arXiv · arXiv · 2025
Concentrated Liquidity Market Makers (CLMMs) represent a fundamental innovation in market microstructure, transforming liquidity provision from passive portfolio allocation to active risk management. This evolution creates significant challenges for performance evaluation and strategy optimization, particularly due to the absence of comprehensive historical liquidity data. We address these challenges through a novel …
Andrey Urusov, Rostislav Berezovskiy, Anatoly Krestenko, Andrei Kornilov, Yury Yanovich
arXiv · arXiv · 2024
Performance attribution analysis, defined as the process of explaining the drivers of the excess performance of an investment portfolio against a benchmark, stands as a significant feature of portfolio management and plays a crucial role in the investment decision-making process, particularly within the fund management industry. Rooted in a solid financial and mathematical framework, the importance and methodologies …
Bruno de Melo, Jamiel Sheikh
arXiv · arXiv · 2023
We develop a method to decompose the PnL of a portfolio of assets into four parts: (a) PnL due to FX rate changes, (b) PnL due to interest rate changes, (c) carry gain due to time passing, (d) PnL due to residual market risk changes (credit risk, liquidity risk, volatility risk etc.). We demonstrate the usefulness of our approach by decomposing the performance of an FX- and interest rate-hedged negative basis positio…
Jan-Frederik Mai
arXiv · arXiv · 2020
We discuss and extend a powerful, geometric framework to represent the set of portfolios, which identifies the space of asset allocations with the points lying in a convex polytope. Based on this viewpoint, we survey certain state-of-the-art tools from geometric and statistical computing in order to handle important and difficult problems in digital finance. Although our tools are quite general, in this paper we focu…
Apostolos Chalkis, Emmanouil Christoforou, Ioannis Z. Emiris, Theodore Dalamagas
arXiv · arXiv · 2026
Multinomial probit choice probabilities over n alternatives are Gaussian orthant integrals, computed by simulation for thirty years, one expensive integral per alternative. Inversion, which is to say determining item attractiveness consistent with a prescribed choice probability vector, is even more difficult and has been considered impractical for correlated contests when n is large. Yet here, for families lying wit…
Peter Cotton
arXiv · arXiv · 2026
We present a large scale benchmark of modern deep learning architectures for a financial time series prediction and position sizing task, with a primary focus on Sharpe ratio optimization. Evaluating linear models, recurrent networks, transformer based architectures, state space models, and recent sequence representation approaches, we assess out of sample performance on a daily futures dataset spanning commodities, …
Adir Saly-Kaufmann, Kieran Wood, Jan Peter-Calliess, Stefan Zohren
arXiv · arXiv · 2025
Through its initiative known as the Climate Change Act (2008), the Government of the United Kingdom encourages corporations to enhance their environmental performance with the significant aim of reducing targeted greenhouse gas emissions by the year 2050. Previous research has predominantly assessed this encouragement favourably, suggesting that improved environmental performance bolsters governmental efforts to prot…
Probowo Erawan Sastroredjo, Marcel Ausloos, Polina Khrennikova
arXiv · arXiv · 2025
In a rapidly evolving landscape marked by continuous change and complex challenges, effective cash management stands as a cornerstone for ensuring business sustainability and driving performance. To address these pressing demands, cash managersare increasingly turning to innovative financing solutions such as venture capital, green finance, crowdfunding, advanced services from Pan-African banks, and blockchain techno…
Nohayla Badrane, Zineb Bamousse
arXiv · arXiv · 2024
This article applies natural language processing (NLP) to extract and quantify textual information to predict stock performance. Using an extensive dataset of Chinese analyst reports and employing a customized BERT deep learning model for Chinese text, this study categorizes the sentiment of the reports as positive, neutral, or negative. The findings underscore the predictive capacity of this sentiment indicator for …
Rui Liu, Jiayou Liang, Haolong Chen, Yujia Hu
arXiv · arXiv · 2024
Credit scores are critical for allocating consumer debt in the United States, yet little evidence is available on their performance. We benchmark a widely used credit score against a machine learning model of consumer default and find significant misclassification of borrowers, especially those with low scores. Our model improves predictive accuracy for young, low-income, and minority groups due to its superior perfo…
Stefania Albanesi, Domonkos F. Vamossy
arXiv · arXiv · 2024
This paper introduces a novel methodology for index return forecasting, blending highly correlated stock prices, advanced deep learning techniques, and intricate factor integration. Departing from conventional cap-weighted approaches, our innovative framework promises to reimagine traditional methodologies, offering heightened diversification, amplified performance capture, and nuanced market depiction. At its core l…
Tian Tian, Ricky Cooper, Jiahao Deng, Qingquan Zhang
arXiv · arXiv · 2023
We propose a discrete-time econometric model that combines autoregressive filters with factor regressions to predict stock returns for portfolio optimisation purposes. In particular, we test both robust linear regressions and general additive models on two different investment universes composed of the Dow Jones Industrial Average and the Standard & Poor's 500 indexes, and we compare the out-of-sample performances of…
Davide Lauria, W. Brent Lindquist, Svetlozar T. Rachev
arXiv · arXiv · 2023
Designing an optimum portfolio for allocating suitable weights to its constituent assets so that the return and risk associated with the portfolio are optimized is a computationally hard problem. The seminal work of Markowitz that attempted to solve the problem by estimating the future returns of the stocks is found to perform sub-optimally on real-world stock market data. This is because the estimation task becomes …
Abhiraj Sen, Jaydip Sen
arXiv · arXiv · 2023
Financial performance management is at the core of business management and has historically relied on financial ratio analysis using Balance Sheet and Income Statement data to assess company performance as compared with competitors. Little progress has been made in predicting how a company will perform or in assessing the risks (probabilities) of financial underperformance. In this study I introduce a new set of fina…
Ricardo Cuervo
arXiv · arXiv · 2023
This research investigates the multifaceted relationship underlying capital structure dynamics along with financial performance as a result of mergers and acquisitions, or M&As, in Indian banks. In the face of increasing competition, banks have deliberately embraced M&A as a strategy of improving commercial prospects and maintaining financial stability. The primary goal of this study is to examine the changes in the …
Kurada T S S Satyanarayana, Addada Narasimha Rao, Kumpatla jaya surya
arXiv · arXiv · 2023
The US stock market experienced instability following the recession (2007-2009). COVID-19 poses a significant challenge to US stock traders and investors. Traders and investors should keep up with the stock market. This is to mitigate risks and improve profits by using forecasting models that account for the effects of the pandemic. With consideration of the COVID-19 pandemic after the recession, two machine learning…
Reza Nematirad, Amin Ahmadisharaf, Ali Lashgari
arXiv · arXiv · 2023
Designing dynamic portfolio insurance strategies under market conditions switching between two or more regimes is a challenging task in financial economics. Recently, a promising approach employing the value-at-risk (VaR) measure to assign weights to risky and riskless assets has been proposed in [Jiang C., Ma Y. and An Y. "The effectiveness of the VaR-based portfolio insurance strategy: An empirical analysis" , Inte…
Peyman Alipour, Ali Foroush Bastani
arXiv · arXiv · 2023
Credit risk is a crucial topic in the field of financial stability, especially at this time given the profound impact of the ongoing pandemic on the world economy. This study provides insight into the impact of credit risk on the financial performance of 26 commercial banks in Vietnam for the period from 2006 to 2016. The financial performance of commercial banks is measured by return on assets (ROA), return on equit…
Ha Nguyen