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- Announcing The Release of DLPAL v1.0
- Announcing The Release of DLPAL PRO
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Category Archives: Quantitative trading
There is a simple explanation for the rally in stocks this year. Explanatory hypotheses are valid if they generate testable predictions. This one does unlike a number of suggested alternative hypotheses that are not falsifiable.
Six months are not responsible for all gains in stock market since 2000. This conclusion in some articles was based on the wrong choice of returns. The correct number is about 32.
Apart from the trend-followers of the 1980s who used simple math models and exploited a real market anomaly, any other claims of high trading returns from the use of math models should be taken with a grain of salt. There … Continue reading
After a long time there are nearly equal long and short signals in the quantitative analysis of S&P 100 stocks. This is a rare signal and possibly bearish short-term.
Every trader’s resolution for this year should include a transition to a mode of operation that is compatible with current market environment. Among other things, this includes abandoning random discretionary trading and adopting a systematic framework. When human traders start … Continue reading
Articles in mainstream media constantly praise the returns of some hedge funds and attribute them to quantitative trading. But can quantitative models extract billions of dollars worth of alpha from noisy data? Is it possible that these hedge funds have … Continue reading
Developing trading strategies is a tedious and time consuming task with a low success rate. Significance of results often cannot be inferred from historical tests and validation samples due to data snooping, especially when many trials are involved. As a … Continue reading
We are pleased to announce the release of DLPAL v1.0, a software program for short-term systematic and discretionary traders that can identify anomalies in price action via the use of proprietary unsupervised and supervised machine learning algorithms.