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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.

168,695 papers · 148 categories

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285785113 · Jan 202619922001200920172026
48 results for Latin American Markets

Study applies HRP to Latin American markets, showing smoother risk-return profile.

problem Lack of empirical analyses of HRP in Latin American markets.
method Hierarchical Risk Parity (HRP) with hierarchical clustering and recursive bisection.
result HRP portfolio outperforms Max Sharpe portfolio in NUAM markets, with smoother risk-return profile.

Surveying mean curvature flow on solvmanifolds, focusing on translating solutions.

problem Understanding translating solutions on solvmanifolds.
method Exploration of mean curvature flow, introduction of translating solutions, discussion of solvmanifolds.
result Equations describing translating solutions on the family of 3D solvmanifolds.

RL controls small soccer robots in a real league, beating human-designed policies.

problem Training robots to play complex, real-world sports.
method Sim-to-Real RL approach, training in simulated environment, applying to real-world robots.
result Robots learned policies to compete effectively, beating human-designed strategies.

Paper proposes an alternative method to price American options using HJM approach.

problem Price American options efficiently and accurately.
method Utilizes HJM technique to model term structure of volatility for equity markets.
result Proposes a new value function, stopping criteria, and stopping time for American options.

Paper calculates perpetual American put option pricing with drawdown event in Lévy market.

problem Pricing perpetual American put options with a drawdown event in a Lévy market.
method Derives explicit price using geometric Lévy process with downward jumps, optimal stopping rule, and martingale arguments.
result Optimal stopping rule is the first time asset price falls below a specific value.

Novel method uses PDifMPs to price American options more accurately.

problem Inaccurate pricing of American options due to constant drift and volatility assumptions.
method Piecewise diffusion Markov processes (PDifMPs) integrated with continuous dynamics and discrete jumps.
result PDifMPs provide a more accurate reflection of market behaviour in American option pricing.

Study bounds for prices of European and American options with optional termination.

problem Bounding prices of options with potential termination.
method Duality results linking upper prices of vulnerable options to American options with constrained exercise times.
result Linking upper prices of vulnerable options to American options and game options.

This paper evaluates investment risks in LATAM AI startups using DCF method.

problem Unique challenges and risks faced by LATAM tech startups.
method Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) metrics; Discounted Cash Flow (DCF) method.
result Developed a ranking of emerging powers in Latin America for tech startup investment.

Chagas disease is a neglected disease, and information about its geographical spread is very scarse. We analyze here mobility and calling patterns in order to identify potential risk zones for the disease, by using public health information and mobile phone records. Geolocalized call records are rich in social and mobi…

2018-08-09abs ↗pdf ↗

With the random matrix theory, we study the spatial structure of the Chinese stock market, American stock market and global market indices. After taking into account the signs of the components in the eigenvectors of the cross-correlation matrix, we detect the subsector structure of the financial systems. The positive …

2012-01-31abs ↗pdf ↗

Study examines short-term stress of COVID-19 on major global stock indices.

problem Short-term impact of COVID-19 on global stock markets.
method Secondary data from 41 stock exchanges in 32 countries, focusing on first reported cases.
result Volatility in stock markets increases with the rise of COVID-19 cases, and there is a significant negative correlation.

A tailored HTR system improves CER to 0.015 for medieval Latin.

problem Digitizing handwritten medieval Latin records for a low-resource language.
method End-to-end pipeline using image segmentation and transformer-based models with extensive data augmentation.
result Best-performing setup achieved CER of 0.015, superior to commercial models.

