Testing the robustness of moving average distance in the ASEAN stock markets

Several researches have provided empirical evidence that moving average distance (MAD) can be used in predicting equity returns focusing on developed markets. These ultimately challenge the proposition of the efficient market hypothesis (EMH) theory that historical prices cannot be used to create a strategy to predict returns. This study aims to test the robustness of moving average distance in the ASEAN stock markets using a statistical method that runs all possible combinations of the regressors. The Bayesian Model Averaging (BMA) approach is employed for fifteen control variables namely moving average distance signal (MDS), 200-day moving average signal, MAD threshold signal, moving average convergence divergence, momentum, market value of equity, book-to-market ratio, turnover, 52-week high, net stock issues, return on equity, return on assets, gross profitability, asset growth, and volatility on a monthly timeframe throughout January 2010 - January 2020 with a sample of 4, 524 firms. With BMA, thousands of regression combinations are estimated and results suggest that MAD is a robust predictor in the Philippines, Thailand, and Vietnam. Employing both Fama-Macbeth regressions and BMA, this study concludes that EMH is not evident in the three countries and there is anchoring in the trading indicators considered

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora