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Conducting PCA on features of dataset

To preface, I am very new to quantitative finance and nowhere near the point of actually trading so forgive me if this question is trivial to most of you. I am making a basic k-means clustering ...
Dylan McClish's user avatar
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0 answers
34 views

Price display of weighted spreads via PCA and value changed

Using PCA I have the below PC1, first component weights, for 4 quarterly expiries of short term interest rate future. These are hypothetical values used to help my question. March: 0.005542604, June: ...
ChairmanMeow's user avatar
2 votes
3 answers
339 views

Does PCA for yield curve has any tangible value?

I am aware of an abundant literature on Principal Component Analysis (PCA) application for yield curves. All of these papers to me look merely a statistics-oriented results. Most of the papers argue ...
Sane's user avatar
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0 votes
1 answer
119 views

PCA factors not uncorrelated

I ran into an interesting case recently. I am trying to construct a set of uncorrelated factors for a statistical factor model. I have started with picking a certain amount of assets (indices) which I ...
Georgi B's user avatar
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0 answers
45 views

Scaling returns to use PCA?

Many machine learning techniques perform better, if the data is preprocessed - either by normalization (MaxMin Scaler) or standardization (Standard Scaler). But that comes with a lack of ...
Marlon Brando's user avatar
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0 answers
46 views

PCA and OLS regression to transform to interest rate risk? [duplicate]

I’ve been working on different interest rate risk transformation methods for swaps and was interested in implementing PCA & OLS regression. I’m looking to bucket my exposure in all tenors to ...
gardensnake's user avatar
0 votes
1 answer
125 views

When you have negative weights in the context of portfolio construction, what is the correct way normalize them?

For context, I am building an eigenportfolio following the conventions of Avellaneda and Lee Statistical Arbitrage in the U.S. Equities Market (2008), and I get negative weights for eigenportfolios 2,...
Kenfisherman's user avatar
0 votes
0 answers
94 views

Dimension reduction of par risk strips

I saw some threads about reducing dimensionality of IR risk strips, e.g. PCA and risk bucketing. However, I did not find a satisfying answer to that yet. Therefore, I decided to formulate a similar ...
SI7's user avatar
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1 vote
1 answer
346 views

PCA for portfolio optimization (Markowitz)

Suppose that I've used the spectral theorem of linear algebra to completely decompose the covariance matrix. I now know the largest and smallest eigenvalue, which corresponds to the largest and ...
Marlon Brando's user avatar
2 votes
1 answer
436 views

Can PCA be used to transform a ladder of interest rate risk?

The context For traders/market makers on interest rate swaps desks, it is essential to have a model that transforms risk from its most complex representation (i.e. a ladder of every tenor) into a less ...
quanty's user avatar
  • 439
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0 answers
29 views

PRIIPs Regulation: Adjustments required by curve methodology

I am currently looking at a structured product whose payoff depends on EURIBOR1Y and the associated requirements for PRIIPs computations. More precisely the regulation says the following: The ...
RDA's user avatar
  • 36
6 votes
1 answer
859 views

Markowitz Eigenvalues & PCA

I came across this passage in a book about PCA and denoising of Markowitz: But eigenvalues that are important from risk perspective are least important ones from portfolio optimization perspective. ...
Markowitz's user avatar
6 votes
1 answer
739 views

What is the textbook answer to dealing with multicollinearity?

I have recently struggled in interviews, for two quantitative trading positions, by producing weak answers to effectively the same (fairly basic) question. I would like to understand, from a quant ...
Zac's user avatar
  • 207
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0 answers
287 views

PCA on levels or returns, and standardized or not?

When you run PCA on some financial assets, let’s say stocks, do you calculate covariance on levels, standardized levels, returns or standardized returns? I’ve seen several papers and posts that ...
Nick's user avatar
  • 13
0 votes
1 answer
212 views

Why cant I use PCA to find all stock factors? [closed]

Why cant I run all the stocks in the stock market thru a PCA model, and use the resulting principal components to create a factor model to price stocks and then buy stocks under priced and short ...
Matthias Tom's user avatar
-1 votes
1 answer
529 views

Yield curve PCA: levels or daily moves?

