Quantocracy

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Quantocracy’s Daily Wrap for 12/06/2017

This is a summary of links featured on Quantocracy on Wednesday, 12/06/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • External Strategy Rule Evaluation. Too many rules? [Alvarez Quant Trading]

    A common question I get is where do I find all my research ideas. My main source is Quantocracy. He does a great job of curating posts because the work is manually done. Then there the Better System Trader and Trend Following Radio podcasts. Usually from these sources I get a nugget of an idea to research or a simple strategy. Sometimes the post/podcast will recommend a book. From one of these
  • Can Time Solve the Issue of High Valuations? [EconomPic]

    What an investors pays for an asset directly impacts the forward return an investor is likely to receive. The question for any investor given todays high stock multiples AND low bond yields globally is how much this matters not only over an intermediate time frame, but over a period potentially as long as the rest of many investors investing lifetimes. Sneak preview it may matter a lot more
  • 5 Questions For Wesley Gray of @AlphaArchitect [Capital Spectator]

    Momentum investing betting on the persistence of price trends in the short to medium term has captured the crowds attention in recent years. Consider, for instance, the strong growth in ETF assets in the niche. The first fund launched a bit more than five years ago; today, there are dozens of momentum ETFs, collectively holding nearly $15 billion in assets, according to etfdb.com.
  • Iron Condor Results Summary – Part 5 – IC Structure vs Metrics Correlation [DTR Trading]

    In the last article, posted way back in August, I looked at the Iron Condor structures that appeared to perform the best for each of the seven metrics I tracked. Recall that I tested 3024 different Iron Condor strategy variations over the period from January 2007 through September 2016. This testing generated more than 600,000 Iron Condor trades. The past articles can be found at: Iron Condor

Quantocracy’s Daily Wrap for 12/05/2017

This is a summary of links featured on Quantocracy on Tuesday, 12/05/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Skis and Bikes: The Untold Story of Diversification with Risk Parity [Invest Resolve]

    In most parts of Canada we have very distinct seasons. Some months of the year are temperate and relatively dry, while other months are cold and snowy. As a result, most Canadian towns of any size have stores that sell skis and bikes. Of course, they dont inventory both skis and bikes at the same time. Rather, in the spring they sell off all their ski related inventory and set out their bike
  • Portable Beta: Making the Most of the Returns You’re Already Getting [Flirting with Models]

    Traditionally, investors have used a balance between stocks and bonds to govern their asset allocation. Expanding this palette to include other asset classes can allow them to potentially both enhance return and reduce risk, benefiting from diversification. Modern portfolio theory tells us, however, that the truly optimal choice is to apply leverage to the most risk-efficient portfolio. In a low
  • Why The SPX Reversal May Be A Positive For The Bulls [Quantifiable Edges]

    Before spending much Monday selling off, the SPX managed to make a new intraday all-time high. The new high followed by a poor and downward close triggered the study below, from the Quantifinder. Results are all updated. 2017-12-05 Results here seem to suggest an upside edge over the next 1-2 weeks. Though the reversal may have felt frustrating to bulls at the time, it does not appear to be
  • Equity Market is Efficient – But on a Long Term [Quantpedia]

    We provide further evidence that markets trend on the medium term (months) and mean-revert on the long term (several years). Our results bolster Blacks intuition that prices tend to be off roughly by a factor of 2, and take years to equilibrate. The story behind these results fits well with the existence of two types of behaviour in financial markets: chartists, who act as trend
  • Diverisification is Not Always a Free Lunch [Alpha Architect]

    Shawn McKay, Robert Shapiro, Ric Thomas A version of this paper can be found here Want to read our summaries of academic finance papers? Check out our Academic Research Insight category. What are the research questions? Diversification is often thought of as the only free lunch in finance and it is a primary duty for fiduciaries, as codified in the Uniform Prudent Investor Act. The Act is

Quantocracy’s Daily Wrap for 12/01/2017

This is a summary of links featured on Quantocracy on Friday, 12/01/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Alternative Data Conference [Quandl]

    ADC 18 is an event for institutional investors and business professionals working to stay on top of the radically evolving landscape of alternative data. Signal Graphic Alternative Data Vizualization The alternative data landscape is evolving quickly. In less than one year, we've seen rapid adoption of alternative data throughout capital markets. This year's conference will: Deep dive

Quantocracy’s Daily Wrap for 11/30/2017

This is a summary of links featured on Quantocracy on Thursday, 11/30/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Adaptive Volatility: A Robustness Test Using Global Risk Parity [CSS Analytics]

