Home » Research Blog » Fiscal policy criteria for fixed-income allocation

Fiscal policy criteria for fixed-income allocation

Jupyter Notebook

The fiscal stance of governments can be a powerful force in local fixed-income markets. On its own, an expansionary stance is seen as a headwind for long-duration or government bond positions due to increased debt issuance, greater default or inflation risk, and less need for monetary policy stimulus. Quantamental indicators of general government balances and estimated fiscal stimulus allow backtesting the impact of fiscal stance information. Empirical evidence for 20 countries since the early 2000s shows that returns on interest rate swap receiver positions in fiscally more expansionary countries have significantly underperformed those in fiscally more conservative countries. Indicators of fiscal stance have been timely, theoretically plausible, and profitable criteria for fixed-income allocations across currency areas.

A Jupyter notebook for audit and replication of the research results can be downloaded here. The notebook operation requires access to J.P. Morgan DataQuery to download data from JPMaQS, a premium service of quantamental indicators. J.P. Morgan offers free trials for institutional clients.

Also, there is an academic research support program that sponsors data sets for relevant projects.

The below post is based on proprietary research of Macrosynergy.  

This post ties in with this site’s summary on systemic value generation with macro trends.

Fiscal policy and fixed-income markets

Fiscal policy is widely recognized as a powerful force in fixed-income markets. Government budget policy determines public borrowing requirements, shapes debt dynamics, and influences aggregate spending in the economy. An expansionary fiscal stance typically refers to a policy of increased deficits and borrowing that supports aggregate demand in the economy. Conversely, a contractionary fiscal stance refers to a policy of deficit reduction and dampening effects on aggregate demand. The fiscal policy stance plausibly affects the prices of government bonds and interest rate swaps through three main channels:

  • Bond supply channel: Expansionary fiscal policy requires higher deficits and larger net borrowing requirements. All other things equal and in equilibrium, these require somewhat greater incentives of the private sector to add fixed-income risk to their portfolio.
  • Debt sustainability channel: Higher deficits mean a less favorable project public debt trajectory. At varying degrees, this translates into a greater risk of default or inflation and, hence, principally justifies a rise in risk premia on longer-term fixed-income exposure.
  • Economic growth channel: Expansionary fiscal policy leads, all other things equal, to stronger demand and growth relative to the economy’s potential. This lessens the need for monetary policy accommodation and increases the risk of monetary policy tightening.

There are two main indicators of the fiscal stance.

  • The first is the general government budget deficit, maybe relative to a sustainable threshold. A high deficit relative to what may be considered “normal” or “sustainable” indicates expansionary policy from a medium-term perspective.
  • The second is “fiscal thrust” of “fiscal stimulus“, a measure of the discretionary change in policy that tracks the addition of fiscal support to the economy in the current year versus the previous. Naturally, such indicators are just proxies and do not account for potential countervailing policies, such as central bank bond purchases, but by themselves, their negative directional impact on the fixed-income market is not controversial.

Put simply, a high deficit and a strong fiscal stimulus should on their own be negative for fixed-income returns. A low deficit or surplus and negative fiscal thrust (“fiscal tightening”) should be positive for fixed-income returns. If financial markets are not fully information efficient with respect to tracking governments’ fiscal stance consistently across countries, we should expect that currency areas with more expansionary fiscal policies see underperformance of (low-risk) rates positions’ returns versus those of countries with more contractionary policies. And if this holds true, the fiscal policy stance across countries would be a plausible criterion for allocating fixed-income portfolios across currency areas.

It is important to distinguish directional and cross-country predictions based on fiscal indicators. A directional relation means that the fiscal indicator predicts the absolute return of a fixed-income instrument. Such predictions require the consideration of the cyclical position of the economy because often fiscal policy is “counter-cyclical”, for example by stabilizing the economy in downturns. In this case, the economic downturn and fiscal policy stance must be viewed in conjunction, as they affect low-risk fixed-income markets in opposite directions. A cross-country relation means that the relative policy stance affects relative fixed income return. Since business cycles are often global occurrences, this relative relation is more likely to be discerned even without considering business cycle indicators.

Simple quantamental indicators of the fiscal stance

We can approximate the concurrent observable fiscal stance of governments across countries and currency areas through two indicators of the J.P. Morgan Macrosynergy Quantamental System (“JPMaQS”). Quantamental indicators of this service are real-time information states of the market with respect to an economic concept and, hence, are suitable for testing relations with subsequent returns and backtesting related trading strategies. JPMaQS has collected concurrent-year fiscal ratios and derived concepts based on data vintages of the IMF Fiscal Monitor and World Economic Outlook. These only update three times a year (at the release of the report and at the change of the calendar year) but are comparable across countries are widely followed by market economists, and consider a broad range of factors that influence fiscal policies, not merely the budget law.

