The modeling tag has no wiki summary.
1
vote
1answer
65 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 $\sigma(t)$.
...
2
votes
3answers
92 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 ...
1
vote
2answers
69 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 ...
4
votes
1answer
140 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
1answer
65 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
votes
1answer
84 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 ...
1
vote
0answers
68 views
Modelling long run relationship between dividend and earnings
I am working on a paper where I have to model the long run relationship between earnings and dividends. I have downloaded the raw data from shillers website. I have converted the series to ...
7
votes
3answers
152 views
How to justify a model that could not predict external factors?
I'm building some models, for example, Bad Loan (NPL) rate.
It's based on historical simulation method -- basically it's saying the future behavior could be predicted by history data.
However, this ...
5
votes
0answers
290 views
VaR model Unconditional Coverage Tests: Is this extension of Kupiec POF test correct?
Background: Kupiec P. in 1995, published paper "Techniques for Verifying the Accuracy of Risk Management Models" on Journal of Derivatives, v3, P73-84, it's a Unconditional Coverage Tests designe for ...
1
vote
1answer
54 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 ...
5
votes
1answer
100 views
Looking for a recommendation for a Fund Transfer Pricing modelling book
Recently I started working in a bank as a modeler, one of the possible topic is FTP - Fund Transfer Pricing.
After I studied that subject a little on wiki and read a website or two in that field I ...
3
votes
0answers
182 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 ...
5
votes
1answer
408 views
Problems with dealing with GARCH models and intra-day data
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.
Long time ago I was preparing my thesis, one ...
0
votes
1answer
131 views
Numerical difficulties in fitting option prices
In [1], the authors state that "Although some studies apply the curve-fitting method directly to option prices, the severely nonlinear relationship between option price and strike price often leads to ...
4
votes
1answer
258 views
Derive a short rate model from HJM
Suppose we are assuming the HJM framework. My question is, if it is possible to derive for different choices of the volatility function $\sigma$ (and hence of the drift function) the most common short ...
0
votes
1answer
202 views
Using OpenCL video cards to offload Quant Finance calculations, what features should I look for?
I'm benchmarking some software and am looking for cards that are better at parallel multiplication vs parallel addition.
Is there any prior work that may have this information?
What GPU features ...
3
votes
0answers
195 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 ...
4
votes
1answer
409 views
Coin Toss System
Coin Toss Runs Calculator
The expected number of runs for two consecutive heads or tails is 3. Is there an edge if we place a progressive constant size bet(limited to 3 times)for consecutive ...
1
vote
0answers
116 views
Modeling asset performance to Bitcoin revenue
I'm attempting to model asset performance to Bitcoin revenue, which is a driving force in the Bitcoin community.
Question
Is there any model, or research being done that tracks "hashes per second" ...
2
votes
0answers
335 views
Can the Heston model be shown to reduce to the original Black Scholes model if appropriate parameters are chosen?
Summary
For Heston model parameters that render the variance process constant, the solution should revert to plain Black-Scholes. Closed from solutions to the Heston model don't seem to do this, even ...
6
votes
0answers
582 views
Modelling with negative interest rates
For a project, I am interested to model the impact of recently negative interest bonds on the portfolio. The literature on modelling negative interest rates is limited, and the only theory I could ...
2
votes
1answer
200 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, ...
1
vote
1answer
760 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:
...
-3
votes
1answer
359 views
Tutorial for working with tick data? [closed]
Can you recommend a good tutorial for working with tick data for the purpose of algorithmic trading?
Is the data normally stored in a database and only bits are read into memory at a time?
Is there ...
1
vote
1answer
219 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.
...
8
votes
1answer
292 views
What is a commonly accepted econometric model for volume?
What is the gold standard econometric model for volume? For example, a common model for price is the autoregressive (AR) model with GARCH(1,1) innovations. Do you know of any good survey articles ...
5
votes
1answer
362 views
How to model time series of illiquid stocks - 400 observations (transactions) per 8 hours?
How to model time series which are illiquid - 400 observations (transactions) per 8 hours ? Are there models suitable for this situation which incorporate not only size of the transactions but also ...
3
votes
1answer
414 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 ...
11
votes
3answers
572 views
What are some research articles on using principle components to generate alpha?
