Recent content by mbquant

  1. M

    Which books should you read if you want to learn trading?

    What sort of trading are you contemplating? If it's algo trading, you can go through this blog: https://blog.quantinsti.com/books-algorithmic-trading/
  2. M

    Some books on trading

    You can refer this blog for a comprehensive list of books on Algo Trading: https://blog.quantinsti.com/books-algorithmic-trading/
  3. M

    Volatility vs Risk

    It's more nuanced. Risk is commonly defined as the possibility of something bad happening. And since this "something bad" is unknown, we tend to use volatility as an alias for it. When you're investing, longer your investment horizon (holding period), more can you treat daily, or even weekly...
  4. M

    Algo & Quant traders

    Do you have any real data to back up your claims?
  5. M

    Algo & Quant traders

    Not really. You can be profitable only when you get to identify a certain 'edge' over the market, or be able to tap into some inefficiency or mispricing. And it takes quant methods to identify, quantify, and act efficiently and quickly upon these. You simply can't rely on some chart patterns...
  6. M

    Using Machine Learning for discretionary trading

    Yup, you can do much more than that. Here's a read that can provide you some food for thought: https://blog.quantinsti.com/artificial-intelligence-machine-learning-trading/ Of course, this was just a beginner-level blog to help you understand the scheme of things. Hope it helps!
  7. M

    How to know if my edge is going away?

    For seasoned long-only practitioners, identifying a waning edge can be a nuanced challenge. Here's a technical toolkit to aid in this endeavor: Performance Degradation: Lagging Returns: Monitor for underperformance relative to historical benchmarks or the broader market. This might indicate a...
  8. M

    Monte Carlo question

    Risk % in Backtesting can be Tricky Especially for Monte Carlo simulations, using a constant risk percentage per trade isn't ideal. Why? Because in real life, you might not risk more as your account grows. This can mess up the simulation, especially if early big losses happen (which might not...
  9. M

    Intraday Option Price Modeling

    Hi, If you're proficient in Python, you can use the Quantlib library. You can also consider these sites: https://upstox.com/calculator/option-value/ https://www.samco.in/calculators/option-fair-value-calculator https://www.hoadley.net/Options/optionstools.htm https://optionomega.com/ Hope it...
  10. M

    My bond strategy...Does this make sense??

    Sounds good! But you might just have to take care of two potential downsides: 1. Opportunity cost: While the current yields are attractive, you might miss out on potentially higher returns if the market shifts and interest rates start to decline. 2. Reinvestment risk: As your shorter-term...
  11. M

    Can someone share the code for downloading historical data

    You can try this (Python):
  12. M

    algo Trading optimization

    Hi there, One reason that comes to my mind would be the time complexity of your strategy. The underlying model that you are using may not be well suited for larger timeframes. Another reason can be numerous and/or complex parameters in your strategy.
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