Description Usage Arguments Details Value References Examples

`indexMemberSelection`

derives the number of index members for the coming period based on an Information Criterion, e.g. AIC. The methodology is according to Trimborn and Haerdle (2018). The method derives the new weights according to the specifications of the weight reevaluation. The function expects the data period provided to be twice the number of months specified in derivation.period.ic. In case of a mismatch, a warning is given. This function is meant for continuous updating and display of an index on a website. For the derivation of an index for analysis purposes, please refer to the function `"indexComp"`

.

1 2 3 4 | ```
indexMemberSelection(market, price, vol, weighting = "market",
weighting.all = "market", ic = "AIC", eval.seq = c("sequential", "all.together"),
optimum = c("local", "global"), start.const = 1, steps = 1, fixed.value = NULL,
derivation.period = 1, derivation.period.ic = 3, base.value = 1000, days.line)
``` |

`market` |
An xts object with the market capitalization data. The default is |

`price` |
An xts object with the price data. An entry is always required. |

`vol` |
An xts object with the trading volume (liquidity) data. The default is |

`weighting` |
The weighting scheme to be applied. |

`weighting.all` |
The weighting scheme to be applied to the full market index. |

`ic` |
Information Criterion to be used for the evaluation of the appropriate index to be used. Possible entries are |

`eval.seq` |
Indicates how the evaluation of the candidate indices by the ic shall be performed. |

`optimum` |
Define how to choose the optimal index. Either a |

`start.const` |
The number of constituents to start constructing the indices with. The default is |

`steps` |
The step width for the number of constituents to construct the next index from. The default is |

`fixed.value` |
In case no ic for the number of constituents for the index shall be applied, give the number of constituents the index shall contain. In that case, |

`base.value` |
The starting value for the index. The default is |

`derivation.period` |
The number of month after which the weights of the index are reallocated. The default is |

`derivation.period.ic` |
The number of month after which the composition of the index is derived again, thus the number of constituents is reevaluated. The default is |

`days.line` |
The days of the month to perform the recalculation on. Can be calculated from SwitchDates. |

`indexMemberSelection`

derives the number of index members for the coming period based on an Information Criterion, e.g. AIC. The methodology is according to Trimborn and Haerdle (2018). The method derives the new weights according to the specifications of the weight reevaluation. The function expects the data period provided to be twice the number of months specified in derivation.period.ic. In case of a mismatch, a warning is given. The data from the first period are used to derived the likelihood, the second period is used for out-of-sample derivation of the number of constituents. Hence for a 3 month reevaluation period, 6 month of data are required by this function. For more details, please see the methodology section of the paper Trimborn and Haerdle (2018).

Returns the number of index members for application in the next period.

Trimborn, S. and Haerdle, W.K. (2018). CRIX an Index for cryptocurrencies, *Journal of Empirical Finance* 49, pp. 107-122. https://doi.org/10.1016/j.jempfin.2018.08.004

1 2 3 4 5 6 7 8 9 10 | ```
data(CryptoData)
price = price["2016-07-31::2017-01-31"]
market = market["2016-07-31::2017-01-31"]
vol = vol["2016-07-31::2017-01-31"]
days.line = switchDates(price, specificDate = "1")
indexMemberSelection(market = market, price = price, vol = vol,
weighting = "market", weighting.all = "market", ic = "AIC", eval.seq = "sequential",
optimum = "local", start.const = 5, steps = 5, days.line = days.line)
``` |

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