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Trading options for edge : profit from options and manage risk like the professional trading firms
\"If you have experience in option trading, or a strong understanding of the options markets, but want to better understand how to trade given certain market conditions, this is the book for you. Many people have some knowledge of trading strategies, but have no idea how to pull it all together. Mark Sebastian's latest book will teach trade evaluation, using Greeks, trading various spreads under different market conditions, portfolio-building, and risk management. Sebastian's approach will help traders understand how to find edge, what kind of trade under what conditions will capture edge, and how to create and successfully hedge to help you build your own personal Goldman Sachs or Merrill Lynch. The book demonstrates how to structure a portfolio of trades that makes more money with less risk\"-- Provided by publisher.
Book
Effectiveness of the ESG approach in portfolio selection – an empirical evidence from the US stock market
The purpose of this study is to explore whether ESG (Environmental, Social, and Governance) criteria can serve as a valuable tool for investors when making rational decisions about financial security selection and portfolio construction. By applying Modern and Post-Modern portfolio theories (MPT and PMPT) under the conditions of ESG and Return Max criterion, our primary objective was determined: “Is ESG a criterion for investors in the rational selection of financial securities and portfolio construction?” A five-year analysis (2018–2023) was carried out on 484 financial securities (companies) from the S&P 500 Stock Index to answer this question. Data collected included the daily close price of the S&P 500 Stock Index, its constituents (484 stocks), ESG scores, risk-free rate, and the equity risk premium of the U.S. market. The results showed that financial securities chosen based on the Return Max criterion were generally undervalued on the market; however, this was not consistently observed by ESG Max where examples of overvalued securities were also identified. Nevertheless, using the Sharpe and Sortino Ratio performance indicators, it was concluded that the return per unit of assumed risk is more appealing to investors (with risk aversion) when considering the portfolios built on the ESG Max criterion.
Journal Article
Quick Introduction into the General Framework of Portfolio Theory
This survey offers a succinct overview of the General Framework of Portfolio Theory (GFPT), consolidating Markowitz portfolio theory, the growth optimal portfolio theory, and the theory of risk measures. Central to this framework is the use of convex analysis and duality, reflecting the concavity of reward functions and the convexity of risk measures due to diversification effects. Furthermore, practical considerations, such as managing multiple risks in bank balance sheets, have expanded the theory to encompass vector risk analysis. The goal of this survey is to provide readers with a concise tour of the GFPT’s key concepts and practical applications without delving into excessive technicalities. Instead, it directs interested readers to the comprehensive monograph of Maier-Paape, Júdice, Platen, and Zhu (2023) for detailed proofs and further exploration.
Journal Article
Cryptocurrencies as an asset class in portfolio optimisation
In this paper, cryptocurrencies are analysed as investment instruments. The study aims to verify whether they can be classified as an asset class and what kind of benefits they may bring to the investor's portfolio. We used 6 indices as proxies for the major asset classes, including the cryptocurrency index CRIX, for all cryptographic assets.Cryptocurrencies relatively fully satisfied 7 asset class requirements, namely stable aggregation, investability, internal homogeneity, external heterogeneity, expected utility, selection skill and cost-effective access. It was found that crypto assets have diversification properties. Portfolio optimisation with the Modern Portfolio Theory showed an increase in the Sharpe ratio of tangency portfolios with the inclusion of CRIX. However, the Post-Modern Portfolio Theory identified significant deterioration of the downside risk and the Sortino ratio.
Journal Article
Dealing with Uncertainty in Flood Management Through Diversification
This paper shows, through a numerical example, how to develop portfolios of flood management activities that generate the highest return under an acceptable risk for an area in the central part of the Netherlands. The paper shows a method based on Modern Portfolio Theory (MPT) that contributes to developing flood management strategies. MPT aims at finding sets of investments that diversify risks thereby reducing the overall risk of the total portfolio of investments. This paper shows that through systematically combining four different flood protection measures in portfolios containing three or four measures; risk is reduced compared with portfolios that only contain one or two measures. Adding partly uncorrelated measures to the portfolio diversifies risk. We demonstrate how MPT encourages a systematic discussion of the relationship between the return and risk of individual flood mitigation activities and the return and risk of complete portfolios. It is also shown how important it is to understand the correlation of the returns of various flood management activities. The MPT approach, therefore, fits well with the notion of adaptive water management, which perceives the future as inherently uncertain. Through applying MPT on flood protection strategies current vulnerability will be reduced by diversifying risk.
