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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
Exquisitely Specific Bisubstrate Inhibitors of c‑Src Kinase
We have developed a modular approach
to bisubstrate inhibition
of protein kinases. We apply our methodology to c-Src and identify
a highly selective bisubstrate inhibitor for this target. Our approach
has yielded the most selective c-Src inhibitor to date, and the methodology
to render the bisubstrate inhibitor cell-permeable provides a highly
valuable tool for the study of c-Src signaling. In addition, we have
applied our bisubstrate inhibitor to develop a novel screening methodology
to identify non-ATP-competitive inhibitors of c-Src. Using this methodology,
we have discovered the most potent non-ATP-competitive inhibitor reported
to date. Our methodology is designed to be general and could be applicable
to additional kinases inhibited by the promiscuous ATP-competitive
fragment used in our studies
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