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  1. Demand for C++ Developers?

    Try HackerRank.com
  2. Machine learning for trading

    I recently published my studies on machine learning methods in algorithmic trading. Source codes on GitHub, Jupyter notebook format: Machine learning for Finance Deep learning for Finance Full write-up is available on Amazon - Mastering Python for Finance, second edition. Hope it will be...
  3. Master reading list for Quants, MFE (Financial Engineering) students

    Hi Andy, Mind adding my book Mastering Python for Finance to the list? Some topics covered are linearity, nonlinearity, algo trading and backtesting.. Thanks!
  4. What problems does machine learning solve in Quantitative Finance

    backtesting. you might have models that are profitable, some not so profitable, some suddenly become less profitable. ML would help me to find optimum model parameters in my line of work.
  5. fair price

    Yes, you're right. From what I've learnt, the observed prices takes into account: inventory costs transaction costs taxes Risk of the financial institution making that quote Everyone's fair price is different. To me, the fair price is the last traded price, but that could have happened many...
  6. A high-frequency trading model with IB

    The answer doesn't seem to come when someone over the phone demands an answer in one minute. Only when I put down the phone, the answer to mind immediately. Maybe it's the pressure. Great comments, thank you. Looks like I will be spending the rest of my time working on this.
  7. Advice

    very inspiring. still working on the last step
  8. A high-frequency trading model with IB

    So it's the time of the year where I've just graduated and time to look for a job. With all job applications got seemingly sucked into black holes, I grew frustrated and decided to publish a trading system I've been working on in the hope that HR will take better notice of my application...
  9. Quantopian

    i just started playing with this platform and it's really fun with backtester. Did anyone trade with live money, and if so, is the results as expected with simulated results?
  10. Put/Call ratio and Fundamental Factor Model

    i'd go with lagged data as it seems to be some correlation between yesterday's prices and today's prices. time horizon? definitely 2008 onwards.
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