The Russian invasion of Ukraine and its repercussions continue to occupy front pages all around the world. While using nuclear forces in war is probably a red line for all of the mature world, there is still possible to use nuclear weapons for blackmailing. What will be the impact of such an event on financial markets? It’s not easy to determine, but we tried to identify multiple events in the past which were also slightly unexpected and carried an indication of nuclear threat and then analyzed their impact on financial markets.

Can the number or type of images in a firm’s annual report tell us anything about the firm? Or is it just a marketing strategy that doesn’t hold any further information? With the help of novel machine learning techniques, the authors Azi Ben-Rephael, Joshua Ronen, Tavy Ronen, and Mi Zhou study this problem in their paper “Do Images Provide Relevant Information to Investors? An Exploratory Study”. It seems that the proposed metrics help to forecast some of the firms’ fundamental ratios.

Directors, board members, and large shareholders are just some of those who might have non-public material information about their firm. Even though this information could be easily used to profit by trading their own stocks, this insider trading behavior is strictly prohibited. But how profitable can it be? We can study insider trading in the time when it wasn’t regulated at all – in the early 1700s. The 300 hundred-year-old dataset consists of data recovered from original handwritten ledger books and transfer files of the three largest companies in the London stock market at the time. It gives us a glimpse into the evidence of how big the insider’s advantage is, and the result is quite surprising – the authors calculated their outperformance to just 7% per year.

Indisputably, trend-following and mean-reversion are two key concepts in quantitative investing or technical analysis. What about the Bitcoin? Are there trend-following or mean-reversion patterns? Or are both effects present and co-exist? In this short research, we examine how Bitcoin’s price is affected by its maximal or minimal price over the previous 10 to 50 days. Our finding shows that when the BTC is at the local maxima, it tends to continue trending upwards. Furthermore, the local minima are also connected with abnormal price action.