Questions tagged [pca]
The pca tag has no usage guidance.
0
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1answer
96 views
Interpretation of PCA for commodity futures
I've done some PCA analysis of a portfolio consisting of futures on certain commodities. However, I am unsure of how to interpret the output as most of the information found online deals with fixed ...
-1
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2answers
207 views
Why is my Covariance matrix not positive definite?
I'm trying to do PCA on historic forward rates. I'm using forward rates from the Bank of England going from Jan 2015 through end of May 2018. I calculate the differences in the rates from one day to ...
1
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2answers
249 views
Principal component analysis for yield curve
I have Treasury yield data across 11 maturities for past 1 year. I have used a code in MATLAB for PCA on change in yield curve. Now, I have covariance matrix of daily/monthly yield curve changes, ...
2
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0answers
71 views
Using PCA to identify proxies for highly illiquid assets?
Was wondering if anyone had any literature to share on the use of PCA to identify proxies for highly illiquid assets?
Say for example I have sold an option on stock A, an index constituent, and would ...
2
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1answer
273 views
Constructing a stock market index using PCA
Let's say that I've got a final component and its score derived from n number of stock returns (time-series data). I want to construct a stock market index using this component (having negative and ...
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0answers
58 views
PCA Variance Explained on Out-of-sample Data
Currently doing some PCA analysis on yield curves. In order to test the stability of the eigenvectors, would like to train my model over a window of time (ex: 2002-2007) and then calculate the ...
1
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1answer
253 views
Using PCA to predict Stock Prices
I would like to model an index e.g. FTSE 100. I have a list of all companies that make up the index and their stock values (daily high, low, volume, close values). In total, this time series data has ...
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0answers
148 views
log return or simple return in PCA(statistical factor) analysis?
What are pros and cons of using simple versus log returns in PCA?
0
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1answer
180 views
PRIIP Category 3 Curves
Good evening,
I've tried searching similar posts, but most are unanswered or in a more advanced step than what I'm trying to achieve.
I've managed to do the boostrap method for spot prices ...
1
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0answers
408 views
PRIIPs category 3 curve dependent products (PCA)
My question is regarding the PRIIPs regulation, specificaly about category 3 products that depend on yield curves and require PCA. The product in question is index-linked product, which means that the ...
1
vote
1answer
292 views
principal component analysis on non stationary data
I read that since stock prices are non-stationary it does not make sense to take their covariance. So I took the log returns of stocks, computed covariance matrix, took the top few eigen vectors that ...
2
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0answers
47 views
Covariance Matrix: Calculating Error [duplicate]
I have a sample covariance matrix that is non positive-semi definite (due to missing data points). I am looking at a number of techniques to 'fix' my covariance matrix and make it positive semi-...
0
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1answer
190 views
Portfolio Optimisation/Covariance Estimation on a large scale
When using Markowitz Portfolio Theory, e.g. for finding an optimal portfolio composition, one needs to have estimates of the returns, but most importantly of the covariance matrix. If our universe of ...
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1answer
472 views
Forecasting next day return of a stock using PCA of index constituents
I am trying to predict the return of BN4.SI ( a singapore stock ) and part of Strait Times 30 component index using principal component Analysis. I have written my code in python.
My Question is i ...
0
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1answer
404 views
KID PRIIPS regulation: PCA
According to KID/PRIIPS regulation in your opinion
in which case should PCA (as from article 23) be used?
Just for structured products and bond-related products or also in other cases?
Do you have ...
3
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0answers
57 views
Reduced rank / matrix factorisation techniques and their uses in portfolio optimisation?
I am interested in reduced rank / matrix factorisation techniques and their uses across finance and portfolio optimisation. For example, PCA might be used to reduce the number of components you are ...
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0answers
85 views
PCA and constructing an index
Given a set of correlated securities and their corresponding closing prices, I am looking for a way to construct an index of these securities.
When applying PCA to obtain the principal components, ...
3
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0answers
83 views
Why Regression should only be done on Non-Stationary data points?
