References of "Wijnandts, Jean-Charles"
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See detailFund Industry in Luxembourg
Sougné, Danielle ULg; Wijnandts, Jean-Charles ULg

Book published by Larcier (2013)

This book is to be placed in an unexploited niche in the fund industry literature: It has first to be distinguished from the main strand of the literature on mutual funds focusing on funds selection’s ... [more ▼]

This book is to be placed in an unexploited niche in the fund industry literature: It has first to be distinguished from the main strand of the literature on mutual funds focusing on funds selection’s methods and portfolio management strategies available to funds ‘managers’. This book aims at providing the readers with a comprehensive overview of the Luxembourg fund industry together with a better understanding of the mechanisms governing the interactions between its different actors. The goal is to enable the readers to better apprehend the functioning of industry as a whole from both a legal and practical perspective and to operate more efficiently within the industry. As a consequence, the book must be distinguished from practitioner–oriented compilations of legal texts and references. The contribution of renowned experts of fund industry in Luxembourg permitted to summarize the operating in Luxembourg. Consequently, this book aspires to become a reference on the topic. Students in Finance, Law and Management considering a career in the fund industry will benefit from this book by gaining a better understanding of fund industry as a whole, wich would improve their employability in this sector. [less ▲]

Detailed reference viewed: 131 (39 ULg)
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See detailExcess Return Forecast Using a Dynamic Asset Class Factor Model
Hübner, Georges ULg; Sougné, Danielle ULg; Wijnandts, Jean-Charles ULg

E-print/Working paper (2012)

We propose a Dynamic Hierarchical Factor Model using Asset classes to predict mutual funds excess returns. We use different forecast combination schemes of bivariate model considering each asset class ... [more ▼]

We propose a Dynamic Hierarchical Factor Model using Asset classes to predict mutual funds excess returns. We use different forecast combination schemes of bivariate model considering each asset class factor in isolation. Primary analysis highlights the importance to account for asset class specific variations together with between classes or common variations. Further refinements of the a priori repartition are however in order. Forecasting performance of the model outperforms the historical mean benchmark both in terms of MSPE and utility based criteria. A forecasting exercise matching more closely real-time conditions must be undertaken to validate these initial results. [less ▲]

Detailed reference viewed: 53 (8 ULg)