Quant Mashup 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 it’s important to remember that models don’t necessarily reflect the underlying reality of the thing we’re modeling. The Ptolemaic model of the solar system assumed the Earth was(...) 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(...) 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(...) 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.(...) 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 month’s 10 strategies(...) Algorithmic Options Trading, Part 3 [Financial Hacker]In this article we’ll 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(...) 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(...) 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(...) 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(...) 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(...) 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.(...) 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.(...) 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(...) 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(...) 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?(...) 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(...) 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(...) Risk Parity: How Much Data Should We Use When Estimating Volatilities and Correlations? [Flirting with Models]Risk parity portfolios attempt to diversify across asset classes and strategies by risk contribution as opposed to dollar allocation. Implementing a risk parity strategy requires making a number of important construction decisions. A key question we have to answer is “How are we going to measure(...) Sector Rotation with Fama-French Alphas [Allocate Smartly]Allocate Smartly tests and tracks asset allocation strategies sourced from books, academic papers and other publications. Most of the strategies that we test though never make it on to this site. There are a variety of reasons that might be, but often it’s simply because they’re not very good.(...) Quant Strategies in the Cryptocurrency Space [Factor Research]The year 2017 might be regarded as the year where cryptocurrencies became mainstream. Investment funds focused on cryptocurrencies were launched, the CBOE announced Bitcoin futures for the end of the year and some everyday expenses like booking flights at Expedia can be paid in Bitcoins.(...) Candlestick Plotting Function for Octave [Dekalog Blog]I have long been frustrated by the lack of an "out of the box" solution for plotting OHLC candlestick charts natively in Octave, the closest solution I know being the highlow plot function from the financial package ( which does not yet implement a candle function ) over at Octave(...) Recalibrating Expected Shortfall to Match Value-at-Risk for Discrete Distributions [Quant at Risk]By considering the same risk measure, ϱ, applied to two or more portfolios (credit loss distributions, profit-and-loss distributions, etc.) one desires to have a subadditivity property in place: ϱ(X1+X2)≤ϱ(X1)+ϱ(X2) i.e. meaning that two combined portfolios should never be more risky than the(...) Optimizing trading strategies without overfitting [EP Chan]Optimizing the parameters of a trading strategy via backtesting has one major problem: there are typically not enough historical trades to achieve statistical significance. Whatever optimal parameters one found are likely to suffer from data snooping bias, and there may be nothing optimal about them(...) Monetary Momentum [Alpha Architect]On most mainstream finance websites, a good chunk of the stories discuss the FED and where interest rates are going. Intuitively, this makes sense: The FED is arguably an extremely influential component of U.S. economy. But how do markets respond to the FED? Is the response rational, irrational, or(...) Adaptive Volatility [CSS Analytics]One of the inherent challenges in designing strategies is the need to specify certain parameters. Volatility parameters tend to work fairly well regardless of lookback, but there are inherent trade-offs to using short-term versus longer-term volatility. The former is more responsive to current(...) Weekly Mean Reversion Rotation Strategy on S&P500 Stocks [Alvarez Quant Trading]A reader emailed me about testing a weekly mean reversion rotation strategy on S&P500 stocks. My first thought was, why had I not done this type of test before? The very first strategy that I worked on with Larry Connors was this type of strategy. The strategy I will be testing today is a(...) Investing Outside the U.S. - Purgatory for Pessimists [Factor Investor]The current equity bull market has not been kind to non-U.S. allocations. At a recent conference I attended, the term ‘TINA: there is no alternative’ came up more than once in the context of allocating investor portfolios. It captures the collective sentiment that equities, despite a massive(...) Ensemble Methods for E-Mini S&P 500 Futures Long/Short Strategy [Golden Compass]Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. This is with the intention that ensembles will achieve better prediction accuracy than individual classifiers. In machine learning(...) Comparing Some Strategies from Easy Volatility Investing, and the Table.Drawdowns Command [QuantStrat TradeR]This post will be about comparing strategies from the paper “Easy Volatility Investing”, along with a demonstration of R’s table.Drawdowns command. First off, before going further, while I think the execution assumptions found in EVI don’t lend the strategies well to actual live trading(...) Can asset bubbles be mathematically quantified before they burst? [Alpha Architect]The subject of asset bubbles and market crashes has fascinated me for more than 20 years. As an options market maker for Susquehanna International Group (“SIG”), extreme price movements were a daily source of concern. I sat next to Jeff Yass for years and watched him manage option positions in(...) Hedge Fund Factor Exposure and Alternatives [Factor Research]Equity hedge fund returns have been disappointing over the last 14 years An exposure analysis shows no structural factor exposure, but frequent factor rotation Multi-factor long-short products are an