In some options markets (e.g. commodities), options are listed with only a single maturity for each underlying. In others, (e.g. equities, currencies), options are listed with multiple maturities. In this paper, we provide an algorithm for calibrating a pure jump Markov martingale model to match the market prices of Eu…
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This study measures price risk aversion using indirect utility functions in a lab experiment.
New method combines score lists using joint CDFs, improving computation.
Game-theoretic models predict asset prices in financial markets.
The real estate market is exposed to many fluctuations in prices because of existing correlations with many variables, some of which cannot be controlled or might even be unknown. Housing prices can increase rapidly (or in some cases, also drop very fast), yet the numerous listings available online where houses are sol…
This paper analyzes Airbnb listings in the city of San Francisco to better understand how different attributes such as bedrooms, location, house type amongst others can be used to accurately predict the price of a new listing that optimal in terms of the host's profitability yet affordable to their guests. This model i…
Study shows registration regime improves IPO pricing efficiency in China.
We study the rank distribution, the cumulative probability, and the probability density of returns of stock prices of listed firms traded in four stock markets. We find that the rank distribution and the cumulative probability of stock prices traded in are consistent approximately with the Zipf's law or a power law. It…
This study examines how ChiNext IPOs' initial returns are influenced by regulation regime changes.
The paper examines the Chinese market reaction to the ADR issue by comparing returns and their stochastic variances of the Chinese firms cross-listed in the U.S. stock market. First, It was implemented capital asset pricing model (CAPM) to determine expected returns A and N shares. The CAPM provided with a methodology …
Oil prices affect Russian banks' stability, with negative impacts from decreases.
Study shows houses appreciated more during pandemic due to speculation, not just price uncertainty.
The study finds flaws in methods used to estimate foreign exchange option prices.
Predicts short-term futures contract direction using neural networks and order flow data.
We explore inverse and quanto inverse crypto options, their pricing, and applications.
List-wise learning to rank methods are considered to be the state-of-the-art. One of the major problems with these methods is that the ambiguous nature of relevance labels in learning to rank data is ignored. Ambiguity of relevance labels refers to the phenomenon that multiple documents may be assigned the same relevan…
In a stock market, the price fluctuations are interactive, that is, one listed company can influence others. In this paper, we seek to study the influence relationships among listed companies by constructing a directed network on the basis of Chinese stock market. This influence network shows distinct topological prope…
Efficiently calculates Brazilian stock options with discrete dividends.
We discuss the finding that cross-sectional characteristic based models have yielded portfolios with higher excess monthly returns but lower risk than their arbitrage pricing theory counterparts in an analysis of equity returns of stocks listed on the JSE. Under the assumption of general no-arbitrage conditions, we arg…
Study compares market microstructure between two South African exchanges.
We present an outlook of the studies on correlations in the price timeseries of stocks, discussing the construction and applications of "asset tree". The topic discussed here should illustrate how the complex economic system (financial market) enrichens the list of existing dynamical systems that physicists have been s…
New algorithm for robust mean estimation in high dimensions with nearly-PCA time complexity.
This paper investigates the effect of cross-shareholding on stock price synchronicity, as a measure of price informativeness, of the listed firms in the Chinese stock market. We gauge firms' levels of cross-shareholdings in terms of centrality in the cross-shareholding network. It is confirmed that it is through a nois…
Model for dynamic pricing across multiple RE groups to maximize revenue.
A protocol reduces transaction costs for portfolio managers.
Anti-ELAB protests affected Hong Kong firms' stock prices, especially those linked to pan-democrats.
We study the nature of fluctuations in variety of price indices involving companies listed on the New York Stock Exchange. The fluctuations at multiple scales are extracted through the use of wavelets belonging to Daubechies basis. The fact that these basis sets satisfy vanishing moments conditions makes them ideal to …
Share prices of financial companies from the S&P 500 list have been modeled by a linear function of consumer price indices in the USA. The Johansen and Engle-Granger tests for cointegration both demonstrated the presence of an equilibrium long-term relation between observed and predicted time series. Econometrically, t…
Investigates principles of generalization in list learning, refutes sample compression conjecture.
Research on predicting with lists of labels, characterizing learnability and providing algorithms.
Paper cleans option price datasets by removing outliers.
This paper considers possible price paths of a financial security in an idealized market. Its main result is that the variation index of typical price paths is at most 2, in this sense, typical price paths are not rougher than typical paths of Brownian motion. We do not make any stochastic assumptions and only assume t…
The study proposes algorithms to minimize rating discordance in missing data.
At the initial stages of this research, the assumption was that the franchised businesses perhaps should not be affected much by recession as there are multiple cash pools available inherent to the franchised business model. However, after analyzing the available data, it indicated otherwise, the stock price performanc…
Robust subgroup discovery finds non-redundant, statistically significant subgroups.
This paper presents approaches to determine a network based pricing for 3D printing services in the context of a two-sided manufacturing-as-a-service marketplace. The intent is to provide cost analytics to enable service bureaus to better compete in the market by moving away from setting ad-hoc and subjective prices. A…
We report on the occurrence of an anomaly in the price impacts of small transaction volumes following a change in the fee structure of an electronic market. We first review evidence for the existence of a master curve for price impact on the Johannesburg Stock Exchange (JSE). On attempting to re-estimate a master curve…
Study finds high cyber risk stocks generate significant excess returns.
In this paper, we describe a newly discovered statistical property of time series data for daily price changes. We conducted quantitative investigation of the {\it calm-time intervals} of price changes for 800 companies listed in the Tokyo Stock Exchange, and for the Nikkei 225 index over a 27-year period from January …
In most OTC markets, a small number of market makers provide liquidity to other market participants. More precisely, for a list of assets, they set prices at which they agree to buy and sell. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money while …
Study finds chirally cosmetic surgeries on knots and manifolds, contradicting previous conjectures.
Online purchase decisions in organizations can go through a complex journey with multiple agents involved in the decision making process. Depending on the product being purchased, and the organizational structure, the process may involve employees who first conduct market research, and then influence decision makers wh…
Prediction markets can be manipulated by traders who can move contract settlements, harming price discovery.
The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that …
Deep learning LSTM predicts stock prices for portfolio design in Indian sectors.
Geometric Brownian motion simulates stock prices for Brazilian small caps index.
Study finds GBM model accurately predicts stock prices on Ghana Stock Exchange.
Modeling price clustering in financial markets using discrete distributions.