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Fabers sector rotation trading strategy

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fabers sector rotation trading strategy

I came across this nice post on Mebane Faber's research page outlining a simple rules-based sector momentum model for long term investing. This algo is designed to work in minute mode and to be compatible with paper trading and live trading, as implemented rebalance is triggered once per week. Also take a look at Dan's post on these new methods for some more context. There are lots of easy knobs to turn with this one, from the selection of the sector Strategy to the rebalance frequency, the momentum horizon and even the rules themselves, so clone it and see if you can find a better version than this one! The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific strategy. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Rotation Retirement Income Security Act ofas amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. Sector views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. One of the first things I wanted to backtest was a strategy like this. I'd not thought of basing it purely on the market sectors like this. Is it really supposed to be this simple? The key model inputs driving the decision-making process of the algorithm are data on total return movements, volatility, and rate of change in volatility for the subject equity sector. Have you any idea what formula they might be using? It sounds very vague and "hand wavey". I'd expect some kind of channel with width based on recent candle widths would be a step in the right direction http: Below we examine 9 sectors, equal weighted if above 10sma. I'm sure that the original F-squared logic is indeed more complex, though whether it generates better risk adjusted returns after fees is probably the more interesting question: I haven't done much work tweaking this strategy, but I'd love to see any improvements or modifications that you find to be interesting if you'd like to share them on this thread! Aha please excuse my mistake, it was late when I read your post and I never got that far down before I looked at the code. It seems like a reasonable first step. It would be interesting to zoom in on the entry and exit points on the chart to see if how badly it gets chopped up at the crossing points. The chart they show just has cumulative returns. It would be interesting to run this on sector data from the Japanese market. I'd prefer to know that any strategy was proven in less bullish conditions. I spent a few hours tonight loking for Japanese data but I couldnt find anything except daily data. The quantopian data is only 5 years IIRC. So we just bought some longer term historical data 15 years of 1 min data from quantquote. I have some rotation for entering and exiting swing trade positions that I'd like to test as well. I may pay for their ETFs data if we make good progress with the stock data. Just fabers clarify on the data history, we actually have pricing back almost 12 years start date is Jan - see the FAQ: Sector you have ideas you'd like coded up in Python that you are willing to share this community has a lot of technical expertise and could probably be helpful with the language conversion. This is my first post in this community, I had clone this trading and do the backtest, But I cannot got the same performance compare to Jess backtest, Could someone kindly let sector know trading is wrong for me! You are getting the same result as Jess i. The difference is that the benchmark is now performing better - see https: This means that every backtest run on Quantopian from Aug. Thanks your kindly reply, now I see the benchmark have been changed. How do you think the algorithm that why cannot got better performance than benchmark from bull market? Sorry, something went wrong. Try again or contact us by sending feedback. Point72 is a family office. Point72 does not fabers, solicit or accept investors that are not eligible family clients. This is not intended to be a testimonial and the reader should not construe it as such. Investor Relations Allocations Research Datasets Notebooks Algorithms Community Forums Events Contest Learn Getting Started Tutorials Lectures Workshops Help FAQ API Reference Contact Support Log In Sign Up. There was an error loading this backtest. Backtest from to with initial capital. Overall Metrics Returns Alpha Beta Sharpe Sortino Volatility Max Drawdown Total Returns. Returns 1 Month 3 Month 6 Month 12 Month. Alpha 1 Month 3 Month 6 Month 12 Month. Beta 1 Month 3 Month 6 Month 12 Month. Sharpe 1 Month 3 Month 6 Month 12 Month. Sortino 1 Month 3 Month 6 Month 12 Month. Volatility 1 Month 3 Month 6 Month 12 Month. Max Drawdown 1 Month 3 Month 6 Month 12 Month. This backtest was created using an older version of the backtester. Please re-run this backtest to see results using the latest backtester. Learn more about the recent changes. There was a runtime error. Sorry for the inconvenience. Try using the built-in debugger to analyze your code. If you would like help, send us an email. It sounds very vague and "hand wavey" I'd expect some kind of channel with width based on recent candle widths would be a step in the right direction http: Hi Jason, The algo that I wrote is an fabers of the rules based system that Meb Faber outlines as: Hi Jason, Just to clarify on the data history, we actually have pricing back almost 12 years start date is Jan - see the FAQ: Dear sir, This is my first post in this community, I had clone this algorithm and do the backtest, But I cannot got the same performance compare to Jess backtest, Could someone kindly strategy me know what is wrong for me! Hello Ding, You are getting the same result as Jess i. Hello Peter, Thanks your kindly reply, now I see the benchmark have been changed. Please sign in or join Quantopian to post a reply. Once you join, you can: Run full backtests, with detailed risk metrics and full transaction reports. Algorithm Rotation Live Algorithm Notebook. Sorry, research is currently undergoing maintenance. Please check back shortly. If the maintenance period lasts longer than expected, you can find updates on status. Sorry, something went wrong on trading end. Please try again or contact Quantopian support. You've successfully submitted a support ticket. Our support team will be in touch soon. Send Error submitting support request. fabers sector rotation trading strategy

Nov 30, 2016 Sector Rotation Strategy Trades

Nov 30, 2016 Sector Rotation Strategy Trades

3 thoughts on “Fabers sector rotation trading strategy”

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