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We describe the pricing and hedging of financial options without the use of probability using rough paths. By encoding the volatility of assets in an enhancement of the price trajectory, we give a pathwise presentation of the replication of…

Mathematical Finance · Quantitative Finance 2020-07-09 John Armstrong , Claudio Bellani , Damiano Brigo , Thomas Cass

This paper explores the effectiveness of high-frequency options trading strategies enhanced by advanced portfolio optimization techniques, investigating their ability to consistently generate positive returns compared to traditional long or…

Trading and Market Microstructure · Quantitative Finance 2024-08-19 Sid Bhatia

We build a state-of-the-art dynamic model of private asset allocation that considers five key features of private asset markets: (1) the illiquid nature of private assets, (2) timing lags between capital commitments, capital calls, and…

Portfolio Management · Quantitative Finance 2025-03-04 Hui Chen , Giovanni Gambarotta , Simon Scheidegger , Yu Xu

We show that the moments of the distribution of historic stock returns are in excellent agreement with the Heston model and not with the multiplicative model, which predicts power-law tails of volatility and stock returns. We also show that…

Mathematical Finance · Quantitative Finance 2019-08-01 Zhiyuan Liu , M. Dashti Moghaddam , R. A. Serota

Risk and uncertainty will always be a matter of experience, luck, skills, and modelling. Leverage is another concept, which is critical for the investor decisions and results. Adaptive skills and quantitative probabilistic methods need to…

Risk Management · Quantitative Finance 2016-12-22 Mihail Turlakov

Stochastic volatility models describe asset prices $S_t$ as driven by an unobserved process capturing the random dynamics of volatility $\sigma_t$. Here, we quantify how much information about $\sigma_t$ can be inferred from asset prices…

Statistical Finance · Quantitative Finance 2015-12-29 Nils Bertschinger , Oliver Pfante

In this paper we propose a new model for volatility fluctuations in financial time series. This model relies on a non-stationary gaussian process that exhibits aging behavior. It turns out that its properties, over any finite time interval,…

Statistical Finance · Quantitative Finance 2015-06-12 J. F. Muzy , R. Baile , E. Bacry

We shortly review the statistical properties of the escape times, or hitting times, for stock price returns by using different models which describe the stock market evolution. We compare the probability function (PF) of these escape times…

Statistical Finance · Quantitative Finance 2015-05-13 Bernardo Spagnolo , Davide Valenti

We show that typical behaviors of market participants at the high frequency scale generate leverage effect and rough volatility. To do so, we build a simple microscopic model for the price of an asset based on Hawkes processes. We encode in…

Trading and Market Microstructure · Quantitative Finance 2016-09-19 El Euch Omar , Fukasawa Masaaki , Rosenbaum Mathieu

When the planning horizon is long, and the safe asset grows indefinitely, isoelastic portfolios are nearly optimal for investors who are close to isoelastic for high wealth, and not too risk averse for low wealth. We prove this result in a…

Portfolio Management · Quantitative Finance 2014-08-19 Paolo Guasoni , Johannes Muhle-Karbe , Hao Xing

We review some fundamental concepts of investment from a mathematical perspective, concentrating specifically on fractional-Kelly portfolios, which allocate a fraction of wealth to a growth-optimal portfolio while the remainder collects (or…

Portfolio Management · Quantitative Finance 2021-09-23 Anthony E. Brockwell

We show that recent stock market fluctuations are characterized by the cumulative distributions whose tails on short, minute time scales exhibit power scaling with the scaling index alpha > 3 and this index tends to increase quickly with…

Statistical Finance · Quantitative Finance 2009-11-13 S. Drozdz , M. Forczek , J. Kwapien , P. Oswiecimka , R. Rak

Financial volatility obeys two fascinating empirical regularities that apply to various assets, on various markets, and on various time scales: it is fat-tailed (more precisely power-law distributed) and it tends to be clustered in time.…

General Finance · Quantitative Finance 2023-09-12 Sabiou Inoua

Distributions of assets returns exhibit a slight skewness. In this note we show that our model of endogenous price formation \cite{Reimann2006} creates an asymmetric return distribution if the price dynamics are a process in which…

Physics and Society · Physics 2008-12-02 Stefan Reimann

Detailed study of multifractal characteristics of the financial time series of asset values and of its returns is performed using a collection of the high frequency Deutsche Aktienindex data. The tail index ($\alpha$), the Renyi exponents…

Statistical Mechanics · Physics 2009-11-07 A. Z. Gorski , S. Drozdz , J. Speth

A simple quantum model explains the Levy-unstable distributions for individual stock returns observed by ref.[1]. The probability density function of the returns is written as the squared modulus of an amplitude. For short time intervals…

Physics and Society · Physics 2008-12-02 Martin Schaden

We derive a consistent differential representation for the dynamics of a self-financing portfolio for different hedging strategies. In the basis of the derivation there is the so called "retarded action principle", which represents the…

Mathematical Finance · Quantitative Finance 2016-06-23 Dmitry Lesnik

We attempt to unveil the fine structure of volatility feedback effects in the context of general quadratic autoregressive (QARCH) models, which assume that today's volatility can be expressed as a general quadratic form of the past daily…

Statistical Finance · Quantitative Finance 2014-05-28 Rémy Chicheportiche , Jean-Philippe Bouchaud

Background: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However,…

Statistical Finance · Quantitative Finance 2014-07-22 Jun-jie Chen , Bo Zheng , Lei Tan

We analyze empirical data for 4,000 real-life trading portfolios (U.S. equities) with holding periods of about 0.7-19 trading days. We find a simple scaling C ~ 1/T, where C is cents-per-share, and T is the portfolio turnover. Thus, the…

Portfolio Management · Quantitative Finance 2016-03-22 Zura Kakushadze , Igor Tulchinsky