Davor Zoričić, Denis Dolinar and Zrinka Lovretin Golubić
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.
The fact that cap-weighted indices provide an inefficient risk-return trade-off is well known today. Various research approaches evolved suggesting alternative to cap-weighting in an effort to come up with a more efficient market index benchmark. In this paper we aim to use such an approach and focus on the Croatian capital market. We apply statistical shrinkage method suggested by Ledoit and Wolf (2004) to estimate the covariance matrix and follow the work of Amenc et al. (2011) to obtain estimates of expected returns that rely on risk-return trade-off. Empirical findings for the proposed portfolio optimization include out-of-sample and robustness testing. This way we compare the performance of the capital-weighted benchmark to the alternative and ensure that consistency is achieved in different volatility environments. Research findings do not seem to support relevant research results for the developed markets but rather complement earlier research (Zoričić et al., 2014).
The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in India
This study evaluates optimal hedge ratios and the hedging effectiveness of stock index futures. The optimal hedge ratios are estimated from the ordinary least square (OLS) regression model, the vector autoregression model (VAR), the vector error correction model (VECM) and multivariate generalized autoregressive conditional heteroskedasticity (M-GARCH) models such as VAR-GARCH and VEC-GARCH using the S&P CNX Nifty index and its futures index. Hedging effectiveness is measured in terms of within sample and out of sample risk-return trade-off at various forecasting horizons. The analysis found that the VEC-GARCH time varying hedge ratio provides the greatest portfolio risk reduction and generates the highest portfolio returns.
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