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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,738 papers · 148 categories

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23456890 · Jun 202019922001200920172026
48 results for German bond futures

We apply the formalism of the continuous time random walk (CTRW) theory to financial tick data of the bond futures transacted in Korean Futures Exchange (KOFEX) market. For our case, the tick dynamical behaviors of the returns and volatility for bond futures are treated particularly at the long-time limit. The volatili…

2003-11-07abs ↗pdf ↗

We study the tick dynamical behavior of the bond futures in Korean Futures Exchange(KOFEX) market. Since the survival probability in the continuous-time random walk theory is applied to the bond futures transaction, the form of the decay function in our bond futures model is discussed from two kinds of Korean Treasury …

2002-12-17abs ↗pdf ↗

This paper constructs and studies the long-term factorization of affine pricing kernels into discounting at the rate of return on the long bond and the martingale component that accomplishes the change of probability measure to the long forward measure. The principal eigenfunction of the affine pricing kernel germane t…

2016-10-03abs ↗pdf ↗

Bond prices are a reflection of extremely complex market interactions and policies, making prediction of future prices difficult. This task becomes even more challenging due to the dearth of relevant information, and accuracy is not the only consideration--in trading situations, time is of the essence. Thus, machine le…

2017-03-31abs ↗pdf ↗

We analyze the time series of overnight returns for the bund and btp futures exchanged at LIFFE (London). The overnight returns of both assets are mapped onto a one-dimensional symbolic-dynamics random walk: The `bond walk'. During the considered period (October 1991 - January 1994) the bund-future market opened earlie…

1999-03-14abs ↗pdf ↗

A pricing formula for discount bonds, based on the consideration of the market perception of future liquidity risk, is established. An information-based model for liquidity is then introduced, which is used to obtain an expression for the bond price. Analysis of the bond price dynamics shows that the bond volatility is…

2009-05-01abs ↗pdf ↗

Accurate volatility modelling is paramount for optimal risk management practices. One stylized feature of financial volatility that impacts the modelling process is long memory explored in this paper for alternative risk measures, observed absolute and squared returns for high frequency intraday UK futures. Volatility …

2011-03-29abs ↗pdf ↗

Corporate bond factor research is flawed due to measurement errors and ex-post filtering.

problem Replication crisis in corporate bond factor research.
method Analysis of 108 signals across nine thematic clusters, correction of transaction prices and return filtering.
result Majority of previously documented factors do not produce statistically significant alphas after correction.

We explore the effect of past market movements on the instantaneous correlations between assets within the futures market. Quantifying this effect is of interest to estimate and manage the risk associated to portfolios of futures in a non-stationary context. We apply and extend a previously reported method called the P…

2019-12-27abs ↗pdf ↗

The study compares VaR and ES models for tail risk of electricity futures, finding AR(1)-GARCH(1,1) with Student-t distribution best.

problem Modeling tail risk of electricity futures contracts in various markets.
method Comparison of VaR and ES models using AR(1)-GARCH(1,1) with Student-t distribution, historical simulation, and quantile regression.
result AR(1)-GARCH(1,1) with Student-t distribution is the best-performing model for tail risk estimation.

Research optimizes a small RES utility's portfolio by dynamically trading in German electricity markets.

problem Managing risks in RES producers and electricity traders in changing electricity markets.
method Uses SVAR model to estimate market relationships and data-driven trading strategies to optimize revenue and reduce risk.
result Data-driven trading strategies increase utility revenue and reduce trading risk.

The Heath-Jarrow-Morton (HJM) formulation of treasury bonds in terms of forward rates is recast as a problem in path integration. The HJM-model is generalized to the case where all the forward rates are allowed to fluctuate independently. The resulting theory is shown to be a two-dimensional Gaussian quantum field theo…

1998-09-14abs ↗pdf ↗

A study finds that only a few factors explain corporate bond risk, rendering extensive bond factor literature redundant.

problem The redundancy of extensive bond factor literature in explaining corporate bond risk premia.
method Bayesian Model Averaging Stochastic Discount Factor analysis of 18 quadrillion models.
result A Bayesian Model Averaging SDF explains risk premia better than low-dimensional models, with an out-of-sample Sharpe ratio of 1.5 to 1.8.

We apply the Continuous Time Random Walk (CTRW) framework, introduced in finance by Scalas et al., to the analysis of the probability distribution of time intervals between two consecutive trades in the case of BTP futures prices traded at LIFFE in 1997. Results corroborate the validity of the CTRW approach for the des…

2000-12-28abs ↗pdf ↗

We introduce the minority game theory for two kinds of the Korean treasury bond (KTB) in Korean futures exchange markets. Since we discuss numerically the standard deviation and the global efficiency for an arbitrary strategy, our case is found to be approximate to the majority game. Our result presented will be compar…

2005-03-01abs ↗pdf ↗

Machine learning models show intermarket data can predict stock market performance better than expected.

problem Evaluating the semi-strong form of the Efficient Market Hypothesis.
method Used machine learning techniques on various intermarket data sets to predict stock market performance.
result Intermarket data significantly outperforms baselines in predicting stock market movement, contradicting the semi-strong EMH.