I have tried using both yield curve levels as well as daily moves (absolute change) while doing PCA. Using both types of input/dataset gives me roughly the same shape in terms of principal components ...
abckk's user avatar
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0 answers
78 views

FX weights and P&L

How to correctly express basket of currencies in and index, such that P&L would align? Assume our index is 20% EURUSD and 80% GBPUSD and rates are 1.10 and 1.31 for T1 and 1.05 and 1.35 for T2. On ...
John's user avatar
  • 21
0 votes
1 answer
758 views

Principal component analysis on a yield curve

When conducting principal component analysis on the yield curve, PC1 = constant (level shift), PC2 = Slope, PC3 = Curvature. How do you interpret PC>3, e.g. PC 4?
One Pablo's user avatar
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0 answers
171 views

PCA on portfolio depending on multiple time series

There is extensive documentation about PCA on specific time series (for example the UK yield curve). When you have a portfolio which only depends on the change of the UK yield curve then a PCA on the ...
Oamriotn's user avatar
  • 355
2 votes
3 answers
965 views

Attribute P&L to PCA vectors (swaps)

I have a daily US swaps data here for 2020 https://easyupload.io/yh4rnd . I have run PCA on standardized data and got PCA matrix (and basic statistics): I also have such hypothetical portfolio that ...
John's user avatar
  • 21
0 votes
1 answer
594 views

Principal Component Analysis for attributing yield curve changes

I have calculated the Principal components using daily yield curve changes. After calculating these components, i noticed that 98% of the return can be attributed to the first 3 components. How do i ...
One Pablo's user avatar
2 votes
2 answers
260 views

PCA analysis within Private Credit

A very broad question but nevertheless a important and difficult one. Within private markets (Private Equity funds, infrastructure funds and private credit funds) how should one do a risk-based PCA ...
Jeweller89's user avatar
1 vote
0 answers
127 views

factor hedging erodes portfolio alpha

I am hedging a long-short equity portfolio for statistical factors, and finding an improvement in sharpe but not surprisingly an erosion of portfolio alpha (ex ante and ex post). No one factor is ...
Henry's user avatar
  • 111
4 votes
0 answers
121 views

Implementing Hierarchical PCA for financial time series in R

I would like to implement the method "Hierarchical PCA", as described in the following paper and compare it to a "standard" PCA. I like to do this in R AVELLANEDA, Marco. ...
ds_col's user avatar
  • 61
2 votes
1 answer
728 views

How to extract normalised portfolio weights from PCA, when the eigenvector has negative elements?

Most of the examples of using PCA of asset returns to construct an eigen portfolio seem to tend to focus on equities, which tend to all be positively correlated. As such I usually see normalised (such ...
rwb's user avatar
  • 123
0 votes
0 answers
258 views

Terminology - are each of the eigenvectors of a PCA themselves called an "eigen portfolio"

Sorry, I suspect this is rather trivial but just want to confirm that, given a portfolio constructed of n assets, each of the n ...
rwb's user avatar
  • 123
1 vote
0 answers
88 views

How to extract informative value from correlations of assets? Subadditivity of correlation calculation an issue

I was reading Nassim Taleb's Paper: Fooled by Correlation and found it very informative. I had always struggled with finding value in correlation in Finance, especially seeing a lot of bad ...
Kareem Sayed's user avatar
1 vote
0 answers
147 views

How to use PCA to find best portfolio replication

I have an exposure to 3 products. I have another 12 tradable products that I can use for hedging myself. I have the correlation matrix between the 15 (12+3) products. How can I use PCA to find the ...
akasolace's user avatar
  • 151
0 votes
0 answers
85 views

Choose the best combination of 5 stocks from 15 stocks using PCA

I am working on a project to choose the perfect combination of 5 stocks from a total of 15 stocks to get the "highest gains". Here's the approach I plan to use. Run a loop for all ...
atastix's user avatar
  • 85
1 vote
2 answers
210 views

Pca on multidimensional data

My data has stock returns over n periods for x stocks and m factor exposures for each stock ( ex: value, momentum) for n periods(output of regressions ) . Can I club this data together and then ...
qfd's user avatar
  • 255
0 votes
1 answer
252 views

PCA on returns gives negative loadings on market short

I have run a PCA on some returns to get a set of factors. All is good except that the first PC seems to be the short of the market, it has a correlation of -0.9 with the S&P500 but all the ...
Simon Nicholls's user avatar
1 vote
1 answer
311 views

PCA and K-means clustering on returns

I am running a PCA on a set of returns and I would like to cluster the results of the output to group stocks that have similar factor exposures. However when I run the PCA on the covariance of the ...
Simon Nicholls's user avatar
0 votes
0 answers
90 views

First Principal Component Large Volatility

I am conducting PCA on several return series of funds and am finding that when I look at the first principal component the values are huge and this the volatility is also enormous relative to the ...
Simon Nicholls's user avatar
1 vote
0 answers
96 views

PCA on covariance matrix with weights on the columns?

