QuantMax

PY

Python and data for quants

NumPy and pandas at the level market data demands, and the biases that hide inside a backtest.

  1. 1

    Python fundamentals

    Idiomatic Python, generators, itertools, functools and typing.

  2. 2

    NumPy

    Broadcasting, vectorisation, axis semantics, einsum and seeded randomness.

  3. 3

    pandas

    groupby, merge_asof, resample, rolling windows and time zones.

  4. 4

    Market data handling

    Ticks versus bars, adjustment, point-in-time data and look-ahead bias.

  5. 5

    Vectorised backtesting

    Signal to position to P&L, costs, turnover, Sharpe and drawdown.

  6. 6

    Performance

    Profiling, vectorising, numba, and when to drop to C++.