New strategy uses consumer and government actions for climate change.
problem Insufficient low-carbon investments despite ethical savings potential.
method Voluntary low-carbon fund and ethical investments for sustainable development.
result Potential for global climate change response through individual actions and investments.
The key characteristic of a true free market economy is that exchanges are entirely voluntary. When there is a monopoly in the creation of currency as we have in today's markets, you no longer have a true free market. Features of the current economic system such as central banking and taxation would be nonexistent in a…
Research shows higher damages may encourage more disclosure in corporate disputes.
problem How to resolve disputes over undisclosed material events in a way that encourages voluntary disclosure.
method Dynamic continuous-time model of management's equilibrium disclosure decision.
result Increased damages may lead to an endogenous increase in voluntary disclosure.
Firms disclosing positive earnings surprises are more likely to disclose ESG information.
problem Transparency vs. performance in financial markets.
method Empirical analysis of earnings surprises and ESG disclosures.
result Positive earnings firms disclose more ESG information than negative earnings firms.
Model analyzes how firms balance full disclosure with selective disclosure to maintain a good reputation.
problem Managing reputation in financial markets through voluntary disclosure.
method Developed a dynamic model with two disclosure strategies: candid and sparing, using a piecewise-deterministic model.
result Firms are rewarded for full disclosure but may switch to selective disclosure to avoid potential downgrades.
Novel approach checks mutual fund style consistency with actual composition.
problem Ensuring mutual fund style consistency with actual fund composition.
method Time series decomposition of stock prices to analyze mutual fund composition.
result Notable deviations found between proclaimed fund style and actual composition.
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.
Investigates how NSFR affects FVA and formulates FVA as a shortest path problem.
problem Relationship between FVA and NSFR, and optimal funding strategy.
method Formulates FVA as a shortest path problem, calculates optimal funding decisions.
result Provides optimal funding decisions for minimum funding cost.
Collectivized funds need less initial capital to match individual funds, improving pension adequacy.
problem Determining optimal fund management for diverse investor needs.
method Modeling collectivized investment funds with realistic parameters and demonstrating their superiority over individual funds.
result Collectivized funds require less initial capital to match individual funds, enhancing pension adequacy.
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…
Study on CEF discount in Bangladesh, finds size and maturity impact, turnover negative.
problem Exploring the discount puzzle in closed-end mutual funds in Bangladesh.
method Fixed effects panel regression with diagnostic tests.
result Fund size and maturity positively impact CEF discount, turnover negatively impacts.
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.
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.
SRMF with high ESG ratings outperform during economic crises.
problem Performance of socially responsible mutual funds during economic downturns.
method Comparative analysis of SRMF with different ESG ratings.
result High ESG rated SRMF outperform low ESG rated SRMF during economic crises.
Target Date Funds may not adapt well, leading to poor performance.
problem Target Date Funds may not adapt to investors' needs effectively.
method Modeling with historical returns and bootstrap resampling to compare performance.
result Adaptive investment strategies significantly outperform Target Date Funds.
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.
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.
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.
Sparse portfolio strategy from mutual funds' favorite stocks in China A share market.
problem Building a sparse portfolio from mutual funds' favorite stocks in a market with limited fund information.
method Analyzed mutual fund favorite stocks, used portfolio optimizer with constraints, and compared different methods.
result Sparse portfolios consistently outperform the benchmark index 930950.CSI.
A fund manager invests both the fund's assets and own private wealth in separate but potentially correlated risky assets, aiming to maximize expected utility from private wealth in the long run. If relative risk aversion and investment opportunities are constant, we find that the fund's portfolio depends only on the fu…
Study uses topic modeling and sentiment analysis to uncover hedge fund performance insights.
problem Hedge fund opacity and limited disclosure make them hard to analyze.
method Applied topic modeling and sentiment analysis to hedge fund documents using DistilBERT and Top2Vec.
result Automated topic modeling and sentiment analysis can predict hedge fund performance.
Estimates growth loss in fund models and proposes a shrinkage method.
problem Estimating growth loss in fund models under frequentist and Bayesian estimation.
method Proposes a shrinkage method to target maximal growth with minimal deviation.
result Empirical evidence shows shrinkage gives a stable estimate closer to growth potential.
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…
Funding is a cost to trading desks that they see as an input. Current FVA-related literature reflects this by also taking funding costs as an input, usually constant, and always risk-neutral. However, this funding curve is the output from a Treasury point of view. Treasury must consider Regulatory-required liquidity bu…
New methods for equity fund selection and portfolio construction using mutual fund top holdings.
problem Classic equity fund selection and portfolio construction problems.
method Propose an easy-to-implement framework to produce a long-short portfolio from mutual fund top holdings.
result Generate impressive results and show statistical evidence.
Upper bounds on utility for managing heterogeneous collectivised funds.
problem Managing pension funds with diverse investor preferences and mortality.
method Axiomatic approach to define optimal management strategies.
result Asymptotically optimal strategies for maximizing investor utility.
