nep-cfn New Economics Papers
on Corporate Finance
Issue of 2015‒02‒22
five papers chosen by
Zelia Serrasqueiro
Universidade da Beira Interior

  1. Does Trading Anonymously Enhance Liquidity? By Dennis, Patrick J.; Sandås, Patrik
  2. Stepwise Investment and Capacity Sizing under Uncertainty By Chronopoulos, Michail; Hagspiel, Verena; Fleten, Stein–Erik
  3. Financing for Infrastructure Investment in G-20 Countries. By Sengupta, Ramprasad; Mukherjee, Sacchidananda; Gupta, Manish
  4. Pseudo-naïve approaches to investment performance measurement By Carlo Alberto Magni
  5. Distillation of News Flow into Analysis of Stock Reactions By Junni L. Zhang; Wolfgang K. Härdle; Cathy Y. Chen; Elisabeth Bommes

  1. By: Dennis, Patrick J. (McIntire School of Commerce, University of Virginia); Sandås, Patrik (McIntire School of Commerce, University of Virginia)
    Abstract: Anonymous trading is the norm in today's financial markets but there are a few exceptions. We study one such case, the OMX Nordic Exchanges (Stockholm, Helsinki, Copenhagen, and Reykjavik) that have traditionally been more transparent than most other markets. On June 2, 2008 OMX Nordic switched to making post-trade reporting anonymous for some of their markets. We exploit this quasinatural experiment to investigate the impact this change had on liquidity and trading behavior. Our difference-in-difference method reveals a modest, though statistically insignificant, 14 basis point improvement in the quoted spread under the post-trade anonymous regime. The price impact of a trade decreased by a statistically significant four basis points for seller-initiated trades and did not change for buyer-initiated trades.
    Keywords: Anonymity; Transparency; Liquidity; Broker ID
    JEL: G10 G14 G15
    Date: 2014–10–01
    URL: http://d.repec.org/n?u=RePEc:hhs:rbnkwp:0288&r=cfn
  2. By: Chronopoulos, Michail (Dept. of Business and Management Science, Norwegian School of Economics); Hagspiel, Verena (Dept. of Industrial Economics and Technology Management, Norwegian University of Science and Technology); Fleten, Stein–Erik (Dept. of Industrial Economics and Technology Management, Norwegian University of Science and Technology)
    Abstract: The relationship between uncertainty and managerial flexibility is particularly crucial in addressing capital projects. We consider a firm that can invest in a project in either a single (lumpy investment) or multiple stages (stepwise investment) under price uncertainty and has discretion over not only the time of investment but also the size of the project. We confirm that, if the capacity of a project is fixed, then lumpy investment becomes more valuable than a stepwise investment strategy under high price uncertainty. By contrast, if a firm has discretion over capacity, then we show that the stepwise investment strategy always dominates that of lumpy investment. In addition, we show that the total amount of installed capacity under a stepwise investment strategy is always greater than that under lumpy investment.
    Keywords: Investment analysis; capacity sizing; flexibility; real options
    JEL: G00 G10 G11
    Date: 2015–02–13
    URL: http://d.repec.org/n?u=RePEc:hhs:nhhfms:2015_010&r=cfn
  3. By: Sengupta, Ramprasad (Jawaharlal Nehru University); Mukherjee, Sacchidananda (National Institute of Public Finance and Policy); Gupta, Manish (National Institute of Public Finance and Policy)
    Abstract: This study looks into various sources of financing infrastructure and the demands for infrastructure investments and highlights the mismatch between demand and supply of funds for infrastructure financing in India. In order to address this mismatch, and given the constraints of traditional sources of infrastructure finance in India, this paper suggests credit enhancement scheme (CES) as an alternative framework for mobilizing long-term infrastructure finance. It suggests for scaling up CES as one of the options for leveraging global finance for long-term investment in infrastructure projects. The suggested scheme of credit enhancement could be scaled up at the G-20 level for mobilizing finance from sources which were earlier shying away from investing in infrastructure projects (e.g., pension and insurance fund). This study also suggests a possible structure for operationalizing this scheme at the G-20 level. The proposed scheme is not specific to G-20 countries, but could be used by other countries (including developing countries which have low sovereign ratings) to leverage long term finance for infrastructure sector.
