Analysis of financial network and the role of asymmetry instock and fund returns

Abstract
Research focuses on three different topics about stocks, stock markets and funds. First
study is about the effect of financial network on equity markets and analysis are based on threedifferent investment flows. The geographical importance of the markets have been thoroughly
analyzed in previous studies and found that home bias as well as uncertainty related to foreign
markets led investors to focus on domestic markets. However, due to the interconnectedness ofeconomies in today’s world, the high priority of domestic investment decreased and international
portfolio investments increased. Our study investigated the significance of the economy’s positionin financial network and compared with spatial effect. Based on empirical results from spatial
autoregressive (SAR) model, we found the spatial effect to be statistically significant to explain
index rate of returns together with economy’s centrality on the debt based financial flows.
Moreover, Jensen’s Alpha is studied by employing a skew-symmetric model for error terms.
Jensen’s α has been the core quantity in the empirical test for CAPM (Capital Asset PricingModel). CAPM states that expected excess rate of return of stocks and portfolio is equal toβ times expected excess return of Market portfolio. But Jensen’s α is an additional expectedexcess rate of return of stocks and portfolio,
E[Rp − rf ] = α + βE[Rm − rf ]where Rp is rate of return of portfolio, Rm is that of market portfolio and rf is risk free rate.
It has been popular to estimate α by OLS(Ordinary Least Squares) method. α is the interceptand β is the regression coefficient in a simple linear model. Our approach uses estimates of βbased on Rank statistics which is known to be robust against outliers or heavy tail. Moreover,research analyzes α in a new statistical model (Generalized Lehmann’s Alternative Model, (Miuraand Tsukahara, 1993)) that describes α and error terms together. GLAM is semi-parametricand assumes F (underlying distribution) to be symmetric around zero and to be unknown. OLS
method estimates α and β simultaneously. But rank statistics method estimates β only in the firststage, then use the observed residuals to estimate location parameter and asymmetry parameters.
Our main result is that Jensen’s α is a sum of location (of error terms) and asymmetry (θ) effect.
Moreover, θ is found to be related to volatility index and quarterly index rate of return.
Last research focuses on manager performance evaluation based on Unit Trust data. A surge
in a number and types of investment funds attracted a great deal of attention by researchers toevaluate manager and fund performance. However, literature lack of studies with an applicationof robust methods but OLS. OLS is found to be imprecise when data has outliers and canlead to different results as our previous study found for the case of stock rate of returns. By
focusing on monthly data from 1970 until 2015, performance (regression α) evaluated based on
non-parametric rank statistics (R) and OLS. R estimates are found to be more efficient than
OLS counterpart for most of the periods. To separate R estimate of alpha based on manager
skill alone, a cross sectional bootstrap method is used. Observed ηi (α included residuals) arefurther analyzed by fitting Generalized Lehmann’s Alternative Model to obtain parameters for1

asymmetry and location. By looking at performance persistence, research found that alpha due
to manager skill persists together with asymmetry for long horizon. This study clearly showsthat skill of the manager and portfolio allocation of fund is reflected in asymmetry of residuals(ηi ) from the regression which is used to evaluate the performance.

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