Continuous-time random walks are a well suited tool for the description of market behaviour at the smallest scale: the tick-to-tick evolution. We will apply this kind of market model to the valuation of perpetual American options: derivatives with no maturity that can be exercised at any time. Our approach leads to opt…

2007-08-03abs ↗pdf ↗

We re-examine and extend the findings from the recent paper by Dumitrescu, Quenez and Sulem (2018) who studied American and game options in a particular market model using the nonlinear arbitrage-free pricing approach developed in El Karoui and Quenez (1997). In the first part, we provide a detailed study of unilateral…

2018-04-28abs ↗pdf ↗

We investigate the relative market efficiency in financial market data, using the approximate entropy(ApEn) method for a quantification of randomness in time series. We used the global foreign exchange market indices for 17 countries during two periods from 1984 to 1998 and from 1999 to 2004 in order to study the effic…

2006-08-02abs ↗pdf ↗

Paper applies subdiffusive dynamics to American and barrier options pricing.

problem Valuation of American and barrier options in subdiffusive financial models.
method Proposes weighted finite difference and Longstaff-Schwartz methods for valuation.
result Numerical valuation of American and barrier options demonstrated.

We consider the pricing of American put options in a model-independent setting: that is, we do not assume that asset prices behave according to a given model, but aim to draw conclusions that hold in any model. We incorporate market information by supposing that the prices of European options are known. In this setting…

2013-01-23abs ↗pdf ↗

Study on hedging and valuation of basis risk in incomplete markets with partial information.

problem Hedging and valuation of European and American claims in an incomplete market with correlated assets and partial information.
method Stochastic control and partial information scenario, forward indifference valuation, dual representation, PDE approach.
result Derivation of optimal hedging strategy and forward indifference price representation for claims.

We consider an American contingent claim on a financial market where the buyer has additional information. Both agents (seller and buyer) observe the same prices, while the information available to them may differ due to some extra exogenous knowledge the buyer has. The buyer's information flow is modeled by an initial…

2015-05-19abs ↗pdf ↗

New method for pricing and hedging options in risky markets.

problem Pricing and hedging derivatives in markets with equivalent local martingale measures not existing.
method Introduces a new superhedging duality for American options in a general market setting.
result Answers a question raised by Fernholz, Karatzas, and Kardaras about pricing American options.

Study predicts US stock market will continue to fall post-COVID-19.

problem Analyzing the recovery trend of the US stock market post-COVID-19.
method Used Deep Learning, Neuro Network, and Time-series analysis on S&P 500, Nasdaq 100, and Dow Jones Industrial Average data.
result LSTM model predicts US stock market will continue to fall post-COVID-19.

Researchers find a way to price American options without relying on specific asset price models.

problem Determining the upper bound on the price of American options under model uncertainty.
method Using martingale optimal transport problem to describe model uncertainty and proving that optimal exercise schemes must be nonrandomized under certain conditions.
result The price upper bound and its relaxed version coincide under suitable convexity conditions, removing the need for the model-free price upper bound to be nonrandomized.

This study optimizes DRL for American option hedging with new training methods.

problem Optimizing Deep Reinforcement Learning for American Put Option Hedging
method Investigates hyperparameters, introduces new training methods, and compares with Black-Scholes method.
result Weekly-trained DRL agents outperform Black-Scholes at transaction costs of 1% and 3%

This paper uses deep learning to price American options under stochastic volatility.

problem Pricing American options with a time-varying exercise boundary under the Heston model.
method Coupled PINNs with curriculum learning and adaptive resampling.
result Demonstrates the effectiveness of the proposed deep learning framework for American option pricing.

Defined by Joyce and Matveev, the fundamental quandle is a complete invariant of oriented classical knots. We consider invariants of knots defined from quotients of the fundamental quandle. In particular, we introduce the fundamental Latin Alexander quandle of a knot and consider its Gröbner basis-valued invariants, wh…

2014-04-24abs ↗pdf ↗

We discuss the pricing methodology for Bonus Certificates and Barrier Reverse-Convertible Structured Products. Pricing for a European barrier condition is straightforward for products of both types and depends on an efficient interpolation of observed market option pricing. Pricing products We discuss the pricing metho…

2016-07-31abs ↗pdf ↗