I'm reading two papers by Mark Kritzman on two indicators (turbulence proxied by the Mahalanobis distance and absorption ratio which is basically the ratio of the variance captured by the top 20% PCA ...
Bach Pham's user avatar
1 vote
1 answer
2k views

Factor investing and PCA

I'm struggling to understand how Principal Component Analysis (PCA) is used in Factor Models of returns. For example, in the JPMorgan paper (p.19) the authors write: In a multi asset portfolio, factor ...
Qwerty's user avatar
  • 179
-1 votes
1 answer
407 views

Why is PCA/ML not used frequently in trading?

I'm curious why things like PCA/ML aren't use frequently in trading? Is there an underlying philosophy that prevent this? What I was thinking, was that if PCA worked for making money, then everyone ...
James Lanny's user avatar
1 vote
0 answers
51 views

Some questions to canonical correlations between principle components and asset pricing factors using R

I have done a asympotical principle component analysis (APCA), using eigen() in R, of the covariance matrix of a global dataset of excess returns. I took the ...
YemenBlues's user avatar
3 votes
1 answer
496 views

how to construct a diversified portfolio based on correlation

I have a porfolio of indexes and I built up a python model based on spearman correlation (I used a spearman and not a pearson because, after running some test on outliers and normality ...
Luigi87's user avatar
  • 326
1 vote
0 answers
109 views

Why doesn't the first principal component maximize the standard deviation of returns

I am trying to apply PCA to portfolio of securities. My understanding is that the first principal component can be used to evaluate weights for portfolio of maximum variance and each next principal ...
mfolusiak's user avatar
3 votes
1 answer
1k views

Bond Hedging: PCA and regression based hedge ratios

This is my first question and I would very much appreciate any help. For a project I am trying to compare different hedging techniques for hedging a long portfolio of bonds. I have a history of ...
ratesandslates's user avatar
2 votes
0 answers
114 views

machine-learning method to predict PCA weights

I have been using certain linear-regression to extract the PCA (top 3) weights relating to a certain data-set. I was wondering, instead of using linear-regression to generate the weights, I can use ...
Kiann's user avatar
  • 622
3 votes
1 answer
3k views

Hedging a trade for PCA component neutrality

Suppose I am given a set of financial instruments, e.g. {1Y, 2Y, ..., 30Y} interest rate swaps or {Barclays, Lloyds, .. } FTSE100 companies. It doesn't matter which so let's go with IRS. I have ...
Attack68's user avatar
  • 10.8k
3 votes
2 answers
2k views

PCA and risk bucketing

I have a portfolio of bonds and I have calculated their PV01 per risk bucket. The relevant buckets are 1m,2m,...,1y,2y,...30y; a total of 40 buckets. I also run a PCA and have identified the three ...
tgeorge's user avatar
  • 41
0 votes
1 answer
313 views

INTERPRETING PCA ANALYSIS

I am having little trouble figuring our which variables are the most important when I am using PCA . What I am trying to do is see which variables explain the most variance when it comes to stock ...
Pelumi's user avatar
  • 339
0 votes
1 answer
309 views

PCA FOR STOCK PICKING

lets say I am an equity analyst and I want to figure out what fundamental metrics I should use when I am analyzing an industry , I can use pca on a bunch of stocks in an industry using their ...
Pelumi's user avatar
  • 339
1 vote
0 answers
252 views

pca for yield curve

I used Principe component analysis on yield curve data this was the result ...
Pelumi's user avatar
  • 339
1 vote
1 answer
172 views

PCA in PRIIPs regulation for simple floating interest rate

From the Q&A on the PRIIPs KID: 4. The principal component analysis of Annex II, Point 23 ensures the consistent simulation of curves. Is it mandatory to use this method also for PRIIPs that ...
Amaterasu's user avatar
  • 151
2 votes
1 answer
316 views

PCA on a portfolio of spot and forward contracts

I have a portfolio of spot and FX forwards on various currencies all based to AUD. I need to able to quantify how the changes in amount, tilt and curvature of the AUD curve would impact my p/l. ...
RamRam's user avatar
  • 61
5 votes
3 answers
343 views

PCA: How to select a smaller set of the original features that best represent first PC with minimal contribution to the other PCs

I have performed PCA on a covariance matrix. I have 24 original features and subject to some constraints over which features are used i would like to chose the combination of features that best ...
Joel's user avatar
  • 51
1 vote
0 answers
96 views

Predicting stock returns using principal components of macroeconomic variables

I'm trying to detect return predictability by regressing stock returns on the first couple of principal components of a set of macroeconomic variables. I'm doing this for different stock styles such ...
Louis's user avatar
  • 11