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This paper introduces a novel robust trading paradigm, called \textit{multi-double linear policies}, situated within a \textit{generalized} lattice market. Distinctively, our framework departs from most existing robust trading strategies,…

Portfolio Management · Quantitative Finance 2025-04-18 Chung-Han Hsieh , Xin-Yu Wang

We consider a financial market in which traders potentially face restrictions in trading some of the available securities. Traders are heterogeneous with respect to their beliefs and risk profiles, and the market is assumed thin: traders…

Economics · Quantitative Finance 2023-12-06 Michail Anthropelos , Constantinos Kardaras

Investors trade shifting prices, portfolio values, and in turn their ability to borrow. Concentrated ownership, high price impact and low collateral requirements are propitious for arbitrage.

Portfolio Management · Quantitative Finance 2022-09-13 Bernhard K Meister

Financial markets across all asset classes are known to exhibit trends. These trends have been exploited by traders for decades. Here, we empirically measure when trends revert, based on 30 years of daily futures prices for equity indices,…

Statistical Finance · Quantitative Finance 2021-07-26 Christof Schmidhuber

The fundamental theorem behind financial markets is that stock prices are intrinsically complex and stochastic. One of the complexities is the volatility associated with stock prices. Volatility is a tendency for prices to change…

Statistical Finance · Quantitative Finance 2023-11-21 Leonard Mushunje , Maxwell Mashasha , Edina Chandiwana

Many cryptographic protocols are intended to coordinate state changes among principals. Exchange protocols coordinate delivery of new values to the participants, e.g. additions to the set of values they possess. An exchange protocol is fair…

Cryptography and Security · Computer Science 2009-10-23 Joshua D. Guttman

We present an approach, based on deep neural networks, that allows identifying robust statistical arbitrage strategies in financial markets. Robust statistical arbitrage strategies refer to trading strategies that enable profitable trading…

Computational Finance · Quantitative Finance 2024-02-27 Ariel Neufeld , Julian Sester , Daiying Yin

Foreign exchange is the largest financial market in the world, and it is also one of the most volatile markets. Technical analysis plays an important role in the forex market and trading algorithms are designed utilizing machine learning…

Statistical Finance · Quantitative Finance 2020-08-24 Zezheng Zhang , Matloob Khushi

We investigate the optimal execution of contracts that are used in merger\&acquisition deals. We consider cash-settled and physically delivered contracts between a broker and a counterpart. Contracts are linear (total returns swaps),…

Mathematical Finance · Quantitative Finance 2026-04-24 Emilio Barucci , Yuheng Lan , Daniele Marazzina

Cryptocoins (i.e., Bitcoin, Ether, Litecoin) are tradable digital assets. Ownerships of cryptocoins are registered on distributed ledgers (i.e., blockchains). Secure encryption techniques guarantee the security of the transactions…

Computational Engineering, Finance, and Science · Computer Science 2024-09-06 Pasquale De Rosa , Pascal Felber , Valerio Schiavoni

Prediction markets are powerful mechanisms for information aggregation, but existing designs are optimized for single-event contracts. In practice, traders frequently express beliefs about joint outcomes - through parlays in sports,…

Computational Engineering, Finance, and Science · Computer Science 2026-05-21 Ranvir Rana , Viraj Nadkarni , Niusha Moshrefi , Pramod Viswanath

The time proximity of high-frequency trades can contain a salient signal. In this paper, we propose a method to classify every trade, based on its proximity with other trades in the market within a short period of time, into five types. By…

Trading and Market Microstructure · Quantitative Finance 2024-03-15 Yutong Lu , Gesine Reinert , Mihai Cucuringu

An expanding literature articulates the view that Taylor rules are helpful in predicting exchange rates. In a changing world however, Taylor rule parameters may be subject to structural instabilities, for example during the Global Financial…

Statistical Finance · Quantitative Finance 2014-03-05 Joseph Byrne , Dimitris Korobilis , Pinho Ribeiro

Crowded trades by similarly trading peers influence the dynamics of asset prices, possibly creating systemic risk. We propose a market clustering measure using granular trading data. For each stock the clustering measure captures the degree…

Statistical Finance · Quantitative Finance 2021-03-16 Marc van Kralingen , Diego Garlaschelli , Karolina Scholtus , Iman van Lelyveld

We consider a model of matching in trading networks in which firms can enter into bilateral contracts. In trading networks, stable outcomes, which are immune to deviations of arbitrary sets of firms, may not exist. We define a new solution…

Computer Science and Game Theory · Computer Science 2021-10-05 Tamás Fleiner , Zsuzsanna Jankó , Akihisa Tamura , Alexander Teytelboym

We investigate how price variations of a stock are transformed into profits and losses (P&Ls) of a trend following strategy. In the frame of a Gaussian model, we derive the probability distribution of P&Ls and analyze its moments (mean,…

Statistical Finance · Quantitative Finance 2020-01-03 D. S. Grebenkov , J. Serror

In this paper, a new approach to bivariate modeling of autoregressive conditional duration (ACD) models is proposed. Specifically, we consider the joint modeling of durations and the number of transactions made during the spell. The…

Applications · Statistics 2023-06-27 Helton Saulo , Suvra Pal , Roberto Vila

Using a model of wealth distribution where traders are characterized by quenched random saving propensities and trade among themselves by bipartite transactions, we mimic the enhanced rates of trading of the rich by introducing the…

General Finance · Quantitative Finance 2015-05-14 Abhijit Chakraborty , S. S. Manna

In the context of investment analysis, we formulate an abstract online computing problem called a planning game and develop general tools for solving such a game. We then use the tools to investigate a practical buy-and-hold trading problem…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Gen-Huey Chen , Ming-Yang Kao , Yuh-Dauh Lyuu , Hsing-Kuo Wong

Organizations typically train large models individually. This is costly and time-consuming, particularly for large-scale foundation models. Such vertical production is known to be suboptimal. Inspired by this economic insight, we ask…

Machine Learning · Computer Science 2023-12-11 Tzu-Heng Huang , Harit Vishwakarma , Frederic Sala
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