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7
votes
1answer
466 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
558 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 ...
12
votes
3answers
681 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
395 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 ...
7
votes
1answer
3k 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
261 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
424 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
1k 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
532 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 ...
8
votes
1answer
779 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
312 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
666 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
212 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
472 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 ...
7
votes
5answers
1k 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
453 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
183 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 ...
11
votes
2answers
1k 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
479 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
2k 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 ...
6
votes
2answers
524 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
2k 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 ...
30
votes
6answers
5k 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
385 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 ...
9
votes
1answer
409 views

Fixed income modeling

I am currently working on my research paper and trying to explain a two-dimensional variable: volume and instrument of corporate debt financing. Independent variables that I believe must be included ...
4
votes
7answers
1k views

Recommendation for a book on CVA/Credit Risk and PD/LGD/EAD modeling?

I need suggestions for some good books on the following topics: Credit Value Adjustment (CVA) / Credit Risk Probability of Default / Loss-Given-Default / Exposure-At-Default modeling Any pointers ...
5
votes
1answer
235 views

Multiple comparison problems

I recently read a blog entry where some statistics were generated for a common technical analysis indicator. Below is the link. My question shows up close to the bottom under the name bill_080, in ...
6
votes
5answers
3k views

Predicting Price Movements on a Betting Exchange

On a betting exchange the price (the odds that an event will happen expressed as a decimal, 1/(percentage chance event occurring) of a runner can experience a great deal of volatility before the event ...
4
votes
1answer
893 views

Simple model for option premium (for covered call simulation)?

Given a historical distribution of weekly prices and price changes for a stock, how can I estimate the the option premium for a nearly at-the-money (ATM) option, say with an expiration date 3 months ...
24
votes
2answers
4k views

How useful is Markov chain Monte Carlo for quantitative finance?

Naively, it seems that Bayesian modeling, structural models particularly, would be quite useful in finance because of their ability to incorporate market idiosyncrasies and produce accurate ...