interesting alternative, depending on the fee level INTRODUCTION Hedge fund assets reached an(...) How to Balance Short and Long term Goals in Asset Allocation [Alpha Architect]Peng Wang and Jon Spinney 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? Investors following a purely quantitative approach to asset allocation are often left with(...) Better Small Cap Premium [Quantpedia]We find that when measured in terms of dollar-turnover, and once beta-neutralised and Low-Vol neutralised, the Size Effect is alive and well. With a long term t-stat of 5.1, the “Cold-Minus-Hot” (CMH) anomaly is certainly not less significant than other well-known factors such as Value or(...) A Case Against Overweighting International Equity [Flirting with Models]We’ve read a number of outlooks and commentaries lately from firms arguing for investors to take a tactical tilt away from U.S. equities and towards International equities. The logic behind this tilt is largely driven by relative valuations: international equities appear significantly cheaper than(...) Podcast: Building Mean Reversion trading strategies with @AlvarezQuant - Part 3 [Better System Trader]And we’re back for the final episode in this 3-part series on building Mean Reversion strategies with Cesar Alvarez from Alvarez Quant Trading. In the 1st episode we discussed the goal of Mean Reversion trading, how to select a trading universe, a number of effective techniques to measuring Mean(...) Matrix Iterations for Adaptive Asset Allocation [TrendXplorer]Adaptive Asset Allocation (AAA) is based on the Nobel Prize winning portfolio theory of Markowitz (1952) AAA combines asset’s momentum, volatilities, and cross-correlations for building diversified investment portfolios In a tactical application AAA exploits momentum for crash detection and(...) How To Get Funding For Your Trading Strategy [Quant Insti]So, it’s been some time since you’ve been thinking of making more money out of your successful trading strategy. And why should you not? After all, you’ve worked hard for it and there is only a small % of people who are successful in this business. The idea is to add more funds to your trading(...) Factor Investors Beware: Positive SMB May Not Mean You Own Small-Caps [Alpha Architect]Regression analysis is used all the time to assess how a portfolio “loads” on certain factors. The most common factor loadings examined are the market, size, value, and momentum factors. This can be an informative exercise, and there are nice tools online, such as portfolio visualizer, which(...) Research Review | 10 November 2017 | Factor Strategies [Capital Spectator]Investing in a Multi-Asset Multi-Factor World Alexandar Cherkezov (Invesco), et al. August 31, 2017 In this article, we advance the use of factor investing across multiple asset classes. It turns out that style factors well established in the equity domain – such as value, momentum or quality –(...) Overnight Risk [Qusma]Why are overnight periods riskier? For one, you can’t use stops to limit your risk. But more importantly, the distribution of overnight returns has far more extreme negative returns than the intraday or close-to-close periods. Let’s take a look at some stats on close-to-open, open-to-close, and(...) PDF: Two Centuries of Value and Momentum 1800-2014 Risk Parity in Python [Quant Dare]Once we are familiar with the theory surrounding Risk Parity, it’s time to put the strategy into practice and try out the algorithm for ourselves. We discover how it works, analyse the strategy and create our own portfolios. Thanks to the posts written by T.Fuertes and mplanaslasa we already know(...) 800 Years of Risk-Free Rate [Quantpedia]This paper presents a new dataset for the annual risk-free rate in both nominal and real terms going back to the 13th century. On this basis, we establish for the first time a long-term comparative investigation of ‘bond bull markets’. It is shown that the global risk-free rate in July 2016(...) State of Trend Following in October [Au Tra Sy]Last month saw a strong upwards performance from the State of Trend Following index, single-handedly reversing half the negative performance for the year, which still stands close to double-digit territory. Please check below for more details. Detailed Results The figures for the month are: October(...) Timing TAA Strategies Based on Relative Strength: A Suboptimal Approach [Allocate Smartly]We track a wide range of tactical asset allocation strategies in near real-time (41 and counting), which members can combine into their own custom portfolios. We provide members with a wealth of data to understand how each strategy fits into a coherent trading plan, but we don’t tell members the(...) Replicating Indexes In R (Part III): Socially Responsible Investing [Capital Spectator]In previous installments of replicating indexes I profiled the style-analysis methodology and presented an example using a hedge fund index. Now let’s turn to a strategy of replicating the S&P 500 Index with a handful of stocks that are considered socially responsible investments (SRI).(...) Earning Money in Cryptocurrency Markets by Spotting Statistical Arbitrage Opportunities [Quant at Risk]When you come in contact with cryptocurrencies, e.g. Bitcoin (BTC), you quickly realise that there is no single price of BTC at any given moment. The reason is that Bitcoin is traded on different markets. It can be worth more on Coinbase exchange and less on Kraken exchange. In particular, the(...) Cointegration, Correlation and Log Returns [Quantoisseur]The differences between correlation and cointegration can often be confusing. While there are some helpful explanations online, I wasn’t satisfied with the visual examples. When looking at a plot of an actual pair of symbols where the correlation and cointegration test results differ, it can be(...) Are we misidentifying seasonal patterns as genuine earnings news? [Alpha Architect]Changes in earnings are comprised of the expected earnings number plus any seasonal component of earnings. If the seasonal component is expected then it should not affect prices in an efficient market. However, unusual returns have been documented surrounding earnings announcements at the seasonal(...)