Trading Academic: Thomas Cantone, #1

By Thomas Cantone

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• Language: English
• Publisher: Thomas Cantone
• Release date: Nov 23, 2022
• ISBN: 9798215157862

Book preview

Chapter 1

VAR AND CVAR

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Quantifying the danger once we trade became one of the biggest concerns (or at least it should be) as traders. Volatility, volatility of exchange rates, interest rates, and so on. has elaborated that the analysis of the danger is bigger and bigger.

Another key aspect that made it possible to improve the analysis of danger, among those associated with our operations, was the exponential increase in the computing functionality that we currently have. Currently, as a trader, you have at your fingertips, from your laptop or smartphone, databases with all the elementary information of the cost history of almost any financial asset in which you want to trade.

Once we develop a trading plan or system we must not only focus on precisely establishing the rules of access and exit from the market, but we must also objectively examine the results of our trading system.

In order to carry out an objective study, a wide variety of metrics have been developed that evaluate different points of our operations. In this article I am going to teach you how to use 2 metrics based on hazard control: Cost in Danger (VaR) and Cost Conditioned to Danger (CVaR). These measures for the evaluation of the danger have different methodologies and techniques for its estimation.

Before going directly into the analysis of them, it is essential that we are clear about certain basic concepts, such as what is financial danger and what are the types of danger.

1. What is Financial Hazard?

In the investment environment, the danger is the possibility of loss due to events that have the possibility of creating relevant changes and that are affecting a financial asset.

For this reason, it is essential that once we decide to make an investment, we identify and quantify the different types of dangers to which we will be exposed when making the investment.

Each of the investments carries an associated danger, however once we make an optimal performance of the danger we have the possibility of finding gigantic opportunities to obtain significant returns.

Surely you have heard that risk aversion. Aversion to danger is related to an investor's reaction or preference to avoid financial uncertainty or danger. This leads you to invest in safer financial assets, even when they are less profitable.

2. Types of Financial Hazard.

Even though on the investment planet there is a gigantic proportion of dangers, the financial danger we have the possibility of classifying into 3 main categories:

Market danger: refers to the danger of having losses derived from the movements of the costs of a financial asset or the market generally.

Credit danger: the inability of one of the pieces to respond with the obligations of an issue or with the rigorous terms of the same (amount, interest, etc.), resulting in a loss for the counterparty.

Operational hazard: defined as the risk of loss due to inadequacies or failures of processes, personnel, and internal systems.

Now that we have clarified these basic concepts, let's see what everything mentioned about VaR and CVaR is about.

3. Cost in Danger (Value at Risk, VaR).

Cost at Risk is a statistical metric used to assess the danger of a certain position or portfolio of assets. VaR is the maximum expected loss, under normal market conditions, in a portfolio or trading system, with a possibility (usually 1% or 5%) and a known time interval (usually a day, a week or a month) .

The VaR is measured by means of 3 changes: amount of the loss, the possibility of the loss occurring (confidence level) and the time interval of its occurrence.

It is essential to note that VaR does not seek to explain or prophesy worst-case scenarios, but rather seeks to provide a darling from the range of probable gains or losses.

3.1. Ways to calculate VaR.

There are 3 primary methodologies or approaches to calculate VaR:

Parametric procedure: once we calculate the VaR through the parametric procedure, we assume that productivity has a usual distribution and the portfolio is a linear functionality of the components. For the parametric calculation, it is necessary to have the main statistical limits (mean, variances, covariance, standard deviations, etc.) of the financial asset or portfolio that we are analyzing.

The formula for calculating VaR using the parametric procedure is as follows:

VaR = F * S * σ *

Where:

F = Cost defined by the degree of confidence (also known as Z cost).

S = Cost of the portfolio or financial asset at recent market costs.

σ = Standard deviation of asset returns.

t = Time horizon in which the VaR is to be calculated.

Historical simulation procedure: it uses a gigantic proportion of historical data to estimate VaR, however it does not make any assumptions about the distribution of possibility. One of the biggest restrictions of this procedure is that it implies that each of the probable future variations in the costs of the assets has already been seen in the past. The cost of VaR will depend on the origin of the data and the size of the series (time frame of the data).

Cerro Carlo VaR model: VaR calculation using the Monte Carlo procedure is based on creating hundreds or an enormous number of hypothetical scenarios based on the series of initial data entered by the client. The accuracy of the VaR will depend on the number of hypothetical scenarios we simulate, the higher it is, the more accurate it will be. The validation of the model is important, for that it is offered to do backtest tests to check that the valued VaR is verified with the historical series.

3.2. Convenient example of how to calculate VaR.

I'm going to do it by putting an exemplification to calculate in VaR in occupations to simplify calculations of pips and lots:

Suppose we have a portfolio made up of 1000 ABC company occupations and the present cost per share is $ 12, the daily standard deviation is 1.8%. How do we have the possibility of calculating the VaR with a 95% confidence level for one day?

The formula to calculate VaR is:

VaR = F * S * σ *

To calculate the cost of F, we use the inverse standard common distribution function NORM.STAND.INV (probability) from the Excel spreadsheet.

F = NORM.DIST.INV (confidence level) = NORM.DIST.INV (95%) = 1.6448

S is the total cost invested in the portfolio and is calculated as follows:

S = proportion of occupations * market cost = 1,000 activities * $ 12 = $ 12,000

The standard deviation σ is equal to 1.8%.

Since we want to calculate the VaR for one day, then t = 1.

We substitute the values ​​in the VaR formula and we have:

VaR = 1.6448 * $ 12,000 * 1.8% * = $ 355.28

This cost of VaR suggests that the investor has a 95% degree of confidence that his investment will not lose much more than $ 355.28 in one day.What would happen if we increase the confidence level to 99%? In this situation the VaR would be:

VaR = 2.3263 * $ 12,000 * 1.8% * = $ 502.48

This cost of VaR suggests that the investor has a degree of confidence of 99% that his investment will not lose much more than $ 502.48 in one day,