Assignment Sample FIN516 Corporate Finance

Question 1

When looking at projected stock returns over time, the authors of Cochrane (2011) found “overwhelming evidence” that they fluctuate over time. According to the authors, this has significant implications for how investors should allocate their money when faced with a variety of investment horizons. 1 When investors account for variances in projected returns over the course of an investment opportunity’s life cycle, they will be able to better align their investment horizons with their investments in the future, resulting in improved overall results. Investors must provide estimates of expected holding period returns at the company level in order to properly manage their money over time, which is a necessity of long-term investing (Drobetz2018).http://FIN516 Corporate Finance It is necessary for investors who divide their money across time to provide estimates of projected holding period returns at the firm level in order to deploy their capital effectivelyhttp://FIN516 Corporate Finance when designing optimal portfolios, for example. Failure to account for the dynamics of projected returns increases the risk of making poor capital allocation decisions and making significant stock valuation errors, according to the literature. For example, expecting that expected returns for a single firm will be constant over time is wrong, which can lead to this conclusion. (Kling, 2021)http://FIN516 Corporate Finance

Question 2  

The fact that, despite the fact that it is frequently used, there is no universal approach for calculating time-varying projected holding period returns on equity at the business level that can be applied to a broad range of firms is worth mentioning, given the significance of this issue and the fact that this approach is often used. Traditional CAPMs, such as the three-factor model developed by Fama and French (1993) http://FIN516 Corporate Financeor modern counterparts presented in the implied cost of equity capital literature, do not maintain constant expected returns over time.

Using an easily implementable model of expected holding period returns over arbitrarily long time horizons that are both theoretically motivated and efficient, this research was successful in bridging a significant gap in the existing literature. The model can be applied in a variety of situations and is both theoretically motivated and efficient. This model, according to Drobetz, (2018),http://FIN516 Corporate Finance can be used to anticipate future cash flows in the future. However, it incorporates dynamic projected returns in order to correspond to the present value technique provided by Vuolteenaho, and as a result, it may be used to anticipate future cash flows in the same way as the present value technique (2002).http://FIN516 Corporate Finance

During the course of this process, we came up with the following two key assumptions, which we will discuss in greater detail later on. Having established the assumption that s1 and s2 are identical, we may move on to the next phase in the process. It is possible to conclude from an evaluation of the facts contained in this report that all of these phrases were used interchangeably throughout the drafting process of the article (Vartiainen,2020).http://FIN516 Corporate Finance

It is reasonable to predict a reversion to the mean for the forecasted stock returns and return on equity (ROE) of one. Firstly, we predict that long-term expected returns (LTER) and long-term expected return on equity (ROE) will be integrated into a single measure in the long run, rather than two separate measures. As an alternative expression, as time passes, a company’s ability to create abnormal profits that are continuously higher than its cost of capital (abnormal profitability) will deteriorate. A basic method for calculating future holding period returns across a wide range of time horizons is to use regressions of historical returns on two fundamentals: the book to market (BM) ratio and return on equity (ROE) (Berry‐Stölzle,2018). http://FIN516 Corporate Finance

Question 3

In comparison to the prior processes that were in use in the industry at the time of development, it does not constitute a considerable divergence from them. Because it focuses on firm-level returns and their capacity to predict future prospective generalized returns, our investigation differs from previous research in that it is more empirically grounded (the market or portfolio level).

A new study on the matter is also being carried out, with a particular emphasis on pricing and risk premiums, the term structure of dividend strips, and other elements that are important. It is significantly more important for us to consider the long-term performance of stocks than the performance of stocks in the short term, which are more common in the short run but more volatile in the long run. When it comes to forecasting holding period returns, the term structure literature makes use of methods such as dividend strips. However, we construct our estimations based on actual realized returns and accounting data rather than theoretical models (Houston,2018).http://FIN516 Corporate Finance

