Questions tagged [bayes-theory]

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151 views

Bayesian analysis in R for low default portfolios

I want to apply the knowledge of this paper (Bayesian estimation of probabilities of default for low default portfolios, by Dirk Tasche) in R, but I can't find the right bayesian package and functions ...
6
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0answers
158 views

Let $\mathbb{P} \sim \mathbb{Q} \sim \mathbb{R}$ be equivalent probability measures on some measurable space

Let $\mathbb{P} \sim \mathbb{Q} \sim \mathbb{R}$ be equivalent probability measures on some measurable space $(\Omega, \mathcal{F})$, and let $\mathcal{G} \subset \mathcal{F}$ be a sub- $\sigma$-...
2
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0answers
89 views

A Bayesian-Stein based expected return estimator by J.P. Morgan

Please consider the following estimator for the expected returns specified in the paper "Improving on risk parity: Hedging forecast uncertainty" by Peter Rappoport, J.P. Morgan, October 2012....
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0answers
20 views

Which scikit learn module to use for bayesian nonlinear regression?

I have a nonlinear dataset and I am using GradientBoostingRegressor from scikit-learn. It gives me an r2 score of 96.9 after hyperparameter tuning. I want to use a bayesian model for this nonlinear ...
2
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1answer
824 views

PD calibration using Bayes formula

When calculating ECLs for loans under IFRS 9, one of the requirements is that the PD estimates have to be Point-in-time ($PD_{PIT}$) rather than through-the-cycle ($PD_{TTC}$).The setting is as ...
1
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0answers
47 views

Kalman Filtering theory and application in Finance models under asymmetric or incomplete information

Why do we need Kalman Filtering theory in dynamic models in finance when we consider an environment of asymmetric or incomplete information? I understand that this has to do with the update of the ...
2
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0answers
259 views

James-Stein estimator for superior estimates of returns in m.v. portfolio optimization

I am currently learning about statistical techniques to enhance the estimation of input parameters in a m.v. optimization. Specifically I have some doubts about the James-Stein estimator applied as an ...
1
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1answer
322 views

Can someone explain the particle filter algorithm in detail with intuition

I am trying to understand particle filters and their application but i am not able to understand the underlying methodology. I have read a few sources but either the language is not clear or they dive ...
1
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0answers
237 views

Normal default probability vs forward default probability/conditional default

is the diagram correct in calculating foward PD(conditional default) ? Or should the formula be Probability of default = probability of survival x forward PD Which of this is equal to marginal PD(...
1
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1answer
61 views

Rationale for likelihood function parameter choice in Black-Litterman model?

So we are interested in a PDF for equilibrium returns given the views. Why do we choose our view means as the mean parameter and observed market covariance as the covariance parameter? Seems a bit ...
0
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1answer
257 views

Bayesian trade probability with factors

I have a strategy Y which is influenced by some factors X1, ..., Xn (for example asset volatility, distribution of macroeconomic factors). At moment t0 I have historical distribution(prior) of X1, ...,...
1
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1answer
67 views

Knightian Uncertainty Iff Bayesian Probabilistic View Point

If an investor operates under knightian uncertainty, does that investor then have a Bayesian viewpoint on probability implicitly, and vice versa? Has this been answered or do I have a poor ...
5
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0answers
321 views

Bayesian strategy selection

I have N strategies/signals that I would like to allocate to. I want to estimate an estimate of future performance based off of recent realized performance (momentum of strategies per se - e.g. ...
2
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0answers
379 views

Bayesian analysis in R: Probability of default, low default portfolios

I want to apply the knowledge of this paper (Bayesian estimation of probabilities of default for low default portfolios, by Dirk Tasche) in R, but I can't find the right bayesian package and functions ...
2
votes
1answer
101 views

Critical Appraisal of Approaches countering Parameter Uncertainty in Portfolio Optimization

It is very hard to come up with legit and solid advantages and drawbacks of the various approaches wich are trying to counteract parameter uncertainty in portfolio optimization procedures. In my ...
2
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0answers
175 views

Bayesian logit model in Psychometric or Behavioural Testing for Credit Scoring in Developing Countries

A lot of parameters in one title, I know. So there's credit scoring but not using credit history. Then there's using a Bayesian logit model. Then there's doing so in a developing country such as Haiti ...
2
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0answers
204 views

Identifiability of a state space model (Dynamic Linear Model)

Take a general linear Gaussian state space model (SSM)(aka Dynamic Linear Model DLM): $X_{t+1}=FX_t + V_t$ $Y=HX_t+W_t$ $V_t \sim N(0,Q)$ $W_t \sim N(0,R)$ I am interested in the ...
2
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1answer
773 views

Why model the variance-covariance matrix as an inverse-Wishart distribution in bayesian portfolio analysis?

I am following Risk and asset allocation (Attilio Meucci,2007). I must say I am enjoying this reading quite a lot so I hope nobody takes my question as a critique on the text. When we are introduced ...
2
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1answer
571 views

Is an arbitrary prior for Black-Litterman valid? Or do we need a market implied one?

I went through The Black-Litterman Approach: Original Model and Extensions - see also. The BL approeach starts with a prior on the expected returns vector derived from the hypothesis that the market ...