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on Corporate Finance |
| By: | Niinimäki, Juha-Pekka (Department of Economics, Helsinki School of Economics); Takalo, Tuomas (Bank of Finland Research); Kultti, Klaus (Department of Economics, University of Helsinki) |
| Abstract: | This paper studies how comparing can be used to provide information in financial markets in the presence of a hidden characteristics problem. Although an investor cannot precisely estimate the future returns of an entrepreneur’s projects, the investor can mitigate the asymmetric information problem by ranking different entrepreneurs and financing only the very best ones. Information asymmetry can be eliminated with certainty if the number of compared projects is sufficiently large. Because comparing favours centralised information gathering, it creates a novel rationale for the establishment of a financial intermediary. |
| Keywords: | asymmetric information; banking; corporate finance; financial intermediation; ranking; venture capital |
| JEL: | G21 G24 |
| Date: | 2006–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:bofrdp:2006_001&r=cfn |
| By: | Chollete, Lorán (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration); Næs, Randi (Norges Bank); Skjeltorp, Johannes A. (Norges Bank) |
| Abstract: | This paper constructs fundamental liquidity measures and investigates the pricing implications of shared variation in a large set of high frequency liquidity measures. Through a common factor analysis we estimate three orthogonal liquidity variables that statistically capture time series variation in market wide liquidity. We uncover three main results. First, we document that not one but two of the common liquidity factors are significantly related to cross-sectional differences in returns. Interestingly, the two factors are related to the time and quantity dimension of liquidity, not the price dimension. Second, and perhaps more striking, we discover substantial heterogeneity in the liquidity factors. In particular, order-based liquidity measures cannot explain return differences while trade-based liquidity measures can explain returns. This heterogeneity is borne out by asset pricing tests, which indicate substantial differences in the pricing of trade and order-based portfolios. Third, there is strong evidence of parameter instability in the pricing of liquidity. |
| Keywords: | Market microstructure; Common factor; Asset pricing; Liquidity factor; high frequency liquidity |
| JEL: | G12 G14 |
| Date: | 2006–08–04 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:nhhfms:2006_009&r=cfn |
| By: | Aase, Knut K. (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration) |
| Abstract: | In this paper we make use of option pricing theory to infer about historical equity premiums. This we do by comparing the prices of an American perpetual put option computed using two different models: The first is the standard one with continuous, zero expectation, Gaussian noise, the second is a strikingly similar model, except that the zero expectation noise is of Poissonian type. The interesting fact that makes this comparison worthwhile, is that the probability distribution under the risk adjusted measure turns out to depend on the equity premium in the Poisson model, while this is not so for the standard, Brownian motion version. This difference is utilized to find the intertemporal, equilibrium equity premium. We apply this technique to the US equity data of the last century and find that, if the risk free short rate was around one per cent, this corresponds to a risk premium on equity about two and a half per cent. On the other hand, if the risk free rate was about four per cent, we find that this corresponds to an equity premium of around four and a half per cent. The advantage with our approach is that we only need equity data and option pricing theory, no consumption data was necessary to arrive at these conclusions. We round off the paper by investigating if the procedure also works for incomplete models. |
| Keywords: | Historical equity premiums; perpetual American put option; equity premium puzzle; risk free rate puzzle; geometric Brownian motion; geometric Poisson process; CCAPM |
| JEL: | G00 |
| Date: | 2005–11–30 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:nhhfms:2005_011&r=cfn |
| By: | Panicos Demetriades; Michail Karoglou; Siong Hook Law |
| Abstract: | This paper employs several newly proposed techniques to identify the number and timing of structural breaks in the variance dynamics of stock market returns. These techniques are applied to five East Asian emerging markets, all of which liberalised their financial markets during the period under consideration. It is shown that the detected breakdates in the volatility of stock market returns do not correspond to official liberalisation dates; as a result the use of official liberalisation dates as breakdates is likely to result in inaccurate inference. By using data driven techniques to detect multiple structural changes a richer - and inevitably more accurate - pattern of volatility dynamics emerges in comparison to focussing on official liberalisation dates. |
| Date: | 2006–10 |
| URL: | http://d.repec.org/n?u=RePEc:lec:leecon:06/13&r=cfn |
| By: | L. Grossi; G. Morelli |
| Abstract: | In order to cope with the stylized facts of financial time series, many models have been proposed inside the GARCH family (e.g. EGARCH, GJR-GARCH, QGARCH, FIGARCH, LSTGARCH) and the stochastic volatility models (e.g. SV). Generally, all these models tend to produce very similar results as concerns forecasting performance. Most of the time it is difficult to choose which is the most appropriate specification. In addition, all these models are very sensitive to the presence of atypical observations. The purpose of this paper is to provide the user with new robust model selection procedures in financial models which downweight or eliminate the effect of atypical observations. The extreme case is when outliers are treated as missing data. In this paper we extend the theory of missing data to the family of GARCH models and show how to robustify the loglikelihood to make it insensitive to the presence of outliers. The suggested procedure enables us both to detect atypical observations and to select the best models in terms of forecasting performance. |
| Keywords: | GARCH models, extreme value, robust estimation |
| JEL: | C16 C22 C53 G15 |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:par:dipeco:2006-se02&r=cfn |
| By: | Ojo, Marianne |
| Abstract: | Prior to the adoption of the FSA (Financial Services Authority) model, supervision of UK banks was carried out by the Bank of England. Although the Bank of England's informal involvement in bank supervision dates back to the mid nineteenth century, it was only in 1979 that it acquired formal powers to grant or refuse authorization to carry out banking business in the UK. Events such as the Secondary Banking Crisis of 1973-74 and the Banking Coordination Directive of 1977 resulted in legislative changes in the form of the Banking Act 1979. Bank failures through the following years then resulted in changes to the legislative framework. This article looks into the claim that the FSA model has improved in terms of accountability in comparison to its predecessor, the Bank of England. It considers the impact the FSA has made on the financial services sector and on certain legislation since its introduction. Through a comparison with the Bank of England, previous and present legislation, reports and other sources, an assessment can be made as to whether the FSA provides more accountability. Evidence provided here supports the conclusion that the FSA is both equipped with better accountability mechanisms and executes its functions in a more accountable way than its predecessor. |
| Keywords: | regulators; accountability; supervision; financial; services |
| JEL: | G28 |
| Date: | 2005–11 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:228&r=cfn |
| By: | Scalas, Enrico; Kim, Kyungsik |
| Abstract: | This paper illustrates a procedure for fitting financial data with alpha-stable distributions. After using all the available methods to evaluate the distribution parameters, one can qualitatively select the best estimate and run some goodness-of-fit tests on this estimate, in order to quantitatively assess its quality. It turns out that, for the two investigated data sets (MIB30 and DJIA from 2000 to present), an alpha-stable fit of log-returns is reasonably good. |
| Keywords: | finance; statistical methods; stable distributions |
| JEL: | C14 C16 G00 |
| Date: | 2006–08–23 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:336&r=cfn |