4
votes
0answers
258 views

Value-at-Risk formula when using skewed-t distribution

I am trying to find a formula for the skewed-t VaR. For example the VaR formula for a t-distribution is $$ \sqrt{\frac{df-2}{df}} \times \Sigma{t} \times \mbox{quantitle}(t-\mbox{dist}, 0.01) + \mu ...
4
votes
0answers
91 views

Simple way to get the crossing probabilities of a moving barrier

Hello Quant Finance StackExchange, Is there a simple way to find the crossing probabilities of a moving barrier, namely a barrier written in the form $U(t)=\alpha_1t^2 + \beta_1t + \gamma_1$ and ...
4
votes
0answers
128 views

ERP and FF 3-factor model

In a more conservative estimate than a simple historical average, Fama & French estimate (US) equity risk premium at 3-4% (e.g., Equity Risk Premium, JF, 2002). This suggests that in an APT-like ...
4
votes
0answers
290 views

Rate Distortion Minimization in a Python Clustering Algorithm

I'm attempting to solve for $\hat{k}$ clusters, such that the rate distortion is minimized, as described here, however, the answers that I am getting from my algorithm are not following the "Jump" ...
4
votes
0answers
304 views

compute time from FX forward, how use DEPO rates?

assume I have following delta-term vol data from broker: ...
4
votes
0answers
143 views

Estimation of ranks of log-returns via copula

I have successfully chosen and estimate a copula for the ranks of the log-returns of my actions. My question is, since I have worked with the ranks instead of directly the log-returns (in order to be ...
4
votes
0answers
248 views

Analyzing the angle between vector of weights and vector of returns in mean-variance optimization

I am using the paper "A Sharper Angle on Optimization" by Golts and Jones (2009) as a basis for my (minor) masters thesis in mathematical finance. The paper focuses on the mean-variance analysis of ...
4
votes
0answers
376 views

Asymmetric Volatility Modeling (Interpretation)

I am currently writing a paper on asymmetric volatility modeling of brent, gold, silver, wheat, soybean and corn from 1986-2012 and divided them into 4 sub-sample periods (i.e. 1986-1991, 1991-1997, ...
4
votes
0answers
148 views

Discrete-time Jump-Diffusion Model

I am wondering if anybody could point me to any literature that talks about a discrete time version of the jump-diffusion model, I am aware that there is a paper by Amin (1993) that shows a discrete ...
4
votes
0answers
141 views

Rolling window Kendall's tau against APARCH(1,1) correlation

Assume you want to forecast the correlation matrix of a stocks' basket (say 15 ~ 20 stocks from different sectors); assume you need to forecast at $T$ days because you will use the forecast ouput with ...
4
votes
0answers
166 views

How to estimate CAViaR (Engle and Manganelli 2004) using non linear quantile regression?

I am trying to replicate results from Engle and Manganelli (2004). The following is one of their specifications, $q_t(\theta)=\gamma_0+\gamma_1q_{t-1}(\theta)+\alpha|r_{t-1}|$, $q$ is the quantile of ...
4
votes
0answers
155 views

Is it more accurate to analyze returns on a calendar day basis than a trading day basis?

I'm rather new to the actual practice of this kind of analysis, but it just seems wrong to me to throw Mondays' returns in with the rest without accounting for the passage of time on the weekend when ...
4
votes
0answers
437 views

ATM volatility versus OTM volatility and directional standard deviation

The forward instrument vol curve is skewed to the downside (50 delta risk reversal, 25 put, 25 call) were trading several ticks to the put). Is there a smaller standard deviation (in price terms) to ...
4
votes
0answers
681 views

Help With Quant Modelling Software

Im a software developer (freelance) working in investment banking, and I'm looking to improve my CV by gaining a better understanding of the financial quant role and the software used by quants to ...
4
votes
0answers
185 views

Taking into account the correlation in Barrier options on a Basket

In a Barrier option (where the contract cancels when the underlying hits the barrier) I succesfully found the way to compute the probability of a single underlying touching the barrier (with constant ...
4
votes
0answers
475 views

Algorithms for predicting a couple points in the future

I'm familiar with supervised learning algorithms like regression and neural networks which look at a bunch of input points and learn a function which outputs a value (the value varying depending on ...
4
votes
0answers
569 views

Hasbrouck's information share

Given a cointegrated set of price series, I am trying to compute the Hasbrouck's information share, as described in page 12-13 of this article. page 7-8 of this article I have the vector error ...
4
votes
0answers
161 views

Use of Local Times in Option Pricing

I know two applications of local time in option pricing theory. First, it allows a derivation of Dupire's formula on local volatility in a neat way (i.e. without resorting to differential operator ...
3
votes
0answers
82 views

How do I calculate the probability of a stock being above or below a value using the Heston model?