I am working through a course on PCA and Factor analysis, where the example is to perform regression on stock prices, with an objective to predict the stock prices.
The author claims, that we need to ...
0
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1answer
532 views
Applications of PCA to yield curve analysis
One of the applications of Principal Component Analysis in Finance is to analyse the shape of the yield curve.
But what conclusions can be drawn exactly from performing this exercise? Does it help us ...
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0answers
56 views
PCA: FTSE100 or any other index
I am relatively new and want to do a Principle Component Analysis (PCA) of the FTSE100 or any other index. What's the best way to downloaded the constituent parts of the index so that I can perform a ...
0
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1answer
94 views
Low-rank approximation techniques for portfolio optimisation
I am trying to understand how low-rank approximation techniques such as PCA, factor analysis, total least squares, orthogonal regression, etc could be used in portfolio optimisation. Say I have a ...
0
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1answer
104 views
Yield curve PCA vs real life frequency
The yield curve can be explained using a PCA, where the cumulative proportion explained for many practical purposes is high enough with three factors.
For one set of data, used at https://www.r-...
2
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0answers
51 views
What is special about covariance estimation from statistical factor models?
If you were to compare the usual sample covariance estimate to a robust covariance estimate (such as MCD), you can say that the robust estimate is more tolerant to outliers in the data and will not be ...
1
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1answer
63 views
How do I test if my betas form a co-integrated vector?
I have identified a model using principal component regression where $Y_t$ is explained by 4 factors such as:
$$Y_t = \beta_1 X_{1t} + \beta_2 X_{2t} + \beta_3 X_{3t} + \beta_4 X_{4t} + \epsilon_t$$
...
4
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1answer
217 views
Interpreting Eigenvalues of Co-variance Matrix
Im working on market reaction to events and I'm using the co-variance matrix to do this. In this paper the author writes
It has been known for some time that the largest eigenvalue (λ1) contains ...
4
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0answers
143 views
VAR FPCA analysis paper replication
I've been trying to replicate the following publication: CONSISTENT FUNCTIONAL PCA FOR FINANCIAL TIME-SERIES, Sebastian Jaimungal, Eddie K. H. Ng, 2007
but I havent been able to get the same results ...
5
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2answers
390 views
PCA for stand alone equity VaR
I am trying to compute equity VaR, forex VaR and total VaR on an international portfolio (10 stocks x 4 countries). Since I am not interested in the risk disaggregation among diffrent countries I was ...
4
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0answers
131 views
Interplay of statistical factors (PCA) and market factors (value, momentum, low vol, …)
Is there any research done on the interplay between statistical factors (as a result of principle component analysis PCA) and the market factors (especially value, size, low vol, momentum, quality)?
...
0
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1answer
595 views
Calculating PCA hedge ratio for 3-leg spread
I'm wondering how can I find PCA hedge ratio for a 3-leg spread? I've taken the simple steps laid out in here.
I've taken some treasury futures data for 2yr,5yr,10yr and ran the PCA. The first ...
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4answers
1k views
Hedge Fund risk management on a daily basis
Since Hedge Funds/Fund of Funds report on a monthly basis usually within 10 days after the month end, monitoring and managing (hedging) potential risks is quite a difficult task. Having done some ...
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1answer
129 views
Rebucketing Risk using PCA/other methods
was working on a project and could use some help. New to the community and looking fwd to being an active part of it.
My question is, let's say we have a vector of securities V, and it trades with ...
3
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1answer
588 views
Weights Blowing up in PCA
I'm using daily settlement data to get yield levels for a couple of products. From this data I am doing PCA on a rolling collection of the yield levels. I have been using sci-kit learn's PCA function, ...
0
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0answers
40 views
Is there a considered floor for variation the 1st principal component must explain?
I am wondering if there is a considered floor to the percentage variation the 1st principal component must explain in general for PCA - ie. any lower and it is not worth doing PCA at all? Is the floor ...
2
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1answer
267 views
Orthogonal Regression/PCA
I am doing orthogonal regression. My X matrix consists of returns on a broad market index, value index, growth index, a few sectors,.....(my Y is the returns on an equity fund)
I am regressing the Y ...
