https://faculty.fuqua.duke.edu/~charvey/Research/Working_Papers/W73_The_economic_implications.pdf

The economic implications of corporate financial reporting

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

Non-Gaussian processes of Ornstein–Uhlenbeck (OU) type offer the possibility of capturing important distributional deviations from Gaussianity and for flexible modelling of dependence structures. This paper develops this potential, drawing on and extending powerful results from probability theory for applications in statistical analysis. Their power is illustrated by a sustained application of OU processes within the context of finance and econometrics. We construct continuous time stochastic volatility models for financial assets where the volatility processes are superpositions of positive OU processes, and we study these models in relation to financial data and theory.

Non-Gaussian Ornstein–Uhlenbeck-based models and some of their uses in financial economics

Correlations between international equity market returns tend to increase in highly volatile bear markets, which has led some to doubt the benefits of international diversification. This article solves the dynamic portfolio choice problem of a U.S. investor faced with a time-varying investment opportunity set modeled using a regime-switching process which may be characterized by correlations and volatilities that increase in bad times. International diversification is still valuable with regime changes and currency hedging imparts further benefit. The costs of ignoring the regimes are small for all-equity portfolios but increase when a conditionally risk-free asset can be held. In standard international portfolio choice models such as Sercu (1980) and Solnik (1974a), agents optimally hold the world market portfolio and a series of hedge portfolios to hedge against real exchange rate risk. From the perspective of these models, investors across the world display strongly homebiased asset choices. One popular argument often heard to rationalize the “home bias puzzle” relies on the asymmetric correlation behavior of international equity returns. A number of empirical studies document that correlations between international equity returns are higher during bear markets than during bull markets. 1 If the diversification benefits from international investing are not forthcoming at the time that investors need them the most (when their home market experiences a downturn), the strong case for international investing may have to be reconsidered. Our goal is to formally evaluate this claim. To quantify the effect of these asymmetric correlations on optimal portfolio choice, we need a dynamic asset allocation model that accommodates time-varying correlations and volatilities. In the standard portfolio choice models and their empirical applications [French and Poterba (1991), Tesar and Werner (1995)], correlations

/pdf/international-asset-allocation-with-regime-shifts-1bs5ynr723.pdf

International Asset Allocation With Regime Shifts

We find that the difference between implied and realized variances, or the variance risk premium, is able to explain more than fifteen percent of the ex-post time series variation in quarterly excess returns on the market portfolio over the 1990 to 2005 sample period, with high (low) premia predicting high (low) future returns. The magnitude of the return predictability of the variance risk premium easily dominates that afforded by standard predictor variables like the P/E ratio, the dividend yield, the default spread, and the consumption-wealth ratio (CAY). Moreover, combining the variance risk premium with the P/E ratio results in an R 2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of “modelfree”, as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed to daily, data. Our findings suggest that temporal variation in risk and risk-aversion both play an important role in determining stock market returns.

/pdf/expected-stock-returns-and-variance-risk-premia-2qqzsna3ss.pdf

Expected Stock Returns and Variance Risk Premia

This paper characterizes all continuous price processes that are consistent with current option prices. This extends Derman and Kani (1994), Dupire (1994, 1997), and Rubinstein (1994), who only consider processes with deterministic volatility. Our characterization implies a volatility forecast that does not require a specific model, only current option prices. We show how arbitrary volatility processes can be adjusted to fit current option prices exactly, just as interest rate processes can be adjusted to fit bond prices exactly. The procedure works with many volatility models, is fast to calibrate, and can price exotic options efficiently using familiar lattice techniques.

Option Prices, Implied Price Processes, and Stochastic Volatility

This paper presents an exact finite-sample statistical procedure for testing hypotheses about the weights of mean-variance efficient portfolios. The estimation and inference procedures on efficient portfolio weights are performed in the same way as for the coefficients in an OLS regression. OLS t- and F-statistics can be used for tests on efficient weights, and when returns are multivariate normal, these statistics have exact t and F distributions in a finite sample. Using 20 years of data on 11 country stock indexes, we find that the sampling error in estimates of the weights of a global efficient portfolio is large.

The Sampling Error in Estimates of Mean‐Variance Efficient Portfolio Weights

Value-at-risk methods which employ a linear ("delta only") approximation to the relation between instrument values and the underlying risk factors are unlikely to be robust when applied to portfolios containing non-linear contracts such as options. The most widely used alternative to the delta-only approach involves revaluing each contract for a large number of simulated values of the underlying factors. In this paper we explore an alternative approach which uses a quadratic approximation to the relation between asset values and the risk factors. This method (i) is likely to be better adapted than the linear method to the problem of assessing risk in portfolios containing non-linear assets, (ii) is less computationally intensive than simulation using full-revaluation and (iii) in common with the delta-only method, operates at the level of portfolio characteristics (deltas and gammas) rather than individual instruments.

/pdf/non-linear-value-at-risk-3bgpfn4zym.pdf

Non-Linear Value-at-Risk ?

We present an improved method for inference in linear regressions with overlapping observations. By aggregating the matrix of explanatory variables in a simple way, our method transforms the original regression into an equivalent representation in which the dependent variables are non-overlapping. This transformation removes that part of the autocorrelation in the error terms which is induced by the overlapping scheme. Our method can easily be applied within standard software packages since conventional inference procedures (OLS-, White-, Newey-West- standard errors) are asymptotically valid when applied to the transformed regression. Through Monte Carlo analysis we show that it performs better in finite samples than the methods applied to the original regression that are in common usage. We illustrate the significance of our method with three empirical applications.

/pdf/improved-inference-in-regression-with-overlapping-ljje7ey5uq.pdf

Improved Inference in Regression with Overlapping Observations

In this paper we develop a corporate-finance oriented theory of financial innovations. The theory is motivated by the different corporate insolvency procedures in England and America. In the paper’s empirical section we show that these procedures have emerged from different innovation regimes. English law was innovated by lenders and borrowers exercising their right to contract freely, while American law was innovated by judges and legislators whose intervention often violated pre-contractual agreements. In the paper’s theoretical section we develop a formal model that analyzes the potential advantages and disadvantages of the two innovation regimes. The freedom of contracting regime preserves the ex ante outlook of the parties. Its disadvantage is that the innovating parties fail to internalize all the benefits of the innovation to other parties, and as a result under innovation occurs. Legislative intervention attempts to solve this externality, but once in control of the innovation process, judges and legislators may place their political objectives above those of the parties. Our analysis is much affected by the notion that corporate law is a set of contractual standards.

/pdf/financial-innovations-and-corporate-insolvency-dj8nj8ib6f.pdf

Mark Britten-Jones

Papers

Option Prices, Implied Price Processes, and Stochastic Volatility

The Sampling Error in Estimates of Mean‐Variance Efficient Portfolio Weights

Non-Linear Value-at-Risk ?

Improved Inference in Regression with Overlapping Observations

Financial Innovations and Corporate Insolvency