Vasant Naik

Bio: Vasant Naik is an academic researcher from Lehman Brothers. The author has contributed to research in topics: Risk premium & Cash flow. The author has an hindex of 11, co-authored 16 publications receiving 3082 citations. Previous affiliations of Vasant Naik include University of British Columbia.

Optimal Investment, Growth Options, and Security Returns

Abstract: As a consequence of optimal investment choices, firms' assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm's systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: (i) the time series relation between the book-to-market ratio and asset returns, (ii) the cross-sectional relation between book to market, market value and return, (iii) contrarian effects at short horizons, (iv) momentum effects at longer horizons, and (v) the inverse relation between interest rates and the market risk premium.

Optimal Investment, Growth Options, and Security Returns

Abstract: As a consequence of optimal investment choices, a firm's assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm's systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: (i) the time-series relation between the book-to-market ratio and asset returns; (ii) the cross-sectional relation between book-to-market, market value, and return; (iii) contrarian effects at short horizons; (iv) momentum effects at longer horizons; and (v) the inverse relation between interest rates and the market risk premium. RECENT EMPIRICAL RESEARCH IN FINANCE has focused on regularities in the cross section of expected returns that appear anomalous relative to traditional models. Stock returns are related to book-to-market, and market value.1 Past returns have also been shown to predict relative performance, through the documented success of contrarian and momentum strategies.2 Existing explanations for these results are that they are due to behavioral biases or risk premia for omitted state variables.3 These competing explanations are difficult to evaluate without models that explicitly tie the characteristics of interest to risks and risk premia. For example, with respect to book-to-market, Lakonishok et al. (1994) argue: "The point here is simple: although the returns to the B/M strategy are impressive, B/M is not a 'clean' variable uniquely associated with eco

Valuation and Return Dynamics of New Ventures

Abstract: We develop and analyze a model of a multi-stage investment project that captures many features of R&D ventures and start-up companies. An important feature these problems share is that the firm learns about the potential profitability of the project throughout its life, but that research and development effort itself is only resolved through additional investment by the firm. In addition, the risks associated with the ultimate cash flows the firm realizes on completion of the project have a systematic component, while the purely technical risks are idiosyncratic. Our model captures these different sources of risk, and allows us to study their interaction in determining the risk premia earned by the venture during development. Our results show that the systematic risk, and the required risk premium, of the venture are highest early in its life, and decrease as it approaches completion, despite the idiosyncratic nature of the technical risk.

Valuation and Return Dynamics of New Ventures

Abstract: A dynamic model of a multistage investment project that captures many features of research and development (R&D) ventures and start-up companies is developed. An important feature these problems share is that firms learn about the potential profitability of the project throughout its life, but that technical uncertainty about the R&D effort is only resolved through additional investment. Consequently the risks associated with the ultimate cash flows have a systematic component even while the purely technical risks are idiosyncratic. Our model captures these different sources of risk and allows us to study their interaction in determining the value and risk premium of the venture. Copyright 2004, Oxford University Press.

Leverage Constraints and the Optimal Hedging of Stock and Bond Options

Abstract: This paper considers the problem of a financial institution that needs to hedge a stream of state-contingent cash flows while facing borrowing and short-sales restrictions. The study determines analytically the strategy that minimizes the initial cost of hedging the desired cash flow, which is also the upper bound on its market price, and shows that the impact of leverage constraints on the cost of hedging call and put options is significant and, therefore, the biases detected by tests of option pricing models may not represent arbitrage opportunities. The paper also shows that with credit limits, it is optimal to reduce the rate of trading; thus, these constraints need to be recognized when estimating the trading volume generated in replicating contingent payoffs such as portfolio insurance.

Do Industries Explain Momentum

Abstract: This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book-to-market equity, individual stock momentum, the cross-sectional dispersion in mean returns, and potential microstructure influences.

The Stock Market Valuation of Research and Development Expenditures

Abstract: We examine whether stock prices fully reflect the value of firms? intangible assets, focusing on research and development (R&D). Since intangible assets are not reported on financial statements under current U.S. accounting standards and R&D spending is expensed, the valuation problem may be especially challenging. Nonetheless we find that historically the stock returns of firms doing R&D on average matches the returns on firms with no R&D. For companies engaged in R&D, high R&D intensity has a distinctive effect on returns for two groups of stocks. Within the set of growth stocks, R&D-intensive stocks tend to out-perform stocks with little or no R&D. Companies with high R&D relative to equity market value (who tend to have poor past returns) show strong signs of mis-pricing. In both cases the market apparently fails to give sufficient credit for firms? R&D investments. Our exploratory investigation of the effects of advertising on returns yields similar results. We also provide evidence that R&D intensity is positively associated with return volatility, everything else equal. Insofar as the association reflects investors? lack of information about firms? R&D activity, increased accounting disclosure may be beneficial.

Optimal Investment, Growth Options, and Security Returns

Abstract: As a consequence of optimal investment choices, firms' assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm's systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: (i) the time series relation between the book-to-market ratio and asset returns, (ii) the cross-sectional relation between book to market, market value and return, (iii) contrarian effects at short horizons, (iv) momentum effects at longer horizons, and (v) the inverse relation between interest rates and the market risk premium.