Keynesian Dynamics and the Wage-Price Spiral:Estimating a Baseline Disequilibrium Approach

We reformulate the baseline disequilibrium AS-AD model of Asada et al. (2004) to make it applicable for empirical estimation. The model now exhibits a Taylor interest rate rule in the place of an LM curve, a dynamic IS curve and dynamic employment adjustment. It is based on sticky wages and prices, perfect foresight of current inflation rates and adaptive expectations concerning the inflation climate in which the economy is operating. The implied nonlinear 5D model of real markets disequilibrium dynamics avoids anomalies of the Neoclassical synthesis (Stage I). It exhibits Keynesian feedback structures with asymptotic stability of its steady state for low adjustment speeds and with cyclical loss of stability when adjustment speeds are made sufficiently large. In the second part we estimated the equations of the model to study its stability features from the empirical point of view with respect to the feedback chains it exhibits. Based on these estimates we also study to which extent a Blanchard and Katz error correction mechanism, more pronounced interest rate feedback rules or downward wage rigidity can stabilize the dynamics in the large when the steady state is locally repelling. The achievements of this baseline disequilibrium AS-AD model and its Keynesian feedback channels can be usefully contrasted with those of the microfounded, but in scope more limited now fashionable New Keynesian alternative (the Neoclassical Synthesiso, Stage IIDAS-AD growth, wage and price Phillips curves,adverse real wage adjustment, (in)stability, persistent business cycles

Investigating nonlinear speculation in cattle, corn, and hog futures markets using logistic smooth transition regression models

This article explores nonlinearities in the response of speculators’ trading activity to price changes in live cattle, corn, and lean hog futures markets. Analyzing weekly data from March 4, 1997 to December 27, 2005, we reject linearity in all of these markets. Using smooth transition regression models, we find a similar structure of nonlinearities with regard to the number of different regimes, the choice of the transition variable, and the value at which the transition occurs.Futures markets, speculation, nonlinear dynamics, smooth transition regression model

American Call Options on Jump-Diffusion Processes: A Fourier Transform Approach

This paper considers the Fourier transform approach to derive the implicit integral equation for the price of an American call option in the case where the underlying asset follows a jump-diffusion process. Using the method of Jamshidian (1992), we demonstrate that the call option price is given by the solution to an inhomogeneous integro-partial differential equation in an unbounded domain, and subsequently derive the solution using Fourier transforms. We also extend McKean’s incomplete Fourier transform approach to solve the free boundary problem under Merton’s framework, for a general jump size distribution. We show how the two methods are related to each other, and also to the Geske-Johnson compound option approach used by Gukhal (2001). The paper also derives results concerning the limit for the free boundary at expiry, and presents a numerical algorithm for solving the linked integral equation system for the American call price, delta and early exercise boundary. This scheme is applied to Merton’s jump-diffusion model, where the jumps are log-normally distributed.American options; jump-diffusion; Volterra integral equation; free boundary problem

Diagnostic testing for earnings simulation engines in the Australian electricity market

This study has endeavoured to propose and implement a series of diagnostic tests to determine the appropriateness of electricity simulation engines (ESEs) for generating electricity load and price paths to be used as input in the determination of a retailer’s earnings distribution and the assessment of earnings-at-risk (EaR) measures. Additional diagnostic measures require development before a routine can be developed whereby a complete diagnostic report can be generated as output using simulated and historical data as input. This work includes: (1) Further partitioning of output load and prices from an ESE into off-peak, peak and weekend periods to determine the subsequent effect on earnings. (2) The diagnosis of simulated load paths. As simulated load was not supplied for all engines, the diagnostics developed in this report did not include an analysis of load. (3) The building of a response surface to capture the interaction between temperature, load and price. (4) Examination of the convergence behaviour of an ESE. Convergence in this context means the determination of the minimum number of load and price paths required from a simulator in order to return expected profiles that conform to industry expectations. This would involve the sequential testing of an increasing number of simulated paths from an ESE in order to determine the number required. In conclusion, it is important to understand that each of the simulators that were diagnosed in this study were criticised according to industry expectations, and to the degree that the diagnostics employed here reflect those expectations. In fact, all simulators will attract criticism given that they are calibrated on historical data and are expected to generate future prices for market conditions that are unknown. The mark of an appropriate ESE is that the future load and pricing structure it generates is not too much at variance with industry expectations. A critical function of a simulator is for it not to overestimate or underestimate load and prices such that the risk metrics used to govern earnings risk faced by an electricity retailer are compromised to the extent that their book is either grossly over-hedged or under-hedged

