The Cosmic Microwave Background and the Ionization History of the Universe

Details of how the primordial plasma recombined and how the universe later reionized are currently somewhat uncertain. This uncertainty can restrict the accuracy of cosmological parameter measurements from the Cosmic Microwave Background (CMB). More positively, future CMB data can be used to constrain the ionization history using observations. We first discuss how current uncertainties in the recombination history impact parameter constraints, and show how suitable parameterizations can be used to obtain unbiased parameter estimates from future data. Some parameters can be constrained robustly, however there is clear motivation to model recombination more accurately with quantified errors. We then discuss constraints on the ionization fraction binned in redshift during reionization. Perfect CMB polarization data could in principle distinguish different histories that have the same optical depth. We discuss how well the Planck satellite may be able to constrain the ionization history, and show the currently very weak constraints from WMAP three-year data.Comment: Changes to match MNRAS accepted versio

Central bank intervention with limited arbitrage

Shleifer and Vishny (1997) pointed out some of the practical and theoretical problems associated with assuming that rational risk-arbitrage would quickly drive asset prices back to long-run equilibrium. In particular, they showed that the possibility that asset price disequilibrium would worsen, before being corrected, tends to limit rational speculators. Uniquely, Shleifer and Vishny (1997) showed that “performance-based asset management” would tend to reduce risk-arbitrage when it is needed most, when asset prices are furthest from equilibrium. We analyze a generalized Shleifer and Vishny (1997) model for central bank intervention. We show that increasing availability of arbitrage capital has a pronounced effect on the dynamic intervention strategy of the central bank. Intervention is reduced during periods of moderate misalignment and amplified at times of extreme misalignment. This pattern is consistent with empirical observation.

Predicting exchange rate volatility: genetic programming vs. GARCH and RiskMetrics

This article investigates the use of genetic programming to forecast out-of-sample daily volatility in the foreign exchange market. Forecasting performance is evaluated relative to GARCH(1,1) and RiskMetrics models for two currencies, DEM and JPY. Although the GARCH/RiskMetrics models appear to have a inconsistent marginal edge over the genetic program using the mean-squared-error (MSE) and R2 criteria, the genetic program consistently produces lower mean absolute forecast errors (MAE) at all horizons and for both currencies.Foreign exchange rates ; Forecasting ; Programming (Mathematics)

Intraday technical trading in the foreign exchange market

This paper examines the out-of-sample performance of intraday technical trading strategies selected using two methodologies, a genetic program and an optimized linear forecasting model. When realistic transaction costs and trading hours are taken into account, we find no evidence of excess returns to the trading rules derived with either methodology. Thus, our results are consistent with market efficiency. We do, however, find that the trading rules discover some remarkably stable patterns in the data.Foreign exchange

Technical analysis in the foreign exchange market

This article introduces the subject of technical analysis in the foreign exchange market, with emphasis on its importance for questions of market efficiency. Technicians view their craft, the study of price patterns, as exploiting traders’ psychological regularities. The literature on technical analysis has established that simple technical trading rules on dollar exchange rates provided 15 years of positive, risk-adjusted returns during the 1970s and 80s before those returns were extinguished. More recently, more complex and less studied rules have produced more modest returns for a similar length of time. Conventional explanations that rely on risk adjustment and/or central bank intervention are not plausible justifications for the observed excess returns from following simple technical trading rules. Psychological biases, however, could contribute to the profitability of these rules. We view the observed pattern of excess returns to technical trading rules as being consistent with an adaptive markets view of the world.Foreign exchange rates

Lessons from the evolution of foreign exchange trading strategies

The adaptive markets hypothesis posits that trading strategies evolve as traders adapt their behavior to changing circumstances. This paper studies the evolution of trading strategies for a hypothetical trader who chooses portfolios from foreign exchange (forex) technical rules in major and emerging markets, the carry trade, and U.S. equities. The results show that forex trading alone dramatically outperforms the S&P 500 but there is little gain to coordinating forex and equity strategies, which explains why practitioners consider these tools separately. In addition, a backtesting procedure to choose optimal portfolios does not select carry trade strategies until well into the 1990s, which helps to explain the relatively recent surge in interest in this strategy. Forex trading returns dip significantly in the 1990s but recover by the end of the decade and have greatly outperformed an equity position since 1998. Overall, trading rule returns still exist in forex markets—with substantial stability in the types of rules—though they have migrated to emerging markets to a considerable degree.Foreign exchange ; Trade

A learning object success story

This paper outlines an approach to designing a course entirely in learning objects. It provides a theoretical basis for the design and then presents evaluation data from a master’s level course using this design. It also describes several re-uses of the learning objects on other courses and in different contexts. Each learning object is conceived as a whole learning experience, thus avoiding many of the problems associated with assembling components of disparate kinds

Is technical analysis in the foreign exchange market profitable? a genetic programming approach

Using genetic programming techniques to find technical trading rules, we find strong evidence of economically significant out-of-sample excess returns to those rules for each of six exchange rates, over the period 1981-1995. Further, when the dollar/deutschemark rules are allowed to determine trades in the other markets, there is a significant improvement in performance in all cases, except for the deutschemark/yen. Betas calculated for the returns according to various benchmark portfolios provide no evidence that the returns to these rules are compensation for bearing systematic risk. Bootstrapping results on the dollar/deutschemark indicate that the trading rules are detecting patterns in the data that are not captured by standard statistical models.Programming (Mathematics) ; Foreign exchange