1 – Short every gap up. Cover either when the gap is filled or if not, at the close.

% Profitable: 74

Avg Gain: 3bps

Count: 2530

Std: 66bps

t 2.6

2 – Short every gap up. Cover either when the gap is half filled or if not, at the close:

% Profitable: 85

Avg Gain: 3bps

Count: 2530

Std: 49bps

t 2.6

The data is robust and significant. But 3bps in profits is useless, as it would all be eaten up by commissions and slippage. That doesn’t mean there is not something useful about this data, just that basic stats on fading gaps is the start of the search for a good trade, not the end.

]]>Going back to January of 2009, we found 19 occurrences. The average return of the Russ was a loss of 1.2% with a Standard Deviation of 3%. The results are not all that significant statistically, but the tendency seems towards mean reversion.

But then we looked at the equity curve of this trade over the years:

As you can see, for a while the system was great for catching breakouts, before it became great for mean reversion. To us, that means there is really nothing here and we can’t say we know anything by observing how the R2k behaves compared to the S&P on any given day. But this is a great example of how even quantitative testing is as much art as it is science. How does one treat a pattern that flip flops? How far back do you test? Is it curve fitting if you add another variable to try to smooth it out?

These are all important questions for any quant to ask, and the answer is as much about personal style and preference as it is about math and statistics.

]]>Futures margin requirements exist because the exchanges guarantee all trades so they want market participants to put up collateral against future losses. Logically, how much collateral is required should be based on the potential losses on the position. One way of measuring such is to look at market volatility along with the multiplier on the futures contract.

For example, during the April 25 24 hour trading session, Comex Silver had an over 4 pt high to low range. With a multiplier of $5000 per contract, someone who caught the high and the low could have lost or made over $20,000. Using the then Comex initial margin requirement of $11,745, traders were theoretically risking losing twice their margin capital in one session. To put that into perspective using today’s mini S&P 500 futures contract, the Spoo would have to make an over 100 pt move in the span of one trading session to bust through as much margin capital.

To analyze the thinking behind the 7 different margin hikes at the Comex this year, we constructed a ratio of the recent dollar volatility over the prior month before the margin hike to the pre-hike initial margin requirement. (Our dollar volatility was measured as the prior 21 day standard deviation of 1 day moves times the contract multiplier).

As the table below demonstrates, the amount of margin coverage has actually been falling, despite the various hikes, thanks to the exploding volatility in the Silver market. The numbers speak more towards the exchange trying to keep up with increasing volatility than an attempt to reign in the market.

Going forward, the bigger question is whether there is anything predictive about changes in margin requirements.

]]>As it turns out, the S&P return component totally dominates the overall portfolio performance, apparently because stocks are a lot more volatile than bonds. Another way to visualize this is to look at the 12 month rolling correlation between the “just stocks” portfolio and the “stocks + levered bonds” portfolio.

All of this begs the question: why a mix of stocks and bonds in the first place? The whole idea of the combined portfolio, often in a 60/40 allocation, is one of the most common practices on Wall Street. But does it necessarily make sense? There are several ways to approach this question, and as a starting point we’d like to offer the following chart of the rolling 12 month correlation between the S&P 500 and US Treasuries.

]]>Unlike a protective put buying strategy or a long position in Vix futures, bonds have positive carry. The best way to test the merits of a hedging strategy is to compare the individual performances of the market, the hedge, and the combined entity. So we tested the following scenarios:

- 100% Allocation to S&P 500
- 100% Allocation to US Treasury Bond futures (returns don’t include t-bills)
- 100% Allocation to S&P 500 cash and 100% to US Treasury Bond futures rebalanced monthly

Here’s a plot of the returns for each portfolio from 1987 to present.

Here is the statistical breakdown of the results:

(Data source: St Louis Fed FRED Database, Robert Shiller)

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