Proposes an end-to-end deep learning framework for active investing.
problem Constructing an active investment portfolio via deep learning.
method End-to-end deep learning framework covering factor selection, combination, stock selection, and portfolio construction.
result Demonstrates effectiveness of E2E deep learning framework in active investing.
We study the role of active and passive investors in an investment market with uncertainties. Active investors concentrate on a single or a few stocks with a given probability of determining the quality of them. Passive investors spread their investment uniformly, resembling buying the market index. In this toy market …
Study shows big winner stocks significantly impact passive and active investment strategies.
problem Impact of big winner stocks on passive and active investment strategies.
method Numerical and analytical techniques applied to historical stock price data.
result Concentrated portfolios underperform equally weighted indexes due to missing big winner stocks.
This study improves stock investment strategies using advanced neural networks.
problem Improving stock investment strategies for better performance.
method Used LSTM-GRU neural networks combined with SVM for stock prediction.
result LSTM-GRU outperformed benchmarks in stock predictions.
We propose a methodological framework to study the dynamics of inter-regional investment flow in Europe from a Complex Networks perspective, an approach with recent proven success in many fields including economics. In this work we study the network of investment stocks in Europe at two different levels: first, we comp…
The Heston model optimizes portfolio management based on real market data.
problem Choosing between active and passive investment strategies.
method Calibrated Heston model to real stock market data.
result Passive strategy can outperform active strategy depending on market parameters.
This paper proposes an embedding-based neural network for more accurate investment return prediction.
problem Accurately predicting investment returns requires understanding industry knowledge and news, as well as leveraging relevant theories.
method The approach uses embedding to encode investment IDs into low-dimensional vectors, leveraging dual branches to separate different information, and employs the swish activation function.
result The proposed embedding-based dual branch model outperforms traditional machine learning models like Xgboost, Lightgbm, and Catboost on the Ubiquant Market Prediction dataset.
Wavelet analysis reveals financialization effects on oil-food price correlation.
problem Investigating the correlation between oil and food prices and their determinants.
method Wavelet analysis and energy-based measures to differentiate high and low frequency movements.
result Significant local correlation between food and oil is due to financialization and emerging economies' demand.
Using more than 6.7 billions of trades, we explore how the tick-by-tick dynamics of limit order books depends on the aggregate actions of large investment funds on a much larger (quarterly) timescale. In particular, we find that the well-established long memory of market order signs is markedly weaker when large invest…
ROI-driven data analytics guides investment in empirical data analysis.
problem Determining the optimal depth and breadth of data analytics.
method Conceptual framework validated through empirical studies focusing on dependency extraction in Mozilla Firefox project.
result ROI-driven data analytics helps avoid over-analyzing empirical data.
The study reveals distinct patterns in retail investors' holding periods affecting stock returns.
problem Understanding the impact of retail investors' investment horizons on stock returns.
method Using self-reported holding periods from StockTwits, the study categorizes retail investors into long-horizon and short-horizon groups and analyzes their return patterns.
result Long-horizon retail investors exhibit underreaction to earnings announcements, while short-horizon investors show overreaction.
We investigate whether fractal markets hypothesis and its focus on liquidity and invest- ment horizons give reasonable predictions about dynamics of the financial markets during the turbulences such as the Global Financial Crisis of late 2000s. Compared to the mainstream efficient markets hypothesis, fractal markets hy…
Study insurance pricing under correlation ambiguity without increasing prices or reducing utility.
problem Understanding the dependence structure between insurance and financial risks.
method Dynamic equilibrium analysis of insurance pricing with worst-case beliefs.
result Correlation ambiguity does not necessarily increase insurance prices or reduce insurers' utility.
Turnover-adjusted IR is always lower than classic IR, suggesting managers can improve performance by limiting turnover.
problem The classic relationship between IR and its determinants does not account for turnover costs.
method Mathematical derivations and simulations considering volatility of information coefficient and portfolio turnover.
result Turnover-adjusted IR is lower and managers can improve performance by limiting turnover.
This paper explores portfolio management strategies to maximize alpha and minimize beta.
problem Maximizing returns while minimizing risk in investment portfolios.
method Examines asset allocation, diversification, active management, and risk management strategies.
result Combining these strategies optimizes portfolio performance.
