In its most recent statement the FOMC stated “Inflation is anticipated to remain near its recent low level in the near term, but the Committee expects inflation to rise gradually toward 2 percent over the medium term as the labor market improves further and the transitory effects of earlier declines in energy and import prices … More On Inflation
In our previous post we showed a simplistic implementation of a logistic regression model in excel. In practice we need to be able to estimate a multivariate version of the model and also asses the quality of the model calibration. All the requirements make a spreadsheet implementation impractical and we need to rely on VBA. … More Logistic Regression in VBA
A logit model is a type of a binary choice model. We use a logistic equation to assign a probability to an event. We define a logistic cumulative density function as: which is equivalent to Another property of the logistic function is that: The first derivative of the logistic function, which we will need when … More Logistic Regression in Excel
In previous post we showed a method of how to test for statistically significant seasonality in Excel. We also mentioned that the dummy regression approach can be applied to test other hypothesis. In this post we will use a similar approach to test for statistically different returns in selected securities conditional on the global business … More Global Business Cycles and FX Returns
A favourite Bloomberg function on the sell side seems to be SEAG . This function shows seasonality for a selected security and is popular among sales desks, particularly in quiet markets. Below is an example of the function for EURUSD 1year ATM volatility over the past 10 years. It is apparent that January tends to … More Testing for Seasonality In Excel
Today’s post is a second in a planned series about the use of Principal Component Analysis (PCA) to manage risk and trade. In a previous post we tried to provide an intuitive explanation behind the method and a way to implement PCA in excel using a free addin. Today we want to show a PCA … More Principal Component Analysis ~ PART II
We decided to write a series of posts on a very useful statistical technique called Principal Component Analysis (PCA). In the current post we give a brief explanation of the technique and its implementation in excel. In practice it is less important to know the computations behind PCA than it is to understand the intuition … More Principal Component Analysis in Excel ~ PART I
Granger causality is a simple formulation to test if preceding values of a variable X help explain some of the variance observed in variable Y. To test for this we first need to regress Y on past value of itself to capture any autoregressive features. Typical set up of the test sets up below equation: … More Granger Causality in Excel
Hodrick Prescott (HP) filter is a method to decompose a time series into two components, a long-term trend and a residual. The residual is interpreted as a cyclical component. The formula is as follows: where y is the time series we are considering and g is the growth rate, while c is the cyclical part … More Hodrick Prescott Filter in Excel
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