nep-fmk New Economics Papers
on Financial Markets
Issue of 2016‒04‒30
six papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Equity Markets’ Clustering and the Global Financial Crisis By Carlos León; Geun-Young Kim; Constanza Martínez; Daeyup Lee
  2. The Wall Street walk when blockholders compete for flows By Amil Dasgupta; Giorgia Piacentino
  3. Random factor approach for large sets of equity time-series By Antti Tanskanen; Jani Lukkarinen; Kari Vatanen
  4. Bid-Ask Spreads in OTC Markets By Carol Osler; Geir Bjonnes; Neophytos Kathitziotis
  5. Term structures of asset prices and returns By Backus, David; Boyarchenko, Nina; Chernov, Mikhail
  6. Calendar Anomalies in the Ukrainian Stock Market By Guglielmo Maria Caporale; Alex Plastun

  1. By: Carlos León (Banco de la República de Colombia); Geun-Young Kim; Constanza Martínez (Banco de la República de Colombia); Daeyup Lee (The Bank of Korea; The Bank of Korea)
    Abstract: The effect of the Global Financial Crisis (GFC) has been substantial across markets and countries worldwide. We examine how the GFC has changed the way equity markets group together based on the similarity of stock indices’ daily returns. Our examination is based on agglomerative clustering methods, which yield a hierarchical structure that represents how stock markets relate to each other based on their cross-section similarity. Main results show that both hierarchical structures, before and after the GFC, are readily interpretable, and indicate that geographical factors dominate the hierarchy. The main features of equity markets’ hierarchical structure agree with most stylized facts reported in related literature. The most noticeable change after the GFC is a stronger geographical clustering. Some changes in the hierarchy that do not conform to geographical clustering are explained by well-known idiosyncratic features or shocks. Classification JEL:C38, L22, G15
    Keywords: clustering, unsupervised learning, stock market, connectedness
    Date: 2016–04
  2. By: Amil Dasgupta; Giorgia Piacentino
    Abstract: Effective monitoring by equity blockholders is important for good corporate governance. A prominent theoretical literature argues that the threat of block sale (“exit”) can be an effective governance mechanism. Many blockholders are money managers. We show that when money managers compete for investor capital, the threat of exit loses credibility, weakening its governance role. Money managers with more skin in the game will govern more successfully using exit. Allowing funds to engage in activist measures (“voice”) does not alter our qualitative results. Our results link widely prevalent incentives in the ever-expanding money management industry to the nature of corporate governance.
    JEL: F3 G3
    Date: 2015
  3. By: Antti Tanskanen; Jani Lukkarinen; Kari Vatanen
    Abstract: Factor models are commonly used in financial applications to analyze portfolio risk and to decompose it to loadings of risk factors. A linear factor model often depends on a small number of carefully-chosen factors and it has been assumed that an arbitrary selection of factors does not yield a feasible factor model. We develop a statistical factor model, the random factor model, in which factors are chosen at random based on the random projection method. Random selection of factors has the important consequence that the factors are almost orthogonal with respect to each other. The developed random factor model is expected to preserve covariance between time-series. We derive probabilistic bounds for the accuracy of the random factor representation of time-series, their cross-correlations and covariances. As an application of the random factor model, we analyze reproduction of correlation coefficients in the well-diversified Russell 3,000 equity index using the random factor model. Comparison with the principal component analysis (PCA) shows that the random factor model requires significantly fewer factors to provide an equally accurate reproduction of correlation coefficients. This occurs despite the finding that PCA reproduces single equity return time-series more faithfully than the random factor model. Accuracy of a random factor model is not very sensitive to which particular set of randomly-chosen factors is used. A more general kind of universality of random factor models is also present: it does not much matter which particular method is used to construct the random factor model, accuracy of the resulting factor model is almost identical.
    Date: 2016–04
  4. By: Carol Osler (Brandeis University); Geir Bjonnes (Norwegian Business School); Neophytos Kathitziotis (University of Hamburg)
    Abstract: According to well-accepted theory, the three primary components of bid-ask spreads reflect operating costs, inventory costs, and adverse selection. We challenge the idea that the traditional trinity applies in all markets, arguing that OTC spreads include a price discrimination component rather than an adverse-selection component. Because OTC trades are not anonymous, OTC dealers will price discriminate according to their clients' information, market sophistication, and trading volume. Adverse selection could influence the information dimension of price discrimination or it could be irrelevant. We support this view with an empirical analysis of transactions data from the world's largest OTC market that include venue and customer IDs. The estimated price discrimination component ranges from two-thirds to six times the combined operating and inventory cost components for different cutomer groups. Adverse selection is irrelevant for most customer groups, and its contribution to spreads paid by the other two customer groups, hedge funds and customer banks, is small in absolute terms but large relative to their average markup. We indentify two structural determinants of the relevance of adverse selection: the presence of an active interdealer market and a customer's engagement in HFT.
    Date: 2016–03
  5. By: Backus, David; Boyarchenko, Nina; Chernov, Mikhail
    Abstract: We explore the term structures of claims to a variety of cash flows: US government bonds (claims to dollars), foreign government bonds (claims to foreign currency), inflation-adjusted bonds (claims to the price index), and equity (claims to future equity indexes or dividends). Average term structures reflect the dynamics of the dollar pricing kernel, of cash flow growth, and of their interaction. We use simple models to illustrate how relations between the two components can deliver term structures with a wide range of levels and shapes.
    Keywords: entropy; coentropy; term structure; yields; excess returns
    JEL: G12 G13
    Date: 2016–04
  6. By: Guglielmo Maria Caporale; Alex Plastun
    Abstract: This paper is a comprehensive investigation of calendar anomalies in the Ukrainian stock market. It employs various statistical techniques (average analysis, Student's t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) and a trading simulation approach to test for the presence of the following anomalies: Day of the Week Effect; Turn of the Month Effect; Turn of the Year Effect; Month of the Year Effect; January Effect; Holiday Effect; HalloweenEffect. The results suggest that in general calendar anomalies are not present in the Ukrainian stock market, but there are a few exceptions, i.e. the Turn of the Year and Halloween Effect for the PFTS index, and the Month of the Year Effect for UX futures. However, the trading simulation analysis shows that only trading strategies based on the Turn of the Year Effect for the PFTS index and the Month of the Year Effect for the UX futures can generate exploitable profit opportunities that can be interpreted as evidence against market efficiency.
    Keywords: Calendar anomalies, day of the week effect, turn of the month effect, month of the year effect, january effect, holiday effect, halloween effect
    JEL: G12 C63
    Date: 2016

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