如果待仿真的对象系统是随机(stochastic)系统,可以用概率模型来描述系统中的随机性并进行仿真实验,称为随机仿真(stochastic simulation)。它有一个更酷炫的名称叫做蒙特卡罗仿真(monte-carlo simulation),这个名字来源于世界著名的赌城摩纳哥的蒙特卡罗。通过对研究问题或系统进行随机抽样,然后对样本值进行统计分析,
b. Libraries: Python offers numerous libraries, such as NumPy and SciPy, which provide efficient tools for numerical computing and simulation tasks. c. Visualization: Python libraries like Matplotlib and Seaborn enable users to create appealing visualizations of Monte Carlo simulation results. 2. Exampl...
Monte Carlo simulations are used to estimate a range of outcomes for uncertain events, and Python libraries such as SciPy and NumPy make creating your own simulations fast and easy! Apply New Skills in a Principled Simulation As you learn each step of creating a simulation, you’ll apply ...
2.21.4.3.2 代码实现 importnumpyasnpdefmonte_carlo_simulation(S,K,T,r,sigma,num_simulations):# 参数解释# S: 当前股票价格# K: 行权价格# T: 到期时间(年)# r: 无风险利率# sigma: 波动率# num_simulations: 模拟次数# 生成随机数z=np.random.standard_normal(num_simulations)# 生成标准正态分布...
calc_AF_MonteCarlo_ARR(MC, size, filename=None, FF_China=None, RESPscheme=None, bootstrap=True): ''' Calculation of the Airborne fraction using a Monte Carlo simulation, based on the linear approximations of the LU time series. For a (size+1 x size+1) array, the AF is calculated ...
蒙特卡罗模拟法(Monte Carlo Simulation Approach) 随机抽样方法或统计实验方法,是一种随机模拟方法。 采用的是随机的方法来获得大量的情景,由此得到资产组合的收益分布。 模型构建合理,参数选择正确的情况下,蒙特卡罗模拟法会更加精确可靠,而且可以处理非线性、收益率非正态的数据 ...
In this article we will outline the Vasicek Model for interest rate derivatives pricing, describe its mathematical formulation, implement and carry out a Monte Carlo simulation using Python and discuss a few real world applications of the model in quantitative finance....
without having to compromise on efficiency. Furthermore mcpele abstracts each element of a Monte Carlo simulation eliminating the need for frequent code rewriting that experienced Monte Carlo developers typically go through, thus reducing the time required for the implementation of an idea and reducing...
Python内置的random模块和第三方库NumPy的random模块都提供了生成随机漫步序列的方法,接下来我们分别介绍下这两种方法的使用。 内置模块random 实现 代码语言:javascript 代码运行次数:0 运行 importrandom # 生成呈正态分布的随机数 #print("normalvariate: ",random.normalvariate(0,1))# 产生一组满足正太分布的随机数...
有时候,我们可能需要根据一个自定义的概率分布来进行选择,这时可以利用Python中的统计学库来实现。下面是一个使用scipy.stats库来实现的例子: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 from scipy.statsimportbernoulli defmake_decision(probability):returnbernoulli.rvs(probability) ...