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Results for “Morgan” · papers 14 · wiki 1
Academic Papers · 14arXiv q-fin live 14 · desk corpus 1
arXiv · arXiv q-fin · 2012

Cross comparison and modelling of Goldman Sachs, Morgan Stanley, JPMorgan Chase, Bank of America, and Franklin Resources

We have studied statistical characteristics of five share price time series. For each stock price, we estimated a best fit quantitative model for the monthly closing price as based on the decomposition into two defining consumer price indices selected from a large set of CPIs. It was found that there are two pairs of similar models (Bank of America/Morgan Stanley and Goldman Sachs/JPMorgan Chase) with a standalone mo

Ivan Kitov
arXiv · arXiv q-fin · 2025

Market-Based Portfolio Variance

The variance measures the portfolio risks the investors are taking. The investor, who holds his portfolio and doesn't trade his shares, at the current time can use the time series of the market trades that were made during the averaging interval with the securities of his portfolio and assess the current return, variance, and hence the current risks of his portfolio. We show how the time series of trades with the sec

Victor Olkhov
arXiv · arXiv q-fin · 2025

Markowitz Variance May Vastly Undervalue or Overestimate Portfolio Variance and Risks

We consider the investor who doesn't trade shares of his portfolio. The investor only observes the current trades made in the market with his securities to estimate the current return, variance, and risks of his unchanged portfolio. We show how the time series of consecutive trades made in the market with the securities of the portfolio can determine the time series that model the trades with the portfolio as with a

Victor Olkhov
arXiv · arXiv q-fin · 2024

Expressions of Market-Based Correlations Between Prices and Returns of Two Assets

This paper derives the expressions of correlations between prices of two assets, returns of two assets, and price-return correlations of two assets that depend on statistical moments and correlations of the current values, past values, and volumes of their market trades. The usual frequency-based expressions of correlations of time series of prices and returns describe a partial case of our model when all trade volum

Victor Olkhov
arXiv · arXiv q-fin · 2023

Market-Based Probability of Stock Returns

This paper describes the dependence of market-based statistical moments of returns on statistical moments and correlations of the current and past trade values. We use Markowitz's definition of value weighted return of a portfolio as the definition of market-based average return of trades during the averaging period. Then we derive the dependence of market-based volatility and higher statistical moments of returns on

Victor Olkhov
arXiv · arXiv q-fin · 2023

Prime Match: A Privacy-Preserving Inventory Matching System

Inventory matching is a standard mechanism/auction for trading financial stocks by which buyers and sellers can be paired. In the financial world, banks often undertake the task of finding such matches between their clients. The related stocks can be traded without adversely impacting the market price for either client. If matches between clients are found, the bank can offer the trade at advantageous rates. If no ma

Antigoni Polychroniadou, Gilad Asharov, Benjamin Diamond, Tucker Balch, Hans Buehler
arXiv · arXiv q-fin · 2022

Market-Based Asset Price Probability

The random values and volumes of consecutive trades made at the exchange with shares of security determine its mean, variance, and higher statistical moments. The volume weighted average price (VWAP) is the simplest example of such a dependence. We derive the dependence of the market-based variance and 3rd statistical moment of prices on the means, variances, covariances, and 3rd moments of the values and volumes of

Victor Olkhov
arXiv · arXiv q-fin · 2019

A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy

Stock return predictability is an important research theme as it reflects our economic and social organization, and significant efforts are made to explain the dynamism therein. Statistics of strong explanative power, called "factor" have been proposed to summarize the essence of predictive stock returns. Although machine learning methods are increasingly popular in stock return prediction, an inference of the stock

Kei Nakagawa, Masaya Abe, Junpei Komiyama
arXiv · arXiv q-fin · 2013

Analyzing Herd Behavior in Global Stock Markets: An Intercontinental Comparison

Herd behavior is an important economic phenomenon, especially in the context of the recent financial crises. In this paper, herd behavior in global stock markets is investigated with a focus on intercontinental comparison. Since most existing herd behavior indices do not provide a comparative method, we propose a new herd behavior index and demonstrate its desirable properties through simple theoretical models. As fo

Changki Kim, Yangho Choi, Woojoo Lee, Jae Youn Ahn
arXiv · arXiv q-fin · 2005

Characteristics of the Korean stock market correlations

In this study, we establish a network structure of the Korean stock market, one of the emerging markets, with its minimum spanning tree through the correlation matrix. Base on this analysis, it is found that the Korean stock market doesn't form the clusters of the business sectors or of the industry categories. When the MSCI (Morgan Stanley Capital International Inc.) index is exploited, we found that the clusters of

Woo-Sung Jung, Seungbyung Chae, Jae-Suk Yang, Hie-Tae Moon
arXiv · arXiv q-fin · 2024

On Quantum Ambiguity and Potential Exponential Computational Speed-Ups to Solving Dynamic Asset Pricing Models

We formulate quantum computing solutions to a large class of dynamic nonlinear asset pricing models using algorithms, in theory exponentially more efficient than classical ones, which leverage the quantum properties of superposition and entanglement. The equilibrium asset pricing solution is a quantum state. We introduce quantum decision-theoretic foundations of ambiguity and model/parameter uncertainty to deal with

Eric Ghysels, Jack Morgan
arXiv · arXiv q-fin · 2023

Quantum Computational Algorithms for Derivative Pricing and Credit Risk in a Regime Switching Economy

Quantum computers are not yet up to the task of providing computational advantages for practical stochastic diffusion models commonly used by financial analysts. In this paper we introduce a class of stochastic processes that are both realistic in terms of mimicking financial market risks as well as more amenable to potential quantum computational advantages. The type of models we study are based on a regime switchin

Eric Ghysels, Jack Morgan, Hamed Mohammadbagherpoor
arXiv · arXiv q-fin · 2018

A common trajectory recapitulated by urban economies

Is there a general economic pathway recapitulated by individual cities over and over? Identifying such evolution structure, if any, would inform models for the assessment, maintenance, and forecasting of urban sustainability and economic success as a quantitative baseline. This premise seems to contradict the existing body of empirical evidences for path-dependent growth shaping the unique history of individual citie

Inho Hong, Morgan R. Frank, Iyad Rahwan, Woo-Sung Jung, Hyejin Youn
arXiv · arXiv q-fin · 2011

Extreme Measures of Agricultural Financial Risk

Risk is an inherent feature of agricultural production and marketing and accurate measurement of it helps inform more efficient use of resources. This paper examines three tail quantile-based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value at Risk (VaR), Expected Shortfall (ES) and Spectral Risk Measures (SRMs). We use Extreme Value Theor

John Cotter, Kevin Dowd, Wyn Morgan
Wiki Entities · 1
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