Intangible capital,corporate valuation and asset pricing

Recent studies have found unmeasured intangible capital to be large and important. In this paper we observe that by nature intangible capital is also very different from physical capital. We find it plausible to argue that the accumulation process for intangible capital differs significantly from the process by which physical capital accumulates. We study the implications of this hypothesis for rational firm valuation and asset pricing using a two-sector general equilibrium model. Our main finding is that the properties of firm valuation and stock prices are very dependent on the assumed accumulation process for intangible capital. If one entertains the possibility that intangible investments translates into capital stochastically, we find that plausible levels of macroeconomic volatility are compatible with highly variable corporate valuations, P/E ratios and stock returns. We thank Ellen McGrattan, Edward Prescott, Rene Stulz and an anonymous referee for their helpful comments as well as workshop participants at FAME, the 5th Conference of the Swiss Society for Financial Market Research, the European Central Bank, Columbia Business School Finance Free Lunch and the University of Zürich. This research has benefited from financial support from the National Center for Competence in Research “Financial Valuation and Risk Management”. The National Centers of Competence in Research are managed by the Swiss National Science Foundation on behalf of the Federal Authorities.     

Portfolio efficiency of a dynamic capital asset pricing model

In the present study we show that, based on equally weighted portfolios of continuously listed Finnish and Swedish stocks, aDynamic Model of Capital Asset Pricing (DCAPM) outperforms the static Capital Asset Pricing Model (CAPM) in the Super Criterion Test. It is demonstrated that the portfolio efficiency of the dynamic model is improved, when using a properly defined transition matrix in the Kalman Filtering Algorithm.The advice and encouragement of Professor Leif Nordberg (Department of Statistics, Åbo Akademi University) is gratefully acknowledged. I thank Jaana Aaltonen for her assistance in monitoring the computer programs. I also thank an anonymous referee for his valuable comments and suggestions for improving the quality of the paper.     

过度自信、流动性和资产定价

本文研究了过度自信的投资者在一个多阶段金融市场中是如何影响均衡价格和投资者要求的期望收益的.结论表明,由于投资者过度自信,容易低估风险,从而在一段时期内会使得价格急剧上升.投资者人数实际上是股票市场流动性的一个表征,我们的结论表明,由于过度自信的投资者的存在,他们实际上充当了流动性提供者的角色,从而使得一段时期内即使对理性投资者来说,依然导致了风险的暂时降低,他们也会接受比较高的资产价格,要求相对比较低的期望收益.     

The evolution of portfolio rules and the capital asset pricing model

The aim of this paper is to test the performance of capital asset pricing model (CAPM) in an evolutionary framework. We model an economy where a heterogeneous population of long-lived agents invest their wealth according to different portfolio rules, and prove that traders who either “believe” in CAPM and use it as a rule of thumb, or are endowed with genuine mean-variance preferences, under some very weak conditions, vanish in the long run.We show that a sufficient condition to drive CAPM or mean-variance traders’ wealth shares to zero is that an investor endowed with a logarithmic utility function enters the market.     

固定资产折旧方法的比较分析

影响固定资产折旧的因素主要表现为折旧基数、折旧年限、预计净残值以及折旧方法的选择。企业在选择折旧方法时,要根据企业自身的特点,按照国家政策的相关规定,选择恰当的折旧方法,以适应企业发展的需要。     

A comparison of pricing and hedging performances of equity derivatives models

This article investigates the pricing/hedging conundrum, i.e. the observation of a mismatch between derivatives models’ pricing and hedging performances, that has so far been under-emphasized as the literature tends to focus on increasingly complicated option pricing models, without adequately addressing hedging performance. Hence, we analyse the ability of the Black–Scholes, Practitioner Black–Scholes, Heston–Nandi and Heston models to Delta-hedge a set of call options on the S&P500 index and Apple stock. We extend earlier studies in that we consider the impact of asset dynamics, apply a stringent payoff replication strategy, look at the impact of moneyness at maturity and test for the robustness to the parameters’ calibration frequency and Delta-Vega hedging. The study shows that adding risk factors to a model, as stochastic volatility, should only be considered in light of the data dynamics. Even then, however, more complicated models generally fare poorly for hedging purposes. Hence, a better fit of a model to option prices is not a good indicator of its hedging performance, and so of its ability to describe the underlying dynamics. This can be understood for reasons of over-fitting. Those findings hint to a potentially appealing hedging-based calibration of models’ parameters, rather than the standard pricing-based one.     

