def adjust_returns_for_slippage(returns, turnover, slippage_bps):
    """Apply a slippage penalty for every dollar traded.

    Parameters
    ----------
    returns : pd.Series
        Time series of daily returns.
    turnover: pd.Series
        Time series of daily total of buys and sells
        divided by portfolio value.
            - See txn.get_turnover.
    slippage_bps: int/float
        Basis points of slippage to apply.

    Returns
    -------
    pd.Series
        Time series of daily returns, adjusted for slippage.
    """
    slippage = 0.0001 * slippage_bps
    # Only include returns in the period where the algo traded.
    trim_returns = returns.loc[turnover.index]
    return trim_returns - turnover * slippage