For empirical analysis, we consider the following currency areas: Australia (AUD), Canada (CAD), Switzerland (CHF), China (CNY), the euro area (EUR), the UK (GBP), Hong Kong (HKD), India (INR), Japan (JPY), South Korea (KRW), Mexico (MXN), Malaysia (MYR), Poland (PLN), Sweden (SEK), Singapore (SGD), Thailand (THB), Taiwan (TWD), Tukey (TRY), the U.S. (USD), and South Africa (ZAR). These include all major developed and emerging markets for which JPMaQS provides as of now a sufficient history of fiscal indicators and good-quality 5-year interest rate swap returns.

For tracking the fiscal stance in a comparable fashion across countries we focus on two sets of quantamental indicators:

  • General government balance ratios: General government is defined as the sum of central, state, and local governments including the social security funds controlled by these units. The ratio here means that the balances are set as a percent of GDP. Furthermore, we consider two types of balance ratios, the overall and the structural balance ratio. The overall balance ratio is based simply on the difference between consolidated revenues and expenditures in the current year, including debt service cost. The structural balance is defined as the difference between government revenues and expenditures in the current year, adjusted by the estimated effect of a broad set of transitory factors such as commodity shocks, housing, stock, and other asset price cycles, output composition, absorption effects, and one-off factors. The adjustment is estimated by IMF staff. View methodological notes here. The drawback of this more elaborate measure is that it often takes longer to update, due to the analytical work

  • General government fiscal thrust: Fiscal thrust, also called fiscal stimulus, measures the direct impact of fiscal policy on aggregate demand in the economy. Here it is approximated by the negative of the difference between a country’s (expected or estimated) structural balance as % of GDP in the current year versus the previous year. Since structural balances are adjusted for the impact of business cycles and terms-of-trade they are indicative of the stance of fiscal policy, i.e. the effect of discretionary fiscal measures on the economy. A positive value means that the structural balance shifts towards deficit and that fiscal policy looks expansionary. A negative value means that the structural balance has shifted towards surplus and that policy is restrictive.

We combine these two sets of indicators into a simple fiscal policy score. This is accomplished by averaging their normalized values (z-scores, winsorized at 3 standard deviations) and adding them such that budget balances and fiscal thrust each have a 50% weight. Note that the sign for fiscal thrust must be set to negative so that positive values of the scores consistently mean contractionary policies (good for fixed-income returns) and negative values for expansionary policies (bad for fixed-income returns). The 50-50 weighting is obviously not optimized but just the simplest plausible combination for checking the proof of concept. Then we take relative values of the fiscal expansion scores for each country versus all 20 countries (or as many as are available for a specific period) by simple subtraction. The results are relative fiscal policy scores.

An empirical review of the relative fiscal policy scores shows both cyclical fluctuations and medium-term trends. The scores would be a slow-moving and low-frequency criteria for cross-market positioning, suitable for moving lathe positions.

The target returns of the below analysis are fixed receiver positions in 5-year interest swaps, targeted at 10% volatility to allow comparable risk-taking across all currency areas, relative to a basket of the currency areas. Outperformance or underperformance of countries has often been persistent over months or even years.

Simple empirical evidence

Relative fiscal scores have indeed been positively correlated with subsequent relative IRS returns for the available panel of data. The probability of significance from 2000-2022 has been above 99% at monthly or quarterly frequencies. The correlation coefficient has been 5% at a monthly and 7% at a quarterly frequency, which is modest but respectable for a single low-frequency indicator that has not been optimized and uses no whatsoever market information. Also, a positive correlation was recorded for 80% of all years and 82% of all countries, which suggests that it has been a subtle but consistent predictive relation.

The accuracy of the fiscal score in predicting the direction of relative returns across the panel has been 51% and was above 50% in about two-thirds of all years. Also, a positive correlation with returns prevailed in 78% of all countries and 86% of all years. Looking at the two components of the fiscal score, high deficits and positive fiscal thrust also predicted lower swap returns individually.

The value generated by simply allocating fixed-income risk according to the fiscal expansion score has been considerable and quite consistent across time. The below shows an approximate PnL based on the standard normalized fiscal scores across all 20 countries (for the periods when signals were available and the market was tradable) and monthly rebalancing of positions in accordance with signal values. Positions are changed on the first trading day of the month and are assumed to have been updated by the beginning of the second trading day. The PnL chart has been normalized to 10% annualized volatility. This PnL is “naïve” insofar as we do not consider transaction costs and standard risk-management tools.

The long-term Sharpe ratio of this PnL has been 0.7. The Sortino ratio has been above 1. Correlation with either the U.S. equity or U.S. rates market has been near zero.

The above naïve PnL does not account for transaction cost. For a stand-alone strategy, which would take leveraged relative positions based only on the estimated fiscal stance, these costs could reduce returns significantly. However, in combination with other factors, such as carry and inflation dynamics, a fiscal overlay does not necessarily increase trading costs while almost certainly adding to overall performance. Most importantly, a fiscal overlay of standard capitalization-based fixed income allocation will plausibly even reduce transaction costs, as it would, on balance, reduce allocation to fiscally more expansionary countries, i.e. countries where governments tend to issue more debt and whose weight would therefore otherwise rather increase.


Related articles