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2answers
280 views
Reproducing levels when PCA has been done on changes
I want to use PCA for rich/cheap analysis of interest rates. For this I did the PCA on the time series of daily difference in interest rates, which is stationary. I cant do pca on levels, as they are ...
3
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0answers
169 views
Which kind of normalization to prefer before PCA (generic solution for any factor analysis)
I have financial assets with totally different volatilities, thus I must standardize them before PCA, otherwise, assets with high variance may be considered as principle components, which is wrong.
...
1
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1answer
106 views
Why normalize only data for CDSs for PCA?
I'm reading a Credit Suisse Research Report on PCA.
The report says that to preprocess the data, you should "Centre data (and normalize when considering CDS data)."
Why would you only normalize ...
11
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1answer
574 views
The danger of using Principal Component Analysis (PCA) in Robust Optimization problems
I have received a reviewer's comment on a paper which applies PCA to reduce the size of a problem and the application is in the robust optimization field. The reviewer implies that "In robust ...
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1answer
704 views
PCA on term structure of interest rates
Interest rate time series seems to be non-stationary whenever test is performed
But covariance or correlation matrix is derived from term structure time series which are non stationary and later PCA ...
4
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2answers
870 views
Factor Model - Minimum Variance Portfolio [Complete Proof]
Can someone check my proof? I think there is something not quite right. I have found limited resources online for this as well so I think it might benefit others to get this on the internet.
Assume ...
4
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1answer
1k views
Statistical arbitrage using eigen portfolios
I was trying to understand below paper
https://www.math.nyu.edu/faculty/avellane/AvellanedaLeeStatArb071108.pdf
Page 20 explains about "Entering a trade". I wan't to know clearly what it means to ...
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0answers
478 views
How to reduce fx currency pairs ? PCA or other tools?
I have 19 currency pairs like USD.AUD, USD.CAD, etc. Also 82 cross currency pairs like AUD.CAD, EUR.AUD,EUR.CAD etc.
When I look to their graphs, most look similar, so I want to reduce number of pair ...
7
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2answers
660 views
Looking for Research Paper on Creation of Currency Baskets
I came across a paper, not sure it originated from academia or a blog or such, that reported on applying principal components to build currency baskets from a set of individual currency pairs and to ...
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2answers
944 views
Some clarifications on eigenvectors and eigenvalues from PCA
Could somebody tell me whether suggestions in bold true or not?
Q # 1: http://www.math.nyu.edu/faculty/avellane/AvellanedaLeeStatArb071108.pdf
...
0
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1answer
287 views
How to get permanently growing chart within PCA
I looked onto different questions and answers about application of PCA on this site and found this interesting article :
http://systematicedge.wordpress.com/2013/06/02/principal-component-analysis-in-...
2
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1answer
1k views
What is PCA and how does it relate to eigenvectors and eigenvalues?
What are the principal components? How they are calculated? What is their relationship with eigenvalues and eigenvectors? This is a lead-in question to explain PCA basics.
EDIT: PCA is implemented ...
3
votes
1answer
193 views
After PCA on original factors, how to tell which original factors are dominant?
When doing the PCA analysis, you end up with eigenvalues which are ordered by how much variance they explained for each eigenvector. Say, the eigenvectors since they are orthogonal, do not represent ...
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2answers
1k views
Non-negative matrix factorization for factor analysis of stocks
I stumbled over the term Non-negative matrix factorization in presentations such as Application of Machine Learning to Finance and this Big Data in Asset Management.
The basic idea is to decompose a ...
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1answer
631 views
Calculating Variance Explained from PCA Loadings
I have a return history for a universe of risky assets and I've run a principal component algorithm and obtained a loadings matrix (num_factors by num_assets) for the first 5 factors.
I have a ...
0
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1answer
119 views
Can we model components in a set of multivariate multi-period time-series data?
There are N data sets in periods occurring weekly/monthly, across a 10-year historical timeline.
In each period, five dates are observed (labelled a to e), where a denotes the day the period starts/...
