Paper presents a faster method for computing cost of equity and performing comparable company analysis.
problem Tedium and subjectivity in traditional cost of equity and comparable company analysis methods.
method Uses spectral and agglomerative clustering to compute cost of equity and perform comparable company analysis.
result Reduces time required for comps by orders of magnitude and improves consistency and reliability.
Model shows how discount rates affect intergenerational equity in climate mitigation.
problem Intergenerational equity in climate mitigation decisions.
method Extended DICE model with stochastic discount rates and financing extensions.
result Discount-rate uncertainty amplifies intergenerational inequality in climate mitigation.
Study shows how 'crowding' in equity trading affects performance and costs.
problem Deterioration of strategy performance, increased trading costs, and systemic risk due to equity factor crowding.
method Direct metrics of crowding based on imbalances of trades executed on the market, analyzing U.S. equity market data.
result Significant signs of crowding in well-known equity signals, especially Momentum, affecting order flow and portfolio rebalancing.
Chebyshev technique reduces FRTB-IMA equity autocallables computation costs by 90%.
problem Efficient computation of FRTB-IMA capital for equity autocallables.
method Orthogonal Chebyshev Sliding Technique applied to equity autocallables.
result Computational cost reduction of about 90% for equity autocallables.
Model analyzes debt recycling strategies under various fiscal regimes and jurisdictions.
problem Understanding debt recycling dynamics and their impact on repayment times and equity growth.
method Developed a calibrated model incorporating mortgage interest rates, borrowing costs, and tax shields.
result Introducing positive interest rates without tax shields contracts success regions and lengthens repayment times, but tax shields partially reverse these effects.
Study uses put-call parity to estimate cost of funding in equity derivatives markets.
problem Estimating the cost of funding in active equity derivative markets.
method Develops a method using European put and call prices to recover the implicit discount factor and cost of funding.
result Identifies the cost of funding in major equity markets, showing it is typically around 34 basis points above OIS.
Study compares short vs long strategies for equity factors, finds short strategy better.
problem Determining the best market-neutral implementation of equity factors.
method Revisited the relative predictability of short and long legs, diversification, and costs.
result Long-Short implementation yields superior risk-adjusted returns compared to Hedged Long-Only.
Study examines the impact of employment benefit costs on firm profitability.
problem Impact of employment benefit costs on firm profitability.
method Panel data regression analysis using E-Views.
result There is a significant positive relationship between employment benefit costs and firm profitability.
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.
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 …
The study provides a practical strategy for pricing and hedging equity-release mortgages guarantees.
problem Pricing and hedging the No-Negative-Equity-Guarantee in incomplete markets.
method Discrete-time model, Excess-of-Loss reinsurance, numerical illustrations.
result Superhedge cost decreases with more lives in the portfolio, making it more realistic.
A new XVA strategy rooted in balance sheet perspective improves equity process for bank shareholders.
problem Counterparty risk valuation adjustments (XVAs) in financial derivatives.
method Develops a cost-of-capital XVA strategy in a balance sheet perspective, solving explicitly in static setup and dynamically in trade context.
result Ensures a submartingale equity process corresponding to a target hurdle rate on capital at risk.
Benchmarking deep time series models for equity portfolios
problem Selecting the best deep time series model for equity portfolios
method Using a CRSP benchmark and multi-criteria acceptability analysis
result No architecture dominates the benchmark, with TransEnc-8 having the highest rank-1 acceptability
A RL framework for hedging equity index options with realistic costs.
problem Dynamic hedging of equity index option exposures under transaction costs.
method Reinforcement Learning (RL) with a leak-free environment, cost-aware reward function, and stochastic actor-critic agent.
result The RL policy improves risk-adjusted performance compared to no-hedge, momentum, and volatility-targeting baselines.
Using an artificial neural network (ANN), a fixed universe of approximately 1500 equities from the Value Line index are rank-ordered by their predicted price changes over the next quarter. Inputs to the network consist only of the ten prior quarterly percentage changes in price and in earnings for each equity (by quart…
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.
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…
Study uses RL to optimize global equity portfolios, finds mixed results.
problem Optimizing dynamic portfolio weights across diverse global markets.
method Deep reinforcement learning with Soft Actor-Critic, incorporating various constraints and reward formulations.
result RL strategies achieve competitive performance, but no strategy consistently outperforms Buy and Hold.
In this paper we present formulas for the valuation of debt and equity of firms in a financial network under comonotonic endowments. We demonstrate that the comonotonic setting provides a lower bound and Jensen's inequality provides an upper bound to the price of debt under Eisenberg-Noe financial networks with bankrup…
Modeling climate change costs with stochastic interest rates shows inequality, but funding abatement can reduce this.
problem Evaluating the costs and benefits of climate change mitigation with uncertain discount rates.
method Amended DICE model with stochastic interest rates and funding abatement costs.
result Introducing funding abatement can reduce intergenerational inequality in climate change costs.
Equity-Transformer solves NP-hard min-max routing problems efficiently.
problem Min-max routing problems with multiple agents and large-scale applications.
method Sequential planning approach with Transformer and equitable workload distribution inductive biases.
result Significant runtime and cost reductions in min-max mTSP and min-max mPDP tasks.
New framework improves cost-benefit analysis of policies.
problem Limitations of MVPF in welfare analysis.
method Developed an axiomatic framework to create RPV.
result RPV provides better equity-efficiency trade-off quantification.
Study shows environmental spending positively impacts company profitability.
problem Impact of environmental spending on company profitability.
method Panel data regression analysis using E-Views.
result Environmental spending positively impacts profitability metrics.
