nep-fmk New Economics Papers
on Financial Markets
Issue of 2016‒08‒14
four papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Why Does Idiosyncratic Risk Increase with Market Risk? By Söhnke M. Bartram; Gregory Brown; René M. Stulz
  2. Dynamic structure of stock communities: A comparative study between stock returns and turnover rates By Li-Ling Su; Xiong-Fei Jiang; Sai-Ping Li; Li-Xin Zhong; Fei Ren
  3. An Experimental Study of Bond Market Pricing By Matthias Weber; John Duffy; Arthur Schram
  4. Do Private Equity Funds Manipulate Reported Returns? By Gregory W. Brown; Oleg R. Gredil; Steven N. Kaplan

  1. By: Söhnke M. Bartram; Gregory Brown; René M. Stulz
    Abstract: From 1963 through 2015, idiosyncratic risk (IR) is high when market risk (MR) is high. We show that the positive relation between IR and MR is highly stable through time and is robust across exchanges, firm size, liquidity, and market-to-book groupings. Though stock liquidity affects the strength of the relation, the relation is strong for the most liquid stocks. The relation has roots in fundamentals as higher market risk predicts greater idiosyncratic earnings volatility and as firm characteristics related to the ability of firms to adjust to higher uncertainty help explain the strength of the relation. Consistent with the view that growth options provide a hedge against macroeconomic uncertainty, we find evidence that the relation is weaker for firms with more growth options.
    JEL: G10 G11 G12
    Date: 2016–08
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:22492&r=fmk
  2. By: Li-Ling Su; Xiong-Fei Jiang; Sai-Ping Li; Li-Xin Zhong; Fei Ren
    Abstract: The detection of community structure in stock market is of theoretical and practical significance for the study of financial dynamics and portfolio risk estimation. We here study the community structures in Chinese stock markets from the aspects of both price returns and turnover rates, by using a combination of the PMFG and infomap methods based on a distance matrix. We find that a few of the largest communities are composed of certain specific industry or conceptional sectors and the correlation inside a sector is generally larger than the correlation between different sectors. In comparison with returns, the community structure for turnover rates is more complex and the sector effect is relatively weaker. The financial dynamics is further studied by analyzing the community structures over five sub-periods. Sectors like banks, real estate, health care and New Shanghai take turns to compose a few of the largest communities for both returns and turnover rates in different sub-periods. Several specific sectors appear in the communities with different rank orders for the two time series even in the same sub-period. A comparison between the evolution of prices and turnover rates of stocks from these sectors is conducted to better understand their differences. We find that stock prices only had large changes around some important events while turnover rates surged after each of these events relevant to specific sectors, which may offer a possible explanation for the complexity of stock communities for turnover rates.
    Date: 2016–08
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1608.03053&r=fmk
  3. By: Matthias Weber (Bank of Lithuania and Faculty of Economics, Vilnius University); John Duffy (Department of Economics, University of California-Irvine); Arthur Schram (University of Amsterdam and European University Institute)
    Abstract: An important feature of bond markets is the relationship between initial public offering prices and the probability of the issuer defaulting. First, this probability affects the bond prices. Second, IPO prices determine the default probability. Though market equilibrium has been shown to predict well for other assets, it is a priori unclear whether markets will yield competitive prices when such interaction with the default probability occurs. We develop a flexible bond market model that is easily implemented in the laboratory and examine how subjects price bonds. We find that subjects learn to price bonds well after only a few repetitions.
    Keywords: Bond markets; Experimental finance; Experimental markets; Asset pricing; Learning
    JEL: C92 C90 D47 G12
    Date: 2016–08
    URL: http://d.repec.org/n?u=RePEc:irv:wpaper:161701&r=fmk
  4. By: Gregory W. Brown; Oleg R. Gredil; Steven N. Kaplan
    Abstract: Private equity funds hold assets that are hard to value. Managers may have an incentive to distort reported valuations if these are used by investors to decide on commitments to subsequent funds managed by the same firm. Using a large dataset of buyout and venture funds, we test for the presence of reported return manipulation. We find evidence that some under-performing managers boost reported returns during times when fundraising takes place. However, those managers are unlikely to raise a next fund, suggesting that investors see through much of the manipulation. In contrast, we find that top-performing funds likely understate their valuations.
    JEL: G23 G24 G30
    Date: 2016–08
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:22493&r=fmk

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