    Keywords: Infrastructure finance ; Demand for infrastructure investment ; Credit Enhancement Scheme ; Sovereign risk rating ; G-20 ; India
    Date: 2015–02
    URL: http://d.repec.org/n?u=RePEc:npf:wpaper:15/144&r=cfn
  4. By: Carlo Alberto Magni
    Abstract: This paper makes use of Magni’s (2013. Insurance Mathematics and Economics, 53, 747-756) Average Interest Rate (AIR) in order to find a performance index which does not depend on the valuation rate (i.e., benchmark return). To this end, we distort the AIR by dropping the discount factors in the formula. The resulting modified AIR (MAIR) is the ratio of overall (undiscounted) return to overall (undiscounted) capital. While seemingly a na¨ive metric, we show that it is a genuinely internal metric, capable of capturing an investment’s economic profitability, as long as it is compared with an appropriate cutoff rate which adequately takes account of the opportunity cost of capital. The not-so na¨ive MAIR is then extended to several different capital bases; the result is that other well-known (allegedly na¨ive) metrics, such as cash multiple, undiscounted profitability, Modified Dietz and Simple Dietz return are given economic significance: each such metric is a (pseudo-na¨ive) performance index that correctly expresses the investment’s amount of return per unit of a specific capital: overall capital, initial investment, total cash outflow, average cash outflow).
    Keywords: Finance, investment, performance measurement, rate of return, average interest rate, na¨ive approach, Modified Dietz
    JEL: M4 G31
    Date: 2015–02
    URL: http://d.repec.org/n?u=RePEc:mod:wcefin:15021&r=cfn
  5. By: Junni L. Zhang; Wolfgang K. Härdle; Cathy Y. Chen; Elisabeth Bommes
    Abstract: News carry information of market moves. The gargantuan plethora of opinions, facts and tweets on nancial business oers the opportunity to test and analyze the influence of such text sources on future directions of stocks. It also creates though the necessity to distill via statistical technology the informative elements of this prodigious and indeed colossal data source. Using mixed text sources from professional platforms, blog fora and stock message boards we distill via dierent lexica sentiment variables. These are employed for an analysis of stock reactions: volatility, volume and returns. An increased (negative) sentiment will in uence volatility as well as volume. This influuence is contingent on the lexical projection and dierent across GICS sectors. Based on review articles on 100 S&P 500 constituents for the period of October 20, 2009 to October 13, 2014 we project into BL, MPQA, LM lexica and use the distilled sentiment variables to forecast individual stock indicators in a panel context. Exploiting dierent lexical projections, and using dierent stock reaction indicators we aim at answering the following research questions: (i) Are the lexica consistent in their analytic ability to produce stock reaction indicators, including volatility, detrended log trading volume and return? (ii) To which degree is there an asymmetric response given the sentiment scales (positive v.s. negative)? (iii) Are the news of high attention rms diusing faster and result in more timely and ecient stock reaction? (iv) Is there a sector specic reaction from the distilled sentiment measures? We nd there is signicant incremental information in the distilled news ow. The three lexica though are not consistent in their analytic ability. Based on condence bands an asymmetric, attention-specic and sector-specic response of stock reactions is diagnosed.
    Keywords: Investor Sentiment, Attention Analysis, Sector Analysis, Volatility Simulation, Trading Volume, Returns, Bootstrap
    JEL: C81 G14 G17
    Date: 2015–01
    URL: http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2015-005&r=cfn

This nep-cfn issue is ©2015 by Zelia Serrasqueiro. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.