Intertemporal data and travel cost analysis

This paper considers the use of multi-year data in travel cost analysis. To exploit the information embedded within intertemporal data, two broad approaches are examined: multiple year cross sections and panel models. Multiple year cross sections can be used to detect trends, and to test for stability of behavior. Panel models can be used to control for unobservable factors that are individual specific. Unfortunately, the low intertemporal variability of travel cost data sets weakens the power of panel estimators. Using aggregate data from the Boundary Waters Canoe Area, the stability of demand processes over the 1980–1986 period is investigated, as well as the problems inherent in using panel estimators in travel cost analysis.     

Portfolio Composition and Valuation Effects in Emerging Market Economies*

ABSTRACT

The increase in cross-border assets and liabilities of nations with globalization, implies small asset price and currency movements create large wealth changes. The national net external position is increasingly driven by valuation effects, which the current account does not capture. We analyze valuation effects for a group of seven emerging economies, namely Brazil, Colombia, India, Republic of Korea, Mexico, Peru and Turkey for the time period 2005:Q1-2015:Q4 by scrutinizing their external asset portfolio while controlling for country fundamentals. Both asset and liability categories of Direct Investment equity are found to positively impact valuation. Equity liabilities and debt assets of Portfolio Investment positively influence valuation. Debt liabilities of all kinds of investment negatively impact valuation. Countries with stronger currency tend to gain through valuation effects. An appreciated real effective exchange rate is associated with higher valuation gains. We also found non-linear effects of the composition of external debt portfolio by interacting external portfolio and country characteristics. The external portfolio selection of emerging economies (with more in Direct Investment equity liabilities and Portfolio Investment debt assets) in the period has shielded them from global volatility, and enabled valuation gains.     

Augmenting travel cost models with contingent behavior data

This paper proposes contingent behavior survey questions as a valuable supplement to observed data in travel cost models of non-market demand for recreational resources. A set of observed and contingent behavior results for each survey respondent allows the researcher to control for individual heterogeneity by taking advantage of panel data methods when exploring the nature of respondent demands. The contingent scenarios also provide opportunities to (a) test for differences between observed and contingent preferences and/or (b) assess likely demands under conditionsbeyond the domain of observed variation in costs or resource attributes. Most importantly, contingent scenarios allow the researcher to imposeexogenously varying travel costs. Exogenous imposition of travel costs together with panel methods reduces the omitted variables bias that plagues observed-data travel cost models of recreational demand. Using a convenience sample of data for illustrative purposes, we show how to estimate the demand for recreational angling by combining observed and contingent behavior data. We begin with simple naive pooled Poisson models and progress to more theoretically appropriate fixed effects panel Poisson specifications.The authors are at the University of Nevada and UCLA, respectively. We gratefully acknowledge the comments of both Scott Shonkwiler and participants in the W133 meetings in Santa Fe, New Mexico and for research material provided by Wayne Gray. The data were provided by Rang Narayanan. Research assistance was provided by Jerry McGraw and Natalie Tucker. Research partially supported by the Nevada Experiment Station. Any errors or omissions remain the authors' responsibility.     

Which is the best: A comparison of asset pricing factor models in Chinese mutual fund industry

Factor models are commonly used in estimating risk-adjusted fund performance. We compare the commonly used factor models in empirical asset pricing studies and find that Fama and French (2015) five-factor model outperforms other models in the Chinese mutual fund industry and in most fund segments. The factor models we tested are more effective in explaining the return of index funds than other types. Meanwhile, we also find that the capital asset pricing model (CAPM) better controls the estimated alpha dispersion than other models. Though most multifactor models including Carhart (1997) have higher R-squared than CAPM, the cross-sectional differences between them are not statistically significant.     

A counterfactual analysis of the Argentinian monetary transformation in 2002

A hard peg restored economic stability in Argentina during the nineties but made it also vulnerable to real shocks in so far as the economy was highly dollarized. A devaluation in 1998 in Brasil, its main partner, damaged the Argentinian competitiveness and resulted in a fall in export demand. There was a need for a real adjustment but removing the peg would have implied large balance sheet effects and raised serious financial issues. This article endeavours to learn a lesson about the aftermath of hard peg regime from the Argentinian experience. It is based on a dynamic macroeconomic model to assess the impact of three scenarios, already suggested in the literature. Two hypothetical, a floating regime and dollarization and one which was actually implemented in 2002, the pesification of the whole economy. The simulations suggest that pesification was the only scenario with unambiguous expansionary effects.     

