95fd0b324529fac7f2eb09c49832f035f9cf52b7,pypfopt/efficient_frontier.py,EfficientFrontier,max_sharpe,#EfficientFrontier#Any#,155

Before Change

        self._solve_cvxpy_opt_problem()
        // Inverse-transform
        self.weights = (self._w.value / k.value).round(16) + 0.0
        return dict(zip(self.tickers, self.weights))

    def max_quadratic_utility(self, risk_aversion=1, market_neutral=False):
        r
        Maximise the given quadratic utility, i.e:

After Change

        self._solve_cvxpy_opt_problem()
        // Inverse-transform
        self.weights = (self._w.value / k.value).round(16) + 0.0
        return self._make_output_weights()

    def max_quadratic_utility(self, risk_aversion=1, market_neutral=False):
        r
        Maximise the given quadratic utility, i.e:

Instances