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17 views

Calibration: comparing models

Exponential Lévy models fall in two main categories: jump diffusion models and infinite activity Lévy models. For my paper, I study jump diffusion models and in particular Merton's model (i.e normall ...
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1answer
80 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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5answers
3k views

Why aren't econometric models used more in Quant Finance?

There is a big body of literature on econometric models like ARIMA, ARIMAX or VAR. Yet to the best of my knowledge practically nobody is making use of that in Quantitative Finance. Yes, there is a ...
4
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1answer
127 views

GARCH volatility modeling, squared returns, and convergence

After reading some more of Volatility Trading, I decided to try to make a simple volatility model using daily log returns of an ETF I follow. It turns out "simple" is sort of relative. Unfortunately, ...
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1answer
716 views

Models crumbling down due to negative (nominal) interest rates

Given that the negative interest rates on a lot of sovereign bonds with maturity under 10 years are trading in the negative (nominal) interest rate territory (recently also the short term EURIBOR has ...
4
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2answers
73 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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3answers
83 views

Is there a way to meaningfully generate daily returns from monthly?

I have a set of 7 investments in a portfolio and I need to optimize the weightings based on some exposures to various markets/styles/economic factors. I was hoping to do some sort of simple exposure ...
0
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3answers
191 views

Step By Step method to calculating VaR using MonteCarlo Simulations

In trying to find VaR for 5 financial assets with prices over a long period of time(2000 days worth of data) how would I do the following: Carry out monte-carlo simulation in order to find a VaR ...
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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 ...
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0answers
20 views

How to measure practically the performance of Venture Capital backed tech firms following an IPO?

I am currently writing a thesis about whether the fact that a tech firm backed by venture capital companies achieves higher returns following an IPO (Horizon of 3 years). I have about 800 tech ...
3
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1answer
53 views

Model reference price of Limit order book

first of all, the description of this Stackexchange forum says its for professionals or academics. I'm doing a lot of self studying and with that I was able to understand some white papers but still I'...
2
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0answers
29 views

Calibration of intensity model

I could use some advice on calibration of stochastic intensity models. I am thinking that the CIR model is most suitable, as it can not take negative values (when feller condition is satisfied). I ...
3
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0answers
149 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
26 views

How to fit model implied forward curve with market forward curve for Ornstein-Uhlebeck?

I have a spread option model of 2 correlated Ornstein-Uhlenbeck commodity prices that I estimate the parameters of with Maximum Likelihood. What is the formula for introducing the additional ...
2
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0answers
76 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 ...
2
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2answers
57 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 "...
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0answers
57 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 ...
3
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1answer
136 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) = \frac{\...
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2answers
123 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 ...
2
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0answers
64 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 ...
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1answer
1k views

Problems with dealing with GARCH models and intra-day data

A Short question would be "Which type of model from GARCH family is most suitable for modeling 5-minute data returns ?" but I've added some story to it. A Long time ago I was preparing my thesis, one ...
6
votes
1answer
112 views

Modelling EUR/USD with Ornstein-Uhlenbeck + jumps?

I'm trying to simulate a process as close as possible to EUR/USD of the ten past years. I've used a Ornstein-Uhlenbeck process: $$d X_t = -\theta (X_t - \mu) d t + \sigma d B_t$$ with the ...
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2answers
231 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 ...
2
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2answers
449 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 ...
1
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1answer
86 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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2answers
80 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?
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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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2answers
285 views

Quantitative Real Estate Investment Finance

I'm wondering if there is an application of quantitative finance to real estate investment? Specifically I'm wondering about models for pricing small neighborhoods (or even single houses) that take ...
1
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3answers
109 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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0answers
89 views

residential mortgage prepayment modelling

I'm trying to develop a model for predicting prepayments, after reading several arcticles about it over the net. the model should use market data and be behavioral model (i.e. regression/survival ...
7
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2answers
5k views

What are the main differences between discrete and continuous time models when modeling asset price dynamics?

My intuition says that both approaches, discrete time models and continuous time models will be models (i.e. approximations) of reality. Therefore it should be possible to develop useful models in ...
7
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2answers
2k views

What are common methods for modeling intraday trading volume?

What are the most common ways to model intraday trading volume, particularly for futures contracts? There are obviously a number of seasonal-type factors, like roll, economic news releases, time of ...
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1answer
79 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 ...
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0answers
41 views

Is there anyone tried to use simultaneous stochastic differential equations?

I am looking for some examples or attempts of using simultaneous stochastic differential equations for financial analysis but there has been none so far. Is it just so nasty to apply such thing in ...
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2answers
234 views

Covariance structure of call option surface

Assume the observed call option prices $C(K_i,T_i)$ for $i = 1,\dots,N$ are disturbed by some unknown measurement noise $\epsilon$. What would an appropriate covariance structure be for $\epsilon$? ...
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1answer
38 views

Fitting (marginal/multivariate) distributions to financial return data

I have calculated the simple arithmetic return on a number of different financial securities and am fitting both a Student-T and Generalised Pareto Distribution. My question is can I just use the ...
0
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1answer
34 views

Modeling EOD ETFs price returns together or individually?

Let's say you want to model the next day price returns for a set of US equities large cap ETFs (a relatively homogenous group). Would you model all the ETFs as a single, 15 years data set, or each ETF ...
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0answers
52 views

Modelling commodity price uncertainty with brownian motion - time period impacts

background I have two separate models of a metals resources company. Each model produces a series of accounting and cashflows forecast for different assets, and consolidates these to a overall ...
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1answer
31 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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6answers
3k views

What distribution to assume for interest rates?

I am writing a paper with a case study in financial maths. I need to model an interest rate $(I_n)_{n\geq 0}$ as a sequence of non-negative i.i.d. random variables. Which distribution would you advise ...
0
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0answers
88 views

Examples for the option model validation

When implementing a code for the new model, even if it provides sensible price, it is still a good idea to compare it against some benchmarks, even in the special case of constant volatility Black-...
0
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0answers
59 views

calibration of Gaussian two factor short rate model

I am trying to calibrate the gaussian two factor short rate model whose dynamics is given by r(t)=x(t)+y(t)+phi(t) Now to calibrate the model to term structure ...
3
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0answers
121 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 ...
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4answers
932 views

From Fourier Transforms to Option Values

I am trying to understand how Fourier transforms & Characteristics functions can be used to calculate option values. However, I am having difficulty following the process that is used in several ...
1
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1answer
103 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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2answers
5k views

How to tune Kalman filter's parameter?

I plan to use Kalman filter to estimate saving account amount. However, I'm a bit lost at how to tune the filter's parameters. Taking as the example from the Wikipedia page, basically there are ...
2
votes
3answers
492 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 ...
0
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1answer
224 views

How to forecast bond price with time series

I have the goal of being able to develop a model that can forecast the future prices of european government bond (or other private bonds), particularly from the historical prices and returns of the ...
2
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0answers
140 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 ...
2
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2answers
152 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 :...