Lin and Chang (2009, 2010) establish a VIX futures and option pricing theory when modelingS&P 500 index by using a stochastic volatility process with asset return and volatility jumps.In this note, we prove that Lin and Chang's formula is not an exact solution of their pricingequation. More generally, we show that the characteristic function of their pricing equationcannot be exponentially ane, as proposed by them. Furthermore, their formula cannot serve asa reasonable approximation. Using the Heston (1993) model as a special case, we demonstratethat Lin and Chang formula misprices VIX futures and options in general and the error canbecome substantially large.
We study the pricing of options on realized variance in a general class of Log-OU stochastic volatility models. The class includes several important models proposed in the literature. Having as common feature the log-normal law of instantaneous variance, the application of standard Fourier-Laplace transform methods is not feasible. We derive extensions of Asian pricing methods, to obtain bounds, in particular, a very tight lower bound for options on realized variance.
We find that price and earnings momentum are pervasive features of international equity markets even when controlling for data snooping biases. For European countries, we find that price momentum is subsumed by earnings momentum on an aggregate level. However, this rationale does not apply to each and every country. While the above explanation is confined to certain time periods in the U.S., earnings momentum nevertheless appears to be a crucial driver of the price momentum anomaly in many markets. Since we cannot establish a decent relation between momentum and macroeconomic risks, we suspect a behavioral-based explanation to be at work. In fact, we find momentum profits to be more pronounced for portfolios characterized by higher information uncertainty. Hence, the momentum anomaly may well be rationalized in a model of investors underreacting to fundamental news. Finally, we find that momentum works better when limited to stocks with high idiosyncratic risk or higher illiquidity, suggesting that limits to arbitrage deter rational investors from exploiting the anomaly.
This paper proposes a novel measure of economic uncertainty based on the frequency of internet searches. The theoretical motivation is offered by findings in economic psychology that agents respond to increased uncertainty by intensifying their information search. The main advantages of using internet searches are broad reach, timeliness and the fact that they reflect actions, rather than words, which however are not directly related to the stock market. The search-based uncertainty measure compares well against a peer group of alternative indicators and is shown to have a significant relationship with aggregate stock returns and volatility.
Climate change is one of the greatest challenges facing our planet in the foreseeable future anddespite the urgency of the situation global GHG emissions are still increasing. In this context,and since future climate changes appear now unavoidable to some extent, adaptation measureshave recently gained a new political momentum as an important component of climate policies.Contrary to mitigation options, adaptation measures do not reduce emission levels but reducetheir impacts. To assess the relationship and effects on the global economy of both mitigationand adaptation, we use in this paper an integrated assessment model (IAM) that includes bothproactive adaptation strategies and access to “green” investments (clean technologies) for mitigation.We find that the relationship between adaptation and mitigation is complex and largelydependent on their respective attributes, with weakly effective adaptation acting as a late complementto mitigation efforts. As its effectiveness increases, adaptation becomes more and morea substitute for mitigation. Sensitivity analysis on the potential magnitude of damages also indicatesthat scientific efforts to better describe GHG impacts will have immediate and importantconsequences on the sequence of mitigation and adaptation strategies.
We conduct a laboratory experiment to study whether people intuitively use real-option strategies in a dynamic investment setting. The participants were asked to play as an oil manager and make production decisions in response to a simulated mean-reverting oil price. Using cluster analysis, participants can be classified into four groups, which we label ‘mean-reverting’, ‘Brownian motion real-option’, ‘Brownian motion myopic real-option’, and ‘ambiguous’. We find two behavioral biases in the strategies of our participants: ignoring the mean-reverting process, and myopic behavior. Both lead to too frequent switches when compared with the theoretical benchmark. We also find that the last group behaved as if they have learned to incorporate the true underlying process into their decisions, and improved their decisions during the later stage.
This paper determines the value of asset tradeability in an option pricing framework. In our model, tradeability is valuable since it allows investors to exploit temporary mispricings of stocks. The model delivers several novel insights on the value of tradeability: The value of tradeability is the larger, the higher the pricing efficiency of the market is. Uncertainty increases the value of tradeability, no matter whether the uncertainty results from noise trading or from new information about the fundamental value of the stock. The value of tradeability is the larger, the longer the illiquid stock cannot be traded and the more trading dates the liquid stock offers.
This appendix extends the empirical results in Chesney, Crameri, and Mancini (2011). Informed trading activities on put and call options are analyzed for 19 companies in the banking and insurance sectors from January 1996 to September 2009. Our empirical findings suggest that certain events such as the takeovers of AIG and Fannie Mae/Freddie Mac, the collapse of Bear Stearns Corporation and public announcements of large losses/writedowns are preceded by informed trading activities in put and call options. The realized gains amount to several hundreds of millions of dollars. Several cases are discussed in detail.
Marcet and Marimon (1994, revised 1998) developed a recursive saddle point method which can be used to solve dynamic contracting problems that include participation, enforcement and incentive constraints. Their method uses a recursive multiplier to capture implicit prior promises to the agent(s) that were made in order to satisfy earlier instances of these constraints. As a result, their method relies on the invertibility of the derivative of the Pareto frontier and cannot be applied to problems for which this frontier is not strictly concave. In this paper we show how one can extend their method to a weakly concave Pareto frontier by expanding the state space to include the realizations of an end of period lottery over the extreme points of a flat region of the Pareto frontier. With this expansion the basic insight of Marcet and Marimon goes through - one can make the problem recursive in the Lagrangian multiplier which yields significant computational advantages over the conventional approach of using utility as the state variable. The case of a weakly concave Pareto frontier arises naturally in applications where the principal's choice set is not convex but where randomization is possible.