Journal Article
MEAN-VARIANCE PORTFOLIO OPTIMIZATION WHEN MEANS AND COVARIANCES ARE UNKNOWN
Markowitz's celebrated mean-variance portfolio optimization theory assumes that the means and covariances of the underlying asset returns are known. In practice, they are unknown and have to be estimated from historical data. Plugging the estimates into the efficient frontier that assumes known parameters has led to portfolios that may perform poorly and have counterintuitive asset allocation weights; this has been referred to as the \"Markowitz optimization enigma.\" After reviewing different approaches in the literature to address these difficulties, we explain the root cause of the enigma and propose a new approach to resolve it. Not only is the new approach shown to provide substantial improvements over previous methods, but it also allows flexible modeling to incorporate dynamic features and fundamental analysis of the training sample of historical data, as illustrated in simulation and empirical studies.
Journal Article
Portfolio Choice Under Cumulative Prospect Theory: An Analytical Treatment
We formulate and carry out an analytical treatment of a single-period portfolio choice model featuring a reference point in wealth, S-shaped utility (value) functions with loss aversion, and probability weighting under Kahneman and Tversky's
cumulative prospect theory
(CPT). We introduce a new measure of loss aversion for large payoffs, called the
large-loss aversion degree
(LLAD), and show that it is a critical determinant of the well-posedness of the model. The sensitivity of the CPT value function with respect to the stock allocation is then investigated, which, as a by-product, demonstrates that this function is neither concave nor convex. We finally derive optimal solutions explicitly for the cases in which the reference point is the risk-free return and those in which it is not (while the utility function is piecewise linear), and we employ these results to investigate comparative statics of optimal risky exposures with respect to the reference point, the LLAD, and the curvature of the probability weighting.
This paper was accepted by Wei Xiong, finance.
Journal Article
A general framework for portfolio theory, part III, multi-period markets and modular approach
This is Part III of a series of papers which focus on a general framework for portfolio theory. Here, we extend a general framework for portfolio theory in a one-period financial market as introduced in Part I [Maier-Paape and Zhu, Risks 2018, 6(2), 53] to multi-period markets. This extension is reasonable for applications. More importantly, we take a new approach, the 'modular portfolio theory', which is built from the interaction among four related modules: (a) multi period market model; (b) trading strategies; (c) risk and utility functions (performance criteria); and (d) the optimization problem (efficient frontier and efficient portfolio). An important concept that allows dealing with the more general framework discussed here is a trading strategy generating function. This concept limits the discussion to a special class of manageable trading strategies, which is still wide enough to cover many frequently used trading strategies, for instance 'constant weight' (fixed fraction). As application, we discuss the utility function of compounded return and the risk measure of relative log drawdowns.
Journal Article
A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms
We provide a general framework for finding portfolios that perform well out-of-sample in the presence of estimation error. This framework relies on solving the traditional minimum-variance problem but subject to the additional constraint that the norm of the portfolio-weight vector be smaller than a given threshold. We show that our framework nests as special cases the shrinkage approaches of Jagannathan and Ma (Jagannathan, R., T. Ma. 2003. Risk reduction in large portfolios: Why imposing the wrong constraints helps. J. Finance 58 1651–1684) and Ledoit and Wolf (Ledoit, O., M. Wolf. 2003. Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. J. Empirical Finance 10 603–621, and Ledoit, O., M. Wolf. 2004. A well-conditioned estimator for large-dimensional covariance matrices. J. Multivariate Anal. 88 365–411) and the 1/ N portfolio studied in DeMiguel et al. (DeMiguel, V., L. Garlappi, R. Uppal. 2009. Optimal versus naive diversification: How inefficient is the 1/ N portfolio strategy? Rev. Financial Stud. 22 1915–1953). We also use our framework to propose several new portfolio strategies. For the proposed portfolios, we provide a moment-shrinkage interpretation and a Bayesian interpretation where the investor has a prior belief on portfolio weights rather than on moments of asset returns. Finally, we compare empirically the out-of-sample performance of the new portfolios we propose to 10 strategies in the literature across five data sets. We find that the norm-constrained portfolios often have a higher Sharpe ratio than the portfolio strategies in Jagannathan and Ma (2003), Ledoit and Wolf (2003, 2004), the 1/ N portfolio, and other strategies in the literature, such as factor portfolios.
Journal Article
Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
Stochastic programming can effectively describe many decision-making problems in uncertain environments. Unfortunately, such programs are often computationally demanding to solve. In addition, their solution can be misleading when there is ambiguity in the choice of a distribution for the random parameters. In this paper, we propose a model that describes uncertainty in both the distribution form (discrete, Gaussian, exponential, etc.) and moments (mean and covariance matrix). We demonstrate that for a wide range of cost functions the associated distributionally robust (or min-max) stochastic program can be solved efficiently. Furthermore, by deriving a new confidence region for the mean and the covariance matrix of a random vector, we provide probabilistic arguments for using our model in problems that rely heavily on historical data. These arguments are confirmed in a practical example of portfolio selection, where our framework leads to better-performing policies on the \"true\" distribution underlying the daily returns of financial assets.
Journal Article