Analyzing the effect of dynamically assigned treatments using duration models,binary treatment models,and panel data models

Often, the moment of a treatment and the moment at which the outcome of interest occurs are realizations of stochastic processes with dependent unobserved determinants. Notably, both treatment and outcome are characterized by the moment they occur. In this paper, we compare different methods of inference of the treatment effect. We argue that the timing of the treatment relative to the outcome conveys useful information on the treatment effect, which is discarded in binary treatment frameworks. Thanks to participants at the Tenth Panel Data Conference in Berlin, 2002, in particular to our discussant Bo Honoré, for helpful comments. Jaap Abbring acknowledges financial support by the Royal Netherlands Academy of Arts and Sciences.     

Uncertainty of outcome or strengths of teams: an economic analysis of attendance demand for international cricket

A significant body of theoretical literature has argued that popular interest in sporting contests between teams is heavily influenced by how difficult it is to predict the result ex-ante. Empirical research has, however, been unable to reach a consensus on the magnitude of uncertainty of outcome on demand. In this article, we seek to resolve this impasse by distinguishing between uncertainty of outcome in the short run and uncertainty of outcome in the long run. We also show that it is important to control for the independent effect of absolute team strength when testing the uncertainty of outcome hypothesis. Using data on over 380 Test cricket matches played in England, Australia and New Zealand since 1980, we find that short-run uncertainty of outcome has a significant impact on attendance demand and that absolute team strength has better explanatory power for attendance demand than does long-run uncertainty of outcome. Our results suggest some policy implications for the management and organization of international cricket.     

Structural analysis with mixed-frequency data: A model of US capital flows

We develop a new structural Vector Autoregressive (SVAR) model for analysis with mixed-frequency data. The MIDAS-SVAR model allows to identify structural dynamic links exploiting the information contained in variables sampled at different frequencies. It also provides a general framework to test homogeneous frequency-based representations versus mixed-frequency data models. A set of Monte Carlo experiments suggests that the test performs well both in terms of size and power. The MIDAS-SVAR is then used to study how monetary policy and financial uncertainty impact on the dynamics of gross capital inflows to the US. While no relation is found when using standard quarterly data, mixed frequency analysis exploiting the variability present in the series within the quarter shows that the effect of an interest rate shock is greater the longer the time lag between the month of the shock and the end of the quarter.     

Carbon pricing and terms of trade effects for China and India: A general equilibrium analysis

Using country-specific dynamic computable general equilibrium (CGE) models, this paper estimates carbon prices in China and India, and compares the effects of carbon pricing policies under terms of trade effects. Estimated carbon prices are higher in China due to differences in emission intensity and in the rate of deployment of new technologies in the models. Differences in carbon prices open up the possibility of carbon trading between the two countries to achieve mitigation objectives. Further, under assumptions about different exchange rate regimes and international fossil fuel prices, the effects of carbon pricing policies on the two economies are mostly similar in terms of direction but, expectedly, different in terms of magnitude. Terms of trade effects could exacerbate carbon pricing effects to a greater degree in China as the country is significantly more dependent than India on external trade and investment. Policymakers should factor in terms of trade effects while designing or evaluating carbon pricing policies in the two countries.     

Dynamic models of R & D,innovation and productivity: Panel data evidence for Dutch and French manufacturing

This paper introduces dynamics in the R&D-to-innovation and innovation-to-productivity relationships, which have mostly been estimated on cross-sectional data. It considers four nonlinear dynamic simultaneous equations models that include individual effects and idiosyncratic errors correlated across equations and that differ in the way innovation enters the conditional mean of labor productivity: through an observed binary indicator, an observed intensity variable or through the continuous latent variables that correspond to the observed occurrence or intensity. It estimates these models by full information maximum likelihood using two unbalanced panels of Dutch and French manufacturing firms from three waves of the Community Innovation Survey. The results provide evidence of robust unidirectional causality from innovation to productivity and of stronger persistence in productivity than in innovation.     

Effects on the medical revenue of comprehensive pricing reform in Chinese urban public hospitals after removing drug markups: case of Nanjing

Aims: The State Council of China requires that all urban public hospitals must eliminate drug markups by September 2017, and that hospital drugs must be sold at the purchase price. Nanjing-one of the first provincial capital cities to implement the reform—is studied to evaluate the effects of the comprehensive reform on drug prices in public hospitals, and to explore differential compensation plans.

