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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.

168,742 papers · 148 categories

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48 results for funding profit

Study estimates Medallion's compounded return before fees at 31.8%.

problem Incorrectly using yearly returns for compounding leads to overestimation of fund performance.
method Used fund sizes and trading profits to estimate compounded return; used manager's wealth as proxy for Simons.
result Annualized compounded return of Medallion before fees is likely under 35%

The paper uses clustering and integer programming to optimize stock selection for investment funds.

problem Maximizing profits and minimizing risk in stock markets.
method Data-oriented analysis and clustering techniques with integer programming.
result Reconstructed NASDAQ 100 index fund example demonstrates effectiveness.

In this note we sketch an initial tentative approach to funding costs analysis and management for contracts with bilateral counterparty risk in a simplified setting. We depart from the existing literature by analyzing the issue of funding costs and benefits under the assumption that the associated risks cannot be hedge…

2014-10-08abs ↗pdf ↗

The model of this paper gives a convenient strategy that a bank in the federal funds market can use in order to maximize its profit in a contemporaneous reserve requirement (CRR) regime. The reserve requirements are determined by the demand deposit process, modelled as a Brownian motion with drift. We propose a new mod…

2015-07-15abs ↗pdf ↗

Study finds WACC negatively impacts firm profitability in Bangladesh's food industry.

problem Determining the impact of Weighted Average Cost of Capital (WACC) on firm profitability.
method Fixed Effects Panel Regression Model using 12 food and allied industry companies from 2005-2019.
result WACC negatively correlates with firm profitability (ROA), significant relationship.

Valuation adjustments are nowadays a common practice to include credit and liquidity effects in option pricing. Funding costs arising from collateral procedures, hedging strategies and taxes are added to option prices to take into account the production cost of financial contracts so that a profitability analysis can b…

2019-06-06abs ↗pdf ↗

This paper proposes a two-stage scoring approach to help lenders decide their fund allocations in the peer-to-peer (P2P) lending market. The existing scoring approaches focus on only either probability of default (PD) prediction, known as credit scoring, or profitability prediction, known as profit scoring, to identify…

2018-10-05abs ↗pdf ↗

Study examines impact of capital structure on Indian auto companies' profitability.

problem Understanding the impact of capital structure on profitability of Indian auto companies.
method Used fixed and random effect models with 10 years of data from 17 companies.
result Optimal capital structure improves company performance and maintains capital adequacy.

We build a simple model of leveraged asset purchases with margin calls. Investment funds use what is perhaps the most basic financial strategy, called "value investing", i.e. systematically attempting to buy underpriced assets. When funds do not borrow, the price fluctuations of the asset are normally distributed and u…

2009-08-11abs ↗pdf ↗

We point out a simple equities trading strategy that allows a sufficiently large, market-neutral, quantitative hedge fund to achieve outsized returns while simultaneously contributing significantly to increasing global wealth inequality. Overnight and intraday return distributions in major equity indices in the United …

2018-11-12abs ↗pdf ↗

This paper aims to make a new contribution to the study of lifetime ruin problem by considering investment in two hedge funds with high-watermark fees and drift uncertainty. Due to multi-dimensional performance fees that are charged whenever each fund profit exceeds its historical maximum, the value function is expecte…

2019-09-03abs ↗pdf ↗

Online trading platforms manipulate profits and losses, causing 82% of retail traders to lose money.

problem Manipulation of online trading platforms leading to financial losses for retail traders.
method Independent recording of trade details using REST API responses, comparison with broker reviews.
result 82% of retail traders lose money due to platform technical issues.

This paper explores deep learning for financial trading, integrating sentiment analysis.

problem Maximizing profit and minimizing loss in financial trading.
method Supervised and reinforcement learning schemes, integrating sentiment analysis.
result Demonstrates the effectiveness of deep learning methods in financial trading.

Auto..gov uses RL to automate DeFi governance, improving security and profitability.

problem Manual DeFi governance is prone to human bias and financial risks.
method Auto..gov employs a deep Q-network reinforcement learning strategy for semi-automated parameter adjustments.
result Auto..gov outperforms traditional governance methods by at least 14% in terms of protocol profitability.

Optimizes stock portfolios with profit, risk, and sustainability.

problem Balancing profit, risk, and sustainability in stock portfolio management.
method Developed a novel utility function combining Sharpe ratio and ESG scores; used genetic algorithm for optimization.
result System outperforms traditional reinforcement learning methods and improves on risk and sustainability metrics.

The paper explains the fair basis in bond-CDS trading during financial crises.

problem Large basis trading losses during financial crises are not explained by reduced form models.
method Dynamic spread model with bond repo financing, economic capital approach.
result Unhedged and unhedgeable residual jump to default risk exists, affecting fair basis level.

Research proposes a decentralized invoice discounting system using Kelly criterion.

problem Persistent funding gap for SMEs and inefficiencies in traditional factoring.
method Automated Market Maker (AMM) with Kelly criterion for premium calculation.
result Resilient decentralized system with optimal profit distribution policies.

Agent learns to trade currency pairs with improved risk management.

problem Improving systematic FX trading performance with online transfer learning.
method Online inductive transfer learning using feature representation from Gaussian mixture model to a reinforcement learning agent.
result Annualized portfolio information ratio of 0.52, compound return of 9.3%.

