How often do you think about the weights of the assets in your portfolio? Do you weigh your assets equally, or do you prefer value-weighting? The researchers behind a recent research paper analyzed various weighting schemes and examined their effect on factor strategy return. They studied five weighting schemes that ignore prices: equal weighting, rank weighting, z-score weighting, inverse volatility weighting, and fundamental weighting, and three price-based weighting schemes: Rank x mcap (rank-times-mcap), Z-score x mcap (z-score-times-mcap), and Integrated core.

They found that schemes that are not based on price can inflate turnover and costs. However, the weighting schemes based on price are the most practical to target multiple premiums, provide robust risk control, and decrease turnover and expenses.

This second article offers a different look at high inflation periods, which we already analyzed in What’s the Best Factor for High Inflation Periods? – Part I. The second part looks at factor performance during two 10-year periods of high inflation. What’s our main takeaway? The best hedge for a high inflation period is the value or momentum factor. Other promising factors (energy sector, small-cap stocks, or long-run reversal) don’t perform as consistently as value and momentum.

Another period of long sustained high inflation is probably right around the corner, as the Russia-Ukraine Conflict keeps evolving, and its end is nowhere to be seen. In this article, we analyzed the Consumer Price Index from the Federal Reserve Bank of Minneapolis, which includes the rate of inflation in the USA since 1913. We found multiple years during which the inflation was abnormally high and analyzed the performance of the known equity long-short factors. The factors with the highest average performance are HML (value stocks), long-term reversal, momentum, and energy stocks. On the other hand, tech stocks, bond-like assets, and the SMB factor should be avoided during the high inflation periods.

Do common equity factors suffer during bear markets? Undoubtedly, the market factor is a rather unpleasant investment during bear markets, but what about the long-short factors? Are they able to deliver performance? The research paper by Geertsema and Lu (2021) provides several answers and interesting insights.

It is indisputable that the data are changing financial markets – computing power has increased, allowing to rise the trends of ML/AI and big data (number of possible predictors or granularity) or HFT strategies. Indeed, not all the datasets are worth the time of academics, investors or traders, but we are always keen to analyze the novel and unique datasets. Of course, if we believe that the analysis is worthy of sharing, we are happy to do so. This post offers a shorter version of our newest research about Synthetic lending rates and subsequent market return. We hope that you find it enriching; enjoy the reading!