Wealth inequality is an important matter for economic theory and policy. Ongoing debates have been discussing recent rise in wealth inequality in connection with recent development of active financial markets around the world. Existing literature on wealth distribution connects the origins of wealth inequality with a v…
We demonstrate that the tail dependence should always be taken into account as a proxy for systematic risk of loss for investments. We provide the clear statistical evidence of that the structure of investment portfolios on a regulated market should be adjusted to the price of gold. Our finding suggests that the active…
Paper studies optimal investing for retirees with risk constraints.
problem Retirees' longevity and living standard risks in a fluctuating market.
method Formulated as a portfolio choice problem under time-varying risk capacity constraint. Derived optimal investment strategy using differential equations. Demonstrated endogenous spending measure and active investment strategy.
result Time-varying risk capacity constraint impacts asset allocation in retirement.
Investors seek to attribute performance to various features using Shapley value method.
problem Attributing performance to different features in an investment process.
method Use Shapley value method for attribution, either exactly or approximately.
result Shapley value method provides a preferred attribution approach.
We develop a simple stock selection model to explain why active equity managers tend to underperform a benchmark index. We motivate our model with the empirical observation that the best performing stocks in a broad market index often perform much better than the other stocks in the index. Randomly selecting a subset o…
This work models the interconnection of company's investment managers' representations and the market attraction of its shares. The models that reflect the connection of the company's market effectiveness indices and parameters of its economic activity are created on the basis of the Mean-Variance Analysis and Regressi…
Paper applies theorem to find optimal investment boundary in stochastic capacity expansion.
problem Finding optimal investment boundary in a stochastic, time-inhomogeneous capacity expansion problem.
method Applies Bank and El Karoui Representation Theorem to solve first order conditions involving a non-integral term.
result Existence of base capacity ly⋆(t), showing optimal investment process becomes active at this level. This research tackles backdoor attacks on audio data using a stochastic investment approach.
problem The threat of backdoor attacks on audio data, especially in voice-activated systems.
method A Stochastic investment-based backdoor attack (MarketBack) approach.
result MarketBack can achieve an average attack success rate close to 100% with less than 1% of poisoned data.
Enhances robo-advisors with client investment preference inference.
problem Accurately inferring clients' investment preferences from past activities.
method Stochastic control framework with continuous-time model and discounting scheme.
result Proves sufficient conditions for client investment preference identifiability.
The study analyzes ETFs' portfolio optimization and tail-risk management.
problem Analyzing the performance of actively managed ETFs in managing risk and diversification.
method Daily Bloomberg data for 30 funds, evaluating various strategies under long-only and long-short constraints.
result Tangency-type portfolios generally outperform buy-and-hold benchmarks, while minimum-variance and CVaR-minimizing portfolios sacrifice upside for downside control.
In recent years, the economic policy of privatization, which is defined as the transfer of property or responsibility from public sector to private sector, is one of the global phenomenon that increases use of markets to allocate resources. One important motivation for privatization is to help develop factor and produc…
In recent years, the evaluation of the minimal investment risk of the quenched disordered system of a portfolio optimization problem and the investment concentration of the optimal portfolio has been actively investigated using the analysis methods of statistical mechanical informatics. However, the work to date has no…
The paper compares ML models for credit scoring and investment decisions using explainable AI.
problem The opacity of machine learning models in financial services.
method Comparison of various machine learning models (single classifiers, ensembles, neural networks) and explainability techniques (LIME, SHAP).
result Ensemble classifiers and neural networks outperform in credit scoring models.
Study finds similar companies in Dhaka Stock Exchange using technical data.
problem Analyzing all companies in Dhaka Stock Exchange is impractical.
method Used technical data to identify companies moving together.
result Technical data can reveal company relationships without fundamental data.
Paper proposes novel hedging strategies using LSTM models for diversified investment portfolios.
problem Hedging risky asset portfolios in turbulent financial markets.
method Four diverse models (LSTM, ARIMA-GARCH, momentum, contrarian) generate price forecasts for diversified AIS.
result LSTM-based strategies outperform other models, with Bitcoin being the best diversifier for S&P 500 index.
The paper presents a practical method for evaluating investment projects using real options.
problem Evaluating investment projects under uncertainty and strategic risk management.
method Binomial trees and real options techniques for evaluating investment projects.
result The method can be used for most real options and introduces Project Value at Risk for feasibility.