    In the last post we introduced the concept of using adaptive volatility in order to have a flexible lookback as a function of market conditions. We used the R-squared of price as a proxy for the strength of the trend in the underlying market in order to vary the half-life in an exponential moving average framework. The transition function used an exponential formula to translate to a smoothing
  • Statistical Distributions of the Volatility Index [Relative Value Arbitrage]

    VIX related products (ETNs, futures and options) are becoming popular financial instruments, for both hedging and speculation, these days. The volatility index VIX was developed in the early 90s. In its early days, it led the derivative markets. Today the dynamics has changed. Now there is strong evidence that the VIX futures market leads the cash index. In this post we are going to look at
  • Installing TensorFlow on Ubuntu 16.04 with an Nvidia GPU [Quant Start]

    Any serious quant trading research with machine learning models necessitates the use of a framework that abstracts away the model implementation from the model specification. This is particularly crucial for deep learning techniques as production-grade models require training on GPUs to make them computationally tractable. However, direct programming of GPUs requires knowledge of proprietary
  • Podcast: A beginners foray into (part-time) systematic trading w/ Kory Hoang [Chat With Traders]

    Kory Hoang is not a veteran traderhes not someone who has been doing this 10-20 years. Hes someone who has been doing this for only a few years, yet hes begun to make decent gains on his trading capital. Kory is also not a full-time trader well, at the time of recording thisa few weeks agohe wasnt! Kory was a private equity analyst for Pitchbook, who traded on the side. But
  • Everyone, Even a Passive Vanguard Investor, is a Factor Investor [Alpha Architect]

    Much has been made of Factor Investing, and even Vanguard is launching a suite of actively-managed factor ETFs. But even now, with Vanguard offering factor ETFs, there are many investors that only invest passively into an index fund, such as the SP500 or EAFE index. These investors will cite the numerous studies showing that (on average) active management fails compared to an index fund (there are

Quantocracy’s Daily Wrap for 11/29/2017

This is a summary of links featured on Quantocracy on Wednesday, 11/29/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Better Way to Model the VIX [Six Figure Investing]

    Models are useful. They help us understand the world around us and aid us in predicting what will happen next. But its important to remember that models dont necessarily reflect the underlying reality of the thing were modeling. The Ptolemaic model of the solar system assumed the Earth was the center of everything but in spite of that spectacular error, it did a good job of predicting the
  • Combine Market Trend and Economic Trend Signals? [CXO Advisory]

    A subscriber requested review of an analysis concluding that combining economic trend and market trend signals enhances market timing performance. Specifically, per the example in the referenced analysis, we look at combining: The 10-month simple moving average (SMA10) for the broad U.S. stock market. The trend is positive (negative) when the market is above (below) its SMA10. The 12-month simple
  • Myth Busting: Stocks Correlations and Active Investment Opportunities [Alpha Architect]

    Many investors, investment professionals, and pundits make comments regarding the relationship between stock correlations and opportunities for active stock pickers. For example, here is a recent example from the Financial Times: Correlation crash clears way for stockpickers. The basic (albeit flawed) intuition behind the statement is that when correlations are low, the variation in returns is

Quantocracy’s Daily Wrap for 11/28/2017

This is a summary of links featured on Quantocracy on Tuesday, 11/28/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Factor Investing and Trading Costs [Alpha Architect]

    Factor investing, and the associated intellectual battles, have raged for decades in academic finance journals. However, now that factor investing has gone mainstream via ETFs, the debate has broader interest among the investing public. Some investors question the very existence of factor premiums. We are sympathetic to this viewpoint given the noise around poor factor replication and the
  • SPY s 2-Day Pattern Suggesting A Bullish Tendency For Tuesday [Quantifiable Edges]

    SPY gapped up and closed lower Monday after leaving an unfilled up gap on Friday. This triggered the study below that examined similar price action in SPY with regards to how it gapped and finished
  • More About Meta: The Best Asset Allocation Strategies Over Time [Allocate Smartly]

    Last month we launched Meta Strategy, our own smart approach to combining the 40+ tactical asset allocation strategies tracked on our site. Each month, Meta selects 10 strategies and then trades their combined asset allocation. Members can follow Meta in near-real time. Each months 10 strategies are selected based on a number of factors (read more), including how well each strategy plays with

Quantocracy’s Daily Wrap for 11/27/2017

This is a summary of links featured on Quantocracy on Monday, 11/27/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Are Market Implied Probabilities Useful? [Flirting with Models]

    Using historical data from the options market along with realized subsequent returns, we can translate risk-neutral probabilities into real-world probabilities. Market implied probabilities are risk-neutral probabilities derived from the derivatives market. They incorporate both the probability of an event happening and the equilibrium cost associated with it. Since investors have the flexibility
  • Computing Option Skews with Dask [Black Arbs]