How can I use the Heston Model to calculate the probability of a stock being above or below a certain value on a given date in the future?
3
votes
0answers
48 views

Filtering out AR(1) effects before using stochastic volatility model

I wonder if I first filter out AR(1) (autoregressive model with lag 1) effects from univariate time series and then fit stochastic volatility model does above procedure introduce any bias at first or ...
3
votes
0answers
35 views

I want to Derive $P(t)=P(t,T_{n})+\sum_{i=1}^{n}[P(t,T_{i-1})-P(t,T_{i})]$

Derive the pricing formula $$P(t)=P(t,T_{n})+\sum_{i=1}^{n}[P(t,T_{i-1})-P(t,T_{i})]$$directly, by constructing a self-financing portfolio which replicates the cash flow of the floating rate bond. ...
3
votes
0answers
80 views

ISLAMIC FINANCE WACC

I need to calculate WACC for copany operating in the coutry with islamic finance system. I used build-up method to calculate cost of equity. But still searching for cost of debt in the economy. Has ...
3
votes
0answers
117 views

GMM time-series regression factor model with factors that are not returns

Factor models with factors that are not returns are usually estimated and tested by cross-sectional regressions. However, there is a way to use time-series regression to estimate and test the model. ...
3
votes
0answers
88 views

Pricing Callable Floating Rate Note

I have a question concerning pricing of a callable floating rate note (FRN). I have not found a lot of literature concerning callable FRNs (although a lot for callable bonds). With my understanding, ...
3
votes
0answers
32 views

For an affine process, how do we know the second order term is positive definite?

A regular affine process is defined to have the generator $Af(x) = \sum_{k,l=1}^d(a_{kl}+\langle a_{I,kl},y\rangle)\frac{\partial^2f(x)}{\partial x_k\partial x_l}+\langle b+\beta x,\nabla f(x)\rangle ...
3
votes
0answers
115 views

Mid-Point calculation with execution probability

Referring Cao, Hansch, and Wang (2004) "The Informational Content of an Open Limit Order Book" $$ \mbox{WP}^{n_1 - n_2} = \frac{\sum_{j=n_1}^{n_2} (Q_j^d P_j^d + Q_j^s P_j^s)}{(Q_j^d + Q_j^s)} $$ ...
3
votes
0answers
67 views

Particular Conditional Expectation of Geometric Brownian Motion

If we have the density function $$f_{Y}(y,t)=\frac{1}{y \sqrt {2\pi\sigma^2t}}exp(-\frac{(ln \ y - \mu t)^2}{2\sigma^2t})$$ Then the mean of $Y(t)=e^{X(t)}$ conditional on $Y(0)=y_0$ is found to be ...
3
votes
0answers
111 views

What is the most convenient data structure for backtesting a model of futures options prices?

I have an empirical model for the dynamics of futures prices in a particular market that I have implemented using a long series of the front five contracts. (I account for the roll in my model.) I ...
3
votes
0answers
81 views

How to de-seasonalize natural gas term structure data?

I need to de-seasonalize Nat Gas futures data for a project and am hoping to get good suggestions. As we all know natural gas futures are priced higher for the winter months and to analyze/model the ...
3
votes
0answers
114 views

“Stable-Floating” model for non-maturing deposit for FTP purpose

Non-maturing deposits (NMD) is a deposit without maturity date. The deposit rate is normally low. Banks could adjust the rate at any time. The customer can withdraw without penalty, however, in real ...
3
votes
0answers
82 views

Pre- Versus post-2008 Crisis Rates Modeling

Modeling for interest rate derivatives (such as bermudan swaptions) is said to have undergone significant changes since the crisis. Prior to the crisis, counterparty default risk was often ignored, ...
3
votes
0answers
42 views

Characterizing relation “ has no less information than” between information systems represented by Markovian matrices

I crossposted this question on math.stackexchange. Background: Suppose that an investor's utility is both determined by the state and her action taken. A fact of life is that she can't observe the ...
3
votes
0answers
41 views

Is there evidence that illiquid stocks, held less by institutions, have more price momentum?