The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows

In this paper we develop a model of an order-driven market where traders set bids and asks and post market or limit orders according to exogenously fixed rules. Agents are assumed to have three components to the expectation of future asset returns, namely-fundamentalist, chartist and noise trader. Furthermore agents differ in the characteristics describing these components, such as time horizon, risk aversion and the weights given to the various components. The model developed here extends a great deal of earlier literature in that the order submissions of agents are determined by utility maximisation, rather than the mechanical unit order size that is commonly assumed. In this way the order flow is better related to the ongoing evolution of the market. For the given market structure we analyze the impact of the three components of the trading strategies on the statistical properties of prices and order flows and observe that it is the chartist strategy that is mainly responsible of the fat tails and clustering in the artificial price data generated by the model. The paper provides further evidence that large price changes are likely to be generated by the presence of large gaps in the book

A Complete Stochastic Volatility Model in the HJM Framework

This paper considers a stochastic volatility version of the Heath, Jarrow and Morton (1992) term structure model. Market completeness is obtained by adapting the Hobson and Rogers (1998) complete stochastic volatility stock market model to the interest rate setting. Numerical simulation for a special case is used to compare the stochastic volatility model against the traditional Vasicek (1977) model.

Dynamics of Beliefs and Learning Under aL Processes - The Homogeneous Case

This paper studies a class of models in which agents' expectations influence the actual dynamics while the expectations themselves are the outcome of some learning process. Under the assumptions that agents have homogeneous expectations (or beliefs) and that they update their expectations by least-squares L- and general aL - processes, the dynamic of the resulting expectations and learning schemes are analyzed. It is shown how the dynamics of the system, including stability, instability and bifurcation, are affected by the learning processes. The cobweb model with a simple homogeneous expectation scheme is employed as an example to illustrate the stability results, the various types of bifurcations and the routes to complicated price dynamics.homogeneous beliefs; least-squares l-process; genera; al-process; stability; instability; bifurcation; cobweb model

Small Traders in Currency Futures Markets Format

This study examines the interrelation between small traders' open interest and large hedging and speculation in the Canadian dollar, Swiss franc, British pound, and Japanese yen futures markets. The results, based on Granger-causality tests and vector autoregressive models, suggest that small traders' open interest is closely related to large speculators' open interest. Small traders and speculators tend to herd, which means that small traders are long [short] when speculators are long [short] as well. Moreover, small traders and speculators are positive feedback traders whereas hedgers are contrarians. Regarding information flows, speculators lead small traders in three of the four currency futures markets. The results therefore suggest that small traders ares mall speculators who follow the large speculators, indicating that they are less well informed than the large speculators.currency futures; small traders; speculation; hedging

The Evaluation of American Compound Option Prices Under Stochastic Volatility Using the Sparse Grid Approach

A compound option (the mother option) gives the holder the right, but not obligation to buy (long) or sell (short) the underlying option (the daughter option). In this paper, we demonstrate a partial differential equation (PDE) approach to pricing American-type compound options where the underlying dynamics follow Heston’s stochastic volatility model. This price is formulated as the solution to a two-pass free boundary PDE problem. A modified sparse grid approach is implemented to solve the PDEs, which is shown to be accurate and efficient compared with the results from Monte Carlo simulation combined with the Method of Lines.American compound option; stochastic volatility; free boundary problem; sparse grid; combination technique; Monte Carlo simulation; method of lines

Pricing American Options on Jump-Diffusion Processes using Fourier Hermite Series Expansions

This paper presents a numerical method for pricing American call options where the underlying asset price follows a jump-diffusion process. The method is based on the Fourier-Hermite series expansions of Chiarella, El-Hassan & Kucera (1999), which we extend to allow for Poisson jumps, in the case where the jump sizes are log-normally distributed. The series approximation is applied to both European and American call options, and algorithms are presented for calculating the option price in each case. Since the series expansions only require discretisation in time to be implemented, the resulting price approximations require no asset price interpolation, and for certain maturities are demonstrated to produce both accurate and efficient solutions when compared with alternative methods, such as numerical integration, the method of lines and finite difference schemes.American options; jump-diusion; Fourier-Hermite series expansions; free boundary problem