# C Kenneth JonesMassachusetts Institute of Technology | MIT · Advanced Studies Financial Economic

C Kenneth Jones

PHD University of Colorado

## About

27

Publications

7,330

Reads

**How we measure 'reads'**

A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more

122

Citations

Citations since 2017

Introduction

I am now working on new valuation models that incorporate mean-reversion risk. An autocorrelation Arbitrage Pricing Theory model and an auto-covariance Capital Asset Pricing Model will achieve market equilibrium for long-term mean-reversion risks. I have already published a Digital Portfolio Theory model that finds optimal portfolios based on mean-reversion risks. These methods relay on digital signal processing technology.
https://pdfs.semanticscholar.org/fbd4/ece11fda2c4c99b41576ef7f58acda08c44b.pdf
-Ken

Education

September 1980 - May 1986

September 1978 - May 1980

September 1964 - May 1969

## Publications

Publications (27)

I derive a single period, intertemporal, static APT that values asset time-interval risks. Uncorrelated mean-reversion risk factors form an exact factor structure APT. An equilibrium multi-beta CAPM with long-term mean-reversion betas is developed. I define mean-reversion risk by using digital signal processing to decompose risk into orthogonal tim...

The paper compares three portfolio optimization models. Modern portfolio theory (MPT) is a short-horizon volatility model. The relevant time horizon is the sampling interval. MPT is myopic and implies that investors are not concerned with long-term variance or mean-reversion. Intertemporal portfolio choice is a multiple period model that revises po...

The paper compares three portfolio optimization models. Modern portfolio theory (MPT) is a short-horizon volatility model. The relevant time horizon is the sampling interval. MPT is myopic and implies that investors are not concerned with long-term variance or mean-reversion. Intertemporal portfolio choice is a multiple period model that revises po...

Mean-reversion risk measures long-term risk at multiple horizons. Digital signal processing and an additive noise model are used to test the white noise hypothesis for total and idiosyncratic risk of all individual firms. The results suggest that single period risk is composed of multiple long-term calendar and non-calendar variances.

The investment portfolio with stochastic returns can be represented as a maximum flow generalized network with sto-chastic multipliers. Modern portfolio theory (MPT) [1] provides a myopic short horizon solution to this network by adding a parametric variance constraint to the maximize flow objective function. MPT does not allow the number of securi...

This paper presents alternative approach to foreign exchange market trading decisions. The model is equally applicable to the arbitrage practices of international banks, to the hedging decisions of multinational corporations, to the investment decisions of currency fund managers and to the uncovered positions of currency speculators. By using a net...

The nature of risk and long-term returns is not fully understood. There is a need for a measure of long-term risk at multiple horizons. Digital signal processing and an additive noise model are used to test the white noise hypothesis for total and idiosyncratic risk of individual firms at two-month to four-year periods. All firms have significant a...

Digital Portfolio Theory (DPT) permits investors to control their risk exposure with respect to multiple investment time horizons. DPT is a theoretical enhancement for estimating efficient portfolios that drops the normal distribution and zero autocorrelation assumptions of Modern Portfolio Theory (MPT) and allows effects of unconditional mean reve...

I examine capabilities of Digital Portfolio Theory (DPT) and extend it to control portfolio size. DPT is a static, single period mean-variance-autocovariance portfolio optimization paradigm that allows returns to be mean-reverting. The optimal dynamic single period solutions depend on the unconditional predictability of second moments. Optimal port...

The nature of risk and long-term returns is not fully understood. There is a need for a measure of long-term risk at multiple horizons. Digital signal processing and an additive noise model are used to test the white noise hypothesis for total and idiosyncratic risk of individual firms at two-month to four-year periods. All firms have significant a...

The nature of the long-term time-varying risk return relation is not fully understood. It is widely believed, incorrectly, that a risk based explanation of time-varying equilibrium return would require corresponding time variation in risk. There is a need for a new methodology to measure long-term risk at multiple horizons. In this paper we test an...

In this study, we use zero-one variables to control fixed transaction costs independent of trade size in the portfolio selection problem. The optimal solution to the maximum flow, risk constrained stochastic portfolio network is found using Digital Portfolio Theory (DPT). Digital signals describe return processes and power spectral densities descri...

It is widely believed, incorrectly, that a risk based explanation of time-varying equilibrium returns would require corresponding time variation in risk. Empirical research has focused on time-varying risk, to determine if it is associated with time-varying returns. Evidence is mixed in support of a coincident time-varying risk-return relation. Thi...

A model of risk with multiple independent unconditional calendar and non-calendar variance components is used to explain time-varying returns. Digital signals represent finite stock return series. The random walk hypothesis is tested using digital signal processing methods. A stochastic additive market noise model measures total and idiosyncratic r...

The Modern Portfolio Theory of Markowitz maximized portfolio expected return subject to holding total portfolio variance below a selected level. Digital Portfolio Theory is an extension of Modern Portfolio Theory, with the added dimension of memory. Digital Portfolio Theory decomposes the portfolio variance into independent components using the sig...

The Portfolio Selection System (PSS) software package is based on the theoretical concepts developed in Professor C. Kenneth Jones' book Portfolio Management, published by McGraw-Hill in 1992. In this theoretical text a comprehensive modeling language is developed that can be applied generally to all financial problems. In addition, the use of digi...

Throughout the world there is continuing development of more structured approaches to financial management. This book is an in-depth treatment of the concepts and ideas necessary to model complex financial transactions and investment decisions. The book provides a methodology for dissecting and solving most practical investment problems encountered...

Spreadsheet software is now widely used as a decision-making tool,
owing to the simplicity and ease with which generalists can analyse and
obtain fast and precise information. Through spreadsheet programs, a
non-specialist can conduct an exhaustive “what if” search in
order to make decisions regarding “what if” questions. Now,
with the availability...

This paper develops a generalized dynamic network model for portfolio investment diversification. The model considers the situation of the fixed solution subset corresponding to a fixed single-resource economic investment such as that found in many oil-producing nations. Quadratic side constraints on the variance of the resultant flow distribution...

This paper describes a generalized network framework and an efficient, practical algorithm for large scale mean-variance portfolio selection, based on the nonparametric description of stochastic processes in the frequency domain. A constraint on the variance of uncertain incoming flows to a node in a network model results in a quadratic expression,...

This paper introduces a frequency domain model to portfolio theory by using a Fourier series to describe the characteristics of a time series reruns. Each term of the Fourier series can be represented as a vector. The Fourier return vector includes timing information in addition to mean, variance, and covariance of return. The Markowitz two factor...

Thesis (D.B.A.)--University of Colorado, 1986. Includes bibliographical references (leaves [213]-223).