Here's an example by Marco Avellenada from NYU titled "Statistical Arbitrage in the U.S. Equities Market". The idea of this paper involves capturing mean reversion in the residual returns of a ...
4
votes
3answers
314 views
Is it possible to demonstrate that one pricing model is better than another?
Take the classic GBM (geometric Brownian motion) model for equities as an example:
ds = mu * S * dt + sigma * S * dW.
It is the basis for the classic ...
6
votes
1answer
1k 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 ...
3
votes
1answer
242 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 ...
4
votes
1answer
363 views
Discrete time Ho lee model
This is my first question in this forum. I am stuck with my current testing the Ho Lee model. I am having difficulty computing the perturbation factor $\Delta$.
The ho lee model should be completely ...
14
votes
2answers
849 views
From a high frequency point of view, with a price prediction and assuming infinite leverage, how do you determine optimal trade size?
I have read about something like Kelly criterion for long term expectation maximization assuming a fixed starting bankroll. But if one can assume unlimited leverage, and one has a signal for a price ...
6
votes
3answers
408 views
How to account for jumps in intraday data when calculating beta?
I am calculating betas on intraday trade data at 15-minute intervals. For simplicity sake, let's assume I am modeling
\begin{equation}
Y = \beta * X + c
\end{equation}
where $Y$ is the return of XLF ...
6
votes
1answer
481 views
How to 'calibrate' simple pricing models for equity index options and equity options?
I am interested in doing some research on plain vanilla equity options and equity index options. I have historical data for these options. I also happen to have market maker 'fair price' (bid and ask) ...
7
votes
3answers
287 views
How to improve the consistency of explained variance statistics in a linear equity model?
I have an intraday equity returns linear model that, overall, shows good values in terms of $R^2$, p-value and other explained variance statistics. Around 70% of the stocks show consistent R-squared ...
4
votes
0answers
514 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
1answer
150 views
Modeling interest rates with correlation
I'm trying to model interest rates, and will use the following equation:
$dr = \mu r dt + \sigma r dW $
I'm also being told that interest rates are 40% correlated to S&P returns. How can I ...
4
votes
0answers
418 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 ...
6
votes
5answers
827 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 ...
5
votes
1answer
344 views
What is the forward rate for a Black-Karasinski interest rate model?
I was wondering if anyone could help me with the instantaneous forward rate equation for a Black-Karasinski interest rate model?
I was also after the Black-Karasinski Bond Option Pricing Formula.
9
votes
4answers
107 views
Are there any valuation models of securities that use hyperbolic discounting?
To quote Wikipedia:
In hyperbolic discounting, valuations fall very rapidly for small delay periods, but then fall slowly for longer delay periods. This contrasts with exponential discounting, in ...
10
votes
2answers
805 views
How to build a regime-switching model which knows its own limits?
In recent months I've come to the conclusion that there are not only certain regimes in the markets (like bear or bull) but phases where all models fail because we are in uncharted territory. The ...
9
votes
1answer
404 views
What to ask for in a good prototyping framework?
Reading up on quantitative methods, model development, and back-testing, one obvious question springs to mind:
What should one ask of a prototyping (model testing) framework?
I know a lot of people ...
5
votes
5answers
1k views
How many explanatory variables is too many?
When researching any sort of predictive model, whether using ordinary linear regression or more sophisticated methods such as neural networks or classification and regression trees, there seems to ...
4
votes
2answers
377 views
Should I use currency hedged or unhedged returns for a global equity allocation model?
I am building a global tactical equity allocation model. The model will help determine an optimal allocation amongst a number of major developed and emerging stock markets (represented for my purposes ...
2
votes
3answers
980 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 ...
29
votes
6answers
3k views
Which approach dominates? Mathematical modeling or data mining?
According to my current understanding, there is a clear difference between data mining and mathematical modeling.
Data mining methods treat systems (e.g., financial markets) as a "black box". The ...
7
votes
1answer
341 views
Do people use unbounded interest rate models, and what alternatives exist?
A simple interest rate model in discrete time is the autoregressive model,
$$
I_{n+1} = \alpha I_n+w_n
$$
where $\alpha\in [0,1)$ and $w_n\geq 0$ are i.i.d. random variables. When working with ruin ...
