Effect of data acquisition accuracy on timing of stand harvests and expected net present value

Abstract

Power generation investment opportunities evaluation: A comparison between net present value and real options approach

To evaluate an investment project in the competitive electricity market, there are several key factors that affects the project's value: the present value that the project could bring to investor, the possible future course of actions that investor has and the project's management flexibility. The traditional net present value (NPV) criteria has the ability to capture the present value of the project's future cash flow, but it fails to assess the value brought by market uncertainty and management flexibility. By contrast with NPV, the real options approach (ROA) method has the advantage to combining the uncertainty and flexibility in evaluation process. In this paper, a framework for using ROA to evaluate the generation investment opportunity has been proposed. By given a detailed case study, the proposed framework is compared with NPV and showing a different results

Perpetual debt valuation: the net present value myopia

Would you prefer to receive a fixed rent for a period of 50 years, 75 years or perpetually? Well, if you have chosen the perpetual option, you are absolutely right. However, when considering a mathematical and financial approach, they may all end up roughly the same whenever the Net Present Value (NPV) is approximately identical. It makes common sense to choose the perpetual option even if the NPV exhibits myopia when computing the discount value of a fixed yearly rent. After a certain period, the discount value becomes approximately the same even when adding more yearly fixed rents. Corporations and governments issue perpetual bonds while recognizing these may not represent a very good financing strategy and thus implying that most of these issues are either callable or convertible on the issuer’s request. In approaching the existing perpetual debt related NPV myopia, this paper holds two main goals: firstly, we intend to study the behaviours of perpetual debt yields against other perpetual instruments and, secondly, we consider the financial methods for assessing the value of money before proposing a formula adjustment that might serve to overcome default NPV when evaluating fixed rents in perpetuity.

Perpetual debt valuation: the net present value myopia

Would you prefer to receive a fixed rent for a period of 50 years, 75 years or perpetually? Well, if you have chosen the perpetual option, you are absolutely right. However, when considering a mathematical and financial approach, they may all end up roughly the same whenever the Net Present Value (NPV) is approximately identical. It makes common sense to choose the perpetual option even if the NPV exhibits myopia when computing the discount value of a fixed yearly rent. After a certain period, the discount value becomes approximately the same even when adding more yearly fixed rents. Corporations and governments issue perpetual bonds while recognizing these may not represent a very good financing strategy and thus implying that most of these issues are either callable or convertible on the issuer’s request. In approaching the existing perpetual debt related NPV myopia, this paper holds two main goals: firstly, we intend to study the behaviours of perpetual debt yields against other perpetual instruments and, secondly, we consider the financial methods for assessing the value of money before proposing a formula adjustment that might serve to overcome default NPV when evaluating fixed rents in perpetuity.

Net Present Value Table – 2% per annum Weeks 1 through 100 Effective June 27, 2014

This table gives the net present value at 2 per cent for weeks 1 through 100.

Net Present Value Table – 2% per annum Weeks 101 through 500 Effective June 27, 2014

This table gives the net present value at 2 per cent for weeks 101 through 500.

Nettonykyarvon soveltaminen liiketoiminnassa

Työn tavoitteena on selvittää, mitkä ovat nettonykyarvon edut ja haitat, sekä tutkia minkälaisia sovellettuja nettonykyarvomenetelmiä on haittojen eliminoimiseksi. Työssä tutkitaan myös sitä, miten nettonykyarvoa käytetään nykyajan liiketoiminnassa. Työn teoriaosuudessa tarkastellaan lyhyesti nettonykyarvon historiaa, määritellään nettonykyarvo sekä sen edut ja haitat. Sovellusmenetelmistä käsitellään reaalioptioiden tuomaa lisäarvoa investointiprojekteissa sekä nettonykyarvon sovellusta, jossa varaudutaan riskiin erottelemalla se omaksi termikseen. Nykyajan liiketoiminnassa nettonykyarvoa sovelletaan elinkaariajattelussa sekä liiketoimintasuhteissa. Työ sisältää teoriaosuuden sekä laskentaosuuden, jossa eri nettonykyarvomenetelmille on laskettu tulokset osittain samaa lähtötilannetta käyttäen. Työssä havaitaan, että sovellusmenetelmät, etenkin reaalioptiot, tuovat lisäarvoa ja joustavuutta investointiprojekteihin sekä liiketoimintasuhteisiin.

