Browsing by Author "Banerjee, A. K."

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    Assessing the US financial sector post three bank collapses: signals from fintech and financial sector ETFs
    (Elsevier BV, 2023-10-12) Banerjee, A. K.; Pradhan, H. K.; Şensoy, Ahmet; Goodell, J. W.
    We investigate the effects of the collapses of Silicon Valley Bank, Signature Bank, and First Republic Bank on the US financial sector by analysing returns and second moments of traditional financial and fintech ETFs. Using a network model, we examine high-frequency data sampled at one-hour intervals for seventeen ETFs encompassing pre- and crisis periods. We find, using a time-varying parametric vector autoregressive (TVP-VAR) and volatility impulse response analysis, that traditional financial ETFs are net transmitters of returns and volatility spillovers in the network, and that this impact is more pronounced in volatility in the period coinciding with the collapse of the three big banks. We identify effects persisting through the medium term. This study is among the first to comprehensively analyze the recent crisis in the US banking sector, covering a full range of the fall of three big banks.
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    Robust portfolio optimization with fuzzy TODIM, genetic algorithm and multi-criteria constraints
    (Springer New York LLC, 2024-03-27) Banerjee, A. K.; Pradhan, H. K.; Şensoy, Ahmet; Fabozzi, F.; Mahapatra, B.
    This paper adopts the multi-criterion decision-making model of fuzzy-TODIM and geneticalgorithm (GA) for optimal portfolio allocation. We applied Markowitz’s portfolio parame-ters as inputs for the fuzzy TODIM model to rank stocks that are constituents of each indexfrom three different markets. Portfolios are then generated dynamically using three weightingtechniques and subject to multi-objective criteria and additional constraints. The results indi-cate a significant variation in performance metrics between the model-generated portfoliosand the market indices. Replication of the procedure produces a similar outcome. Moreover,the out-of-sample tests conducted over 3 years validate the results’ robustness, indicating thatfuzzy TODIM, combined with GA, can achieve superior performance in dynamic portfolioallocation.