Index derivation for price and liquidity indices

Description

indexComp derives an Index from the given price and market capitalization or liquidity data. The number of constituents can be fixed or being chosen flexible based on the methodology from Trimborn and Haerdle (2018). This is the main function of the package. The derived index is meant for analysis purposes. For a continuous updating and display of an index on a website, please refer to the remaining functions.

Usage

indexComp(market, price, vol = NULL, 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, 
base.value = 1000, derivation.period = 1, derivation.period.ic = 3, days.line)

Arguments

Details

For more details, please see the methodology section of the paper Trimborn and Haerdle (2018).

Value

An object of the class IndexConstruction with the components

• index The optimal index

• totalIndex The index of all constituents

• totalIndexRebased The index of all constituents rebased at the index each time after altering the number of index constituents which is useful for comparisons with the market

• assets A list containing the assets considered for index construction in each period

• weights A list containing the weights assigned to the selected index constituents in each period

• weightsRelative A list containing the relative weights assigned to the selected index constituents in each period

• marketCap The provided dataset of the market capitalization of each asset for index construction

• price The provided dataset of the price series of each asset for index construction

• tradingVolume The provided dataset of the trading volume of each asset for index construction

• daysDerivation The provided vector of dates on which to rederive the index weights and number of index constituents

References

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

Examples

data(CryptoData)

price = price["2014-03-31::2015-01-31"]
market = market["2014-03-31::2015-01-31"]
vol = vol["2014-03-31::2015-01-31"]
days.line = switchDates(price, specificDate = "1")

indexComp(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)

Number of Index Members Derivation

Description

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".

Usage

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)

Arguments

Details

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).

Value

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

References

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

Examples

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)

Reevaluation of Index constituents weights

Description

indexMembersUpdate derives the new weights for the coming period. The methodology is according to Trimborn and Haerdle (2018). The method derives the new weights over the data period provided. The data input defines the length of the period, hence it can be different from full month. 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".

Usage

indexMembersUpdate(market, price, vol, weighting, index.const, last.value)

Arguments

Details

indexMembersUpdate derives the new weights for the coming period. The methodology is according to Trimborn and Haerdle (2018). The method derives the new weights over the data period provided. The data input defines the length of the period, hence it can be different from full month. For more details, please see the methodology section of the paper Trimborn and Haerdle (2018).

Value

A list, entry 1 is the ordered names of index members, entry 2 the respective consideration of the index constituents, entry 3 the weights of the index members which gives multiplied with entry 2 the actual weight and entry 4 the new divisor of the index.

References

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

Examples

data(CryptoData)

price = price["2017-01-01::2017-01-31"]
market = market["2017-01-01::2017-01-31"]
vol = vol["2017-01-01::2017-01-31"]
indexMembersUpdate(market = market, price = price, vol = vol, 
weighting = "market", index.const = 5, last.value = 1000)

Updating an existing index with new index values

Description

indexUpdate derives the next values of an Index from the given price, weights and its divisor. 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".

Usage

indexUpdate(price, index.weights, divisor)

Arguments

Details

For more details, please see the methodology section of the paper Trimborn and Haerdle (2018).

Value

The next value(s) of the Index.

References

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

Examples

data(CryptoData)

const.names = c("btc", "eth", "xrp", "ltc", "xmr")
index.weights = c(16136712, 88440036, 36856524148, 49589181, 13859864)
divisor = 17185084

indexUpdate(price["2017-02-01", const.names], index.weights = index.weights, divisor = divisor)

Market capitalization data for Cryptocurrencies.

Description

The dataset contains market capitalization information for cryptocurrencies.

Usage

data(CryptoData)

Format

A dataset with a xts matrix. Load the R library xts for proper visualization of the dataset.

Source

The dataset was provided by CoinGecko. Up-to-date data are accessible via https://www.coingecko.com/api.

Pricing data for Cryptocurrencies.

Description

The dataset contains pricing information for cryptocurrencies.

Usage

data(CryptoData)

Format

A dataset with a xts matrix. Load the R library xts for proper visualization of the dataset.

Source

The dataset was provided by CoinGecko. Up-to-date data are accessible via https://www.coingecko.com/api.

Retrieving the relative weights of the assets in the index

Description

relativeWeights retrieves the relative weights of the assets in the index from the absolute weights expressed in shares of the assets. The latter is a direct output of indexComp.

Usage

relativeWeights(price, index.weights)

Arguments

Value

The relative weights of the assets in the Index.

References

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

Examples

data(CryptoData)

const.names = c("btc", "eth", "xrp", "ltc", "xmr")
index.weights = c(16136712, 88440036, 36856524148, 49589181, 13859864)

relativeWeights(price = price["2017-02-01", const.names], index.weights = index.weights)

Deriving the dates on which the index constituents are going to be reevaluated

Description

switchDates derives the dates on which the index constituents are going to be reevaluated.

Usage

switchDates(price, specificDate = NULL, WeekDay = NULL, Appearance = 1)

Arguments

Value

A vector of class date with the respective dates on which the index members become reevaluated. This is a necessary input to IndexComp.

References

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

Examples

data(CryptoData)

switchDates(price, specificDate = "1")

Volume data for Cryptocurrencies.

Description

The dataset contains trading volume information for cryptocurrencies.

Usage

data(CryptoData)

Format

A dataset with a xts matrix. Load the R library xts for proper visualization of the dataset.

Source

The dataset was provided by CoinGecko. Up-to-date data are accessible via https://www.coingecko.com/api.