nep-fmk New Economics Papers
on Financial Markets
Issue of 2007‒11‒17
nine papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Risk and Derivative Price By Yusuke Osaki
  2. Liquidity Risk Management By Charles Goodhart
  3. Financial Risk in the Biotechnology Industry By Joseph H. Golec; John A. Vernon
  4. The Structure of Multiple Credit Relationships: Evidence from US Firms By Luigi Guiso; Raoul Minetti
  5. The Effects of Federal Funds Target Rate Changes on S&P100 Stock Returns, Volatilities, and Correlations By Chulia-Soler, H; Martens, M.P.E.; Dijk, D.J.C. van
  6. Financial Markets and International Risk Sharing By Martin Schmitz
  7. Where Does Price Discovery Occur in FX Markets? By Chris D'Souza
  8. Global Yield Curve Dynamics and Interactions: A Dynamic Nelson-Siegel Approach By Francis X. Diebold; Canlin Li; Vivian Z. Yue
  9. The use of derivatives in the spanish mutual fund industry By José M. Marín; Thomas A. Rangel

  1. By: Yusuke Osaki (Risk & Sustainable Management Group, School of Economics, University of Queensland)
    Abstract: We consider an asset market traded three types of assets: the risk–free asset, the market portfolio and derivatives written on the market portfolio return. We determine a sufficient condition to guarantee that noise risk monotonically changes their derivatives. The condition is that Arrow–Pratt absolute risk aversion is decreasing and convex.
    Keywords: Derivative price, Noise risk, Nonlineality, Risk aversion
    JEL: D51 D81 G12
    Date: 2007–03
    URL: http://d.repec.org/n?u=RePEc:rsm:riskun:r07_2&r=fmk
  2. By: Charles Goodhart
    Abstract:  
    Date: 2007–10
    URL: http://d.repec.org/n?u=RePEc:fmg:fmgsps:sp175&r=fmk
  3. By: Joseph H. Golec; John A. Vernon
    Abstract: The biotechnology industry has been an engine of innovation for the U.S. healthcare system and, more generally, the U.S. economy. It is by far the most research intensive industry in the U.S. In our analyses in the current paper, for example, we find that, over the past 25 years, average R&D intensity (R&D spending to total firm assets) for this industry was 38 percent. Consider that over this same period average R&D intensity for all industries was only about 3 percent. In the current paper we examine this industry along a number of dimensions and estimate its average financial risk. Specifically, we use Compustat and Center for Research in Securities Prices (CRSP) data from 1982 to 2005 for firms defined by the North American Industry Classification System (NAICS) as biotechnology firms to estimate several Fama-French three factor return models. The finance literature has established this model as the gold standard. Single factor models like the Capital Asset Pricing Model (CAPM) do not capture all of the types of systematic risk that influence firm cost of capital. In particular, the CAPM does not reflect the empirical evidence that supports both a size-related and a book-to-market related systematic risk factor . Both of these factors, based on biotech industry characteristics, will exert a greater influence on biotech firms, on average. Another implication is, of course, that cost of capital estimates for the industry will be underestimated when a single factor model, like the CAPM, is used. This also implies that the cost estimates of bringing a new drug and/or biologic to market will be understated if financial risk and cost of capital are measured using a single-factor model. In the current study we find that biotechnology firms are exposed to greater financial risk than other industries and are also more sensitive to policy shocks that affect, or could affect, industry profitability. Average nominal costs of capital over the 1982-2005 time period were 16.25 percent for biotechnology firms. Of course, these average estimates obscure significant variation in financial risk at the firm level, but nonetheless shed light on some interesting aggregate differences in risk. In the current paper we discuss the theoretical links between financial risk, stock prices and returns, and R&D spending. Several caveats are also discussed.
    JEL: G18 G32 I0 I18 K23 L0 L2 L21 L5 L65
    Date: 2007–11
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:13604&r=fmk
  4. By: Luigi Guiso; Raoul Minetti
    Abstract: When firms borrow from multiple concentrated creditors such as banks they appear to differentiate their allocation of borrowing. In this paper, we put forward hypotheses for this borrowing pattern based on incomplete contract theories and test them using a sample of small U.S. firms. We find that firms with more valuable, more redeployable, and more homogeneous assets differentiate borrowing more sharply across their concentrated creditors. We also find that borrowing differentiation is inversely related to restructuring costs and positively related to firms’ informational transparency. This evidence supports the predictions of incomplete contract theories: the structure of credit relationships appears to be used as a device to discipline creditors and entrepreneurs, especially during corporate reorganizations.