The proprietary nature of Hedge Fund investing means that it is common practise for managers to release minimal information about their returns. The construction of a Fund of Hedge Funds portfolio requires a correlation matrix which often has to be estimated using a relatively small sample of monthly returns data which…
Exchange Traded Funds (ETFs) have been gaining increasing popularity in the investment community as is evidenced by the high growth both in the number of ETFs and their net assets since 2000. As ETFs are in nature similar to index mutual funds, in this paper we examined if this growing demand for ETFs can be explained …
The study quantifies the impact of fund miscategorization using machine learning.
problem The impact of fund miscategorization on investment decisions.
method Formulated as a distance-based outlier detection problem, used Random Forest based distance metric learning.
result Identified funds with strong relationship to future returns as outliers.
Machine learning categorizes mutual funds for better investment strategies.
problem Identifying similar mutual funds for diversified investment applications.
method Machine learning to learn and reproduce a well-regarded categorization system.
result Machine learning can learn and reproduce a categorization system that is widely regarded.
Binary funding impacts simplify derivative pricing models.
problem Complexity in derivative pricing due to varying lending/borrowing rates.
method Analyzes the binary nature of funding impacts leading to linear or semi-linear equations.
result Derivatives pricing simplifies when only one rate affects the payoff function.
A new method identifies similar mutual funds using graph learning.
problem Identifying similar mutual funds with nuanced portfolio similarities.
method Node2Vec machine learning method applied to a weighted bipartite network of funds and assets.
result Identifies structural similarity among mutual funds' portfolios.
Voluntary insurance contracts constitute a puzzle because they increase the expectation value of one party's wealth, whereas both parties must sign for such contracts to exist. Classically, the puzzle is resolved by introducing non-linear utility functions, which encode asymmetric risk preferences; or by assuming the p…
The paper analyzes fairness of compensation-based risk-sharing schemes for fund payouts.
problem Fair allocation of payouts in an endowment contingency fund.
method Analyzes two types of administrators and general non-negative loss distributions.
result General conditions for actuarial fairness are provided.
AI platforms disrupt investment by personalizing deal sourcing and insights.
problem Lack of scalable, personalized, and privacy-compliant deal sourcing and insights solutions.
method Development of in-house AI platforms that interact directly with funds and learn from interactions.
result AI platforms provide smarter, personalized use cases for funds, offering a competitive advantage.
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.
Study on pooled annuity funds and how initial savings affect income stability.
problem Analyzing the stability of income payments in pooled annuity funds.
method Examining the influence of initial savings on income fluctuations and developing a criterion for pooling funds.
result Identification of a term, the 'implied number of homogeneous members', linking initial savings to income fluctuations.
Better investment strategies identified through a network metric of asset commonality.
problem Identifying investment strategies based on fund portfolio asset popularity.
method Bipartite network analysis of mutual funds and their holdings, calculating the Average Commonality Coefficient (ACC).
result Funds investing in less popular assets outperform those in more popular ones, even after adjusting for standard factors.
Study optimizes funding rates for cryptocurrency perpetual futures to maintain price alignment.
problem Maintaining alignment between perpetual future prices and target values in cryptocurrency markets.
method Developed replicating portfolios and path-dependent funding rates using path-dependent infinite-horizon BSDEs and arbitrage pricing theory.
result Appropriate funding rate design can keep perpetual future prices aligned with target values.
An option market maker incurs funding costs when carrying and hedging inventory. To hedge a net long delta inventory, for example, she pays a fee to borrow stock from the securities lending market. Because of haircuts, she posts additional cash margin to the lender which needs to be financed at her unsecured debt rate.…
The paper analyzes mutual fund advisors' portfolios to improve sales.
problem Improving sales of investment products to suitable advisors.
method Multivariate time series and cosine similarity analysis.
result Recognized patterns in advisors' portfolio interests.
Study analyzes costs of managing research funds, developing a model for optimal administration.
problem High variability in administration costs among research funding agencies.
method Identified standard agency activities, developed a model estimating optimum portfolio success rate and administration ratio.
result Model estimates optimum portfolio success rate and administration ratio based on input variables.
Study measures investment funds' climate transition risk, finds moderate losses.
problem Measuring the impact of climate transition on investment portfolios.
method Comprehensive framework using geographical, sectoral, company and ISIN-level data.
result Investment funds suffer a moderate 5.7% loss in high transition risk scenario.
Researchers analyze optimal investment strategies for a collectivised pension fund with identical investors.
problem Optimizing investment strategies for a collectivised pension fund with identical investors.
method Analytical computation of optimal investment-consumption strategies for a fund of n identical investors with Epstein-Zin preferences.
result Constant consumption strategy is suboptimal for infinite collectives, suggesting annuities and defined benefit investments are suboptimal.
Analyzes how many people can receive stable income in a pooled annuity fund.
problem Quantifying the trade-off between income stability and the number of members in a pooled annuity fund.
method Investment returns held constant, systematic longevity risk omitted. Derived an analytical expression for income stability.
result The number of fund members who receive stable income is independent of the mortality model.
Study categorizes mutual funds using natural language processing from unstructured data.
problem Categorizing mutual funds using unstructured data for financial analysis.
method Used natural language processing models to classify mutual funds from their investment strategy descriptions.
result High accuracy in categorizing mutual funds using NLP from unstructured data.