seeing economic growth booms. I’m simply reminding you that this is the only way out of a Down Currency, Rate Repression government policy.
No, the aristocratic order of Big Government Intervention doesn’t like paying The People instead of plundering them via currency devaluation taxes. And I for one like that very much.
Our immediate-term Risk Ranges are now as follows (we have 12 Big Macro Risk Ranges in our new Daily Trading Range product):
UST 10yr Yield 2.40-2.57%
BSE Sensex 20132-21279
Best of luck out there today,
Keith R. McCullough
Chief Executive Officer
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Takeaway: Hedgeye TREND resistance for US Dollar Index is $81.29
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Will the foreign exchange market reverse all of last week’s US Dollar's gains? Hedgeye TREND resistance for US Dollar Index is $81.29
Trade :: Trend :: Tail Process - These are three durations over which we analyze investment ideas and themes. Hedgeye has created a process as a way of characterizing our investment ideas and their risk profiles, to fit the investing strategies and preferences of our subscribers.
Anything longer than 3 years is unpredictable
Takeaway: Our [new] innovative quantitative tools can help you consistently generate alpha on both the long and short side of the US equity market.
A few months back, we published a note tilted, “MACRO MEETS MICRO: ARE YOU HUNTING WHERE THE FISH ARE IN THE US EQUITY MARKET?” in which we introduced our US equity market screening application.
The model is designed to triangulate sell-side, buy-side and insider sentiment on a particular stock, recording deviations in those metrics (from the sample) in order to systematically produce a list of names that may be under or over-owned; we consider that to be a good starting point to dig into the long or short side of a particular ticker(s) from a bottom-up perspective.
In the months since publishing that note, we’ve greatly expanded upon the model, sourcing valuable feedback from our institutional client base. Noteworthy changes include:
Please CLICK HERE to download the Excel file containing the latest refresh of the model and its summary results. For more information on how the model works, the associated backtest statistics or strategies for how best to apply it to your specific investment process or mandate, please review the following three sections.
***Email us if this is something you’d like to see more often or to have the sample customized for a specific coverage universe.***
1. HOW THE MODEL WORKS
The model is setup as a quantitative screen that assigns +/-1 point for a specific ticker's reading being in excess of [1x] standard deviations from the sample mean, for each of the following three metrics:
The model produces scores for each ticker ranging from -3 to +3 on an integer scale. For example, a reading of +3 signals extreme negative sentiment amongst both the sell-side (+1) and buy-side (+1) amid extreme insider buying (+1), while a reading of -3 would signal extreme positive sentiment amongst both the sell-side (-1) and buy-side (-1) amid extreme insider selling (-1).
2. BACKTEST RESULTS
Interestingly enough, the model was initially setup as a contrarian screening tool and the -3 to +3 scale was setup with the assumption that names the model signaled as under or over-owned would subsequently mean revert from a performance perspective.
What we learned in the backtesting phase, however, is that names which “the market” loved the most were typically rewarded with subsequent outperformance of considerable magnitude over the intermediate-to-long term (as defined by 1Y forward returns). Moreover, names that the market disliked the most were typically punished with subsequent substantial underperformance. Furthermore, the hit rate of positive absolute performance is substantially higher for names which "the market" loved the most that it is for names in which "the market" greatly disliked.
Additionally, names that the market “learned to love” in a short time (as defined by its score dropping -2pts over the span of one month) generally outperformed those that the marked “learned to hate” (as defined by its score growing +2 over the span of one month).
Using these results, we have decided to assign any ticker that scores a -3 or -2 as a compelling LONG idea and any ticker that scores as a +2 as a compelling SHORT idea going forward.
In summary, there appears to be some element of efficient markets present in these backtesting results. While this is certainly not the proper forum to debate the merits of the Efficient Market Hypothesis, we can reasonably conclude that “the market” itself can be a reliable tool for identifying good opportunities on both the long and short side.
It also lends support to our belief that momentum exists in the market place over the immediate term, intermediate term and long term durations, which is precisely why we use a three-factor quantitative risk management model to identify key levels of breakout/breakdown risk in specific securities and/or asset classes.
Lastly, the only potential draw-back to interpreting these results at face value is the lack of historical data beyond MAR ’10 (that’s as far as Bloomberg’s insider ownership change data goes back). While the mini-crises of summer 2010 and 2011 are certainly included in the sample, we’d ideally like to see how the model would perform across multiple market cycles (i.e. 2007-09 would be a good place to start).
All that being said, using end-of-month observations for each ticker in the Russell 3000 Index, we were able to produce 86,976 subsequent 1Y forward return data points to analyze spanning MAR ’10 to OCT ‘12. We’d argue that’s plenty robust enough of a sample to work with.
3. USING THE TOOL EFFECTIVELY
Offhand, we think there are two types of primary users for this tool:
Lastly, all interested parties should feel free to ping us for our proprietary risk management levels on any given ticker(s). As you know, we are hyper-focused on timing, so allowing us to flag names that are breaking out or breaking down from an immediate-term TRADE or intermediate-term TREND perspective should only enhance the probability of generating alpha from this process.
Associate: Macro Team
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