The study identifies features making cross-impact relevant in explaining price variance of US assets.

problem Understanding the relevance of cross-impact in explaining price variance of US assets.
method Using tick-by-tick data spanning 5 years for 500 US assets, the study investigates the features making cross-impact relevant.
result Price formation is endogenous within highly liquid assets, influencing less liquid correlated products with a constrained impact velocity.

Proposes a regularization approach to model German power derivative market, identifying significant risk spillovers.

problem Large portfolio of German power derivative contracts, identifying significant risk spillovers.
method Combines high-dimensional variable selection with dynamic network analysis.
result Identifies significant risk contributors and interdependencies between contracts, especially spot contracts.

Empirical study on long-term discount rates using historical bond prices.

problem Estimating long-term real interest rates and discount rates from historical bond data.
method Using Fourier transforms to derive the discount function and fitting it to historical data.
result Estimated long-term discount rates of 1.7% for UK and 2.2% for US.

Extends credit risky bond market models to include jumps and general semimartingales.

problem Modeling credit risky bonds with jumps and general semimartingales under minimal assumptions.
method Extends Heath-Jarrow-Morton approach to include jumps and generalizes recovery scheme.
result Derives generalized drift conditions for local martingale measures, ensuring no asymptotic free lunch.

Study improves prediction of commodity futures using multi-factor model.

problem Improving accuracy in predicting commodity futures prices.
method State-space functional regression model incorporating yield curve dynamics.
result Functional regression model outperforms Schwartz-Smith model in estimating short-end of futures curve.

We introduce Hermite fractional financial markets, where market uncertainties are described by multidimensional Hermite motions. Hermite markets include as particular cases financial markets driven by multivariate fractional Brownian motion and multivariate Rosenblatt motion. Conditions for no-arbitrage and market comp…

2016-12-21abs ↗pdf ↗

We introduce the entropic measure transform (EMT) problem for a general process and prove the existence of a unique optimal measure characterizing the solution. The density process of the optimal measure is characterized using a semimartingale BSDE under general conditions. The EMT is used to reinterpret the conditiona…

2015-11-19abs ↗pdf ↗

Stochastic model for pension insurer assets and liabilities with mortality risk.

problem Modeling assets and liabilities with mortality risk in pensions insurers.
method Multivariate stochastic process for asset and liability returns, capturing dynamics and dependencies.
result Efficient computation of a million scenarios on personal computers.

Over the last decade, dividends have become a standalone asset class instead of a mere side product of an equity investment. We introduce a framework based on polynomial jump-diffusions to jointly price the term structures of dividends and interest rates. Prices for dividend futures, bonds, and the dividend paying stoc…

2018-03-06abs ↗pdf ↗

We propose a modification of the classical Black-Derman-Toy (BDT) interest rate tree model, which includes the possibility of a jump with small probability at each step to a practically zero interest rate. The corresponding BDT algorithms are consequently modified to calibrate the tree containing the zero interest rate…

2019-08-12abs ↗pdf ↗

Shorting IG ETFs can hedge bond portfolios during market drawdowns effectively.

problem Managing downside risk in bond portfolios during market crises.
method Constructing three signals (Momentum, Liquidity, Credit) to dynamically hedge short IG positions.
result Dynamic hedge removes when predicted hedged return mean reverts, achieving higher returns and Sortino ratios.

This paper uses crypto derivatives data to estimate yield curves for cryptocurrencies.

problem Estimating yield curves for cryptocurrencies without bond markets.
method Using mathematical tools and data from cryptocurrency derivatives markets.
result Yield curves can be constructed for cryptocurrencies using derivative data.

Research aims to predict fallen angel bonds' bankruptcy using machine learning.

problem Predicting which fallen angel bonds will become investment grade or go bankrupt.
method Used four classification methods (logistic regression, KNN, SVM, NN) and Google Cloud's automated machine learning.
result Google Cloud's machine learning model performed best in over-sampled and feature selection data sets.

A method for multidimensional probabilistic electricity market forecasting is proposed.

problem Uncertainty in simultaneous multivariate predictions of electricity markets.
method Repeated resampling to estimate uncertainty of simultaneous multivariate predictions.
result The method provides highly accurate predictions and gains are largest when considering functions of variables.

We implement a Tensor Train layer in the TensorFlow Neural Machine Translation (NMT) model using the t3f library. We perform training runs on the IWSLT English-Vietnamese '15 and WMT German-English '16 datasets with learning rates {0.0004,0.0008,0.0012}\in \{0.0004,0.0008,0.0012\}, maximum ranks {2,4,8,16}\in \{2,4,8,16\} and a range of core dime…

2019-11-05abs ↗pdf ↗

The herd behavior of returns is investigated in Korean futures exchange market. It is obtained that the probability distribution of returns for three types of herding parameter scales as a power law RβR^{-β} with the exponents β=3.6 β=3.6(KTB203) and 2.9(KTB209) in two kinds of Korean treasury bond. For our case since the…

2003-04-07abs ↗pdf ↗

A new multi-factor model improves commodity pricing accuracy.

problem Enhancing accuracy in commodity pricing by integrating multiple risk factors.
method A four-factor model using Kalman filter for simultaneous estimation and state variable filtering.
result The four-factor model outperforms existing models in capturing futures term structures and crude oil pricing.