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Quantocracy’s Daily Wrap for 11/14/2018

This is a summary of links featured on Quantocracy on Wednesday, 11/14/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The History of Russell 2000 Death Crosses & SPX Performance Following Them [Quantifiable Edges]

    I have seen a fair amount of hubbub about the Russell Death Cross that is happening today and the potential bearish implications for the market. A Death Cross is a catchy (though perhaps not terribly accurate) term for when the 50-day moving average of a security cross below its 200-day moving average. It is being promoted as a warning of a potential bear market. Of course all bear

Quantocracy’s Daily Wrap for 11/12/2018

This is a summary of links featured on Quantocracy on Monday, 11/12/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Yield is Gravity [Flirting with Models]

    Rolling 12-month returns for the Newfound Multi-Asset Income strategy are currently ranked 47th of 49 since strategy inception in September 2013. We reflect upon research performed over the last several years that continually points back to one critical idea: yield matters. We rebuild this foundational idea from basic building blocks to establish that in the world of fixed income, mark-to-market
  • Equity Factors: Reducing Portfolio Turnover [Factor Research]

    Portfolio turnover of equity factors can be reduced significantly by trading more conservatively However, reducing turnover does not necessarily increase risk-return ratios It all depends on transaction costs INTRODUCTION Turnover in business tends to be positive or negative, depending on the context. Investors prefer businesses with high turnover in inventory to similar businesses with low
  • Hedge Funds may Profit from Stock-Picking and Help Reduce Mispricing [Alpha Architect]

    What are the research questions? Do hedge funds exploit stock mispricing? Specifically, do hedge funds tend to hold undervalued stocks that exhibit positive alphas? Do hedge funds profit from these holdings in undervalued stocks? Does the trading in these stock reduce mispricing? What are the Academic Insights? YES. The results of the four-factor Fama-French-Carhart (1997) model are presented in

Quantocracy’s Daily Wrap for 11/10/2018

This is a summary of links featured on Quantocracy on Saturday, 11/10/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How systemic financial risk is measured [SR SV]

    Public institutions have developed a wide range of methods to track systemic financial risk. What most of them have in common is reliance on financial market data. This implies that systemic risk indicators typically only show what the market has already priced, in form of correlation, volatility or value. They cannot anticipate market crises. Their main use is to predict when and how market
  • State of Trend Following in October [Au Tra Sy]

    A negative October for the State of Trend Following, which sends the YTD performance just in the red. Please check below for more details. Detailed Results The figures for the month are: October return: -2.42% YTD return: -1.38% Below is the chart displaying individual system results throughout October: StateTF October And in tabular format: System October Return YTD Return BBO-20 0.44% 9.72%
  • Too Much Arbitrage Contributes to Overreaction in Post Earnings Announcement Drift [Quantpedia]

    A new financial research paper has been published and is related to all equity long short strategies but mainly to: #33 – Post-Earnings Announcement Effect Authors: Li Title: Does Too Much Arbitrage Destablize Stock Price? Evidence from Short Selling and Post Earnings Announcement Drift. Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3249254 Abstract: Stein (2009) suggests that too much

Quantocracy’s Daily Wrap for 11/07/2018

This is a summary of links featured on Quantocracy on Wednesday, 11/07/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Ensemble Strategies [Build Alpha]

    What is an Ensemble Strategy or Method? In statistics and machine learning, ensemble methods use multiple learning algorithms (trading strategies in our case) to obtain better predictive performance than could be obtained from any of the constituent (individual strategies) learning algorithms. A simpler example would be to think of it as a voting system. Imagine 3 SPY strategies. In theory
  • Volcano escape with Gradient Descent [Quant Dare]

    Gradient Descent is one of the most important algorithms in Machine Learning. It is an iterative method to find the minimum of a given function. That is the reason why today we will go through the intuition behind it and cover a practical application. Concepts to keep in mind Lets start. For any kind of model that we want to create we will have different parameters to fit. Different sets of

Quantocracy’s Daily Wrap for 11/06/2018

This is a summary of links featured on Quantocracy on Tuesday, 11/06/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Today’s Markets. Tomorrow’s Technology. | Trading Show Chicago | 8 – 9 May 2019

    The Trading Show Chicago is the only event that combines quant, automated trading, exchange technology, big data and derivatives. Whether youre focused on new quantitative models, adopting low latency systems or managing risk, The Trading Show Chicago provides unparalleled opportunities to network and ultimately do business with top trading firms, quant funds, international exchanges, end
  • Profiling Factor ETF Correlations [Capital Spectator]

    Slicing and dicing the US equity market into factor buckets is, at its core, an effort to enhance return by engineering more control over risk management. A key part of this framework is recognizing that risk and return for the stock market overall is a byproduct of multiple factors, such as shares trading at low valuations or posting strong price momentum in the recent past. In turn, its
  • Forward Propagation In Neural Networks [Quant Insti]

    In this blog, we will intuitively understand how a neural network functions and the math behind it with the help of an example. In this example, we will be using a 3-layer network (with 2 input units, 2 hidden layer units, and 2 output units). The network and parameters (or weights) can be represented as follows. forward propagation 1 Let us say that we want to train this neural network to predict
  • Trend Following in October [Wisdom Trading]

    October 2018 Trend Following: DOWN -6.13% / YTD: -14.45% Please find this months report of the Wisdom State of Trend Following. Performance is hypothetical. Chart for October: Wisdom State of Trend Following – October 2018 And the 12-month chart: Wisdom State of Trend Following 12 months – October 2018 Below are the summary stats: Horizon Return Ann. Vol. Last month -6.13% 15.5% Year To Date

Quantocracy’s Daily Wrap for 11/05/2018

This is a summary of links featured on Quantocracy on Monday, 11/05/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Precisely Forecasting Price Ranges with Volatility [Six Figure Investing]

