Quant Mashup Parameter Optimisation for Systematic Trading [Robot Wealth]Optimisation tools have a knack for seducing systematic traders. And what’s not to love? Find me the unique set of parameters that delivered the greatest return in my ten-year backtest. And do it in under five seconds. That’s certainly attractive. But do you want to hear something controversial?(...) Petra on Programming: A Unique Trend Indicator [Financial Hacker]This months project is a new indicator by John Ehlers, first published in the S&C May 2020 issue. Ehlers had a unique idea for early detecting trend in a price curve. No smoothing, no moving average, but something entirely different. Let’s see if this new indicator can rule them all. The basic(...) Dividends, Stock Prices, and Inflation [Alpha Architect]Building on the concepts presented in my Dividends Are Different article, here we present data and observations highlighting the relationship between inflation and 1) company fundamentals, 2) dividends, and 3) stock market movements. 1 We look at empirical data to investigate how inflation relates(...) Attention Data Geeks: Our Factor Investing Data Library is Open [Alpha Architect]Are you doing independent factor research? Have you spent countless hours on Ken French’s website? Do you run factor regressions for “fun”? Congrats — you are officially a finance geek and you will probably benefit from our new factor investing library. Our library has over 300 factors to(...) Working with High-Frequency Tick Data - Cleaning the Data [Quantpedia]Tick data is the most granular high-frequency data available, and so is the most useful in market microstructure analysis. Unfortunately, tick data is also the most susceptible to data corruption and so must be cleaned and conditioned prior to being used for any type of analysis. This article,(...) Tactical Asset Allocation: Mid-April Checkup [Allocate Smartly]Tactical Asset Allocation (TAA) weathered the storm in February and March, significantly paring down losses vs conventional buy & hold. So far it has trailed the bounce in April, but these are early days. We track 50+ TAA strategies sourced from books, papers, etc., allowing us to draw some(...) A Review of Zorro for Systematic Trading [Robot Wealth]One of the keys to running a successful systematic trading business is a relentless focus on high return-on-investment activities. High ROI activities include: Implementing new trading strategies within a proven framework. An example might be to implement a portfolio of pairs trades in the equity(...) Is There a Tail Risk Premium in Stocks? [Alpha Architect]It has been well documented both that stock returns have much fatter tails than a normal distribution would generate, and that tail events occur much more frequently than a normal curve would predict. 1 For example, Benoit Mandelbroit and Richard Hudson examined the daily index movements of the Dow(...) Discounted expectations [OSM]After our little detour into GARCHery, we’re back to discuss capital market expectations. In Mean expectations, we examined using the historical average return to set return expectations when constructing a portfolio. We noted hurdles to this approach due to factors like non-normal distributions,(...) Generic Octave_Oanda_API Function [Dekalog Blog]My last two posts have shown Octave functions that use the Oanda API to access and download data. In the first of these posts I said that I would post more code for further functions as and when I write them. However, on further reflection this would be unnecessary as the generic form of any such(...) Curse of Dimensionality part 4: Distance Metrics [Eran Raviv]Many machine learning algorithms rely on distances between data points as their input, sometimes the only input, especially so for clustering and ranking algorithms. The celebrated k-nearest neighbors (KNN) algorithm is our example chief, but distances are also frequently used as an input in the(...) A primer on embedded currency risk [Quant Dare]In a previous post, we showed that unhedged currency exposure adds unrewarded risk to our investment, hurting risk-adjusted-performance. This risk should either be neutralized through passive hedging; or mitigated and turned into profit with an active overlay, the latter being what ETS has been(...) Dual Momentum & Vortex Indicator: Trading Strategy Review [Oxford Capital]Developer: Etienne Botes and Douglas Siepman (Vortex Indicator). Concept: Dual momentum trading strategy based on Vortex Indicator. Research Goal: Performance verification of dual momentum signals. Specification: Table 1. Results: Figure 1-2. Trade Filter: Long Filter: Slow Positive Vortex Indicator(...) Inverting Differentiated Time-Series in pandas for Deep Learning Prediction Analysis [Quant at Risk]A differentiation of the time-series is a common transformation used when we want to get a stationary time-series given a non-stationary one. The latter usually displays time-dependent relationships like trends, seasonality, quasi-cyclic patterns, and their Fourier power spectrum is characterised by(...) Trading and investing performance - year six [Investment Idiocy]Time for the annual review post, as my reviews follow the UK tax year which ended on the 5th April. And what a year it has been; well 10 months or so of fairly normal stuff, followed by several weeks of stomach churning market chaos. Previous updates can be found here, here, here, here and here.