Methods: Sixteen hospitals were selected, and financial data were collected over the 48-month period before the reform and for 12 months after the reform. An analysis was carried out using a simple linear interrupted time series model.

Results: The average difference ratio of drug surplus fell 13.39% after the reform, and the drug markups were basically eliminated. Revenue from medical services showed a net growth of 28.25%. The overall compensation received from government financial budget and medical service revenue growth was 103.69% for the loss from policy-permitted 15% markup sales, and 116.48% for the net loss. However, there were large differences in compensation levels at different hospitals, ranging from –21.92% to 413.74% by medical services revenue growth, causing the combined rate of both financial and service compensation to vary from 28.87–413.74%, There was a significant positive correlation between the services compensation rate and the proportion of medical service revenue (p?<?.001), and the compensation rate increased by 8% for every 1% increase in the proportion of services revenue.

Discussion: Nanjing’s pricing and compensation reform has basically achieved the policy targets of eliminating the drug markups, promoting the growth of medical services revenue, and adjusting the structure of medical revenue. However, the growth rate of service revenue of hospitals varied significantly from one another.

Conclusions: Nanjing’s reform represents successful pricing and compensation reform in Chinese urban public hospitals. It is recommended that a differentiated and dynamic compensation plan should be established in accordance with the revenue structure of different hospitals.     

A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data

This paper documents multivariate forecast disagreement among professional forecasters and discusses implications for models of heterogeneous expectation formation. Disagreement varies over time and is positively correlated with general (economic) uncertainty. The degree to which individual forecasters disagree with the average forecast tends to persist over time. Models of heterogeneous expectation formation can be modified by introducing heterogeneous signal-to-noise ratios to match this feature. Furthermore, disagreement about correlations of different macroeconomic variables is high on average. In general, multivariate forecast data can be used more effectively than it has been to estimate models with heterogeneous expectations and to test the mechanisms used to generate disagreement in these models.     

Disaggregated data and trade policy analysis: The value of linking partial and general equilibrium models

Computable General Equilibrium (CGE) models are now routinely utilized for the evaluation of trade policy reforms, yet they are typically quite highly aggregated, which limits their usefulness to trade negotiators who are often interested in impacts at the tariff line. On the other hand, Partial Equilibrium (PE) models, which are typically used for analysis at disaggregate levels, deprive the researcher of the benefits of an economy-wide analysis, which is required to examine the overall impact of broad-based trade policy reforms. Therefore, a PE–GE, nested modeling framework has the prospect of offering an ideal tool for trade policy analysis. In this paper, we develop a PE model that captures international trade, domestic consumption and output, using Constant Elasticity of Transformation (CET) and Constant Elasticity of Substitution (CES) structures, market clearing conditions and price linkages, nested within the standard GTAP model. In particular, we extend the welfare decomposition of Huff and Hertel (2001) to this PE–GE model in order to contrast the sources of welfare gain in PE and GE analyses. To illustrate the usefulness of this model, we examine the contentious issue of tariff liberalization in the Indian auto sector, using PE, GE and PE–GE models. Both the PE and PE–GE models show that the imports of motorcycles and automobiles change drastically with both unilateral and bilateral tariff liberalization by India, but the PE model does a poor job predicting the overall size and price level in the industry, post-liberalization. On the other hand, the GE model overestimates substitution between regional suppliers due to “false competition” and underestimates the welfare gain, due to the problem of tariff averaging in the aggregated model. These findings are shown to be robust to wide variation in model parameters. We conclude that the linked model is superior to both the GE and PE counterparts.     

On the performance of the Chow-Lin procedure for quarterly interpolation of annual data: Some Monte-Carlo analysis

Most of the countries of the OECD offer quarterly estimates of their national growth or of their Gross National Product. Official Statistical Agencies in western countries have to deal with the problem of estimating Quarterly National Accounts series congruently with Annual National Accounts. In Spain, the Instituto Nacional de Estadística uses the Chow-Lin disaggregation method, which is based on information provided by a group of high-frequency related variables, to estimate the quarterly components of National Accounts from annual components. In this paper, we analyse the relative quality of the estimates obtained through the Chow-Lin procedure, under different sets of hypotheses.JEL Classification: C15, C43, M40We are grateful to Maria Amparo Ripoll for her assistance. The authors also wish to thank three anonymous referees and an editor for their constructive suggestions and comments. This research was partially made during the stay of the first author at the Universidad Carlos III de Madrid. It has been partially supported by the research project DGCYT PB98-1460.