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The researchers considered a model of investment behaviour comprising six influencing factors. The paper has three main purposes, namely, to assess the degree to which the considered factors influence investment decision-making in young capital markets from Central and Eastern Europe (CEE) to compare the investment behaviour in the three considered countries and to characterise investment behaviour in periods of economic turbulence. This paper aims to make an analysis of investment behaviour in mutual funds, by looking at different investment decision influencers and trying to identify the extent to which the investment decision is knowledge-based. Given the growth of this industry in recent years in young and developing financial markets (Varga, 2011 Akbari et al., 2019 Nguyen and Nguyen, 2019 Rao et al., 2017), including the ones from Central and Eastern Europe (CEE), there is the need for more empirical research in the field of mutual funds and in this region (Tudorache et al., 2015 Filip, 2018 Csikosova et al., 2019) and on the topic of the investment behaviour. The majority of the mutual funds studies conducted so far, focused mainly on developed and mature financial markets (Ferreira et al., 2012 Fahling et al., 2019 Koutsokostas et al., 2019), especially the US market (Kim, 2013 Fu et al., 2012 Babalos et al., 2015 Stotz, 2020), while emerging or frontier financial markets and young financial markets in general were paid less attention. The evolution of mutual funds is also seen as a common indicator for assessing financial markets' performances in different countries (Zaremba, 2019), considering the evolution of inflows and outflows. We also generate diversified positions, and efficient frontiers that exhibit coherent risk-return patterns. Our results show that, by incorporating features, the out-of-sample performance of our strategy outperforms the equally-weighted portfolio. In our experiments we use the Conditional Value-at-Risk as our risk measure, and we work with data from 2007 until 2021 to evaluate our methodology.
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We take a different path and use distribution-free simulation techniques to populate our database. For those intervals, data scarcity is a problem that is often dealt with by making distribution assumptions. We consider yearly intervals for investment opportunities, and a set of indices that cover the most relevant investment classes. We propose a mean-risk portfolio selection problem that uses contextual information to maximize expected returns at each time period, weighing past observations via kernels based on the current state of the world. Taken not only to avoid investment loss but more importantly is toįeatures, or contextual information, are additional data than can help predicting asset returns in financial problems. May change the investment risks therefore certain actions shall be Necessary to do especially if the changes in all of these variables Performance, as well as performances of the underlying assets, are Furthermore, aĬontinuous monitoring of the market condition, fund Stock selection ability and market timing ability. Of the determined investment strategy by implementing significant The research proposes to enhance the methodology of implementation Significant stock selection ability and market timing ability. Investment strategy or passive investment strategy, without Implementation of the determined strategy, whether active In the ASEAN market during the period January 2015 to December 2020Ĭould continuously earn outperform return. This research proposedĮmpirical evidence that none of the equity mutual funds were traded Outperform return in the volatile market. Managing equity mutual funds is no longer enough to earn The traditional approach in the implementation of investment strategy in