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3answers
5k views

relation between asset's and equity volatilities - merton model

In terms of Merton credit risk model need to find the initial value of counterparty's assets and the volatility of the assets. Both value are not directly observable thus we have to approximate them ...
3
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3answers
3k views

Why are exotic options most popular in FX?

I was reading Derman's latest blog post on Vanna Volga pricing, which, according to the linked Wikipedia article, is used mostly for pricing exotic options on foreign exchange (FX). This Willmott ...
3
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2answers
318 views

Shortcomings of generalized Brownian motion for asset price modelling

I'm simply interested on hearing some views on which shortcomings arise by using the (multidimensional) SDE $$dS(t)=S(t)\alpha(t,S(t))dt+S(t)\sigma(t,S(t))dW(t)$$ as a model for asset prices. I know ...
3
votes
2answers
257 views

Modelling driftless stock price with geometric Brownian motion

I wish to understand some basic fact about the (primitive) simulation of stock prices with geometric Brownian motion. If $S(t)$ is the stock price at time $t$, and the stock price follows geometric ...
3
votes
1answer
786 views

What are some applications of bioinformatics or genetics to generating alpha in U.S. equities?

There are many disciplines that have contributed to how one model's risk and return. Physics introduced Brownian motion and RMT. Machine learning has helped to solve complex portfolio construction ...
3
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2answers
430 views

How to select optimal betting strategy from backtest?

I have written a model for predicting the winner of UFC fights. My model calculates the probability of each fighter to win a given match. I have back tested the model and found it to be very ...
3
votes
1answer
144 views

What's the underlying idea of definition of constrained market in Skiadas' Asset Pricing Theory?

I'm self-studying Skiadas' Asset Pricing Theory, and find the definition of constrained market on page 21 confusing(you can find it here in the sample chapter). Definition 1.26. A constrained ...
3
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2answers
261 views

Black-Litterman, how to choose the uncertainty in the views $\Omega$ for smooth transitions form prior to posterior

In Black-Litterman we get a new vector of expected returns of the form: \begin{align} \Pi_{BL} = \Pi + \underbrace{\tau \Sigma P^T[P\tau\Sigma P^T+\Omega]^{-1}}_{\text{correction}}[Q-P\Pi] \end{align} ...
3
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1answer
2k views

How popular is the Linear Gauss Markov (LGM) model?

Some friends recommend to me Linear Gauss Markov model, saying it's interesting to have a look at it. Basically it's a framework different from HJM, with potential to extend, and the merit is that ...
3
votes
1answer
110 views

Why do we usually use normal distribution and not Laplace distribution to generate stochastic process?

When working with a stochastic process based on brownian motion, the increments have normal (gaussian) distribution. However, it seems that a Laplace distribution, with density: $$f(t) = ...
3
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2answers
354 views

How to find the best fitting GARCH model for a portfolio composed of 3 ETFs in R?

I am doing a project for my class Financial Time Series in which I am trying to forecast my portfolio log returns using a GARCH fit. I am having a bit of trouble determining the best way to fit this ...
3
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2answers
412 views

Resources for finding quantitative finance examples using excel, VBA and access

I am seeking to increase my knowledge in the quantitative finance field. I would be grateful if someone could point me to useful resource online, where I can find working examples of they types of ...
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2answers
77 views

Finding Credit Risk Population Data

Are there any free or relatively cheap sources of aggregate data on credit risk for specific geographic regions, ages, and so on?
3
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1answer
281 views

How to use volatility to assess the accuracy of a stock market model?

Background: For a dissertation I have a multi-agent stock market model that I am using to assess different mechanisms for producing particular dynamic regimes. A key point is assessing how closely it ...
3
votes
2answers
49 views

What is the effect of mean-reversion on an upper barrier knock-out call option?

