What Do We Learn from Daily Leaders and Laggards in Stock Investment? Do They Help Outperform the Market Average?

Investors generally believe that rising stocks are more likely to maintain their trend and rise going forward, whereas the losing stocks look more price attractive. This belief can lead the investors to expect that they can outperform the average market by trading the stocks purely based on the price movements. However, this research finds that this simple trading strategy does not effectively outperform the market. Nonetheless, we find five sectors of rising stocks and three sectors of declining stocks that outperform the average market in this limited study.

Do Blockchain Stocks Exhibit More Herding Behaviour than Traditional Stocks?

While the volatile behaviour of cryptocurrency is extensively studied, the stock market’s blockchain sector, which has not been given much attention in the academic world, operates very differently from traditional stock industries. The paper hypothesizes that blockchain stocks exhibit more herding behaviour than traditional stocks and uses quantitative data analysis techniques to study it. The automotive industry is taken as a representative of traditional stocks. Cross-Sectional Absolute Deviation, the academic standard for herding behaviour, is used as the primary comparative measure between blockchain and automotive stocks. It reveals that blockchain industry has significant herding, while rational pricing mechanisms prevail in the automotive industry. Supporting this conclusion, a correlation matrix of stock prices of small market capitalisation firms in each industry is constructed, analysing how closely stock price movements in an industry are related. The correlation coefficient for blockchain stocks is 20% higher than the coefficient for automotive stocks. This indicates that blockchain stocks likely exhibit higher levels of herding. The impact of social media on stock price movements in the two industries is analysed by conducting a correlation study between Google Trends data for industry-related keywords and individual stock returns. The blockchain industry saw a significantly higher correlation, likely suggesting that social media has a stronger influence on blockchain stock price movements. Finally, the paper provides possible explanations for why herding behaviour is more prominent in the blockchain stocks compared to traditional stocks. These include absence of traditional stock valuation metrics, lack of financial knowledge and role of social media.

US financial services will help mainstream cryptos

Significance Yet snowballing interest outpaces crypto's use in any of the three main roles of money: a medium of exchange, unit of account or store of value. Crypto accounts for a sliver of US financial assets and retail sales. It remains overshadowed by its reputation as the currency of cybercriminals. Impacts Safeguards to prevent criminals from exploiting crypto will hinder legitimate crypto innovation. Transaction monitoring and know-your-customer due diligence will become a higher priority for crypto exchanges, reducing anonymity. Crypto's non-correlation with equity and bond price movements, an investor attraction, will lessen with broader use

A Note on Forecasting the Historical Realized Variance of Oil-Price Movements: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios

We examine the predictive value of gold-to-silver and gold-to-platinum price ratios, as proxies for global risks affecting the realized variance (RV) of oil-price movements, using monthly data over the longest available periods of 1915:01–2021:03 and 1968:01–2021:03, respectively. Using the two ratios, we find statistically significant evidence of in-sample predictability for increases in RV for both ratios. This finding also translates into statistically significant out-of-sample forecasting gains derived from these two ratios for RV. Given the importance of real-time forecasts of the volatility of oil-price movements, our results have important implications for investors and policymakers.

Strategic Diversification for Asynchronous Asset Trading: Insights from Generalized Coherence Analysis of Cryptocurrency Price Movements

Non-linear interactions between cryptocurrency price movements can elicit cross-frequency coupling (CFC) wherein one set of frequencies in the 1st timeseries is coupled to another set of frequencies in the 2nd timeseries. To investigate this, we use a generalized coherence approach to detect and quantify both linear (i.e., iso-frequency coupling, IFC) and non-linear coherence (CFC) and the associated phase relationships between the intra-day price changes of various pairs of cryptocurrencies for the year 2020. Using this information, we further assess the risk reduction associated with diversification of portfolios between each pair of a small market capital and a large market capital cryptocurrency, for both synchronous and asynchronous trading conditions. While mean pairwise IFC values were lower for smaller cryptocurrencies, pairwise CFC values were more heterogeneous and had no correlation with the market capital size. Diversification of portfolios resulted in reduced risk for synchronously-traded pairs of those cryptocurrencies which had low IFC. For asynchronous trading conditions, if the larger market capital cryptocurrency was traded at a higher frequency, diversification almost always reduced risk. Thus, the novel approach used in this study reveals important insights into the complex dynamics that govern the price trends of cryptocurrencies.