Lisa Ann

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May 16	comment	Exact value of mean reversion rate knowing terminal value of the process Could it be the $\beta$ of a log-regression $x_{t}\sim \log(t)$?
May 11	comment	Parameter estimation of Ornstein–Uhlenbeck and CIR processes @chrisaycock No problem with his correction, that was just my oversight to mix up UO with CIR formula. By the way, I decided to include both in my question :)
May 11	comment	Parameter estimation of Ornstein–Uhlenbeck and CIR processes CIR, you're right.
May 10	comment	RQuantLib, Hoadley and Bloomberg YAS: fixed rate bond pricing differences? But if `issueDate <- effectiveDate <- as.Date('2013-05-03')` how can I evaluate this bond on 10 May 2014? Doesn't `issueDate <- effectiveDate <- as.Date('2013-05-03')` make the pricing on 03 May 2013 instead of 10 May 2014?
May 10	comment	RQuantLib, Hoadley and Bloomberg YAS: fixed rate bond pricing differences? Then, if I understand my mistake, you're telling me I switched `effectiveDate` field with the `issueDate` one: if I wanted to calculate the price of this bond with `RQuantLib` on 10 May 2014 I would have to set `issueDate <- '2014-05-10'` and `effectiveDate <- '2013-05-03'`. Correct?
May 10	comment	RQuantLib, Hoadley and Bloomberg YAS: fixed rate bond pricing differences? Hi Brian B. I've included all data which are needed to price that bond, I do not understand what else could make my question more comprehensible. I could attach `R` code but in fact it is sufficient one to copy each field value in `FixedRateBondPriceByYield()` to get the same result... unless I've made some mistakes, that is quite likely according to the difference with Bloomberg `YAS`.
May 8	comment	How to normalize technical indicators for machine learning? My opinion: PCA over these indicators after having z-scaled observations to make covariance matrix equal to correlation matrix.
May 7	comment	Hedging credit risk using Put equity options Am I the only one who gets 404 - PAGE NOT FOUND when trying to open Biran B's link?
May 2	comment	How to use PCA for trading Let you have a multifactorial model which takes as inputs about 10 ~ 20 exogenous weakly stationary variables. Then you can use PCA to get just 3 ~ 4 orthogonal variables in order to simplify your model without losing too much information (it maybe first 3 ~ 4 principal components explain more than 90% of the 10 ~ 20 original variables' total variance). For instance, technical traders often use lot of t.a. indicators, such as MACD, RSI, stochastic and so on: it's likely the first principal component of these indicators explain more than 95% of all indicators' variance.
May 2	comment	Bond curve extrapolation What you guys think about LOESS (local regression) with .99 span to build a less liquid yield curve?
Apr 27	comment	How to measure contango? In some paper I've seen these ways: 1) $log(f_{10})-log(f_{3})$, where $f_{t}$ stands for the future value at time $t$; 2) the value of the 2nd principal component of the term structure.
Mar 24	comment	Call options portfolio: what would the underlyings' moments to be maximized? I've edited my question to include `R` reproducible code.
Mar 21	comment	Call options portfolio: what would the underlyings' moments to be maximized? Hi, John. I would like to find optimal weights for underlyings' returns which are suitable to my options position. If I will not find a solution for underlyings' return distribution, I will surely price each option at the end of my terminal time then minimize some measure of risk.
Mar 21	comment	Call options portfolio: what would the underlyings' moments to be maximized? As an example, consider what could happen if I weighted my budget in order to achieve very negative skewness of underlyings' weighted returns: positive small profits would be frequent, while negative large losses rare, but these losses cannot occur because of Call options (you're paying time decay to be protected against them).
Jan 14	comment	Regime switching in mean reverting stochastic process The short name usually used to describe such a model is "TAR" (Threshold Autoregressive Model), isn't it? If so, how a TAR model can perform if the time series sample shows just the first regime (but we know also the second one does exist)?
Jan 11	comment	Regime switching in mean reverting stochastic process I'm used to `R` for quantitative analysis. Please, give a look at Regime Detection: it is a blog article on regime switching detection. Is that the kind of analysis you're suggesting to perform?
Jan 10	comment	Regime switching in mean reverting stochastic process I like your answer, John, and I think your approach may produce suitable results. Let me answer your question: «So the question becomes what do you want to do with the model?». I'm working with a 2-regime model and my final goal is to estimate the $S_{t}$ value which is the threshold between the first and the second regime. E.g.: if $S_{t}>60$ it's likely it will go $\theta=100$ BUT if $S_{t}<60$ it's likely it will go $\theta=25$. What should I do?
Dec 31	comment	Yield Curve Volatility Hi, Brian B. What if you do not have any historical sample that you can use to understand your estimation error? I mean: you've just the yield curve "as is" and three volatility measures about level, slope and curvature. According to your view, I should use these volatilities and some model to build a theoretical yield curve and match it with the actual one. Then I would have to choose the yield curve with the minimum average squared error from the model-based curve. Is it correct? It looks like Nelson-Siegel is the simplest model I can use because of its three factors. What's your opinion?
Dec 16	comment	Basket option pricing: step by step tutorial for beginners If I understand, you mean that my underlying should be the weighted average of each asset's price. Underlying's volatility should therefore come from covariance matrix and the final value of option is BMS with my underlying in input. Is it correct? Is it possible to use all further models (like Heston) on this "synthetic" underlying like I would do with the single option?
Dec 14	comment	Basket option pricing: step by step tutorial for beginners No books, I've got just what I found by Google but this doesn't allow me to build up a smoothed learning curve. I will look for something on J. Hull's Options, futures and derivatives on Tuesday, I hope something is there.