International Journal of Theoretical and Applied Finance

We examine the impact of tax convexity on the optimal leverage, the optimal default barrier, and the credit spread. Contrary to previous papers, debt maturity in our setting is finite. We find that maturity plays a crucial role to fully capture the effect of tax convexity. Our results show that tax convexity has a substantial impact on the optimal default boundary when the maturity is intermediate. We argue that, in the presence of tax convexity, equityholders inject cash into the firm because they weigh the value surplus they achieve from delaying default against the loss they incur, given the absolute priority rule, when the firm fails to fully redeem the debt’s principal at maturity. We also find that the longer is the maturity, the stronger is the negative impact of tax convexity on the optimal leverage.

We derive the price of a spread option based on two assets which follow a bivariate volatility modulated Volterra (VMV) process dynamics. Such a price dynamics is particularly relevant in energy markets, modeling for example the spot price of power and gas. VMV processes are in general not semimartingales, but contain several special cases of interest in energy markets, like for example continuous-time autoregressive moving average processes. Based on a change of measure, we obtain a pricing expression based on a univariate Fourier transform of the payoff function and the characteristic function of the price dynamics. Moreover, the spread option price can be expressed in terms of the forward prices on the underlying dynamics assets. We compute a linear system of equations for the quadratic hedge for the spread option in terms of a portfolio of underlying forward contracts.

This paper studies the optimal expected gain/loss of a portfolio at a given risk level when the initial investment is zero and the number of stocks $p$ grows with the sample size $n$. A new estimator of the optimal expected gain/loss of such a portfolio is proposed after examining the behavior of the sample mean vector and the sample covariance matrix based on conditional expectations. It is found that the effect of the sample mean vector is additive and the effect of the sample covariance matrix is multiplicative, both of which over-predict the optimal expected gain/loss. By virtue of a shrinkage method, a new estimate is proposed when the sample covariance matrix is not invertible. The superiority of the proposed estimator is demonstrated by matrix inequalities and simulation studies.

We study the problem of optimally liquidating a large portfolio position in a limit-order market. We allow for both limit and market orders and the optimal solution is a combination of both types of orders. Market orders deplete the order book, making future trades more expensive, whereas limit orders can be entered at more favorable prices but are not guaranteed to be filled. We model the bid-ask spread with resilience by a jump process, and the market-order arrival process as a controlled Poisson process. The objective is to minimize the execution cost of the strategy. We formulate the problem as a mixed stochastic continuous control and impulse problem for which the value function is shown to be the unique viscosity solution of the associated variational inequalities. We conclude with a calibration of the model on recent market data and a numerical implementation.

A typical gas sales agreement (GSA), also called a gas swing contract, is an agreement between a supplier and a purchaser for the delivery of variable daily quantities of gas, between specified minimum and maximum daily limits, over a certain number of years at a specified set of contract prices. The main constraint of such an agreement that makes them difficult to value is that in each gas year there is a minimum volume of gas (termed take-or-pay or minimum bill) for which the buyer will be charged at the end of the year (or penalty date), regardless of the actual quantity of gas taken. We propose a framework for pricing such swing contracts for an underlying gas forward price curve that follows a regime switching process in order to better capture the volatility behavior in such markets. With the help of a recombining pentanomial tree, we are able to efficiently evaluate the prices of the swing contracts, find optimal daily decisions and optimal yearly use of both the make-up bank and the carry forward bank at different regimes. We also show how the change of regime will affect the decisions.

In general it is not clear which kind of information is supposed to be used for calculating the fair value of a contingent claim. Even if the information is specified, it is not guaranteed that the fair value is uniquely determined by the given information. A further problem is that asset prices are typically expressed in terms of a risk-neutral measure. This makes it difficult to transfer the fundamental results of financial mathematics to econometrics. I show that the aforementioned problems evaporate if the financial market is complete and sensitive. In this case, after an appropriate choice of the numéraire, the discounted price processes turn out to be uniformly integrable martingales under the real-world measure. This leads to a Law of One Price and a simple real-world valuation formula in a model-independent framework where the number of assets as well as the lifetime of the market can be finite or infinite.

This paper derives a multiple-factor asset pricing model with asset price bubbles in an arbitrage-free, competitive, and frictionless market. As such it generalizes existing asset pricing models, all of which implicitly assume asset price bubbles do not exist. This generalization leads to two new empirical implications. The first is that positive alphas can exist in an arbitrage-free market due to the existence of asset price bubbles. These positive alphas do not represent abnormal profit opportunities. The second is that bubble risk factors can exist with positive risk premiums. The testing of these new empirical implications awaits subsequent research.