    Using a tool like Bollinger Bands to forecast future price ranges is a time-honored technique but its calculations are simplified and in some situations flawed. Incorporating the log-normal nature of stock prices into the calculations gives better answers. One greed inducing aspect of volatility is that it enables us to make theoretically sound forecasts about the future. It doesnt matter
  • The Problem With Financial Oracles [Mathematical Investor]

    In recent years, machine learning techniques and big-data facilities have become quite popular in the finance and investment world. In the wake of this success, numerous machine learning researchers have decided to found their own asset management companies, hoping to capitalize on this trend. This begs the question: Are large amounts of data and computing power all that is needed to tame the
  • Fund Capacity Analysis: How Much Capital Will a Strategy Handle? [Alpha Architect]

    The article addresses the estimation of capacity for an equity fund that forms portfolios based on a given investment strategy. It fits within three strands of literature: i) theoretical models of optimal trading or portfolio construction under alpha erosion and trade frictions; ii) empirical estimates of capacity for specific equity strategies; and iii) capacity analysis undertaken within the
  • Measuring the Benefit of Diversification [Flirting with Models]

    The benefits of diversification are often touted, but many investors feel disappointed in diversified portfolios because of the dispersion in performance of the individual holdings. In the context of three different unconstrained sleeves, we look at a way to measure and visualize the benefit (or detriment) of diversification based on achieving different objectives. Through this lens, we get a
  • The Odd Factors: Profitability and Investment [Factor Research]

    The Profitability factor generated attractive returns in the US and Europe since 1990 It is difficult to explain why investors should be compensated for holding highly profitable companies The Investment factor was less attractive and is unusual from a financial analysts perspective INTRODUCTION Discretionary and systematic investors tend to have different perspectives on what works in the
  • Midterm Elections Have Not Provided A Reliable Short-Term Market Edge [Quantifiable Edges]

    Today I decided to look at SPX performance following past mid-term elections. I did not find much that suggested a strong edge. Below is a look at results since 1970 following mid-term elections. 2018-11-04-1 The numbers suggest perhaps a mild inclination for the market to celebrate the results on Wednesday. After that there does not appear to be a strong tendency in either direction. Below
  • Historical Returns for US Bonds since 1793 [Quantpedia]

    We have mentioned it several times – we are quants but we love history and we love research papers like this: Author: McQuarrie Title: The First Eighty Years of the US Bond Market: Investor Total Return from 1793, Combining Federal, Municipal, and Corporate Bonds Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3260733 Abstract: US securities markets took root after Alexander Hamiltons

Quantocracy’s Daily Wrap for 11/03/2018

This is a summary of links featured on Quantocracy on Saturday, 11/03/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 11/01/2018

This is a summary of links featured on Quantocracy on Thursday, 11/01/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in October [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Learn more about what we do or let AllocateSmartly help you
  • Asset Diversification in a Flat World [Alpha Architect]

    Diversification is a fundamental principle of prudent investing due to its ability to mitigate/minimize risks. In fact, it has been called the only free lunch in investing because, done properly, it can reduce risk without reducing expected returns. This led to the conclusion that investors should diversify by including international equities, including emerging markets, in their portfolios,
  • This Incredibly Bullish Seasonal Period Has Just Begun [Quantifiable Edges]

    With the calendar moving from October to November, it has now entered its Best 6 Months. The Best 6 Months tendency was first published by Yale Hirsch, founder of the Stock Traders Almanac, in 1986. The concept behind the Best 6 Months is simple. Seasonality suggests that over the last several decades the market has made a massive portion of its gains between November and
  • The Existence Of A Bubble vs. The Timing Of Its Crash [Alex Chinco]

    Journalists love to talk about bubbles. The Wall Street Journal has hinted at bubbles in both the Chinese stock market and the market for Bitcoin during the past month alone. But, financial economists are much more reluctant to call something a bubble. Theres debate about whether bubbles even exist. And, much of this debate revolves around whether its possible to predict the timing of the
  • Synthetic prices and burgers [Quant Dare]

    If all finance developers around the world were asked to choose the main nightmare they have to face on daily basis, I bet most of them would choose overfitting. Furthermore, imagine you have to develop an algorithm which has only one ingredient to be modelled, only one time-series representing the historical information Yes, in that case, youll need the Synthetic Financial Time

Quantocracy’s Daily Wrap for 10/29/2018

This is a summary of links featured on Quantocracy on Monday, 10/29/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • When Simplicity Met Fragility [Flirting with Models]

    Research suggests that simple heuristics are often far more robust than more complicated, theoretically optimal solutions. Taken too far, we believe simplicity can actually introduce significant fragility into an investment process. Using trend equity as an example, we demonstrate how using only a single signal to drive portfolio allocations can make a portfolio highly sensitive to the impact of
  • The Dark Side of Low-Volatility Stocks [Factor Research]

    This research note was originally published by the CFA Institutes Enterprising Investor blog. Here is the link. SUMMARY Low-volatility stocks have outperformed the market over the last 25 years The strategy has reduced equity drawdowns in the US, Europe, and Japan significantly However, low-volatility stocks have partially been bond-proxies, which poses risk when rates rise MARKETING INGENUITY

Quantocracy’s Daily Wrap for 10/28/2018

This is a summary of links featured on Quantocracy on Sunday, 10/28/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Missing the best or worst market days [Alvarez Quant Trading]

    This morning I saw the chart on Ritholz.com of what happens when you miss the best X days of the market. I see a variation of this chart often and is used to argue why someone should not try and time the market. One concept I like to do is to invert. Meaning try the opposite idea and see what you get. What I rarely see is the chart if you missed the worst X days. Given it is a rainy Sunday morning