Consider a mean-reverting normal model for an underlying $dX^{(1)}_t=-\kappa X^{(1)}_tdt+\sigma^{(1)} dW^{(1)}_t$, for fixed time-independent constants, $\kappa$ (mean-reversion) and $\sigma^{(1)}$ ...
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0answers
119 views

Fitting High Frequency Indicators

I have a high frequency time series of the bid and ask prices of a stock recorded on every tick. For each data point I also have a certain indicators that predict the future movement of the price. The ...
3
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0answers
232 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 ...
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0answers
147 views

A doubt about Evans and Jovanovic (1989) economic model for entrepreneurs with credit constraints

[I already posted this question on the math forum of stackexchange and I was advised that I should post this question here] In Evans and Jovanovic (1989) you will find a model for entrepreneurs with ...
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0answers
173 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
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0answers
237 views

how to represent financial data as a spatial process

Does any one have a good tutorial , introduction or overview on the web for different ways of representing financial data as a spatial process? Such as those spatial processes often used in ...
3
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0answers
392 views

Monty Hall Model

Given a fixed time period,say 3 days, the stock/market can go up,down or stay sideways. A hedge fund can long, short or use rangebound(options strategy) to bet for that 3 days closing level. Hedge ...
2
votes
3answers
453 views

How to estimate parameters of geometric brownian motion with time-varying mean?

Does anyone know how to estimate $A$, $\sigma_1$,$\sigma_2$ from the following system? $$dx = \mu_t x dt + \sigma_1 x dB_x$$ $$d\mu = A(\bar\mu - \mu) dt + \sigma_2 dB_\mu$$ Variation in $x$ could ...
2
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2answers
269 views

Using Financial Ratios to get credit rating or PD

Hello I'm looking for papers, aside from ones that use CDS spreads, about credit rating development or estimating default probability based on financial ratios that also include methodology and maybe ...
2
votes
2answers
150 views

How to compute the conditional expected value of a geometric brownian motion?

I'm working on a project, and I have to use the cumulative and conditional expected value of the variations of a stock following a Geometric Brownian Motion. I know that the cumulative is as follows ...
2
votes
1answer
102 views

To understand FOMC events and its impact on the market

Last month when FOMC meeting decision went out that fed would start to exit QE3, immediately we saw a deleveraging effect: SPY went down, GLD went down, and LQD (bond) went down, but US dollars went ...
2
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2answers
55 views

Automate selection of BIC-minimizing ARIMA(1,0,X) model

I want to estimate an ARIMA(1,0,X) model. The MA(X) in the model is selected to minimize BIC. I have the following code employing the function auto.arima from ...
2
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1answer
719 views

Question on OIS and fed funds rate

If i am considering the 0-5 year irs spread for the USD market, would it be more accurate to use the fed funds rate or the OIS rate? I believe the OIS rate is calculated based on the fed funds rate, ...
2
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2answers
434 views

Ideas about Stochastic volatility models

I am currently working on comparing different models for modelling the volatility and then pricing vanilla options (I use option prices on real stocks in order to calibrate my models and then I ...
2
votes
1answer
159 views

Is there an easily implementable alternative to lognormal growth (something with fatter tails)?

I have a toy model in Excel for the growth of a investment portfolio. I assume iid lognormal annual growth factors: =EXP(mu+sigma*NORM.S.INV(RAND())) where mu and ...
2
votes
2answers
120 views

how to make a distribution model tolerable of trend?

I'm building an model on different loans' NPL rate. The problem is NPL rates are always affected by the market. When NPL rates move in trend, my model will fail the back-testing. Assuming $x(t)$ is a ...
2
votes
1answer
110 views

if market is always assumed right, what happened when LIBOR was manupulated?

Recently Monetary Authority of Singapore (MAS) raps banks in rate-rigging. This is nothing new, LIBOR was also manupulated before, by some "major" banks. however, before the censorship, did any ...
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0answers
75 views

Problems with a Black-Scholes modified equation

I haven't really studied much financial mathematics until about 2 months ago so I'm quite new to this stuff, so I'm sorry if this is a trivial question. At the moment I'm trying to work out what the ...
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0answers
56 views

VAR models for log-returns?

I am wondering if Vector Autoregression (and other autoregressive models) is a sound modelling for the daily (not high-frequency!) log-returns of time series from liquid financial markets. One can ...
2
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0answers
128 views

How can I do a dynamic GARCH model using extended Kalman filter in R?

