arXiv · arXiv q-fin · 2019
Anomalous diffusions arise as scaling limits of continuous-time random walks (CTRWs) whose innovation times are distributed according to a power law. The impact of a non-exponential waiting time does not vanish with time and leads to different distribution spread rates compared to standard models. In financial modelling this has been used to accommodate for random trade duration in the tick-by-tick price process. We …
Antoine Jacquier, Lorenzo Torricelli
arXiv · arXiv q-fin · 2023
At the peak of the tech bubble, only 0.57% of market valuation comes from dividends in the next year. Taking the ratio of total market value to the value of one-year dividends, we obtain a valuation-based duration of 175 years. In contrast, at the height of the global financial crisis, more than 2.2% of market value is from dividends in the next year, implying a duration of 46 years. What drives valuation duration? W…
Ye Li, Chen Wang
arXiv · arXiv · 2026
This paper presents a method for forecasting limit order book durations using a self-exciting flexible residual point process. High-frequency events in modern exchanges exhibit heavy-tailed interarrival times, posing a significant challenge for accurate prediction. The proposed approach incorporates the empirical distributional features of interarrival times while preserving the self-exciting and decay structure. Thi…
Kyungsub Lee
arXiv · arXiv q-fin · 2025
To trade tokens in cryptoeconomic systems, automated market makers (AMMs) typically rely on liquidity providers (LPs) that deposit tokens in exchange for rewards. To profit from such rewards, LPs must use effective liquidity provisioning strategies. However, LPs lack guidance for developing such strategies, which often leads them to financial losses. We developed a measurement model based on impermanent loss to analy…
Thanos Drossos, Daniel Kirste, Niclas Kannengießer, Ali Sunyaev
arXiv · arXiv q-fin · 2013
We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correlations between spreads and Treasury twists reversed recently, which is likely attributable to the Fe…
Arthur M. Berd, Elena Ranguelova, Antonio Baldaque da Silva
arXiv · arXiv · 2026
This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric and Machine Learning (ML) approaches. We compare classical models (e.g., Dynamic Nelson-Siegel (DNS) and Principal Component Analysis (PCA)) with different Neural Network (NN) architectures, including those inspired by the classical models, on the U.S. Treasury …
Tobias Lausser, Joao Eduardo Vuolo, Rudi Zagst
arXiv · arXiv q-fin · 2024
We have designed an innovative portfolio rebalancing mechanism termed the Cascading Waterfall Round Robin Mechanism. This algorithmic approach recommends an ideal size and number of trades for each asset during the periodic rebalancing process, factoring in the gas fee and slippage. The essence of the model we have created gives indications regarding whether trades should be made on individual assets depending on the…
Ravi Kashyap
arXiv · arXiv q-fin · 2016
We develop a fundamentally different stochastic dynamic programming model of trading costs. Built on a strong theoretical foundation, our model provides insights to market participants by splitting the overall move of the security price during the duration of an order into the Market Impact (price move caused by their actions) and Market Timing (price move caused by everyone else) components. We derive formulations o…
Ravi Kashyap
arXiv · arXiv q-fin · 2025
We present the unified market-based description of returns and variances of the trades with shares of a particular security, of the trades with shares of all securities in the market, and of the trades with the market portfolio. We consider the investor who doesn't trade the shares of his portfolio he collected at time t0 in the past. The investor observes the time series of the current trades with all securities mad…
Victor Olkhov
arXiv · arXiv q-fin · 2024
Recent deep reinforcement learning (DRL) methods in finance show promising outcomes. However, there is limited research examining the behavior of these DRL algorithms. This paper aims to investigate their tendencies towards holding or trading financial assets as well as purchase diversity. By analyzing their trading behaviors, we provide insights into the decision-making processes of DRL models in finance application…
Alireza Mohammadshafie, Akram Mirzaeinia, Haseebullah Jumakhan, Amir Mirzaeinia
arXiv · arXiv q-fin · 2022
Crypto-currency market uncertainty drives the need to find adaptive solutions to maximise gain or at least to avoid loss throughout the periods of trading activity. Given the high dimensionality and complexity of the state-action space in this domain, it can be treated as a "Narrow AGI" problem with the scope of goals and environments bound to financial markets. Adaptive Multi-Strategy Agent approach for market-makin…
Ali Raheman, Anton Kolonin, Alexey Glushchenko, Arseniy Fokin, Ikram Ansari
arXiv · arXiv q-fin · 2018
Financial markets show a number of non-stationarities, ranging from volatility fluctuations over ever changing technical and regulatory market conditions to seasonalities. On the other hand, financial markets show various stylized facts which are remarkably stable. It is thus an intriguing question to find out how these stylized facts emerge. As a first example, we here investigate how the bid-ask-spread between best…
Sebastian M. Krause, Jonas A. Fiegen, Thomas Guhr
arXiv · arXiv q-fin · 2014
This paper builds a model of high-frequency equity returns by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in ordinary clock time and in trade time. We show that when controlling for pre-scheduled market news events, trade-time returns of the highly liquid near-mo…
Eric M. Aldrich, Indra Heckenbach, Gregory Laughlin
arXiv · arXiv q-fin · 2014
We build an agent-based model to study how the interplay between low- and high-frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates flash crashes. In the model, low-frequency agents adopt trading rules based on chronological time and can switch between fundamentalist and chartist strategies. On the contrary, high-fre…
Sandrine Jacob Leal, Mauro Napoletano, Andrea Roventini, Giorgio Fagiolo
arXiv · arXiv q-fin · 2013
In this paper, we study the dynamics of absolute return, trading volume and bid-ask spread after the trading halts using high-frequency data from the Shanghai Stock Exchange. We deal with all three types of trading halts, namely intraday halts, one-day halts and inter-day halts, of 203 stocks in Shanghai Stock Exchange from August 2009 to August 2011. We find that absolute return, trading volume, and in case of bid-a…
Hai-Chuan Xu, Wei Zhang, Yi-Fang Liu
arXiv · arXiv q-fin · 2006
In this paper, the survival function of waiting times between orders and the corresponding trades in a double-auction market is studied both by means of experiments and of empirical data. It turns out that, already at the level of order durations, the survival function cannot be represented by a single exponential, thus ruling out the hypothesis of constant activity during trading. This fact has direct consequences f…
Enrico Scalas, Taisei Kaizoji, Michael Kirchler, Juergen Huber, Alessandra Tedeschi
arXiv · arXiv · 2017
Cash collateral is perfect in that it provides simultaneous counterparty credit risk protection and derivatives funding. Securities are imperfect collateral, because of collateral segregation or differences in CSA haircuts and repo haircuts. Moreover, the collateral rate term structure is not observable in the repo market, for derivatives netting sets are perpetual while repo tenors are typically in months. This arti…
Wujiang Lou
arXiv · arXiv · 2026
Generating synthetic financial time series that preserve the statistical properties of real market data is essential for stress testing, risk model validation, and scenario design. Existing approaches struggle to simultaneously reproduce heavy-tailed distributions, negligible linear autocorrelation, and persistent volatility clustering. We developed a hybrid hidden Markov framework that discretized excess growth rate…
Abdulrahman Alswaidan, Jeffrey D. Varner