  Applications of the quantum algorithm for Monte Carlo simulation to pricing
of financial derivatives have been discussed in previous papers. However, up to
now, the pricing model discussed in such papers is Black-Scholes model, which
is important but simple. Therefore, it is motivating to consider how to
implement more complex models used in practice in financial institutions. In
this paper, we then consider the local volatility (LV) model, in which the
volatility of the underlying asset price depends on the price and time. We
present two types of implementation. One is the register-per-RN way, which is
adopted in most of previous papers. In this way, each of random numbers (RNs)
required to generate a path of the asset price is generated on a separated
register, so the required qubit number increases in proportion to the number of
RNs. The other is the PRN-on-a-register way, which is proposed in the author's
previous work. In this way, a sequence of pseudo-random numbers (PRNs)
generated on a register is used to generate paths of the asset price, so the
required qubit number is reduced with a trade-off against circuit depth. We
present circuit diagrams for these two implementations in detail and estimate
required resources: qubit number and T-count.