    Keywords: Credit Relationships, Multiple Creditors, Borrowing Allocation
    JEL: G21 G33 G34
    Date: 2007
    URL: http://d.repec.org/n?u=RePEc:eui:euiwps:eco2007/46&r=fmk
  5. By: Chulia-Soler, H; Martens, M.P.E.; Dijk, D.J.C. van (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)
    Abstract: We study the impact of FOMC announcements of Federal funds target rate decisions on individual stock prices at the intraday level. We find that the returns, volatilities and correlations of the S&P100 index constituents only respond to the surprise component in the announcement, as measured by the change in the Federal funds futures rate. For example, an unexpected 25 basis points increase of the target rate leads on average to a 113 basis points negative market return within five minutes after the announcement. It also increases market volatility during the 60-minute window around the announcement with 147 basis points. Positive surprises, meaning bad news for stocks, provoke a stronger reaction than negative surprises. Market participants also respond differently to good and bad news. In case of bad news for stocks the fact that there is a surprise matters most, whereas in case of good news the magnitude of the surprise is more important. Across sectors, Financials and IT show the strongest response to target rate surprises.
    Keywords: monetary policy announcements;interest rate surprises;high-frequency data;realized volatility;
    Date: 2007–10–25
    URL: http://d.repec.org/n?u=RePEc:dgr:eureri:300011911&r=fmk
  6. By: Martin Schmitz
    Abstract: Panel analysis of 20 industrial countries shows evidence for pro-cyclicality of capital gains on domestic stock markets - in particular over a medium term horizon. Thus, with cross-border ownership of portfolio equity investments, potential for international smoothing of domestic output fluctuations by means of the capital gains channel is found. Individual country analysis reveals substantial heterogeneity of cyclicality patterns. Evidence suggests that this cross-country variation can be explained by the level of economic development and the size of financial markets.
    Date: 2007–11–09
    URL: http://d.repec.org/n?u=RePEc:iis:dispap:iiisdp233&r=fmk
  7. By: Chris D'Souza
    Abstract: Trades in foreign exchange markets are initiated around the world and around the clock. This study illustrates that trades are more informative when initiated in a local country or in major foreign exchange centers like London and New York. Evidence suggests that informational asymmetries based on geography arise from the market making capacity of dealers and the customer order flow that dealers capture during regional business hours. Findings also show that market orders initiated in price-correlated FX markets are not informative. Transparency in quotes on electronic trading platforms may prevent informed participants from exploiting information across FX markets. Overall, these results are robust across different market conditions.
    Keywords: Market structure and pricing; Exchange rates; Financial markets
    JEL: F31 G15
    Date: 2007
    URL: http://d.repec.org/n?u=RePEc:bca:bocawp:07-52&r=fmk
  8. By: Francis X. Diebold; Canlin Li; Vivian Z. Yue
    Abstract: The popular Nelson-Siegel (1987) yield curve is routinely fit to cross sections of intra-country bond yields, and Diebold and Li (2006) have recently proposed a dynamized version. In this paper we extend Diebold-Li to a global context, modeling a potentially large set of country yield curves in a framework that allows for both global and country-specific factors. In an empirical analysis of term structures of government bond yields for the Germany, Japan, the U.K. and the U.S., we find that global yield factors do indeed exist and are economically important, generally explaining significant fractions of country yield curve dynamics, with interesting differences across countries.
    JEL: C01 G12
    Date: 2007–11
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:13588&r=fmk
  9. By: José M. Marín (IE Business School and IMDEA); Thomas A. Rangel (Universitat Pompeu Fabra)
    Abstract: We study the use of derivatives in the Spanish mutual fund industry. The picture that emerges from our analysis is rather negative. In general, the use of derivatives does not improve the performance of the funds. In only one out of eight categories we find some (very weak and not robust) evidence of superior performance. In most of the cases users significantly underperform non users. Furthermore, users do not seem to exhibit superior timing or selectivity skills either, but rather the contrary. This bad performance is only partially explained by the larger fees funds using derivatives charge. Moreover, we do not find evidence of derivatives being used for hedging purposes. We do find evidence of derivatives being used for speculation. But users in only one category exhibit skills as speculators. Finally, we find evidence of derivatives being used to manage the funds\' cash inflows and outflows more efficiently.
    Keywords: mutual funds; derivative use; risk management
    JEL: G11 G2
    Date: 2007–10–28
    URL: http://d.repec.org/n?u=RePEc:imd:wpaper:wp2007-22&r=fmk

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