Contagion measure important in a crisis

Contagion is an important problem in finance. It does not happen often, but if you are not prepared for it, the cost can be high. Foremost, returns can swing quickly during a contagion event, but perhaps as important there can be a change in correlation between markets. The classic view is that correlations will move to one during a crisis. Risk will, of course, also increase with this higher correlation. Finally, the direction of causality will change as the contagion spreads. Causality will move from a primary driver to secondary markets. The spread can be measured which will help with nay portfolio decisions. 

A recent paper focuses on measuring contagion in the currency markets, see "A new way of measuring effects of financial crisis on contagion in currency markets", but more importantly, the authors look at the causal relationship that are generated during a crisis. The linking of markets during a contagion crisis is a risk management problem, but determining how the contagion spreads allows for better portfolio responses and the opportunity to generate profits. 

Contagions can be mapped as a network with the strength of the causal relationship measured by estimating the autoregressive properties of an asset with the autoregression betas of cross-assets, the network contagion part. The network contagion factor (NECOF) is the volatility explained by the cross-asset divided by the autoregressive volatility, the network contagion volatility and the error volatility.

 

Playing offense and defense with trend-following

There has been a significant focus on trend following as a defensive alternative investment. You hold the trend-follower because the strategy is expected to do well during periods of poor equity returns. The name "crisis alpha" has stuck to trending following as the shorthand descriptor. However, trend followers can make money when there are strong uptrends in markets. What trend-followers need are market divergences. If the equity market diverges to the upside, a trend-follower should make money, but the returns will, of course, be less than the returns of a pure equity investment. So, the results are very simple. Possible positive returns in all divergent environments, but excess returns versus stocks when equity markets fall and underperforms when the stock market rises.

Aspect Capital has come up with a new turn of the phrase called "unpredictability alpha" to explain the fact that trend-following can do well in both up and down market divergences. It is trying to cover more than crisis alpha, but I don't think it hits the mark. Let's stick with the basics from years ago, trend-following is divergent trading as opposed to convergent trading. Divergent trading makes money when prices move away from equilibrium level and are likely to trend. 

The important point is that trend-following can be both a defensive and offensive strategy. It can protect when key markets fall and it can make money when prices move to the upside. There is value with holding a strategy that can do both. 

Inflaton expectations - it is about the things you buy all of the time

Inflation has been the number one economic issue for both the Fed and consumers, yet many policymakers have focused on the inflation of the last few years as a supply shock from the pandemic that was abnormal. Inflation is returning to normal levels; however, the inflation of the last few years was anything but normal. There has been a focus on core inflation, but the headline and anti-core is what may drive expectations. 

The first chart shows what has been called anti-core inflation. This is the inflation associated with food and fuel costs. This is the inflation that consumers face every time they go to the store. Anti-core inflation was not just high but extraordinary. The spike hit 40% which was just below the highs in Great Inflation. Headline CPI was the highest in over 40 years which has driven expected inflation highs for the next five-year period. Given the experience of the last three years, inflation expectations will not just return to 2%. The Fed has a consumer expectation problem and lowering rates at this time will not solve this problem. 

Anomalies offer opportunities after they are reported

The paper "Anomaly Time" provides insights on very interesting methodological issue as well as further information on efficient market behavior.  The authors look at the timing of returns around the publication of news or anomalous information signals. Most academic publication form portfolios around a specific calendar data and not when data are produced. Think about this process. Portfolios, for academic work, are usually structure around June regardless of when the company data is really reported. If you look at the actual publicly reporting data, you will get a very different answer on many of the key anomalies that are reported in the academic testing. Who would have thought?

Now getting firm information on 10K was actually not that easy and was a very time consuming and costly process before EDGAR. Getting data in a timely fashion was hard work. It is still hard work to get it arranged properly This paper makes two predictions: 1. Return predictability should be strongest immediately following the release of this key information and then decay. 2. As the cost of information gathering decreases, the markets will become more efficient with less return predictability and more active trading activity after the information release.  These results should not be surprising. What took academics so long to realize what traders knew a long-time ago, yet this provides another good story for how market efficiency works. This study looks at how changes in the EDGAR database reporting and dissemination has made a difference on how research is conducted and thus information is discounted.