In this paper we utilize White's Reality Check bootstrap methodology~White~1999!! to evaluate simple technical trading rules while quantifying the data-snooping bias and fully adjusting for its effect in the context of the full universe from which the trading rules were drawn. Hence, for the first time, the paper presents a comprehensive test of performance across all technical trading rules examined. We consider the study of Brock, Lakonishok, and LeBaron~1992!, expand their universe of 26 trading rules, apply the rules to 100 years of daily data on the Dow Jones Industrial Average, and determine the effects of data-snooping. TECHNICAL TRADING RULES HAVE BEEN USED in financial markets for more than a century. Numerous studies have been performed to determine whether such rules can be employed to provide superior investing performance. 1 By and large, recent academic literature suggests that technical trading rules are capable of producing valuable economic signals. In perhaps the most comprehensive recent study of technical trading rules using 90 years of daily stock prices, Brock, Lakonishok, and LeBaron~1992!~BLL, hereafter! find that 26 technical trading rules applied to the Dow Jones Industrial Averagẽ DJIA! significantly outperform a benchmark of holding cash. Their findings are especially strong because every one of the trading rules they consider is capable of beating the benchmark. When taken at face value, these results indicate either that the stock market is not efficient even in the weak form-a conclusion which, if found to be robust, will go against most researchers' prior beliefs-or that risk premia display considerable variation even over very short periods of time~i.e., at the daily interval!. 1647 occurs when a given set of data is used more than once for purposes of inference or model selection. When such data reuse occurs, there is always the possibility that any satisfactory results obtained may simply be due to chance rather than to any merit inherent in the method yielding the results. With respect to their choice of technical trading rules, BLL state that "numerous moving average rules can be designed, and some, without a doubt, will work. However, the dangers of data snooping are immense"~p. 1736!. Thus, BLL rightfully acknowledge the effects of data-snooping. They go on to evaluate their results by fitting several models to the raw data and resampling the residuals to create numerous bootstrap samples. The goal of this effort is to determine the statistical significance of their findings. However, as acknowledged by BLL, they are not able "to compute a comprehensive test across all rules. Such a test would have to take into account the dependencies between results for different rules"~p. 1743!. 2 This task has thus far eluded researchers.A main purpose of our paper is to extend and enrich the earlier research on technical trading rules by applying a novel procedure that permits computation of precisely such a test. Although the bootstrap approach~intro-duced by Efron~1979!! is not new to...

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Homogeneous catalysis has provided chemists with numerous transformations to enable rapid construction of organic molecules. However, these reactions are complex, requiring multiple substrate‐dependent mechanistic steps to operate in harmony under a single set of experimental conditions. As a consequence, synthetic chemists often carry out laborious, empirical screening to identify suitable catalysts, solvents, and additives to achieve high yields and selectivity. In this Minireview, recently developed tools, technologies, and strategies will be described that improve this development process. In particular, the application of high throughput techniques to run more experiments, experimental design principles to access better data, and statistical tools to provide predictive models will be discussed.

The complexes [(4′-Ph-terpy)Ru(H 2 O) 3 ](OTf) 2 and [(4′-Ph-terpy)Ir(OTf) 3 ] have been evaluated as catalysts for the conversion of 2,5-hexanedione and 2,5-dimethylfuran to hydrodeoxygenated products in aqueous acidic medium at elevated temperature (150−225 °C) under hydrogen gas (5.5 MPa). These two substrates form part of a value chain leading from C 6 sugars to 2,5-hexanediol, 2,5-dimethyltetrahydrofuran, and hexane, which can be generated by the homogeneously acting ruthenium catalyst in up to 69%, 80%, and 10% yield, respectively, while at T > 175 °C the iridium system decomposes to a highly active but heterogeneously acting coating in the reactor defeating the premise of a homogeneous catalyst system. The deactivation and decomposition pathway of both catalysts leads to the formation of a series of isostructural complexes [M(4′-Ph-terpy) 2 ] n+ (M = Fe, Ni, Ru, Ir; n = 2, 3) characterized by ESI-MS and single crystal X-ray crystallography, in which the source of the Fe and Ni is the 316SS reactor body.

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