<feed xmlns="http://www.w3.org/2005/Atom"> <id>https://hanshan.github.io/hanshan.github.io/</id><title>Docs Harbor</title><subtitle>personal docs folder</subtitle> <updated>2026-05-02T14:02:09+08:00</updated> <author> <name>hanshan</name> <uri>https://hanshan.github.io/hanshan.github.io/</uri> </author><link rel="self" type="application/atom+xml" href="https://hanshan.github.io/hanshan.github.io/feed.xml"/><link rel="alternate" type="text/html" hreflang="en" href="https://hanshan.github.io/hanshan.github.io/"/> <generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator> <rights> © 2026 hanshan </rights> <icon>/hanshan.github.io/assets/img/favicons/favicon.ico</icon> <logo>/hanshan.github.io/assets/img/favicons/favicon-96x96.png</logo> <entry><title>Option pricing</title><link href="https://hanshan.github.io/hanshan.github.io/posts/%E6%9C%9F%E6%9D%83/" rel="alternate" type="text/html" title="Option pricing" /><published>2023-06-19T00:00:00+08:00</published> <updated>2023-06-19T00:00:00+08:00</updated> <id>https://hanshan.github.io/hanshan.github.io/posts/%E6%9C%9F%E6%9D%83/</id> <content src="https://hanshan.github.io/hanshan.github.io/posts/%E6%9C%9F%E6%9D%83/" /> <author> <name><author_id></name> </author> <summary> Black-Scholes公式是一种用来计算欧式期权（European option）理论价格的数学公式，它基于以下假设¹²： 期权的标的资产（underlying asset）是一种连续支付股息（dividend）的股票，其价格服从几何布朗运动（geometric Brownian motion），即具有恒定的漂移率（drift rate）和波动率（volatility）。 期权的行权价格（strike price）和到期时间（expiration date）是已知的，并且在到期前不能提前行权。 市场是完全有效的，不存在套利机会，交易成本为零，且无限制地买卖。 无风险利率（risk-free rate）是已知的，并且在期权到期前保持不变。 期权的持有者可以根据Black-Scholes模型建立一个完美对冲（perfect hedge）的投资组合，即通过买卖标... </summary> </entry> <entry><title>Cpp</title><link href="https://hanshan.github.io/hanshan.github.io/posts/cpp/" rel="alternate" type="text/html" title="Cpp" /><published>2023-06-09T00:00:00+08:00</published> <updated>2023-06-09T00:00:00+08:00</updated> <id>https://hanshan.github.io/hanshan.github.io/posts/cpp/</id> <content src="https://hanshan.github.io/hanshan.github.io/posts/cpp/" /> <author> <name>ZYH</name> </author> <summary> </summary> </entry> <entry><title>Time Series Project</title><link href="https://hanshan.github.io/hanshan.github.io/posts/time-series-project-1/" rel="alternate" type="text/html" title="Time Series Project" /><published>2023-06-07T00:00:00+08:00</published> <updated>2023-06-07T00:00:00+08:00</updated> <id>https://hanshan.github.io/hanshan.github.io/posts/time-series-project-1/</id> <content src="https://hanshan.github.io/hanshan.github.io/posts/time-series-project-1/" /> <author> <name><author_id></name> </author> <summary> Abstract The project obtains Ontario Gas Demand from tsdl library and analyzed it with linear time series models and I fitted the data with SARIMA(3,0,3)(4,1,2) 12 which corrected predicted the gasoline demand of next cycle after various transformation and differencing. 1.Introduction Given current high inflation environment and sky-rocketing gasoline price, it is of the interest to analysis ho... </summary> </entry> </feed>
