Clustering ERereuse 419 custering Stock Returns build ling portfolios of stocks,

Question

Clustering ERereuse 419 custering Stock Returns build ling portfolios of stocks, investors seek to obtain good returns while en bbe ariability in those returns over time. This can be achieved by is oks tha how different patterns of returns. In this problem, we will sto ting eing to identify clusters of stocks that have similar returns over time; or might select a diverse portfolio by selecting stocks from different an mvestor dasters. For this problem, we will use the dataset NasdagReturns.csv, which atains monthly stock returns from the NASDAQ stock exchange during 2000- 200. The companies selected in this dataset are limited to those that were isted on the stock exchange for this entire time period and whose stock price ever fell below $1. The NASDAQ is the second-largest stock exchange in the world, and it lists many technology companies. The variables in the dataset are described in Table 22.10. )Let us start by exploring the dataset. i) How many companies are in this dataset? How many companies are there in each of the industries? ii) In the aftermath of the dot-com bubble bursting in the early 2000s, the NASDAQ was quite tumultuous. In December 2000, Table 22.10: Variables in the dataset NasdagReturns.cst Variable Description StockSymbol The symbol identifying the company of the stock The industry the stock is classified under. Industry SubIndustry The sub-industry the stock is classified under Ret2000.01 The return for the stock during the variable's indicated month. The variable names have the format "RetYYYY.MM," where YYYY is the year and MM is the month. For instance, variable Ret2005.02 refers to February 2005. The value stored is a proportional change in stock value during that month. For instance, a value of 0.05 means the stock increased in value 5% during the month, while a value of -0.02 means the stock decreased in value 2% during the month. There are 120 of these variables, for the 120 months in our dataset. Ret2009.12

Explanation / Answer

Given a set of prices, return periodic returns.

Usage

Arguments

Details

periodReturn is the underlying function for wrappers:

Value

Returns object of the class that was originally passed in, with the possible exception of monthly and quarterly return indicies being changed to class yearmon and yearqtr where available. This can be overridden with the indexAt argument passed in the ... to the to.period function.
By default, if subset is NULL, the full dataset will be used.

x object of state prices, or an OHLC type object period character string indicating time period. Valid entries are ‘daily’, ‘weekly’, ‘monthly’, ‘quarterly’, ‘yearly’. All are accessible from wrapper functions described below. Defaults to monthly returns (same as monthlyReturn) subset an xts/ISO8601 style subset string type type of returns: arithmetic (discrete) or log (continuous) leading should incomplete leading period returns be returned ... passed along to to.period

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