Using the most comprehensive source of commercially available data on the US National Market System, we analyze all quotes and trades associated with Dow 30 stocks in 2016 from the vantage point of a single and fixed frame of reference. We find that inefficiencies created in part by the fragmentation of the equity mark…
HRT uses bi-level reinforcement learning to optimize stock selection and execution in multi-asset equity markets.
problem Optimizing automated equity trading decisions under risk, turnover, and transaction costs.
method Hierarchical Reinforced Trader (HRT) framework that separates selection and execution decisions.
result HRT outperforms other methods in learning-based return-risk-cost trade-offs, improving Sharpe ratio and reducing turnover.
Using the most comprehensive, commercially-available dataset of trading activity in U.S. equity markets, we catalog and analyze quote dislocations between the SIP National Best Bid and Offer (NBBO) and a synthetic BBO constructed from direct feeds. We observe a total of over 3.1 billion dislocation segments in the Russ…
This paper examines pricing and hedging strategies for cross-currency equity protection swaps.
problem Dynamic requirements from EPS buyers in cross-currency equity protection swaps.
method Detailed analysis of two hedging paradigms, including separate and aggregated returns, with consideration of different types of returns.
result Proposes various hedging strategies with practical implications for EPS providers and investors.
Study develops a multi-pair trading strategy using graph clustering and machine learning.
problem Improving risk-adjusted returns and reducing transaction costs in US equities market.
method Statistical arbitrage, graph clustering algorithms, Kelly criterion, machine learning classifiers.
result Optimal signal detection and risk management techniques outperformed benchmarks.
The role of portfolio construction in the implementation of equity market neutral factors is often underestimated. Taking the classical momentum strategy as an example, we show that one can significantly improve the main strategy's features by properly taking care of this key step. More precisely, an optimized portfoli…
The paper values and hedges EPS products with jumps and default risks.
problem Valuation and risk management of EPS products under financial crises and default risks.
method Developed pricing frameworks using jump-diffusion and default models, derived closed-form formulas, and analysed hedging strategies.
result Quantified residual losses from counterparty default risk and defined default-adjusted premiums.
The paper discusses decades of stock market manipulation and its benefits.
problem Manipulating public equity markets over 30 years.
method Quantitative analysis of market impact and price movement.
result Price manipulation is a valuable and profitable tool.
The paper analyzes statistical arbitrage using a factor model of equity returns.
problem Analyzing and trading statistical arbitrage strategies in equity markets.
method Conditional factor model, state space framework, online risk premia estimation, mean reversion trades.
result The model outperforms other methods in statistical arbitrage trading strategies over a 29-year period.
Recent studies have shown that online portfolio selection strategies that exploit the mean reversion property can achieve excess return from equity markets. This paper empirically investigates the performance of state-of-the-art mean reversion strategies on real market data. The aims of the study are twofold. The first…
Enhanced Momentum Transformer outperforms traditional trading strategies.
problem Improving trading performance in equities with evolving market conditions.
method Building a Momentum Transformer using an attention mechanism combined with LSTM, capturing long-term dependencies and transaction costs.
result Average returns of 4.14% and Sharpe ratio of 1.12, similar to original results but with higher volatility.
The study extends SPT to account for real-world transaction costs, improving portfolio performance.
problem Real-world transaction costs affect portfolio performance, especially during market stress.
method Developed a continuous-time model with stochastic transaction costs and derived lower bounds for cost-adjusted wealth.
result Functionally generated portfolios can still achieve relative arbitrage after accounting for transaction costs.
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.
In this theoretical paper, I propose creation of a venture bank, able to multiply the capital of a venture capital firm by at least 47 times, without requiring access to the Federal Reserve or other central bank apart from settlement. This concept rests on obtaining default swap instruments on loans in order to create …
This paper addresses practical challenges in portfolio optimisation for automated trading.
problem Implementing optimal portfolio weights into real trades with transaction costs and lot sizes.
method Two-stage framework: optimises portfolio weights first, then generates realistic trades.
result The two-stage approach effectively converts optimal portfolios into actionable trades, mitigating practical difficulties.
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.
Simple model uses time series momentum to outperform benchmarks in equity and bond markets.
problem Finding systematic excess returns in various markets.
method Time series momentum applied to multiple investable indices without complex parameter estimation.
result Significant outperformance in equity and bond markets, nearly doubling returns.
Deep RL optimizes US stock allocations with better performance.
problem Optimizing asset allocation in US equities markets.
method Reinforcement learning applied to asset allocation problems.
result Deep RL models outperform traditional methods in asset allocation.
Unified model learns from both time-series and cross-sectional momentum features.
problem Separate time-series and cross-sectional momentum strategies do not consider concurrent relationships.
method Spatio-Temporal Momentum strategies using neural networks to combine both types of momentum.
result Simple neural network with single fully connected layer generates trading signals for all assets.
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.
The study calculates securities lending haircuts and indemnification costs.
problem Managing borrower default risk in securities markets.
method Repo haircut model applied to securities lending transactions; quantifies haircuts and indemnification costs.
result Computed borrower-dependent haircuts and indemnification costs for US Treasuries and equities.
Lazy, perfectly informed investors trade infrequently due to costs.
problem The paradox of an omniscient yet lazy investor trading infrequently.
method Formalized the paradox using geometric and fractional Brownian motion models, derived closed-form profit functions, and proved existence and uniqueness of the optimal trading frequency.
result The optimal trading frequency can be interpreted through the fractal dimension of the price path.
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.
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.