Modelling Housing Prices using a Present Value State Space Model

This paper introduces a State Space approach to explain the dynamics of rent growth, expected returns and Price-Rent ratio in housing markets. According to the present value model, movements in price to rent ratio should be matched by movements in expected returns and expected rent growth. The state space framework assume that both variables follow an autoregressive process of order one. The model is applied to the US and UK housing market, which yields series of the latent variables given the behaviour of the Price-Rent ratio. Resampling techniques and bootstrapped likelihood ratios show that expected returns tend to be highly persistent compared to rent growth. The Öltered expected returns is considered in a simple predictability of excess returns model with high statistical predictability evidenced for the UK. Overall, it is found that the present value model tends to have strong statistical predictability in the UK housing markets.

Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices

We re-examine the dynamics of returns and dividend growth within the present-value framework of stock prices. We find that the finite sample order of integration of returns is approximately equal to the order of integration of the first-differenced price-dividend ratio. As such, the traditional return forecasting regressions based on the price-dividend ratio are invalid. Moreover, the nonstationary long memory behaviour of the price-dividend ratio induces antipersistence in returns. This suggests that expected returns should be modelled as an AFIRMA process and we show this improves the forecast ability of the present-value model in-sample and out-of-sample.

Modelling Housing Prices using a Present Value State Space Model

This paper introduces a State Space approach to explain the dynamics of rent growth, expected returns and Price-Rent ratio in housing markets. According to the present value model, movements in price to rent ratio should be matched by movements in expected returns and expected rent growth. The state space framework assume that both variables follow an autoregression process of order one. The model is applied to the US and UK housing market, which yields series of the latent variables given the behaviour of the Price-Rent ratio. Resampling techniques and bootstrapped likelihood ratios show that expected returns tend to be highly persistent compared to rent growth. The filtered expected returns is considered in a simple predictability of excess returns model with high statistical predictability evidence for the UK. Overall, it is found that the present value model tends to have strong statistical predictability in the UK housing markets.

Consumption smoothing in Latin America: an empirical assessment of present value models

The study aims to assess the empirical adherence of the permanent income theory and the consumption smoothing view in Latin America. Two present value models are considered, one describing household behavior and the other open economy macroeconomics. Following the methodology developed in Campbell and Schiller (1987), Bivariate Vector Autoregressions are estimated for the saving ratio and the real growth rate of income concerning the household behavior model and for the current account and the change in national cash ‡ow regarding the open economy model. The countries in the sample are considered separately in the estimation process (individual system estimation) as well as jointly (joint system estimation). Ordinary Least Squares (OLS) and Seemingly Unrelated Regressions (SURE) estimates of the coe¢cients are generated. Wald Tests are then conducted to verify if the VAR coe¢cient estimates are in conformity with those predicted by the theory. While the empirical results are sensitive to the estimation method and discount factors used, there is only weak evidence in favor of the permanent income theory and consumption smoothing view in the group of countries analyzed.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

It is well known that cointegration between the level of two variables (e.g. prices and dividends) is a necessary condition to assess the empirical validity of a present-value model (PVM) linking them. The work on cointegration,namelyon long-run co-movements, has been so prevalent that it is often over-looked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. This amounts to investigate whether short-run co-movememts steming from common cyclical feature restrictions are also present in such a system. In this paper we test for the presence of such co-movement on long- and short-term interest rates and on price and dividend for the U.S. economy. We focuss on the potential improvement in forecasting accuracies when imposing those two types of restrictions coming from economic theory.

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.