drawFigure | R Documentation |

Plots the efficient frontiers of risky investments and all investments. The optimum points corresponding to the risk aversion coefficient are indicated by dots. Further, the function plots a predictive return distribution figure.

```
drawFigure(symbol, yield, vol, beta, r = 1,
total = 1, indexVol = 20, nStocks = 7, balanceInt = 12, A = 10,
riskfree = FALSE, bor = FALSE)
```

`symbol` |
character vector of the symbols of the risky investments |

`yield` |
vector of yields (%) |

`vol` |
vector of volatilities (%) |

`beta` |
vector of betas (%) |

`r` |
risk-free interest rate (%) |

`total` |
total investment (for example in euros) |

`indexVol` |
volatility of market portfolio (%) |

`nStocks` |
number of risky investments in the portfolio |

`balanceInt` |
balancing interval of the portfolio in months |

`A` |
risk aversion coefficient (see details) |

`riskfree` |
is risk-free investment included in the portfolio (logical) |

`bor` |
is borrowing (negative risk-free investment) allowed (logical) |

The function uses the single-index model and Markovitz portfolio optimization model to find the optimum risky portfolio. The returns are assumed to be log-normally distributed. The maximized function is mu - 0.5*A*var where mu is expected return, A is risk aversion coefficient, and var is return variance.

`portfolio` |
allocation of the total investment (in euros) |

`returnExpectation` |
expected portfolio return |

`returnDeviation` |
standard deviation of the portfolio |

Arto Luoma <arto.luoma@wippies.com>

Bodie, Kane, and Marcus (2014) *Investments, 10th Global Edition*, McGraw-Hill Education, (see Section 7.4 The Markowitz Portfolio Optimization Model and Section 8.2 The Single-Index Model).

`portfOptim`

```
data(stockData, package="RcmdrPlugin.RiskDemo")
with(stockData,drawFigure(symbol=rownames(stockData),yield=divYield,
vol=vol,beta=beta,r=1,total=100,indexVol=10,
nStocks=5,balanceInt=12,A=10,riskfree=TRUE,bor=FALSE))
```

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