It is well known that backward stochastic differential equations (BSDEs) stem from the study on the Pontryagin type maximum principle for optimal stochastic controls. A solution of a BSDE hits a given terminal value ( which is a random variable) by virtue of an additional martingale term and an indefinite initial state. This paper attempts to explore the relationship between BSDEs and stochastic controls by interpreting BSDEs as some stochastic optimal control problems. More specifically, associated with a BSDE, a new stochastic control problem is introduced with the same dynamics but a definite given initial state. The martingale term in the original BSDE is regarded as the control, and the objective is to minimize the second moment of the difference between the terminal state and the terminal value given in the BSDE. This problem is solved in a closed form by the stochastic linear-quadratic ( LQ) theory developed recently. The general result is then applied to the Black-Scholes model, where an optimal mean-variance hedging portfolio is obtained explicitly in terms of the option price. Finally, a modified model is investigated, where the difference between the state and the expectation of the given terminal value at any time is taken into account.