Maximise the Sharpe Ratio. The result is also referred to as the tangency portfolio,
        as it is the tangent to the efficient frontier curve that intercepts the risk-free
        rate.

        :param risk_free_rate: risk-free rate of borrowing/lending, defaults to 0.02
        :type risk_free_rate: float, optional
        :raises ValueError: if ``risk_free_rate`` is non-numeric
        :return: asset weights for the Sharpe-maximising portfolio
        :rtype: dict

def max_sharpe(self, risk_free_rate=0.02):
        """
        Maximise the Sharpe Ratio. The result is also referred to as the tangency portfolio,
        as it is the tangent to the efficient frontier curve that intercepts the risk-free
        rate.

        :param risk_free_rate: risk-free rate of borrowing/lending, defaults to 0.02
        :type risk_free_rate: float, optional
        :raises ValueError: if ``risk_free_rate`` is non-numeric
        :return: asset weights for the Sharpe-maximising portfolio
        :rtype: dict
        """
        if not isinstance(risk_free_rate, (int, float)):
            raise ValueError("risk_free_rate should be numeric")

        args = (self.expected_returns, self.cov_matrix, self.gamma, risk_free_rate)
        result = sco.minimize(
            objective_functions.negative_sharpe,
            x0=self.initial_guess,
            args=args,
            method="SLSQP",
            bounds=self.bounds,
            constraints=self.constraints,
        )
        self.weights = result["x"]
        return dict(zip(self.tickers, self.weights))