arXiv · arXiv q-fin · 2025
Understanding how market participants react to shocks like scheduled macroeconomic news is crucial for both traders and policymakers. We develop a calibrated data generation process DGP that embeds four stylized trader archetypes retail, pension, institutional, and hedge funds into an extended CAPM augmented by CPI surprises. Each agents order size choice is driven by a softmax discrete choice rule over small, medium…
Haochuan Wang
arXiv · arXiv q-fin · 2018
The composition of natural liquidity has been changing over time. An analysis of intraday volumes for the S&P500 constituent stocks illustrates that (i) volume surprises, i.e., deviations from their respective forecasts, are correlated across stocks, and (ii) this correlation increases during the last few hours of the trading session. These observations could be attributed, in part, to the prevalence of portfolio tra…
Seungki Min, Costis Maglaras, Ciamac C. Moallemi
arXiv · arXiv q-fin · 2026
Decomposing market impact as the difference between realized and counterfactual returns, and requiring both to be diffusive, yields a structural identity that restricts admissible impact dynamics at the level of individual participants. This constraint implies the square-root law in the information-neutral regime and a crossover toward linear impact under strong informational coupling, consistent with empirical obser…
Julius F. Bonart
arXiv · arXiv q-fin · 2021
Advances in Reinforcement Learning (RL) span a wide variety of applications which motivate development in this area. While application tasks serve as suitable benchmarks for real world problems, RL is seldomly used in practical scenarios consisting of abrupt dynamics. This allows one to rethink the problem setup in light of practical challenges. We present Trade Execution using Reinforcement Learning (TradeR) which a…
Karush Suri, Xiao Qi Shi, Konstantinos Plataniotis, Yuri Lawryshyn
arXiv · arXiv q-fin · 2009
We study the behavior of U.S. markets both before and after U.S. Federal Open Market Committee (FOMC) meetings, and show that the announcement of a U.S. Federal Reserve rate change causes a financial shock, where the dynamics after the announcement is described by an analogue of the Omori earthquake law. We quantify the rate n(t) of aftershocks following an interest rate change at time T, and find power-law decay whi…
Alexander M. Petersen, Fengzhong Wang, Shlomo Havlin, H. Eugene Stanley
arXiv · arXiv q-fin · 2020
We consider shared listings on two South African equity exchanges: the Johannesburg Stock Exchange (JSE) and the A2X Exchange. A2X is an alternative exchange that provides for both shared listings and new listings within the financial market ecosystem of South Africa. From a science perspective it provides the opportunity to compare markets trading similar shares, in a similar regulatory and economic environment, but…
Ivan Jericevich, Patrick Chang, Tim Gebbie
arXiv · arXiv q-fin · 2025
Decentralized prediction markets (DePMs) allow open participation in event-based wagering without fully relying on centralized intermediaries. We review the history of DePMs which date back to 2011 and includes hundreds of proposals. Perhaps surprising, modern DePMs like Polymarket deviate materially from earlier designs like Truthcoin and Augur v1. We use our review to present a modular workflow comprising eight sta…
Nahid Rahman, Joseph Al-Chami, Jeremy Clark
arXiv · arXiv · 2026
An important question for an algo trader working an order is to understand if their actions are moving the market against them -- i.e., causing market impact. The conventional answer usually is one of two: (i) monitor price slippage in real-time, potentially reducing adverse activity with increased slippage, or (ii) do away with dynamic trading adjustments and rely on semi-static rules based on ex-post estimates of s…
Ilija I Zovko
arXiv · arXiv q-fin · 2023
It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor's attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little …
Leilei Shi, Bing Han, Yingzi Zhu, Liyan Han, Yiwen Wang
arXiv · arXiv q-fin · 2022
In the problem of online portfolio selection as formulated by Cover (1991), the trader repeatedly distributes her capital over $ d $ assets in each of $ T > 1 $ rounds, with the goal of maximizing the total return. Cover proposed an algorithm, termed Universal Portfolios, that performs nearly as well as the best (in hindsight) static assignment of a portfolio, with an $ O(d\log(T)) $ regret in terms of the logarithmi…
Rémi Jézéquel, Dmitrii M. Ostrovskii, Pierre Gaillard
arXiv · arXiv q-fin · 2020
Prediction and quantification of future volatility and returns play an important role in financial modelling, both in portfolio optimization and risk management. Natural language processing today allows to process news and social media comments to detect signals of investors' confidence. We have explored the relationship between sentiment extracted from financial news and tweets and FTSE100 movements. We investigated…
Justina Deveikyte, Helyette Geman, Carlo Piccari, Alessandro Provetti
arXiv · arXiv q-fin · 2018
Vanna-Volga is a popular method for the interpolation/extrapolation of volatility smiles. The technique is widely used in the FX markets context, due to its ability to consistently construct the entire Lognormal smile using only three Lognormal market quotes. However, the derivation of the Vanna-Volga method itself is free of distributional assumptions. With this is mind, it is surprising there have been no attempts …
Volodymyr Perederiy
arXiv · arXiv q-fin · 2018
It has been widely observed that capitalization-weighted indexes can be beaten by surprisingly simple, systematic investment strategies. Indeed, in the U.S. stock market, equal-weighted portfolios, random-weighted portfolios, and other naive, non- optimized portfolios tend to outperform a capitalization-weighted index over the long term. This outperformance is generally attributed to beneficial factor exposures. Here…
Adrian Banner, Robert Fernholz, Vassilios Papathanakos, Johannes Ruf, David Schofield
arXiv · arXiv q-fin · 2017
The purpose of this paper is to showcase trading strategies that give solutions to three difficult and intriguing problems in business finance, economics and statistics. The paper discusses trading strategies for both commodities and stocks but the main focus is on stock market trading at the New York Stock Exchange. Problem 1: Buy Low and Sell High. The buy low and sell high problem can be summarized like this: supp…
Lanh Tran
arXiv · arXiv q-fin · 2017
In financial markets, greater volatility is usually considered synonym of greater risk and instability. However, large market downturns and upturns are often preceded by long periods where price returns exhibit only small fluctuations. To investigate this surprising feature, here we propose using the mean first hitting time, i.e. the average time a stock return takes to undergo for the first time a large negative or …
Davide Valenti, Giorgio Fazio, Bernardo Spagnolo