Questions tagged [pca]
The pca tag has no usage guidance.
121
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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,...
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48
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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 ...
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128
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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 ...
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156
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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 ...
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23
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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 ...
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58
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PCA 'unnormalize' weights
When computing a PCA on several prices, we usually normalize them first.
Let's say I got the weights (eigenvectors) for the PC5. This weights are made from normalized prices.
If I believe PC5 is too ...
6
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680
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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.
...
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597
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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 ...
- 207
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62
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Implied Volatility Surface Interpolation for fixed moneyness and maturity on each day of the calendar
I'm new to quantitative finance and interested in performing a PCA on the implied volatility surface. However, my dataset displays certain point changes over time. As a result, I need to interpolate ...
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165
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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 ...
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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 ...
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383
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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 ...
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62
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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 ...
- 21
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550
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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?
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137
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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 ...
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724
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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 ...
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449
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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 ...
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206
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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 ...
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112
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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 ...
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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. ...
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568
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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 ...
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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 ...
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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 ...
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112
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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 ...
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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 ...
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2
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191
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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 ...
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183
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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 ...
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276
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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 ...
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81
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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 ...
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88
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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 ...
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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 ...
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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 ...
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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 ...
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462
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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1k
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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 ...
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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 ...
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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 ...
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pca for yield curve
I used Principe component analysis on yield curve data
this was the result
...
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161
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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 ...
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299
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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.
...
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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 ...
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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 ...
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PCA predicted yield curve moves do not match (closely) realized yield curve moves
I have a need to set-up a methodology to decompose the x-day yield curve moves into its underlying (3) PCAs.
Specifically, for an example, to generate the 1-day moves in the EUR-swap yield curve; ...
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298
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stress testing zero coupon yield curve
i'm currently trying to stress test the zero coupon yield curve using daily observations from 2003 to 2019.
Each Zero coupon yield curve originate from an actuarial curve with 37 tenors that range ...
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2k
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PCA for Risk bucketing
I'm working on a project to justify the use the certain tenors (2y, 5y, 10y, 30y) for risk bucketing. I'm a little stuck after calculating the principal components. Just to describe my approach-
a) ...
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525
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How to interpret DV01 in terms of PCA equivalent?
I have computed the PCs for daily changes in the UST yield curve over the last 5 years using the covariance matrix and can explain 94% of the variance using the first two components, which is good ...
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