SAŽETAK: U nastojanjima da se najpoznatiji jedno-faktorski model, model procjenjivanja kapitalne imovine (CAPM), primijeni u praksi esto su se koristili dioni ki indeksi temeljeni na tržišnoj kapitalizaciji. Istraživanja su, me utim, pokazala da takvi indeksi naješ e ne predstavljaju eÞ kasan portfolio svojih sastavnica pa su u posljednjih 10-ak godina razvijani pristupi koji bi investitorima trebali ponuditi eÞ kasnije indekse. Istraživanja za hrvatsko tržište upu uju na otežanu primjenu takvih istraživanja zbog speciÞ nosti malog i nelikvidnog tržišta. U ovome radu kao alternativa tržišnoj kapitalizaciji testiraju se fundamentalni pokazatelji slijede i istraživanje Arnott et al. (2005.). Ispituje se više fundamentalnih pokazatelja, a performanse indeksa uspore uju se s CROBEX indeksom za revizije indeksa u razdoblju 2009. -2016. Rezultati istraživanja pokazuju bolje performanse odre enih testiranih indeksa u vidu ve ih odnosa rizika i nagrade, ali uz slabu robusnost. Tako er, ve i odnosi rizika i nagrade proizlaze iz relativno ve eg pove anja prinosa u odnosu na rizik što sugerira potrebu za provo enje daljnjih istraživanja.KLJU NE RIJE I: CAPM, faktorski modeli, eÞ kasni indeksi, indeksi temeljeni na fundamentalnim pokazateljima. SUMMARY:In order to apply one of the most famous single-factor models (CAPM) in practice, equity market cap-weighted indices were often used. However, research has shown that such indices often do not represent efÞ cient portfolios of their constituents. Therefore, various approaches have been developed in the last 10 years in pursuit of more efÞ cient indices for investors. Research conducted for the Croatian market points out difÞ -* Mario Kova evi ,

Purpose This paper aims to analyze the effects of investors’ sentiment, return and risk series on one to another of selected exchange rates. The empirical analysis consists of a time-varying inter-dependence between the observed variables, with the focus on spillovers between the variables. Design/methodology/approach Monthly data on the index Sentix, exchange rates EUR–USD, EUR–CHF and EUR–JPY are analyzed from February 2003 to December 2019. The applied methodology consists of vector autoregression models (VAR) with Diebold and Yilmaz (2009, 2011) spillover indices. Findings The results of the empirical research indicate that using static analysis could result in misleading conclusions, with dynamic analysis indicating that the financial of 2007-2008 and specific negative events increase the spillovers of shock between the observed variables for all three exchange rates. The sources of shocks in the model change over time because of variables changing their positions being net emitters and net receivers of shocks. Research limitations/implications The shortfalls of this study include using the monthly data frequency, as this was available for the authors, namely, investors are interested to obtain new information on a weekly and daily basis, not only monthly. However, at the time of writing this research, we could obtain only monthly data. Practical implications As the obtained results are in line with previous literature and were found to be robust, there exists the potential to use such analysis in the future when forecasting risk and return series for portfolio management purposes. Thus, a basic comparison was made regarding the investment strategies, which were based on the results from the estimation. It was shown that using information about shock spillovers could result in strategies that can obtain better portfolio value over time compared to basic benchmark strategies. Originality/value First, this paper allows for the spillovers of shocks in variables within the VAR models in all directions. Second, a dynamic analysis is included in the study. Third, the mentioned spillover indices are included in the study as well.

The work of Arnott et al. (2005) presented an interesting fact that the fundamentally-weighted indices generally outperform the market capitalisation-weighted counterparts in the US stock market. The research results prompted the introduction of fundamentally-weighted indices in the US market. Since research dealing with Croatian capital market also points out the inefficiency of the risk return trade-off of the cap-weighted (CROBEX) index this paper examines more closely the risk return characteristics of the potential fundamentally-weighted alternative and analyses the source of higher returns in the case of fundamentally-weighted indices. We use the original and propose a modified Fama French three factor model in order to try to capture specific sources of risk in the small and illiquid market. We find evidence in support of the view that better risk return trade-off of the fundamentally-weighted indices is driven by additional exposure to risk factors in comparison to CROBEX index.

In this paper, the possibility of using fundamental weighting as a tool to intentionally tilt a portfolio toward specific and unobservable risk factors in the illiquid and undeveloped Croatian stock market is explored. Thus far, fundamental-weighting has been shown to be able to outperform the cap-weighted index in such environments but no attempt regarding control for implicit factor exposure of such portfolios has been reported. Therefore, in this study principal component analysis is performed to capture the underlying risk factors of the fundamentally-weighted portfolio in order to optimize the portfolio’s performance by minimizing its volatility. Previous attempts focusing purely on portfolio risk reduction by estimating minimum variance portfolios failed both from an in-sample and out-of-sample perspective. Results in this study are based on 22 in-sample and out-of-sample tests in the period from March 2009 till March 2020. On the in-sample estimation basis, the proposed approach significantly improves the portfolio’s performance and, if restrictions to weights are imposed, it can outperform the cap-weighted benchmark. However, out-of-sample testing yielded poor results both in terms of risk and return. Such results are in contrast to findings for the developed markets but corroborate the claim that a broad investment base is needed for successful risk exposure in the long run.

Instead of traditionally looking at investing in different types of asset classes in order to exploit diversification effects, investors are turning to the underlying performance drivers built-in in many asset classes – factors. The intuition is that assets earn risk premiums because they are exposed to underlying risk factors. Factor models were developed as a simplification and continuation of diversification principle and mean-variance efficiency introduced by Harry Markowitz. This chapter will focus on one of the standard investment and cross section factors called momentum. It became very popular since 1993 when Jegadeesh and Titman documented that strategies that buying stocks that have performed well in the past and selling stocks that have performed poorly generate significant positive returns. This chapter aims to provide an introduction to factor models development and momentum effects on stock and bond markets – description of methodology and detailed literature overview.