The collecting of financial data on a quarter-by-quarter basis improves our capacity to predict the return on investment (ROI) over a three-quarter time period. In conjunction with one another, it is possible to estimate with high precision the cross-section of future holding period returns for periods stretching up to three years into the future. The regression slope coefficient for future log returns for three, twelve, and twenty-four months in the future is 0.86; all coefficients are statistically significant at one percent for future log returns for one, three, and twelve months in the future; and all coefficients are statistically significant at one percent for future log returns for one, three, and twelve months in the future; and all coefficients are statistically significant at one percent for future log returns for one, three, and twelve months in the future. There is no reason to be concerned about proxy values over the next three months because the regression slope and intercept are statistically indistinguishable from one another. If we consider the relationship between portfolio sorting proxies and future returns, we can see that there is a statistically significant monotonic relationship between them: The top deciles of expected returns for the three, twelve, and twenty-four-month time periods, and shorting the lowest deciles of the same returns, can result in spreads of 5.48 percent, 15.42 percent, 30.44 percent, and 46.32 percent, all of which are statistically significant at the one percent level, and shorting the lowest deciles of the same returns. The bottom deciles of expected returns for the three, twelve, and twenty-four-month time periods can result in spreads of 5.48

The same results have been obtained by using a variety of models, including ones based on annual financial statements and others that estimate instrumental factors. Our team was taken by surprise when we discovered that all of the models we tested, including the three-component model created by Fama and French in the early 1990s and a four-element model with an additional momentum factor, failed to appropriately forecast the cross-section of future returns. Generally speaking, proxies at the company level outperform proxies at the factor level when it comes to performance in the vast majority of cases.

Question 4

Following the completion of this research, several previously undisclosed facts have been revealed, including: The first and most important thing we do is create a fundamentals-based model that can forecast stock returns outside of the sample and across a wide range of time periods. This is the first methodological addition we’ve made to the field, and we’re excited about it. A large amount of research was spent on the conditional CAPM model, which was developed by Ang and Liu and is capable of discounting portfolio-level cash flow estimates, as well as on additional models developed by others (2004).http://FIN516 Corporate Finance According to our best knowledge and understanding, there is presently no software adequate for the computation of multi-period forward projected return estimations at the firm level, and we believe that this is accurate to the best of our knowledge and understanding at the present time. We believe that our solution, which is based on accounting data, would be useful to businesses of all sizes as a consequence of its simplicity and transparency. As opposed to the preceding example, where Callen’s expected holding period returns were anticipated using contracts with various expiration dates, the former method makes use of options rather than contracts with varying expiration dates (2011).http://FIN516 Corporate Finance 3 This makes it even more critical that we use firm-level proxies, as typical factor-based models, such as the CAPM and others, are difficult to use over a wide range of investment horizons and do not reliably or favorably anticipate future returns when applied outside of the sample. If investors have the backing of technology improvements, they may be able to make better decisions about where to place their money as a result of technological developments.

.References

Berry‐Stölzle, T.R. and Xu, J., 2018. Enterprise risk management and the cost of capital. Journal of Risk and Insurance, 85(1), pp.159-201.

Drobetz, W., El Ghoul, S., Guedhami, O. and Janzen, M., 2018. Policy uncertainty, investment, and the cost of capital. Journal of Financial Stability, 39, pp.28-45.

El Ghoul, S., Guedhami, O., Kim, H., and Park, K., 2018. Corporate environmental responsibility and the cost of capital: International evidence. Journal of Business Ethics, 149(2), pp.335-361.

Houston, J.F., Lin, C. and Xie, W., 2018. Shareholder protection and the cost of capital. The Journal of Law and Economics, 61(4), pp.677-710.

Kling, G., Volz, U., Murine, V. and Ayas, S., 2021. The impact of climate vulnerability on firms’ cost of capital and access to finance. World Development, 137, p.105131.

Steffen, B., 2020. Estimating the cost of capital for renewable energy projects. Energy Economics, 88, p.104783.

Vartiainen, E., Masson, G., Breyer, C., Moser, D. and Román Medina, E., 2020. Impact of weighted average cost of capital, capital expenditure, and other parameters on future utility‐scale PV levelised cost of electricity. Progress in photovoltaics: research and applications, 28(6), pp.439-453.

Xu, Z., 2020. Economic policy uncertainty, cost of capital, and corporate innovation. Journal of Banking & Finance, 111, p.105698.