Forecasting High-Frequency Futures Returns Using Online Langevin Dynamics

@article{Christensen2012ForecastingHF,
  title={Forecasting High-Frequency Futures Returns Using Online Langevin Dynamics},
  author={Hugh L. Christensen and James K. Murphy and Simon J. Godsill},
  journal={IEEE Journal of Selected Topics in Signal Processing},
  year={2012},
  volume={6},
  pages={366-380}
}
Forecasting the returns of assets at high frequency is the key challenge for high-frequency algorithmic trading strategies. In this paper, we propose a jump-diffusion model for asset price movements that models price and its trend and allows a momentum strategy to be developed. Conditional on jump times, we derive closed-form transition densities for this model. We show how this allows us to extract a trend from high-frequency finance data by using a Rao-Blackwellized variable rate particle… 
Bayesian parameter estimation of Jump-Langevin systems for trend following in finance
  • James K. Murphy, S. Godsill
  • Mathematics
    2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2015
TLDR
A Bayesian method for parameter estimation in linear Jump-Langevin systems, i.e. systems driven by a linear, mean-reverting jump-diffusion trend process, which has been applied successfully to trend following in finance, in order to develop momentum-based trading strategies.
Hidden Markov Models Applied To Intraday Momentum Trading With Side Information
TLDR
A Hidden Markov Model for intraday momentum trading is presented which specifies a latent momentum state responsible for generating the observed securities' noisy returns, and it is shown that splines can be used to capture statistically significant relationships from this information, allowing returns to be predicted.
Integration of technical trading behaviour in asset pricing
TLDR
Methods applied to technical analysis based on particle filtering for detecting the presence of technical trading on foreign exchange and futures markets are investigated to measure the intensity of that trading and its influence on short term price formation of the traded securities.
Streaming Perspective in Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data
TLDR
It is found that the estimator ensuring positive semidefiniteness require much higher bandwidth than the estimators without such constraint, which allows them to operate with limited memory and formulate such estimation approach as a streaming algorithm.
Particle Filtering and Inference for Limit Order Books in High Frequency Finance
TLDR
This paper investigates the on-line analysis of high-frequency financial order book data using Bayesian modelling techniques and proposes that the order book shape is proportional to a gamma or inverse-gamma density function.
Algorithmic arbitrage of open-end funds using variational Bayes
TLDR
The framework presented is a hierarchical graphical model which allows parameter posteriors to be inferred by a variational Bayesian approach and enables prior knowledge about the funds to be incorporated into the model at the same time as being computationally cheap to run.
Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data
Abstract: We investigate the computational issues related to the memory size in the estimation of quadratic covariation, taking into account the specifics of financial ultra-high-frequency data. In
Approximate simulation of linear continuous time models driven by asymmetric stable Lévy processes
  • M. Riabiz, S. Godsill
  • Mathematics
    2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2017
TLDR
This paper extends to the multidimensional case the modified Poisson series representation of linear stochastic processes driven by α-stable innovations a Gaussian approximation of the residuals of the series, via the exact characterization of their moments, to allow for Bayesian techniques for parameter or state inference.
A Dyadic Particle Filter for Price Prediction
TLDR
A dyadic particle filter is proposed that is based on sequential importance resampling that captures the dynamic evolution of a pair of latent vectors, yielding more accurate prediction of stock prices than the state-of-the-art techniques.
...
1
2
3
4
...

References

SHOWING 1-10 OF 81 REFERENCES
Modeling High-Frequency FX Data Dynamics ∗
This paper shows that high-frequency, irregularly-spaced, FX data can generate non-normality, conditional heteroskedasticity, and leptokurtosis when aggregated into fixed-interval, calendar time even
A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
I use a new technique to derive a closed-form solution for the price of a European call option on an asset with stochastic volatility. The model allows arbitrary correlation between volatility and
A Jump-Diffusion Model for Option Pricing
  • S. Kou
  • Economics
    Manag. Sci.
  • 2002
TLDR
A double exponential jump-diffusion model is proposed, for the purpose of option pricing, which is simple enough to produce analytical solutions for a variety of option-pricing problems, including call and put options, interest rate derivatives, and path-dependent options.
Large‐scale volatility models: theoretical properties of professionals’ practice
Abstract.  This article examines the way in which GARCH models are estimated and used for forecasting by practitioners in particular using the highly popular RiskmetricsTM approach. Although it
Momentum Strategies in Commodity Futures Markets
Do Momentum-Based Strategies Still Work in Foreign Currency Markets?
Abstract This paper examines the performance of momentum trading strategies in foreign exchange markets. We find the well-documented profitability of momentum strategies during the 1970s and the
The Econometrics of High Frequency Data
TLDR
This course starts from scratch, introducing the probabilistic model for high frequency data, and then turns to the estimation question in this model, focused on the emblematic problem of estimating volatility.
A Constant-Volatility Framework for Managing Tail Risk
Since Lehman Brothers collapsed in 2008, tail-risk hedging has become an increasingly important concern for investors. Traditional approaches, such as purchasing options or variance swaps as
The Illusory Nature of Momentum Profits
In markets with trading friction, the incorporation of information into market prices can be substantially delayed through a weakening of the arbitrage process. We re-examine the profitability of
The Profitability of Technical Stock Trading Has Moved from Daily To Intraday Data
This paper investigates how technical trading systems exploit the momentum and reversal effects in the S&P 500 spot and futures market. When based on daily data, the profitability of 2580 technical
...
1
2
3
4
5
...