(...) Trend Following Reality: You Need Trends to Trend-Follow [Alpha Architect]Trend Following, as an investing strategy has delivered strong performance during market chaos (e.g., Global Financial Crisis of 2007–2009), but the strategy has gone through a significant drawdown (save the last few months where things are perking up!). We have seen dismal returns in the recent(...) Low Vol-Momentum vs Value-Momentum Portfolios [Factor Research]Low Vol-Momentum & Value-Momentum portfolios outperformed stock markets since 1989 Low factor correlations contributed to the attractive risk-return profiles Excess returns have been lower in the most recent than in previous decades INTRODUCTION If an investor would state today that in ten or(...) Macro trading and macroeconomic trend indicators [SR SV]Macroeconomic trends are powerful asset return factors because they affect risk aversion and risk-neutral valuations of securities at the same time. The influence of macroeconomics appears to be strongest over longer horizons. A macro trend indicator can be defined as an updatable time series that(...) Fermi's Intuition on Models [Falkenblog]In this video snippet, Freeman Dyson talks about an experience he had with Enrico Fermi in 1951. Dyson was originally a mathematician who had just shown how two different formulations of quantum electrodynamics (QED), Feynman diagrams and Schwinger-Tomonoga's operator method, were equivalent.(...) How Do Investment Strategies Perform After Publication? [Quantpedia]In many academic fields like physics, chemistry or natural sciences in general, laws do not change. While economics and theory of investing try to find rules that would be true and always applicable, it is not that simple, there is a “complication“ – human. Psychology of humans is very(...) The other way around: from correlations to returns [Quant Dare]In one way or another, most quantitative models somehow seek to find and exploit relationships between two or more series of returns. Therefore, the usual pipeline has a time-series go through mathematical procedures which condensate in a couple of figures meaningful information: the expected mean,(...) Daily vs. Monthly Trend-Following Rules...Plus Some DIY Tools! [Alpha Architect]Trend-following strategies are a lot like stock-picking strategies — there are endless approaches and varying levels of complexity. In this short piece, we explore the decision related to implementing basic trend-following strategies on either a daily or a monthly basis. Many traders intuitively(...) Volatility, Risk Management, and Market Chaos: Research that Might Help [Alpha Architect]Given the recent market decline, we thought it would be helpful to review some of our blog posts from the past that may be relevant to the current crisis atmosphere. These posts focus on research that explores investment strategies that are believed to help investors manage risk and diversify their(...) Factor Olympics Q1 2020 [Factor Research]We present the performance of five well-known factors on an annual basis for the last 10 years. We only present factors where academic research highlights positive excess returns across market cycles and asset classes. Other strategies like Growth might be widely-followed investment styles, but lack(...) A L-U-V-Wy Recovery [Flirting with Models]There has been considerable speculation as to the shape of the market’s recovery. Practitioners have taken to using letters as short hand for the recovery they forecast. Whether the market makes a fast V-shaped recovery, a slower U-based formation, a W-style double-bottom, or an L-shaped reset is(...) First Octave Function using Oanda API [Dekalog Blog]As part of my on-going code revision I have written my first Octave function to use the Oanda API. This is just a simple "proof of concept" function which downloads an account summary. ## Copyright (C) 2020 dekalog ## ## This program is free software: you can redistribute it and/or modify(...) GARCHery [OSM]In our last post, we discussed using the historical average return as one method for setting capital market expectations prior to constructing a satisfactory portfolio. We glossed over setting expectations for future volatility, mainly because it is such a thorny issue. However, we read an excellent(...) Pandemics and Factor Investing: A Glimpse into the Past [Alpha Architect]When I was in the Marines we were “voluntold” to read a lot on the history of warfare. This mandate came from General Mattis’ desire that we lean on the 5,000+ years of fighting experience amongst us illustrious humans. Of course, history never tells you exactly what will happen in the future,(...) Accelerating Python for Exotic Option Pricing (h/t @PyQuantNews) [Nvidia Developer]In finance, computation efficiency can be directly converted to trading profits sometimes. Quants are facing the challenges of trading off research efficiency with computation efficiency. Using Python can produce succinct research codes, which improves research efficiency. However, vanilla Python(...) A statistical learning workflow for macro trading strategies [SR SV]Statistical learning for macro trading involves model training, model validation and learning method testing. A simple workflow [1] determines form and parameters of trading models, [2] chooses the best of these models based on past out-of-sample performance, and [3] assesses the value of the(...) Portfolio Optimization for Efficient Stock Portfolios [Invest Resolve]It’s time to rethink “passive” stock investing. While capitalization weighted U.S. stock indices have delivered good performance over the past decade and the long-term, many investors don’t realize that they can achieve similar returns with much less risk by employing risk-efficient(...) Managing Expectations: Comparing S&P 500’s Deepest Drawdowns [Capital Spectator]In a previous post, I simulated S&P 500 drawdowns for perspective on what the current market correction may dispense in the weeks and months ahead. Let’s supplement that analysis by visually comparing the current and ongoing peak-to-market decline with the ten deepest drawdowns since 1950.