This study analyzes financial equity research reports to identify frequently asked questions and automates 80% of them.
problem Insufficient empirical analysis of questions answered in financial equity research reports.
method Analyzed 72 financial equity research reports, classifying sentences into 169 unique question archetypes. Used public corporate reports to classify questions' potential for automation.
result Approximately 80% of financial equity research reports can be automated, with 78.7% of questions automatable.
We review the recent approach of correlation based networks of financial equities. We investigate portfolio of stocks at different time horizons, financial indices and volatility time series and we show that meaningful economic information can be extracted from noise dressed correlation matrices. We show that the metho…
Unified framework matches equity and bond yields.
problem Inconsistency in pricing zero-coupon bonds and equity markets.
method Unified term structure of interest rates framework using put-call parity.
result Option-implied yield curves closely match treasury par yield curves.
ChatGPT snapshots predict future stock returns.
problem Predicting future stock returns using pre-cutoff text.
method Extracted LLM outlook scores from OpenAI snapshots.
result Outlook scores positively correlate with future stock returns.
The paper analyzes debt recycling strategies for mortgage repayment, revealing complex phases of success and failure.
problem Evaluating the effectiveness of debt recycling strategies compared to standard mortgage repayment.
method Developed a dynamical model to study the time evolution of equity and mortgage balance under various conditions.
result The model identifies four phases: strongly successful, weakly successful, default, and permanent re-mortgaging, with sensitivity to initial conditions.
We give an explicit algorithm and source code for extracting equity risk factors from dead (a.k.a. "flatlined" or "hockey-stick") alphas and using them to improve performance characteristics of good (tradable) alphas. In a nutshell, we use dead alphas to extract directions in the space of stock returns along which ther…
We discuss a simple, exactly solvable model of stochastic stock dynamics that incorporates regime switching between healthy and distressed regimes. Using this model, which is analytically tractable, we discuss a way of extracting expected returns for stocks from realized CDS spreads, essentially, the CDS market sentime…
Study finds stocks with common firm fears earn lower returns.
problem Identifying and quantifying firm-level investor fears.
method Analysis of equity options to identify common firm-level fears and their impact on stock returns.
result Stocks with exposure to common bad fears earn lower returns and require higher compensation.
New tool uses computer vision to assess FOMC press conference complexity and its impact on equity returns.
problem Understanding the impact of FOMC press conferences on financial markets.
method Developed a measure of discussion complexity using video images and deep learning algorithms.
result Complex discussions during press conferences are associated with higher equity returns and lower volatility.
Develops a deep learning approach for statistical arbitrage.
problem Temporal price differences between similar assets.
method Constructs arbitrage portfolios using latent asset pricing factors and a convolutional transformer for time series signals.
result High risk-adjusted returns and Sharpe ratios with optimal trading policy.
We present an empirical study of price reversion after the executed metaorders. We use a data set with more than 8 million metaorders executed by institutional investors in the US equity market. We show that relaxation takes place as soon as the metaorder ends:{while at the end of the same day it is on average $\approx…
Business taxonomies are indispensable tools for investors to do equity research and make professional decisions. However, to identify the structure of industry sectors in an emerging market is challenging for two reasons. First, existing taxonomies are designed for mature markets, which may not be the appropriate class…
The Hype Index measures media attention to equities using NLP.
problem Quantifying media attention to equities for volatility analysis.
method Constructs News Count-Based and Capitalization Adjusted Hype Indices using NLP.
result The Hype Index family provides valuable tools for stock volatility analysis.
Bank deposits are analyzed as having dual characteristics, akin to quantum physics.
problem Understanding the dual nature of bank deposits.
method Application of quantum physics concepts to bank deposits.
result Bank deposits have a hybrid nature, combining debt and equity features.
Study examines equity in post-Snow Uri recovery, finds disparities.
problem Disproportionate impacts on vulnerable populations during recovery.
method County and census tract level data analysis, satellite imagery, statistical procedures.
result Negative associations between non-Hispanic whites and outages, positive associations with certain demographic variables.
Geometric observables detect financial regime shifts with high accuracy.
problem Detecting regime shifts in financial markets.
method Extracted four geometric observables from equity-index returns and evaluated them against various baseline methods.
result The Berry Phase Rate achieves an unbiased out-of-sample median Cohen's d of 0.72, significantly reducing false alarms.
