The US bond market can be swayed by a variety of factors that affect their demand over time. Some of these factors are transitory such as quantitative easing but most are consistent. I have tried to think of them all but it comes down to what one might call – the these big three:
2. US economic strength
3. Investor fear
I can’t measure it using monthly data releases since they are too infrequent, but I can follow oil prices and the level of a currency of a commodity beneficiary – Australia. That’s all I need since most other commodities will either correlate highly with oil or be driven by its price (since it drives transport costs). I can try to add food commodities or price shocks that might affect inflationary expectations but when I study such things they are always reflected in one or both of my two chosen inputs.
Again, there are a variety of monthly government data releases but these are too old and too infrequent to do us any good. Quite simply, the best indicator of investor expectations about the economy come from the stock market. I already have an index that measures prospective upside for the S&P 500 so I’ll just use its inverse. That index does use bonds as an input but not their coincident price history so there is no overlap here. I am not using negative momentum of bond prices as an input to forecast near term bond returns.
I will once again make use of my synthetic Vix function – this time I apply it to the 10 year futures contract, since that is what I am forecasting. Since bond volatility is far lower than S&P volatility this variable is not as big a factor as it is in the case of the S&P index.
The question we must ask is – can you imagine a significant bond rally where oil, the A$ and the S&P are all rallying. Such rallies are extremely rare. That is the hard case since bonds have been rising over the last 30 years so the bear case is the big test. If the US $ is rallying, oil is falling and the stock market is declining (in the short term) then buying bonds is easy and that upward skew in any long term data set makes it look irresistible.
I honestly don’t think there is another important factor. (Please call me if you think of one.)
Look-backs and Durability
To be confident that the approach is durable we must have internal variables that are not too back-fitted to suit the last (say) 10 years. Here are some of those settings:
1. The synthetic version of Vix (“SynVix”) uses the same look back period as Vix (20 days).
2. The oil and A$ momentum length is set at 20 days and does not vary.
3. The equity index factor is less important than my inflation component.
The factors must be combined to create an index that oscillates between zero and one hundred in a useful way. This will not meaningfully change the nature of the calculation. In the end, if you follow the bond market, you will already have a feel for these inputs and you will frequently be able to anticipate the level of the index.
When Will This Fail?
The worst case for this approach is a huge foreign buyer or seller who is being driven by non-market forces. Even quantitative easing by the fed is alright because it takes place during periods of low inflation and weak stock market performance. If the Fed or (say) the government of China were to choose to buy huge quantities of bonds even when stocks were rallying and the US$ was rising, then this approach would fail. I am confident that we would foresee such conditions and at least temporarily suspend our usage of the index.
Another concern might be that our historical record of disinflation ends. Inflation makes a come-back and bonds trend steeply down. There is considerable monetary overhang that might finally get hit by a rise in money velocity. If so, I am counting on an associated rise in oil and a fall in the US$ which will help the A$. The stock market may rise or fall but the other factors should do their job.
The index is somewhat binary in nature – which I like. It spends a lot of time at extreme bullish or bearish levels. Here is the distribution:
If we were to simply buy bonds in proportion to the level of this index (Q= Index/50) so that the average position size over time were equal to one, then we could compare that performance to the performance of the contract itself over the last ten years. It should give us at least as good a return and protect us from significant pullbacks:
This is not a trading system per se because it has no exits or stops but serves the purpose of describing prospective gain.
Since we see so many readings at the extreme, we can wait to buy when we get above 90 and exit or short when we get below 15. These tables give us a sense of return skews:
The values here are all (approximately) less than a tenth of the average daily return. There is simply no reason to own bonds if this index is below 25.
The average daily return for US 10 year bond futures over the entire ten-and-a-half year period was .024 pts/day.
Time Frame Use
This is not an effort to provide a long term indicator particularly suited to measure the probability of a severe decline. The fact is, no one knows when a correction will be 2%, 5% or 10%. We have to be prepared for any of them.
Since the components of this index are generally rather sticky, the index is not that volatile. It is less volatile than my S&P index. Nevertheless, if we see a significant move in oil or the S&P then we must pay close attention.
This index will help time entries into currency trades when interest rates are the dominant variable. It will help less with respect to the stock market since we have many cases where bonds and stocks rally together over time and many where they are very negatively correlated. It may help indicate when to overweight utility stocks.
The index can be combined with my S&P index to provide an indicator for the “risk parity” trade where both S&P futures and bonds are bought. I shall describe that combination in a separate essay.
For bond traders who take positions where significant rallies or declines will affect their P&L, this index offers an enormously valuable input.