Today I was reading an article quoted here, in this article is proposed an adaptive (dynamic) Garch model. How can I do it in R? The use of extended Kalman filter or particle filter is indifferent. I ...
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0answers
27 views

What methods - inspired by Haavelmo’s Structural Econometrics - can show that a partial equilibrium model is unreliable? [closed]

According to Spanos 2014 Revisiting Haavelmo's Structural econometrics: Bridging the gap between theory and data Dynamic Stochastic General Equilibrium models are statistically inadequate, in such an ...
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1answer
85 views

Portfolio of sum of two Bachelier processes

Suppose you construct a portfolio of two stocks, whose values $A$ and $B$ are modelled as a Bachelier process: $$dA = \sigma_A dW_A(t) \text{ and } dB = \sigma_B d W_B(t).$$ Each of the stock prices ...
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1answer
2k views

Calculating portfolio allocation beta with different asset classes?

I'd like to calculate portfolio allocation beta on a portfolio that has different asset classes. The portfolio may be made up of: ...
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2answers
90 views

Modelling and forecasting mixed frequency financial data

I was wondering if someone could provide some guidance to me. I would like to Combine various financial data of mixed frequencies (some daily, weekly, some quarterly) to a composite index. I have ...
1
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2answers
167 views

Geometric brownian motion vs. Ornstein Uhlenbeck

I'm looking at the SDE of Geometric brownian motion(*): $$d X(t) = \sigma X(t) d B(t) + \mu X(t) d t$$ (with analytic solution $X(t) = X(0) e^{(\mu - \sigma^2 / 2) t + \sigma B(t)}$) and the SDE of ...
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2answers
145 views

how to extend lognormal model so that $\sigma$ is correlated to $\mu$?

Consider a log-normal model, $dx / x = \mu dt + \sigma dW$, where $W(t)$ is a Wiener process. Let's say $\mu$ and $\sigma$ change with time, slowly, so we note them by $\mu(t)$ and $\sigma(t)$. ...
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3answers
93 views

How is fundamental data taken into account when modelling stock prices with a Geometric Brownian Motion?

I have a basic understanding of the principles behind Geometric Brownian Motion and how it can be used to model stock prices, however I am confused as to how it is used in practice. In particular, how ...
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1answer
30 views

Modeling credit utilization and stock market growth

I relatively new to financial mathematics but I am wondering if at all there exists a relationship between credit utilization (the rate at which the public accesses credit from financial institutions) ...
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1answer
256 views

Normalized data

I am new to this. I trained and tested my data using SVM in Matlab with the autoscale option true => the data would be normalized with unit SD. Let's say the training data have the price around 200. ...
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1answer
50 views

Methods or models to predict activity of clients of a bank

I'm a Physicist but I'd like to know if there are some methods or models to predict the activity of the clients of a bank. I heard that banks are interested in this sort of analysis so I got curious ...
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1answer
100 views

Covariance Matrix vs. Volatility Matrix

Consider a general multidimensional market model in which each of $m$ stocks is driven by $d$ Brownian motions (as in Shreve II, p. 226), viz. $$ dS_i/S_i = \alpha_i dt + \sum_{j=1}^d \sigma_{ij}dW_j, ...
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1answer
108 views

How to model the effect of earnings surprises on long-term returns?

I'm looking into modeling the relationship between EPS announcement surprises with long-term returns (1 quarter to 3 years with intervals). I've based my current methodology off papers looking at the ...
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1answer
72 views

How to model housing loan market?

Housing loan market vibrates according to the policies, such as LTV rate, for example, if must pay 20% downpayment, LTV rate would be 80% interest rate, for example, lifting the loan rate, the ...
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1answer
62 views

Generating random yields

I would like to test different methods for fitting a yield curve, like the Nelson-Siegel, cubic splines etc. I would like to generate random yield to maturity data, that somehow reflects the common ...
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0answers
53 views

Modeling Interest-only Mortgages

First post on this forum - happy to be here. Please give feedback if this is off-topic so I can more meaningfully contribute moving forward. Can we infer a range of future all-in costs for I/O ARMs ...
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1answer
75 views

Obtaining the drift of a Wiener process formed from a random walk

I'm trying to understand how the equation for Geometric Brownian Motion is formed from a random walk. I'm following the book 'Statistics of Financial Markets' but I'm struggling to follow how the ...