Download Analysis of Time Series 3rd 2010 by Ruey S. Tsay PDF
By Ruey S. Tsay
This e-book presents a extensive, mature, and systematic advent to present monetary econometric versions and their functions to modeling and prediction of economic time sequence information. It makes use of real-world examples and genuine monetary facts in the course of the e-book to use the versions and strategies described.
The writer starts off with uncomplicated features of monetary time sequence information earlier than overlaying 3 major topics:
- Analysis and alertness of univariate monetary time series
- The go back sequence of a number of assets
- Bayesian inference in finance methods
Key gains of the hot variation comprise extra assurance of recent day themes akin to arbitrage, pair buying and selling, learned volatility, and credits hazard modeling; a tender transition from S-Plus to R; and accelerated empirical monetary info sets.
The total goal of the e-book is to supply a few wisdom of monetary time sequence, introduce a few statistical instruments important for interpreting those sequence and achieve event in monetary purposes of assorted econometric methods.
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Extra info for Analysis of Time Series 3rd 2010
B) Test the null hypothesis that the excess kurtosis of the returns is zero. 5. Daily foreign exchange rates (spot rates) can be obtained from the Federal Reserve Bank in Chicago. The data are the noon buying rates in New York City certiﬁed by the Federal Reserve Bank of New York. S. K. pound, and the Japanese yen from January 4, 2000, to March 27, 2009. The data are also on the Web. (a) Compute the daily log return of each exchange rate. (b) Compute the sample mean, standard deviation, skewness, excess kurtosis, minimum, and maximum of the log returns of each exchange rate.
A) Daily returns of the market indexes and individual stocks tend to have high excess kurtoses. For monthly series, the returns of market indexes have higher excess kurtoses than individual stocks. (b) The mean of a daily return series is close to zero, whereas that of a monthly return series is slightly larger. (c) Monthly returns have higher standard deviations than daily returns. (d) Among the daily returns, market indexes have smaller standard deviations than individual stocks. This is in agreement with common sense.
For monthly series, the returns of market indexes have higher excess kurtoses than individual stocks. (b) The mean of a daily return series is close to zero, whereas that of a monthly return series is slightly larger. (c) Monthly returns have higher standard deviations than daily returns. (d) Among the daily returns, market indexes have smaller standard deviations than individual stocks. This is in agreement with common sense. (e) The skewness is not a serious problem for both daily and monthly returns.