(...) How to Predict Bitcoin Price with Deep Learning LSTM Network - Part 1 [Quant at Risk]You can’t predict the future unless you have a crystal ball but you can predict an asset’s trading price in next time step if you have a right tool and enough confidence in your model. With the development of a new class of forecasting models employing Deep Learning neural networks, we gained(...) How fast should we trade? [Investment Idiocy]This is the final post in a series aimed at answering three fundamental questions in trading: How should we control risk (first post) How much risk should we take? (previous post) How fast should we trade? (this post) Understanding these questions will allow you to avoid the two main mistakes made(...) Volatility Expectations and Returns [Alpha Architect]A large body of research, including the 2017 study “Tail Risk Mitigation with Managed Volatility Strategies” by Anna Dreyer and Stefan Hubrich, demonstrates that while past returns do not predict future returns, past volatility largely predicts future near-term volatility, i.e., volatility is(...) Tactical Asset Allocation: Surveying the Damage in March [Allocate Smartly]Tactical Asset Allocation (TAA) weathered the storm in March well, significantly paring down losses versus conventional buy & hold. We track 50+ TAA strategies sourced from books, papers, etc., allowing us to draw some broad conclusions about TAA as a style. In the table below we show the March(...) Predicting the fall: Revisiting the “Forecasting VIX peaks” experiment [Quant Dare]We are living through unprecedented times. Due to the ongoing global health pandemic, the international markets have plummeted with speeds never seen before, reminiscent of the 1930s and the Great Depression. On February 19, 2020, the SP500 Index closed at an all-time high price and then proceeded(...) The Real Corporate Bond Puzzle [Falkenblog]The conventional academic corporate bond puzzle has been that 'risky' bonds generate too high a return premium (see here). The most conspicuous credit metric captures US BBB and AAA bond yields going back to 1919 (Moody's calls them Baa and Aaa). This generates enough data to make it(...) Revenge of the Stock Pickers [Robot Wealth]To say we’re living through extraordinary times would be an understatement. We saw the best part of 40% wiped off stock indexes in a matter of weeks, unprecedented co-ordinated central bank intervention on a global scale, and an unfolding health crisis that for many has already turned into a(...) Range Bound Trading Strategy [Milton FMR]The following system helps you identify range bound formations and when to enter and exit such trades. Range bound formations occur when prices bounce back and forth establishing a nearly identical pattern of highs and lows. An upper resistance and lower support level is created. A key point to(...) An Empirical Challenge for Trend-Following [Alpha Architect]There is ample evidence in the literature that stock past returns predict future returns. One of the most comprehensive studies is Moskowitz et al. (2012), which shows that time-series momentum (TSM) is everywhere (they test it on 55 assets). 1 Later studies confirmed the results on even a broader(...) Thou Shall Not Short the VIX [Factor Research]The VIX has not remained at high levels for long in recent times, theoretically making a mean-reversion strategy attractive However, there were periods historically where volatility stayed elevated for years Furthermore, the VIX is not a tradeable index and related products should be viewed with(...) One Hedge to Rule Them All [Flirting with Models]About two years ago, we compared and contrasted different approaches to risk managing equity exposure; including fixed income, risk parity, managed futures, tactical equity, and options-based strategies. Given the recent market events as the world navigates through the COVID-19 crisis, we revisit(...) Mean expectations [OSM]We’re taking a break from our extended analysis of rebalancing to get back to the other salient parts of portfolio construction. We haven’t given up on the deep dive into the merits or drawbacks of rebalancing, but we feel we need to move the discussion along to keep the momentum. This should(...) Some Basic Code Housekeeping [Dekalog Blog]Since my last post, back in late November last year, I have been doing a few disparate things such as: improving the coding of some functions in R to use the Oanda API to automatically download data using cronjobs coding some Octave functions to plot/visualise the above data more work on Random(...) Corporate Governance, ESG, and Stock Returns around the World [Alpha Architect]Figuring out exactly how to score companies on social issues isn’t as simple as tossing around a universal “ESG Ratio” that works for all. Instead, we have to dig into the details and find the nuanced answer to discover which companies are performing and delivering on social issues. This paper(...) The basics of low-risk strategies [SR SV]Low-risk investment strategies prefer leveraged low-risk assets over high-risk assets. The measure of risk can be based on price statistics, such as volatility and market correlation, or fundamental features. The rationale for low-risk strategies is that leverage is not available for all investors(...) Correlations go to One [Alvarez Quant Trading]There is a saying: “in bear markets correlations go to one.” I wanted to see how true that is for both stocks and a basket of ETFs. Now they don’t go to exactly one, not that I expected that, but they take some large steps towards one. Definitions When calculating correlation, I am using the(...) Correlation Between the VVIX and VIX indices [Relative Value Arbitrage]The VIX index is an important market indicator that everyone is watching. VVIX, on the other hand, receives less attention. In this post, we are going to take a look at the relationship between the VIX and VVIX indices. While the VIX index measures the volatility risks, VVIX measures the(...) This Crisis Has Not Been Kind to Tactical ETFs [Allocate Smartly]DIY tactical asset allocation (i.e. the types of public strategies that we cover on this site) has been strong through this crisis. Tactical ETFs on the other hand have struggled badly. We track 50+ DIY TAA strategies, allowing us to draw some broad conclusions about TAA as a style. In the graph(...)