Volatility clustering is a well-known effect in equity markets. In simple meaning, volatility clustering refers to a tendency of large changes in asset prices to follow large changes and small changes in asset prices to follow small changes. This interesting effect can be sometimes uncovered as one of the reasons for the functionality of some selected trading strategies. For example, low-volatility months in stock indexes (like the S&P 500 Index) are usually also months with higher performance. As volatility tends to cluster, a low volatility month in the present can signal a low volatility month with a better performance also in the future.

Based on this, we will be testing two hypotheses: (1) firstly, if there is a volatility clustering anomaly present in equity factor strategies; (2) secondly, if there is any performance pattern related to volatility.

The spring is in the air (at least in the northern hemisphere), and we were not sitting idle in the last month. The most interesting development is two new reports for Quantpedia Pro (the Factor Cycle and Inter-Market Correlation reports) that I will describe soon.

But first, let’s recapitulate Quantpedia Premium development. Nine new Quantpedia Premium strategies have been added to our database, and fifteen new related research papers have been included in existing Premium strategies during the last month. Additionally, we have produced 12 new backtests written in QuantConnect code. Our database currently contains over 420 strategies with out-of-sample backtests/codes.

Additionally, four new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month …

Four new strategies have been added.

Ten new related research papers have been included into existing strategy reviews and two short free blog posts have been published during last few weeks. Plus, six trading strategies have been backtested in QuantConnect in the previous two weeks.

The R&D investments represent a company’s unique expenditure, which is responsible for creating an information asymmetry about the firm’s growth potential and future prospects. In a case when market value reflects only the firm’s financial statements without taking the long-term benefits of R&D investments into consideration, the company’s stocks may be underpriced. On the other hand, the firm’s stock prices may also face overpricing. This might happen in a case when the investors judge the possible future outcomes of current R&D investment based on the past firm’s R&D success, which is not a guarantee by any means.

This week’s blog is unique compared to our previous posts. We have identified two papers that are connected, each with interesting findings and implications. One of today’s leading topics is the Robinhood trading platform, but not from the point of view of recent short squeezes and speculations. The Robinhood can be an interesting insight into retail investing and implications for the market. Research suggests that despite the very low share of retail investors, their power is significantly high. This seems to be caused by the inelastic market, which passive investing contributes to. Therefore, inelasticity is another crucial point.

Five new strategies have been added.

Six new related research papers have been included into existing strategy reviews and two short free blog posts have been published during last few weeks. Plus, six trading strategies have been backtested in QuantConnect in the previous two weeks.