Portfolio Optimization

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Portfolio optimization: The all new Portfolio Builder

  From individual Strategies to Portfolio Optimization Based on the interest of our followers and our own investment philosophy, we have gradually evolved from offering single quantitative strategies towards blends or portfolios of strategies. The way we visualize our own development cycle might be best summarized in a chart: Where are we on this path and where are we heading? We believe we have now a stable set of 'core-strategies', which cover a broad spectrum of both risk/performance but also trading and hedging instruments. We will continue our research on new strategies, and will also in future come up with smart ideas in that area. However, we are currently increasing our effort in blending these strategies into portfolio solutions. The "Portfolio Builder" with fixed-weight allocations is here only the first step. Developing a dynamic Strategies of Strategies (or Meta-Strategies) which smartly allocate with changing weights among a set of our strategies is one of the projects we initiated since the four of us met in mid 2014. Our thought: Quickly reacting to or even anticipating changes in the market environment by changing horses on the fly, better dealing with changing correlations of markets and constantly challenging whether one of our strategies has lost ‘steam power’ should be even better than simply allocating funds with fixed weights or even worse discretionary among strategies. To continue the enhancement of our tools towards this vision, we’ve given our fixed-weight Portfolio Builder a major overhaul and implemented many of the requested features. Key features for portfolio optimization Some of the new key features for portfolio optimization are: Equity lines according to most recent strategy review Our subscribers know that we review our strategies periodically, either because we find improvements for the execution (change of IEV to FEZ in the Global Market Rotation), or introduce newly developed [...]

2017-10-02T20:00:00+00:00By |9 Comments

Easy Investing in a multi-strategy Markowitz optimized Portfolio

In our recent post we´ve shared some powerful options to design a well-balanced portfolio of several Logical Invest strategies to achieve a preset portfolio objective using Modern portfolio theory (MPT) techniques developed by Nobel Prize laureate Harry Markowitz. Here, we review the steps to achieving an optimized portfolio with our tools and summarize some portfolio options to illustrate use of our updated tool set:(picture for mobile use)These options might serve as a starting point to design your own portfolio according to your return and risk preferences, fundamental beliefs or asset class preferences.How do I start easily designing my portfolio?You can design a portfolio to meet your objectives in three simple steps that will not take you more than 30 minutes initially, and about 15 minutes monthly for rebalancing: Design and Execute your Custom Portfolio Starting with our Online Custom Portfolio Builder, you can simply select a preset portfolio objective. The tool will report back the allocation across our strategies that achieves that objective based on our quantitative models, and on portfolio optimization procedures that analyze the last 2105 trading days. Additionally, the user can select the “Custom Portfolio” tab, enter any strategy allocation weights he wishes and similarly calculate the performance of his custom allocation. Combined with our “Consolidated Signals” tool which we will introduce in a minute, the results from Portfolio Builder will point the user to the allocation across ETFs and/or stocks that have the best prospect to meet his objective.A Practical Example:Here is a practical example: Let´s assume I  think a historical portfolio volatility of around 15% in the period 2008-2016 is acceptable to me I would simply choose the “Max15% Volatility” (and Max CAGR) portfolio from the preconfigured portfolio list. Strategy allocation weights are immediately shown in the performance table and the portfolio risk/return performance is graphed in comparison to that [...]

2017-10-02T20:00:00+00:00By |2 Comments