LOCAL VARIANCE GAMMA AND EXPLICIT CALIBRATION TO OPTION PRICES

In some options markets (e.g., commodities), options are listed with only a single maturity for each underlying. In others (e.g., equities, currencies), options are listed with multiple maturities. In this paper, we analyze a special class of pure jump Markov martingale models and provide an algorithm for calibrating such models to match the market prices of European options with multiple strikes and maturities. This algorithm matches option prices exactly and only requires solving several one‐dimensional root‐search problems and applying elementary functions. We show how to construct a time‐homogeneous process which meets a single smile, and a piecewise time‐homogeneous process which can meet multiple smiles.     

Crisp monetary acts in multiple-priors models of decision under ambiguity

In axiomatic models of decision under ambiguity using a set of priors, a clear distinction can be made between acts which are affected by ambiguity and those which are not: the crisp acts. In these multiple-priors models, the decision maker is indifferent between holding a constant act or holding a non constant crisp act with the same expected utility, if it exists. In financial settings, we show that this indifference, together with the standard definition of monetary acts in the Anscombe–Aumann framework, implies that the investor ignores the variance of some assets, a behavior which conflicts with the assumption on which modern portfolio theory has been built. In this paper we establish the geometrical and topological properties of the set of priors that rule out the existence of non constant crisp acts. These properties in turn restrict what can possibly be an unambiguous financial asset.     

The Vietnam reforms,change in wage inequality and the role of the minimum wage

The Vietnam ‘renovation’ reforms were implemented during the 1990s, but their full effect was only felt several years later. We present evidence on the developments in real wage growth and inequality in Vietnam from 1998 to 2008. Using a variety of approaches (traditional measures of inequality, comparison of density functions, decomposition of the change in real wage by sector as well as a detailed decomposition of the change in the Gini), we present a consistent picture: contrary to what one might have expected given the nature of the reforms, inequality declined sharply in the private sector (but not in the state sector). This study links these developments to the policy of aggressively increasing the minimum wage over the past several years, differences in implementation by sector as well as variation in the over‐time changes in minimum wage.     

PRICING SWAPTIONS UNDER MULTIFACTOR GAUSSIAN HJM MODELS

Several approximations have been proposed in the literature for the pricing of European‐style swaptions under multifactor term structure models. However, none of them provides an estimate for the inherent approximation error. Until now, only the Edgeworth expansion technique of Collin‐Dufresne and Goldstein is able to characterize the order of the approximation error. Under a multifactor HJM Gaussian framework, this paper proposes a new approximation for European‐style swaptions, which is able to set bounds on the magnitude of the approximation error and is based on the conditioning approach initiated by Curran and Rogers and Shi. All the proposed pricing bounds will arise as a simple by‐product of the Nielsen and Sandmann setup, and will be shown to provide a better accuracy–efficiency trade‐off than all the approximations already proposed in the literature.     

Sources of the stock price fluctuations in Chinese equity market

This paper proposes a latent factor approach based on a state–space framework in order to identify which factor, if any, dominates price fluctuations in the Chinese stock markets. We also illustrate the connection of such stock price decomposition with several general equilibrium asset pricing models and show that the decomposition results can potentially offer useful insights with regard to the empirical relevance of asset pricing models. We use quarterly data of the Chinese A-Share equity market over the period 1995Q3–2011Q1 and find that the estimates of the state–space model suggest that the expected return is the primary driving force behind price fluctuations in the Chinese stock market. We show that the time-varying expected returns appear to be counter-cyclical and this result seems to be consistent with the habit formation model of Campbell and Cochrane [1999. By force of habit: A consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107, no. 2: 205–51.]. However, we also note that there is a great deal of uncertainty with respect to this variance decomposition due to the resulting small signal-to-noise ratio in the estimated state–space model.     

Input-output analysis of carbon emissions embodied in China-Japan trade

Energy-related CO₂ emissions embodied in international trade have been widely studied by researchers all over the world. By using the bilateral trade input–output (BTIO) approach, this study investigates the CO₂ emissions embodied in China–Japan trade during 1995–2009 and attempts to identify the driving forces for the change in CO₂ emissions embodied in China’s exports to Japan during that period by using structural decomposition analysis (SDA). Result shows that CO₂ emissions embodied in China’s exports increased by about 100% from 1995 to 2009, whereas those embodied in China’s imports increased by about 500% during the same period. Result of this research also reveals that the scale effect had a large influence on the increase in CO₂ emissions embodied in China–Japan trade. The technical effect greatly decreased CO₂ emissions embodied in China’s exports to Japan, but obviously increased those embodied in imports. The influence of the structural effect was relatively small and insignificant in the change of CO₂ emissions embodied in China’s exports to Japan, but was notable in the change of emissions embodied in imports.     

Dynamic mode decomposition for financial trading strategies

We demonstrate the application of an algorithmic trading strategy based upon the recently developed dynamic mode decomposition on portfolios of financial data. The method is capable of characterizing complex dynamical systems, in this case financial market dynamics, in an equation-free manner by decomposing the state of the system into low-rank terms whose temporal coefficients in time are known. By extracting key temporal coherent structures (portfolios) in its sampling window, it provides a regression to a best fit linear dynamical system, allowing for a predictive assessment of the market dynamics and informing an investment strategy. The data-driven analytics capitalizes on stock market patterns, either real or perceived, to inform buy/sell/hold investment decisions. Critical to the method is an associated learning algorithm that optimizes the sampling and prediction windows of the algorithm by discovering trading hot-spots. The underlying mathematical structure of the algorithms is rooted in methods from nonlinear dynamical systems and shows that the decomposition is an effective mathematical tool for data-driven discovery of market patterns.     

MEAN–VARIANCE PORTFOLIO OPTIMIZATION WITH STATE‐DEPENDENT RISK AVERSION

The objective of this paper is to study the mean–variance portfolio optimization in continuous time. Since this problem is time inconsistent we attack it by placing the problem within a game theoretic framework and look for subgame perfect Nash equilibrium strategies. This particular problem has already been studied in Basak and Chabakauri where the authors assumed a constant risk aversion parameter. This assumption leads to an equilibrium control where the dollar amount invested in the risky asset is independent of current wealth, and we argue that this result is unrealistic from an economic point of view. In order to have a more realistic model we instead study the case when the risk aversion depends dynamically on current wealth. This is a substantially more complicated problem than the one with constant risk aversion but, using the general theory of time‐inconsistent control developed in Björk and Murgoci, we provide a fairly detailed analysis on the general case. In particular, when the risk aversion is inversely proportional to wealth, we provide an analytical solution where the equilibrium dollar amount invested in the risky asset is proportional to current wealth. The equilibrium for this model thus appears more reasonable than the one for the model with constant risk aversion.     

Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies

The modern portfolio theory pioneered by Markowitz (1952) is widely used in practice and extensively taught to MBAs. However, the estimated Markowitz portfolio rule and most of its extensions not only underperform the naive 1/N rule (that invests equally across N assets) in simulations, but also lose money on a risk-adjusted basis in many real data sets. In this paper, we propose an optimal combination of the naive 1/N rule with one of the four sophisticated strategies—the Markowitz rule, the Jorion (1986) rule, the MacKinlay and Pástor (2000) rule, and the Kan and Zhou (2007) rule—as a way to improve performance. We find that the combined rules not only have a significant impact in improving the sophisticated strategies, but also outperform the 1/N rule in most scenarios. Since the combinations are theory-based, our study may be interpreted as reaffirming the usefulness of the Markowitz theory in practice.