PEARL uses AI to replicate private equity performance with liquid assets.
problem Lack of access to private equity due to high costs and complexity.
method Combines AI with liquid assets, incorporating asymmetry for better performance.
result Model outperforms liquid proxies and aligns with private equity benchmarks.
Examines US equity risk premiums amid COVID-19.
problem Analyzing equity risk premiums during the pandemic.
method Not specified in the abstract.
result Not specified in the abstract.
The paper analyzes bank decisions in a three-step model, focusing on equity and debt raising.
problem Bank decision-making in a three-time-step model with equity and debt raising.
method Theoretical analysis of raising new equity and debt, considering capital requirements and equity holders constraints.
result Raising equity and debt can increase or decrease return on equity, depending on specific cases.
Research analyzes ethical concerns around MEV on blockchain and social media.
problem Fairness issues in transaction ordering on blockchain.
method Applied NLP methods to analyze topics in tweets on MEV.
result Tweets discussed ethical concerns like security, equity, and solutions to MEV.
In this paper we provide evidence that financial option markets for equity indices give rise to non-trivial dependency structures between its constituents. Thus, if the individual constituent distributions of an equity index are inferred from the single-stock option markets and combined via a Gaussian copula, for examp…
Equity risk premium is a central component of every risk and return model in finance and a key input to estimate costs of equity and capital in both corporate finance and valuation. An article by Damodaran examines three broad approaches for estimating the equity risk premium. The first is survey based, it consists in …
We investigate the joint dynamics of spot and implied volatility from an empirical perspective. We focus on the equity market with the SPX Index our underlying of choice. Using only observable quantities, we extract the instantaneous variance curves implied by the market and study their daily variations jointly with sp…
Study finds no significant impact of US sovereign credit rating downgrade on equity market.
problem Impact of US sovereign credit rating downgrade on US equity market.
method Event study methodology using three companies and S&P500 index.
result No significant effects of US sovereign credit rating downgrade on US equity market.
Study on diversifying equity portfolios during financial crises and stability.
problem Determining the effectiveness of diversification strategies during financial crises and stability.
method Analysis of 20 years of US stock price data, including GFC and COVID-19 crashes, using eigenvalues, graph-theoretic diagnostics, and hierarchical clustering.
result During financial crises, diversification via sector-based portfolios is ineffective, while during stability, 30-40 stocks provide sufficient diversification.
The paper extends Merton model to price equity warrants under subdiffusive fractional Brownian motion of the short rate.
problem Equity warrant pricing under subdiffusive fractional Brownian motion of the short rate.
method The paper applies subdiffusive mechanism to analyze equity warrant in a fractional Brownian motion environment, deriving a pricing formula for equity warrant.
result The paper provides a pricing formula for equity warrants under subdiffusive fractional Brownian motion model of the short rate.
The paper shows how cross-ownership increases equity correlations during financial crises.
problem Understanding and explaining rising correlations in financial markets during crises.
method Examined interlinkages among firms through a financial network, mathematically relating equity correlations to asset correlations and network sensitivity.
result Equity correlations are higher than asset correlations, and this relationship is independent of the equities level.
New model values equity-linked securities with guaranteed return.
problem Valuation of equity-linked securities with guaranteed return.
method Replicate security price as sum of guaranteed amount and Asian style option price on basket.
result Analytical formulas derived for security price and hedge ratios.
In this paper, within the framework of uncertainty theory, the valuation of equity warrants is investigated. Different from the methods of probability theory, the equity warrants pricing problem is solved by using the method of uncertain calculus. Based on the assumption that the firm price follows an uncertain differe…
The paper assesses how equity tail risk impacts US Treasury bond returns.
problem The effects of equity tail risk on the US government bond market.
method Estimating equity tail risk using option-implied stock market volatility and assessing its predictive power in reduced-form regressions and a term structure model.
result Equity tail risk significantly predicts one-month excess returns on Treasuries.
Study macroscopic equity market properties affecting active strategies.
problem Lack of adequate models for active equity strategies.
method Empirical study using CRSP Database, focusing on market capitalizations and returns.
result Highlight stylized facts and open questions in equity markets.
The paper analyzes global inflation's systemic nature and its impact on equity markets.
problem Understanding the systemic nature of global inflation and its financial market implications.
method Data-driven study using eigenvalue analysis, inner-product optimization, and time-varying portfolio optimization.
result Countries with high centrality in global inflation are identified, and the robustness of equity indices and sectors during inflationary periods are explored.