Deep neural network learns meaningful factors to predict stock returns.
problem Predicting excess returns of assets like Tesla stock.
method 5-layer deep neural network with gated activation layer to filter noise.
result Proposed model outperforms in predicting stock returns over 2,000 stocks.
How technology affects growth or employment has long been debated. With a hiatus, the debate revived once again in the form of how Information and Communications Technology, as a form of new technology, exerts on productivity and employment. Information and Communications Technology perceived as General Purpose Technol…
Study assesses additional factors for identifying persistent alpha in pension funds.
problem Identify persistent alpha in pension funds using additional factors.
method Reproduces Fama and French's (2010) experiment with additional features and compares results to 3-factor model.
result Additional factors improve persistence of alpha assessment in pension funds.
Negative screening is one method to avoid interactions with inappropriate entities. For example, financial institutions keep investment exclusion lists of inappropriate firms that have environmental, social, and government (ESG) problems. They create their investment exclusion lists by gathering information from variou…
Graph database outperforms in filtering ESG stocks efficiently.
problem Efficiently filtering ESG stocks from large lists of equities.
method Compared SQL, No-SQL, and graph databases; used Python for database interactions; collected data from stock price and financial news.
result Graph database is more efficient for ESG stock filtering.
We present an interacting-agent model of speculative activity explaining bubbles and crashes in stock markets. We describe stock markets through an infinite-range Ising model to formulate the tendency of traders getting influenced by the investment attitude of other traders. Bubbles and crashes are understood and descr…
The study finds significant financial sector volatility and tail risk spillovers to real economy sectors.
problem Volatility and tail risk spillovers from financial to real economy sectors.
method New measure of tail risk spillover, empirical analysis of U.S. economy 2001-2011.
result Significant volatility and tail risk spillovers from financial to real economy sectors, especially during crises.
Model A outperforms passive investment in stock index prediction with less exposure.
problem Predicting short-term stock index movements with high accuracy.
method Dynamic Deep Neural Networks (DNN) for trading decisions.
result Model A outperforms passive investment and conventional ML methods.
Lattice investment projects support process model with corruption is formulated and analyzed. The model is based on the Ising lattice model of ferromagnetic but takes deal with the social phenomenon. Set of corruption agents is considered. It is supposed that agents are placed in sites of the lattice. Agents take decis…
Modelling all possible life cycles of a company in a highly competitive economic environment gives a significant advantage to the owner in his business investment activities. This article proposes and analyses a dynamic model of a company's life cycle with known action costs and transition probabilities, that can be af…
AI-driven sales prioritization boosts renewal bookings by 8.08%.
problem Manual sales account prioritization is inefficient and under-invested.
method Developed an AI-based Account Prioritizer using machine learning and explanation algorithms.
result Generated a +8.08% increase in renewal bookings.
Research identifies four motivational groups for crypto-metaverse landowners.
problem Understanding motivations of retail investors in the crypto-metaverse.
method Detailed financial behavior survey and principal components analysis.
result Four distinct motivational groups identified: Aesthetics, Social, Speculation, Innovation.
PriceSeer benchmarks LLMs in real-time stock prediction.
problem Evaluating LLMs' stock prediction accuracy and robustness.
method Real-time benchmark with 110 U.S. stocks, internal and external information expansion.
result LLMs perform suboptimally in long-term predictions due to fake news and specific industries.
HireVAE adapts to market regimes for online stock prediction.
problem Building an online and adaptive factor model for stock prediction.
method HireVAE uses a hierarchical latent space to estimate latent factors from historical market information.
result HireVAE outperforms previous methods in active returns across benchmarks.
We consider the relationship between economic activity and intervention, including monetary and fiscal policy, using a universal dynamic framework. Central bank policies are designed for growth without excess inflation. However, unemployment, investment, consumption, and inflation are interlinked. Understanding dynamic…
This study proposes an equal-weight portfolio strategy to reduce risk compared to traditional ETFs.
problem Risk of passive ETFs not matching optimal portfolio weights.
method Introduced an equal-weight portfolio strategy to reduce idiosyncratic risk.
result Equal-weight portfolio has lower risk than traditional ETFs, especially during idiosyncratic events.
Birth rates have dramatically decreased and, with continuous improvements in life expectancy, pension expenditure is on an irreversibly increasing path. This will raise serious concerns for the sustainability of the public pension systems usually financed on a pay-as-you-go (PAYG) basis where current contributions cove…