Expectations in Austrian Business Cycle Theory: An Application of the Prisoner's Dilemma

The standard account of Austrian Business Cycle theory posits that central bank manipulations of interest rates fool bankers and investors into believing that there has been an increase in the real supply of loanable funds available for capital investment. However, reliance on foolishness ignores the entrepreneurial emphasis within the Austrian tradition and fails to produce the strongest possible case for Austrian Business Cycle theory. We use the prisoner's dilemma framework to model the profit maximizing behavior of bankers and the investors under uncertainty when the market rate of interest is below the underlying rate of time preference.     

Can channel pattern trading be profitably automated?

Financial markets, such as the global foreign exchange (FX) market, often exhibit trending behaviour. Within such trends, the market level oscillates with changes in market consensus. Continued oscillations of this type result in the formation of wave patterns within the underlying trend known as channels, which are used by technical analysts as trade entry signals. A sample space of such channels has been constructed from a set of US dollar/British pound Spot FX tick data from 1989–1997 using pattern recognition algorithms and the profitability of trading using such patterns has been estimated. A number of attributes of the resulting collection of channels has been subjected to statistical analysis with the aim of classifying patterns that can be traded profitably using a number of simple trading rules. Results of this analysis show that there exist statistically significant links between the channels' attributes and profitability.     

Estimating exponential affine models with correlated measurement errors: Applications to fixed income and commodities

Exponential affine models (EAMs) are factor models popular in financial asset pricing requiring a dynamic term structure, such as for interest rates and commodity futures. When implementing EAMs it is usual to first specify the model in state-space form (SSF) and then to estimate it using the Kalman filter. To specify the SSF, a structure of the measurement error must be provided which is not specified in the EAM itself. Different specifications of the measurement errors will result in different SSFs, leading to different parameter estimates. In this paper we investigate the influence of the measurement error specification on the parameter estimates. Using market data for both fixed income and commodities we provide evidence that measurement errors are cross-sectionally and serially correlated, which is not consistent with the independent identically distributed (iid) assumptions commonly adopted in the literature. Using simulated data we show that measurement error assumptions affect parameter estimates, especially in the presence of serial correlation. We provide a new specification, the augmented state-space form (ASSF), as a solution to these biases and show that the ASSF gives much better estimates than the basic SSF.     

Who gets the goods? Moderate Voting Records,Diminishing Returns,and PAC Contributions

Assuming that a legislator representing a moderate constituency (with respect to a variety of interests) may be expected to vote moderately in general, the authors suggest a measure of the 'moderateness' of a legislator's voting behavior and use it to determine whether a relationship exists between PAC contributions and the degree of moderateness. The results suggest that PACs exhibit a tendency to give more, at the margin, to legislators with moderate voting records.