Probability of local bifurcation type from a fixed point: A random matrix perspective

Results regarding probable bifurcations from fixed points are presented in the context of general dynamical systems (real, random matrices), time-delay dynamical systems (companion matrices), and a set of mappings known for their properties as universal approximators (neural networks). The eigenvalue spectra is considered both numerically and analytically using previous work of Edelman et. al. Based upon the numerical evidence, various conjectures are presented. The conclusion is that in many circumstances, most bifurcations from fixed points of large dynamical systems will be due to complex eigenvalues. Nevertheless, surprising situations are presented for which the aforementioned conclusion is not general, e.g. real random matrices with Gaussian elements with a large positive mean and finite variance.Comment: 21 pages, 19 figure

Technical trading and cryptocurrencies

This paper carries out a comprehensive examination of technical trading rules in cryptocurrency markets, using data from two Bitcoin markets and three other popular cryptocurrencies. We employ almost 15,000 technical trading rules from the main five classes of technical trading rules and find significant predictability and profitability for each class of technical trading rule in each cryptocurrency. We find that the breakeven transaction costs are substantially higher than those typically found in cryptocurrency markets. To safeguard against data-snooping, we implement a number of multiple hypothesis procedures which confirms our findings that technical trading rules do offer significant predictive power and profitability to investors. We also show that the technical trading rules offer substantially higher risk-adjusted returns than the simple buy-and-hold strategy, showing protection against lengthy and severe drawdowns associated with cryptocurrency markets. However there is no predictability for Bitcoin in the out-of-sample period, although predictability remains in other cryptocurrency markets

The Profitability of Technical Stock Trading has Moved from Daily to Intraday Data

This paper investigates how technical trading systems exploit the momentum and reversal effects in the S&P 500 spot and futures market. The former is exploited by trend-following models, the latter by contrarian models. In total, the performance of 2,580 widely used models is analysed. When based on daily data, the profitability of technical stock trading has steadily declined since 1960 and has become unprofitable over the 1990s. However, when based on 30-minutes data the same models produce an average gross return of 8.8 percent per year between 1983 and 2000. These results do not change substantially when trading is simulated over six subperiods. Those 25 models which performed best over the most recent subperiod produce a significantly higher gross return over the subsequent subperiod than do all models together. Over the out-of-sample period 2001-2006 the 2,580 models perform much worse than between 1983 and 2000. This result could be due to stock markets becoming more efficient or to stock price trends shifting from 30-minutes prices to prices of higher frequencies

The Interaction between the Aggregate Behaviour of Technical Trading Systems and Stock Price Dynamics

This study analyses the interaction between the aggregate trading behaviour of technical models and stock price fluctuations in the S&P 500 futures market. It examines 2,580 widely used trading systems based on 30-minutes prices. The sample comprises trend-following as well as contrarian models. It shows that technical trading exerts an excess demand pressure on the stock market. This is because technical models produce clusters of trading signals that are on the same side of the market, either buying or selling. Initial stock price changes triggered by news are strengthened by a sequence of trading signals produced by trend-following models. Once 90 percent of the models have signalled a particular position, stock prices tend to move in the direction congruent with the position-holding of the models. This phenomenon has to be attributed to the transactions of non-technical traders, perhaps amateurs. Once price movements lose their momentum, contrarian technical models contribute to reversals of the trend

Elution of residual monomers from dental composite materials

Aim This study was designed to determine the type and amount of the monomers leached from the different particle sizes of the composite materials

Market Efficiency and Returns to Simple Technical Trading Rules: Further Evidence from U.S., U.K., Asian and Chinese Stock Markets

technical trading rules, market evolution, Chinese stock markets,

MMP20 Hemopexin Domain Mutation in Amelogenesis Imperfecta

Proteolytic enzymes serve important functions during dental enamel formation, and mutations in the kallikrein 4 (KLK4) and enamelysin (MMP20) genes cause autosomal-recessive amelogenesis imperfecta (ARAI). So far, only 1 KLK4 and 3 MMP20 mutations have been reported in ARAI kindreds. To determine whether ARAI in a family with a hypomaturation-type enamel defect is caused by mutations in the genes encoding enamel proteolytic enzymes, we performed mutational analysis on candidate genes. Mutational and haplotype analyses revealed an ARAI-causing point mutation (c. 910G>A, p.A304T) in exon 6 of MMP20 that results in a single amino acid substitution in the hemopexin domain. Western blot analysis showed decreased expression of the mutant protein, but zymogram analysis demonstrated that this mutant was a functional protein. The proband and an affected brother were homozygous for the mutation, and both unaffected parents were carriers. The enamel of newly erupted teeth had normal thickness, but was chalky white and became darker with age

MMP20 Hemopexin Domain Mutation in Amelogenesis Imperfecta

Proteolytic enzymes serve important functions during dental enamel formation, and mutations in the kallikrein 4 (KLK4) and enamelysin (MMP20) genes cause autosomal-recessive amelogenesis imperfecta (ARAI). So far, only 1 KLK4 and 3 MMP20 mutations have been reported in ARAI kindreds. To determine whether ARAI in a family with a hypomaturation-type enamel defect is caused by mutations in the genes encoding enamel proteolytic enzymes, we performed mutational analysis on candidate genes. Mutational and haplotype analyses revealed an ARAI-causing point mutation (c.910G>A, p.A304T) in exon 6 of MMP20 that results in a single amino acid substitution in the hemopexin domain. Western blot analysis showed decreased expression of the mutant protein, but zymogram analysis demonstrated that this mutant was a functional protein. The proband and an affected brother were homozygous for the mutation, and both unaffected parents were carriers. The enamel of newly erupted teeth had normal thickness, but was chalky white and became darker with age