(One of) the standard explanation people gave for momentum is under-reaction of stockholders to firm-specific news. If this is true, then it seems that these stocks should have more momentum, and ...
3
votes
0answers
181 views

How are quants able to verify whether their calculated prices are any good

This question is related to the discussion on Model Validation Criteria However it appeard to be very high level to me and I would like to go more into detail. Not working at a pricing desk the ...
3
votes
0answers
243 views

Explanation or implementation of Ledoit-Wolf estimator (without math packages)

I have calculated weights of selected assets in a market-neutral portfolio (presumably with min variance) using PCA and simple data covariance matrix. The question is : It is obvious that Cov Matrix ...
3
votes
0answers
171 views

How to compute greeks using the adjoint Monte Carlo approach?

Assume I have a stochastic ODE $$dS = a(S)dt + b(S)dW,$$ with Euler approximation $$\hat{S}_{n+1}=F_n(\hat{S}_n)=\hat{S}_n+a(\hat{S}_n)h+b(\hat{S}_n)Z_n\sqrt{h}.$$ This allows me to create sample ...
3
votes
0answers
52 views

FTAP in the model independent case, paper by Schachermayer

I have a question about the following paper by Beatrice Acciaio, Mathias Beiglböck, Friedrich Penkner, Walter Schachermayer. At the very beginning of the paper, on page 3, there are two definitions ...
3
votes
0answers
57 views

How is the redemption right on delisting of underlying shares held by holder in the convertible bond valued?

As title, If there is no delisting constraint, then I can treat the redemption right as the put right on the convertible bond. If there is redemption right on delisting, what is the conventional ...
3
votes
0answers
351 views

mean reversion with Kalman Filter - Spread calculation

Ernest Chan in its book "Algorithmic Trading" shows how to use the Kalman Filter for mean reversion pair trading. I have seen that he uses the measurement prediction error for calculating the spread ...
3
votes
0answers
156 views

Time series (stochastic process) estimating parameters using characteristic function

I have a time series of assets ${A_1, A_2, ..., A_n}$, which is described by a sophisticated distribution having the following characteristic function: $\phi(u; t;\theta)$, where $\theta$ is a vector ...
3
votes
0answers
107 views

default probability

Suppose the hazard rate is $\lambda$ the default probability density function follow exponential $f(t) = \lambda e^{-\lambda t}$ and cumulative probability function is $F(t) = 1 - e^{-\lambda t}$ ...
3
votes
0answers
173 views

Fitting Student t-distributions to log-returns

It seems that some tail-risk centric groups are bent on using Paretian and t-distributions to account for tail risk when fitting log-returns. It has been observed, however, that with and without ...
3
votes
0answers
159 views

How can I introduce exogenous variables in the equation of the conditional variance?

Is it possible to introduce dummy variables or explanatory variables in the GARCH variance equation (garchset and garchfit).This is done in the mean (ARMAX) equation through the input 'Regress' in ...
3
votes
0answers
99 views

Estimating risk aversion (power or exponential utility) from options prices

I came across this literature and it seems like there are a number of ways people do this. You can do it for an option on any underlying as long as you can create the risk-neutral p.d.f. If you agree ...
3
votes
0answers
77 views

Dividend Index Futures

My question is dealing with the proportionality between Dividend Index Futures prices and Index prices. Indeed, we in the past we used to do a simple regression between these variables and use the ...
3
votes
0answers
241 views

pairs trading detrend the spread

I have calculated a hedge ratio that generates a mean reverting spread (stationary, without trends) 60-70% of the time. But the remaining 30% of the time, it seems like there is a trend in the spread. ...
3
votes
0answers
63 views

LSM American Option pricing with dividends

Under the Longstaff-Schwartz LSM method for an American call, how should I account for a continuous dividend paying stock? I assume that it'll needs to be accounted for when simulating the underlying ...
3
votes
0answers
150 views

Credit Rating vs Bond Yield

I am looking for some references on quantifying the dependence between credit rating and bond yield. I have some data (found some Bloomberg indices which give average yield based on credit rating), ...
3
votes
0answers
160 views

Should I use Resampling or Expectation Maximization to compute a robust covariance matrix?

I have several assets, each with different return histories. Some of the assets have 75 days of return history, others have 40 or so days. In calculating a robust covariance matrix, should I be using ...
3
votes
0answers
432 views

Testing Valuation, Size and Momentum (proprietary factors) from 1988-2013: No evidence of driving cross-sectional returns

I am currently testing whether three proprietary factors - Valuation, Size and Momentum - explain cross-sectional returns. A sample of 3000 securities was tested using Fama-MacBeth two-pass ...

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