Study shows similarities and differences in crypto and equity dynamics during pandemic.
problem Comparing cryptocurrency and equity market dynamics during the pandemic.
method New methodologies applied to study cryptocurrency and equity market dynamics, including recently introduced methods for trajectory and anomaly analysis.
result Cryptocurrencies exhibit stronger collective dynamics and correlation, while equities show greater persistence in anomalies over time.
New framework replicates private equity performance using AI and liquid strategies.
problem Inadequate trust and transparency in private equity markets.
method Advanced graphical models and asymmetric risk adjustments.
result Liquid, scalable solution that closely mimics private equity performance.
We develop a large-scale deep learning model to predict price movements from limit order book (LOB) data of cash equities. The architecture utilises convolutional filters to capture the spatial structure of the limit order books as well as LSTM modules to capture longer time dependencies. The proposed network outperfor…
New model solves equity premium puzzle with risk aversion coefficient.
problem Equity premium puzzle in financial markets.
method Developed a new model incorporating investor risk behavior, tested with specific coefficients.
result Validated model with empirical studies, confirming coefficient of 1.033526.
Study shows publicly available news impacts financial markets.
problem Impact of publicly available news on financial markets.
method Extracted news from Common Crawl, identified relevant companies, used sentiment analysis and information theory.
result Publicly available news has significant impact on financial markets.
Study tests if equity factors explain Bitcoin's risk and returns.
problem Explaining Bitcoin's risk and return with equity factors.
method Applied statistical methods to test Fama-French factors on Bitcoin's excess returns.
result Fama-French factors have explanatory power on Bitcoin's risk and returns.
Financial markets provide a natural quantitative lab for understanding some of the most advanced human behaviours. Among them is the use of mathematical tools known as financial instruments. Besides money, the two most fundamental financial instruments are bonds and equities. More than 30 years ago Mehra and Prescott f…
Amid the current financial crisis, there has been one equity index beating all others: the Shanghai Composite. Our analysis of this main Chinese equity index shows clear signatures of a bubble build up and we go on to predict its most likely crash date: July 17-27, 2009 (20%/80% quantile confidence interval).
New model solves equity premium puzzle.
problem Equity premium puzzle regarding risk behavior of investors.
method Developed a new tool called the sufficiency factor to analyze risk behavior of investors.
result Validated the new model with a coefficient of relative risk aversion of 1.033526.
Paper finds significant impact of stock market swings on equity risk premium predictability.
problem Predicting equity risk premium based on stock market behavior changes.
method Introduced Bullish Index and used FDMAA for returns analysis; considered 28 indicators.
result Positive shocks in Bullish Index correlate with strong equity risk premium predictability for up to six months, while negative shocks correlate for up to nine months.
This paper compares token and equity financing for startups.
problem Understanding differences in return rates between token and equity financing.
method Developed a three-period model to analyze liquidity and return differences.
result Entrepreneurs can achieve higher payoffs by issuing tokens, especially for risk-averse investors with liquidity needs.
Investigates cryptocurrency maturity through collective dynamics and diversification.
problem Determining if cryptocurrency market exhibits similar mathematical properties to equity market.
method Adjusts focus to retail cryptocurrency investors' behavioral patterns, contrasting with equity market.
result Identifies ideal portfolio size and spread across cryptocurrencies, revealing signatures of maturity.
The study reveals unspanned risks in equity option risk premiums, explaining negative premiums for certain options.
problem Explaining negative risk premiums for certain equity option types.
method Developed a decomposition of equity option risk premiums, operationalized the pricing kernel process, and incorporated unspanned risks.
result Empirical evidence supports the presence of unspanned risks, explaining negative risk premiums for certain options.
Simple method solves Quanto Skew problem.
problem Quanto Skew problem in Equities and FX.
method Analytical method that accommodates Equity and FX volatility skew.
result Highly efficient and fast performance.
Novel pricing method for equity-indexed annuities under uncertain volatility and stochastic interest rate.
problem Pricing equity-indexed annuities with early surrender risk under uncertain market conditions.
method Advanced financial modeling techniques, including uncertain volatility framework and Hull-White model for interest rate dynamics. Numerical algorithm using tree-based framework with local volatility optimization.
result High effectiveness of the proposed numerical algorithm compared to machine learning-based methods.
MS-CASTLE learns causal structures across multiple time scales.
problem Inferring causal relationships between time series data at different scales.
method Uses stationary wavelet transform and non-convex optimization to estimate causal structures.
result MS-CASTLE reveals meaningful causal interactions, especially at mid-term time resolutions.