Title:	Portfolio Theory
Version:	0.0.3
Description:	Collection of tools to calculate portfolio performance metrics. Portfolio performance is a key measure for investors. These metrics are important to analyse how effectively their money has been invested. This package uses portfolio theories to give investor tools to evaluate their portfolio performance. For more information see, Markowitz, H.M. (1952), <doi:10.2307/2975974>. Analysis of Investments & Management of Portfolios [2012, ISBN:978-8131518748].
License:	GPL-3
Encoding:	UTF-8
LazyData:	true
RoxygenNote:	7.1.0
Imports:	xts, zoo, stats
Depends:	R (≥ 2.10)
Suggests:	spelling
Language:	en-US
NeedsCompilation:	no
Packaged:	2020-06-08 13:17:19 UTC; Kanhaiiya Agrawal
Author:	Anurag Agrawal [aut, cre]
Maintainer:	Anurag Agrawal <agrawalanurag1999@gmail.com>
Repository:	CRAN
Date/Publication:	2020-06-12 10:20:02 UTC

CAPM Alpha

Description

Calculates the portfolio alpha

Usage

alpha.capm(R1, R2)

Arguments

Details

Alpha is a term used in investing to describe a strategy's ability to beat the market, or it's "edge." Alpha is thus also often referred to as “excess return” or “abnormal rate of return,” which refers to the idea that markets are efficient, and so there is no way to systematically earn returns that exceed the broad market as a whole.

Value

Returns the alpha of the portfolio

Examples

alpha.capm(funds$ret1, funds$rfr)

CAPM Beta

Description

Returns the Beta of Security using the CAPM Model

Usage

beta.capm(R1, R2)

Arguments

Details

Beta is a measure of the volatility–or systematic risk–of a security or portfolio compared to the market as a whole.

Value

Value of the beta of the security

Examples

beta.capm(funds$ret1, funds$rfr)

Sample Portfolio Return

Description

An xts dataset to calculate the portfolio metrics in the package

Usage

funds

Format

A xts with 901 rows and 2 variables:

ret1

Portfolio Return

rfr

Benchmark Return (Proxy for risk free rate)

Details

This is a sample returns data of the portfolio to understand and use the functions of the package.

Jenson's Alpha

Description

Calculates the Jenson's Alpha of the security

Usage

jenson.alpha(R1, R2, rf = 0)

Arguments

Value

The Jensen's measure, or Jensen's alpha, is a risk-adjusted performance measure that represents the average return on a portfolio or investment, above or below that predicted by the capital asset pricing model (CAPM), given the portfolio's or investment's beta and the average market return.

Examples

jenson.alpha(funds$ret1, funds$rfr)

Markowitz Mean-Variance Model

Description

Calculates the optimum Portfolio weights

Usage

markowitz.model(R1, R2)

Arguments

Details

Modern portfolio theory (MPT), or mean-variance analysis, is a mathematical framework for assembling a portfolio of assets such that the expected return is maximized for a given level of risk.

Value

Returns the optimum portfolio weights and their risk and return profile.

Examples

markowitz.model(funds$ret1, funds$rfr)

Active Premium

Description

Calculates the active premium

Usage

premium.active(R1, R2)

Arguments

Value

Calculates the active premium of the portfolio

Examples

premium.active(funds$ret1, funds$rfr)

Information Ratio

Description

Calculates the information ratio of the portfolio

Usage

ratio.information(R1, R2)

Arguments

Details

The information ratio (IR) is a measurement of portfolio returns beyond the returns of a benchmark, usually an index, compared to the volatility of those returns.

Value

Calculates the information ratio of the portfolio

Examples

ratio.information(funds$ret1, funds$rfr)

Sharpe Ratio

Description

Calculates the Sharpe Ratio of the Portfolio

Usage

ratio.sharpe(R1, Rf = 0)

Arguments

Details

The Sharpe ratio was developed by Nobel laureate William F. Sharpe and is used to help investors understand the return of an investment compared to its risk.

Value

Calculates the Sharpe Ratio of the portfolio

Sortino Ratio

Description

Calculates the Sortino Ratio

Usage

ratio.sortino(R1, Rf = 0)

Arguments

Details

The Sortino ratio is a variation of the Sharpe ratio that differentiates harmful volatility from total overall volatility by using the asset's standard deviation of negative portfolio returns, called downside deviation, instead of the total standard deviation of portfolio returns.

Value

Gives the Sortino ratio of the portfolio

Examples

ratio.sortino(funds$ret)

Treynor Ratio

Description

Calculates the Treynor ratio of a particular portfolio

Usage

ratio.treynor(R1, Rf = 0)

Arguments

Details

The Treynor ratio, also known as the reward-to-volatility ratio, is a performance metric for determining how much excess return was generated for each unit of risk taken on by a portfolio.

Value

This function can be used to calculate the Treynor ratio of a portfolio.

Examples

ratio.treynor(funds$ret1)

Annualized Returns

Description

Returns the annualized returns of a data returns data

Usage

returns.cal(R1, freq = 252, geometric = TRUE)

Arguments

Details

An annualized total return is the geometric average amount of money earned by an investment each year over a given time period.

Value

Gives annualized returns of data

Examples

returns.cal(funds$ret1)

Risk Premium of a Security

Description

This function is used to calculate the risk premium of excess return over the risk free rate

Usage

risk.premium(R1, Rf)

Arguments

Details

A risk premium is the return in excess of the risk-free rate of return an investment is expected to yield

Value

Returns the risk premium of the security

Examples

risk.premium(funds$ret1, funds$rfr)

Semi Deviation/ Down side Deviation

Description

Calculates the semi deviation of the xts object

Usage

semi.deviation(R1)

Arguments

Details

Semi-deviation is a method of measuring the below-mean fluctuations in the returns on investment.

Value

Calculates the semi deviation of the xts object

Examples

 semi.deviation(funds$ret1)

Tracking Error

Description

Calculates the Tracking Error

Usage

tracking.error(R1, R2)

Arguments

Details

Tracking error is the divergence between the price behavior of a position or a portfolio and the price behavior of a benchmark.

Value

Calculates the Tracking error of the security

Examples

tracking.error(funds$ret1, funds$rfr)