    This article series provides an opportunity to move towards more interactive analysis. My plan is to integrate more Jupyter notebooks and Github repos into my research/publishing workflow. For datasets that are too big to share through github I will provide a download link both here and in the github readme. I will be posting the notebooks into this blog using iframes. If you experience any issues
  • Factor Construction: Portfolio Scenarios [Factor Research]

    Most researchers create factor portfolios by taking the top & bottom 30% of stocks, which results in large portfolios Portfolios can be reduced, but firm risks start influencing factor returns with too few stocks Most investors are likely better of buying factor products then building factor portfolios themselves INTRODUCTION Investors glancing at the Wilshire 5000 Total Market Index would
  • Algorithmic Options Trading, Part 3 [Financial Hacker]

    In this article well look into a real options trading strategy, like the strategies that we code for clients. This one however is based on a system from a trading book. As mentioned before, options trading books often contain systems that really work which can not be said about stock or forex trading books. The system that well examine here is indeed able to produce profits. Even extreme
  • Do Short Selling Costs Affect the Profitability of Stock Anomalies [Quantpedia]

    Short selling frictions cannot explain the persistence of seven prominent stock anomalies. Long-only investing is robust and profitable and can be further enhanced by using a synthetic short. Moreover, portfolios restricted to stocks that are easy to short sell continue to have large and significant short anomaly alphas. I derive cost bounds for switching between implementation methods and show

Quantocracy’s Daily Wrap for 11/26/2017

This is a summary of links featured on Quantocracy on Sunday, 11/26/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Factor Investing: Implementation Costs Really Do Matter [Dual Momentum]

    One of the tenets of modern portfolio theory is that you cannot generally beat the market after transaction costs. Yet academic researchers have shown that momentum consistently beats the market. Other factors besides momentum have also cast doubt on the efficacy of the efficient market hypothesis. There is one way though that academics can still hold on to the efficient market hypothesis. It is
  • QSTrader: November 2017 Update [Quant Start]

    Last month I presented a detailed roadmap for the redevelopment of QSTrader, our open-source systematic trading simulation engine. Today I want to discuss our progress in the month since that article was published and what still remains to be completed prior to the initial 0.1.0 alpha release. Progress To Date The internal QSTrader development version is now mature enough to carry out simple

Quantocracy’s Daily Wrap for 11/24/2017

This is a summary of links featured on Quantocracy on Friday, 11/24/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • From Potential to Proven: Why AI is Taking Off in the Finance World [Robot Wealth]

    This article is a departure from the quantitative research that usually appears on the Robot Wealth blog. Until recently, I was working as a machine learning consultant to financial services organizations and trading firms in Australia and the Asia Pacific region. A few months ago, I left that world behind to join an ex-clients proprietary trading firm. I thought Id jot down a few thoughts

Quantocracy’s Daily Wrap for 11/22/2017

This is a summary of links featured on Quantocracy on Wednesday, 11/22/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How To Get Free Intraday Options Data With Pandas-DataReader [Black Arbs]

    This is a simple reference article for readers that might wonder where I get/got my options data from. In this regard I would like to shout out the contributors to the pandas-datareader, without their efforts this process would be much more complex. Intuitive Explanation So this code consists of three components. The first is the actual script that wraps the pandas-datareader functions and
  • Volume Filters (Part 3) | Trading Strategy (Entry & Exit) [Oxford Capital]

    Developer: Larry Williams (All in one: Price, volume and open interest); R. D. Donchian (Breakout Channels). Concept: Trading strategy based on price breakouts confirmed by POIV (Price, Open Interest, and Volume) filters. Research Question: Can combined filters improve price breakouts? Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Entry Setup: High[i] >
  • A Few Tips for Volatility Trading [Quantpedia]

    We present some empirical evidence for short volatility strategies and for the cyclical pattern of their P&L. The cyclical pattern of the short volatility strategies produces an alpha in good times but collapses to the beta in bad times. We introduce a factor model with risk-aversion to explain the risk-premium of short volatility strategies as a compensation to bear losses in bad market
  • Asset allocation with constraints using Backtracking [Quant Dare]

    Assigning weights to portfolio assets is challenging when we have to consider multiple constraints. Asset allocation may be seen as a constraint satisfaction problem (CSP), and some algorithms allow us to define our own restrictions and look for an optimal weight distribution. In this post, we will show how to define a CSP for your portfolio and how to use the Backtracking algorithm to obtain an