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Portfolio Choice, Liquidity Constraints and Stock Market Mean Reversion

Portfolio Choice, Liquidity Constraints and Stock Market Mean Reversion
Author: Alexander Michaelides
Publisher:
Total Pages: 49
Release: 2008
Genre:
ISBN:

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This paper solves numerically for the optimal consumption and portfolio choice of a long-horizon investor facing short-sales and borrowing constraints, undiversifiable labor income risk and a predictable time varying equity premium. The investor pursues aggressive market timing strategies; a speculative increase in savings arises when stock returns are expected to be high and conversely when future returns are expected to be low. Positive correlation between permanent earnings shocks and stock return innovations generates a substantial hedging demand for the riskless asset for risk averse investors. Hedging demands arising from the correlation of permanent earnings shocks and the factor innovation and from the correlation between the factor innovation and the stock market shock are evaluated and are found to be small in magnitude. Conversely, asset demand changes that arise from relaxing the liquidity constraints are substantial.


Stock Market Mean Reversion and Portfolio Choice Over the Life Cycle

Stock Market Mean Reversion and Portfolio Choice Over the Life Cycle
Author: Alexander Michaelides
Publisher:
Total Pages: 101
Release: 2015
Genre:
ISBN:

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We solve for optimal consumption and portfolio choice in a life-cycle model with short-sales and borrowing constraints, undiversifiable labor income risk and a predictable, time-varying, equity premium and show that the investor pursues aggressive market timing strategies. Importantly, in the presence of stock market predictability, the model suggests that the conventional financial advice of reducing stock market exposure as retirement approaches is correct on average, but ignoring changing market information can lead to substantial welfare losses. Therefore, enhanced target-date funds (ETDFs) that condition on expected equity premia increase welfare relative to target-date funds (TDFs). Out-of-sample analysis supports these conclusions.


Stock Market Mean Reversion and the Optimal Equity Allocation of a Long-Lived Investor

Stock Market Mean Reversion and the Optimal Equity Allocation of a Long-Lived Investor
Author: John Y. Campbell
Publisher:
Total Pages: 28
Release: 2008
Genre:
ISBN:

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This paper solves numerically the intertemporal consumption and portfolio choice problem of an infinitely-lived investor who faces a time-varying equity premium. The solutions we obtain are very similar to the approximate analytical solutions of Campbell and Viceira (1999), except at the upper extreme of the state space where both the numerical consumption and portfolio rules flatten out. We also consider a constrained version of the problem in which the investor faces borrowing and short-sales constraints. These constraints bind when the equity premium moves away from its mean in either direction, and are particularly severe for risk-tolerant investors. The optimal constrained portfolio rules are similar but not identical to the optimal unconstrained rules with the constraints imposed. The portfolio constraints also affect the optimal consumption policy.


Strategic Asset Allocation

Strategic Asset Allocation
Author: John Y. Campbell
Publisher: OUP Oxford
Total Pages: 272
Release: 2002-01-03
Genre: Business & Economics
ISBN: 019160691X

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Academic finance has had a remarkable impact on many financial services. Yet long-term investors have received curiously little guidance from academic financial economists. Mean-variance analysis, developed almost fifty years ago, has provided a basic paradigm for portfolio choice. This approach usefully emphasizes the ability of diversification to reduce risk, but it ignores several critically important factors. Most notably, the analysis is static; it assumes that investors care only about risks to wealth one period ahead. However, many investors—-both individuals and institutions such as charitable foundations or universities—-seek to finance a stream of consumption over a long lifetime. In addition, mean-variance analysis treats financial wealth in isolation from income. Long-term investors typically receive a stream of income and use it, along with financial wealth, to support their consumption. At the theoretical level, it is well understood that the solution to a long-term portfolio choice problem can be very different from the solution to a short-term problem. Long-term investors care about intertemporal shocks to investment opportunities and labor income as well as shocks to wealth itself, and they may use financial assets to hedge their intertemporal risks. This should be important in practice because there is a great deal of empirical evidence that investment opportunities—-both interest rates and risk premia on bonds and stocks—-vary through time. Yet this insight has had little influence on investment practice because it is hard to solve for optimal portfolios in intertemporal models. This book seeks to develop the intertemporal approach into an empirical paradigm that can compete with the standard mean-variance analysis. The book shows that long-term inflation-indexed bonds are the riskless asset for long-term investors, it explains the conditions under which stocks are safer assets for long-term than for short-term investors, and it shows how labor income influences portfolio choice. These results shed new light on the rules of thumb used by financial planners. The book explains recent advances in both analytical and numerical methods, and shows how they can be used to understand the portfolio choice problems of long-term investors.


Portfolio Choice and Liquidity Constraints

Portfolio Choice and Liquidity Constraints
Author: Alexander Michaelides
Publisher:
Total Pages: 41
Release: 2008
Genre:
ISBN:

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In this paper, we study the infinite-horizon model of household portfolio choice under liquidity constraints and revisit the portfolio specialization puzzle for impatient consumers with access to riskless and risky assets. We consider a labor income process that allows us to decompose the consumption and portfolio effects of permanent and transitory shocks to labor income and show their interaction with liquidity constraints and their relative importance in producing precautionary effects and the portfolio specialization result. We show why habit persistence and risk aversion cannot resolve the puzzle and argue that positive correlation between earnings shocks and stock returns is unlikely to provide a plausible resolution. We then offer an alternative explanation for observed stock holding patterns and the slow emergence of an equity culture. Specifically, we find that relatively small, fixed, stock market entry costs are sufficient to deter households from participating in the stock market. Such entry costs could arise, for example, from informational considerations, sign-up fees, and investor inertia.


Online Portfolio Selection

Online Portfolio Selection
Author: Bin Li
Publisher: CRC Press
Total Pages: 227
Release: 2018-10-30
Genre: Business & Economics
ISBN: 1482249642

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With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment. The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision task Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art Investigate possible future directions Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment. Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.