Study optimal control strategy for hedge funds managers with PSAHARA utility family.

problem Optimizing risk and reward in incomplete markets with non-monotone risk aversion and convex compensation.
method Introduced PSAHARA utility family to model non-monotone risk aversion and convex compensation. Proved concavification techniques for non-concave utility functions. Derived explicit optimal control strategy.
result PSAHARA utility induces risk-taking behavior even with convex compensation, leading to high returns and volatility.

Whether you trade futures for yourself or a hedge fund, your strategy is counted. Long and short position limits make the number of unique strategies finite. Formulas of the numbers of strategies, transactions, do nothing actions are derived. A discrete distribution of actions, corresponding probability mass, cumulativ…

2017-12-19abs ↗pdf ↗

Bielecki and Rutkowski (2014) introduced and studied a generic nonlinear market model, which includes several risky assets, multiple funding accounts and margin accounts. In this paper, we examine the pricing and hedging of contract both from the perspective of the hedger and the counterparty with arbitrary initial end…

2014-10-02abs ↗pdf ↗

We consider and extend the adversarial agent-based learning approach of Gy{ö}rfi {\it et al} to the situation of zero-cost portfolio selection implemented with a quadratic approximation derived from the mutual fund separation theorems. The algorithm is applied to daily sampled sequential Open-High-Low-Close data and se…

2016-05-15abs ↗pdf ↗
Ponzi Fundsq-fin.GN

Funds inflate their returns due to price pressure, leading to wealth reallocation and market crashes.

problem Funds inflate their returns due to price pressure, leading to wealth reallocation and market crashes.
method Decomposed fund returns into price pressure and fundamental components, and identified the impact of price chasing on fund flows.
result Funds' self-inflated returns lead to wealth reallocation and market crashes, and can be predicted by fund illiquidity.

This paper supplies two possible resolutions of Fortune's (2000) margin-loan pricing puzzle. Fortune (2000) noted that the margin loan interest rates charged by stock brokers are very high in relation to the actual (low) credit risk and the cost of funds. If we live in the Black-Scholes world, the brokers are presumabl…

2019-06-03abs ↗pdf ↗

This report was originally written as an industry white paper on Hedge Funds. This paper gives an overview to Hedge Funds, with a focus on risk management issues. We define and explain the general characteristics of Hedge Funds, their main investment strategies and the risk models employed. We address the problems in H…

2009-04-17abs ↗pdf ↗

Paper finds funding rates on BitMEX predict Bitcoin inverse swap contracts.

problem Understanding the relationship between BitMEX funding rates and Bitcoin derivatives.
method Examined Heteroskedasticity of funding rates, established Granger causality, developed GARCH models for prediction.
result Funding rates on BitMEX predict Bitcoin inverse swap contracts.

Study uses deep learning for pairs trading in Polish equities, achieving profits in 2017-2019.

problem Statistical arbitrage in Polish equities market using traditional methods.
method Deep learning (LSTMs) for asset replication, PCA for risk factor analysis, Ornstein Uhlenbeck process for residual modeling.
result Deep learning methods, especially LSTMs, show promise for profitable trading in Polish equities.

Deep learning models predict mutual funds' performance better than traditional methods.

problem Predicting mutual funds' performance accurately.
method Deep learning models (LSTM, GRUs) trained with Bayesian optimization and ensemble methods.
result Ensemble method of LSTM and GRUs achieves the highest accuracy in forecasting mutual funds' Sharpe ratios.

This paper optimizes perpetual contract liquidity by accounting for funding rates.

problem Optimal liquidity provision for perpetual contracts with stochastic funding rates.
method Formulated a control problem, solved with a HJB scheme, and calibrated on real data.
result Funding-aware market making improves performance and reduces inventory risk.

Study finds Indian mutual funds adjust cash holdings based on inflows, impacting stock purchases.

problem Active liquidity management by mutual funds in India.
method Examined cash holdings and stock purchases of Indian equity mutual funds.
result Funds with active liquidity choices outperform, highlighting the importance of this strategy.

Blockchain protocol improves traditional mutual funds with performance fees and investor protection.

problem Operational issues and performance fees in traditional mutual funds.
method Developed a blockchain protocol that integrates features of mutual funds and hedge funds.
result Blockchain can simplify performance fee calculations and protect investors.

Structuring a viable pension plan is a problem that arises in the study of financial contracts pricing and bears special importance these days. Deterministic pension models often rely on projections that are based on several assumptions concerning the "average" long-time behavior of the stock market. Our aim here is to…

2014-07-02abs ↗pdf ↗

Study uses machine learning and PolyModel to improve hedge fund performance.

problem Improving hedge fund investment performance with machine learning.
method Integration of machine learning techniques, PolyModel feature selection, and analysis of fund size.
result Machine learning enhances cumulative returns but increases annual volatility.

In this paper we investigate the relationship between Funding Value Adjustment (FVA) and Net Stable Funding Ratio (NSFR). FVA is defined in a consistent way with NSFR such that the new framework of FVA monitors the costs due to keeping NSFR at an acceptable level, as well. In addition, the problem of choosing the optim…

2017-01-01abs ↗pdf ↗

Study examines Indian equity mutual funds' investment style and risk-shifting.

problem Understanding how Indian equity mutual funds' investment styles affect their returns.
method Estimating size and style beta coefficients, identifying breakpoints, analyzing investment styles, and assessing risk-shifting intensity.
result Funds can enhance returns by shifting to high-return styles like Small Value and Small Blend.