Welcome to QFA: Online Quantitative


Excel chart using pictures [0.00]

Posted on May 19, 2016, 10:08 p.m. by Welcome to QFA: Online Quantitative @ [source]


Risk Measurement.

Given a vector of P/L, there can be various risk measures.

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The simplest way to handle dynamic ranges of chart data is to convert the data into Excel Table as explained in following steps.

Select the data and press Ctrl + T Excel will display the selected range, which you can change.

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Creation of heatmaps in R [0.22]

Posted on May 12, 2016, 2:39 a.m. by Welcome to QFA: Online Quantitative @ [source]

In exploratory data analysis, we often need to visualize our data in different formats, in order to gain more understanding about the numbers and the relationship between the parameters.

For this, we need to download financial market data for these stocks from Yahoo.

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The eventful day was marked the 7th of March, 2016, one of the biggest changes was orchestrated in the gateway to professional Actuarial exams: ACET (Actuarial Common Entrance Test).

The number of sittings remain two, though the exam will now be conducted in planned months May and November , instead of June and December, respectively.

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As can be seen, oil prices (Brent) have fallen consistently by about 50% over the past year[1]. IMF advises that oil prices should be treated as permanently on low levels by the oil exporters and fiscal adjustments should start following for the medium term to prevent major erosions of their buffers and reserves[2].

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Probability in R [0.00]

Posted on May 9, 2016, 1:51 a.m. by Welcome to QFA: Online Quantitative @ [source]

In this blog Titled “Probability in R” we will not only learn the basic concepts of probability but also how to implement them in R using package ‘prob’.

A lack of pattern in events is called randomness.In reality however, it is difficult to generate or observe truly random patterns,as the human mind tends to overthink and look for patterns in the data.For example, after getting 4 sixes in 4 consecutive rolls of a die,we would think that getting a 6 on the 5th roll of the dice is very unlikely.But,you will note that the probability of getting a 6 remains the same even on the 5th roll and is not dependant on previous rolls of the die.

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Support Vector Machines (SVMs) are a machine learning method that was originally applied to image and text recognition[1], along with classifications [2]. We will look into the use of Support Vector Machines to enable the selection of stocks by separating the “bulls” and the “bears” and also consider using Support Vector Machines Regression, or Support Vector Regression (SVR), for time-series of individual stocks or indexes.

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