Quant Mashup Trend-Following Filters – Part 3 [Alpha Architect]This is the third article in a series of three, the first two are available here and here. Those articles focus on examining from a digital signal processing (DSP) perspective 1 various types of digital filters that are designed to model trends in time series, in order to illustrate their properties(...) Research Review | 9 April 2021 | Bitcoin [Capital Spectator]How Much Bitcoin Should I Own? A Mathematical Answer Adam Grealish (Betterment) March 9, 2021 It goes without saying that this is a hard question to answer. But we can borrow a page from modern quantitative finance to help us arrive at a potential answer. For years, Wall Street “quants” have(...) What P&L Swings Can I Expect as a Trader? [Robot Wealth]Many beginner traders don’t realize how variable the p&l of a high-performing trading strategy really is. Here’s an example… I simulated ten different 5 year GBM processes with expected annual returns of 20% and annualized volatility of 10%. (If you speak Sharpe Ratios, I’m simulating a(...) Adding candlesticks to mean reversion setup in a portfolio [Alvarez Quant Trading]In my previous post, Adding candlesticks to mean reversion setup, we looked at how various candle patterns could help individual trades. Now we will see how those results translate to a portfolio. And why I usually only do portfolio level testing. The Strategy Setup Rules Stock is a member or was a(...) Estimating the Stock-Bond Correlation [Alpha Architect]The correlation between stock and bond returns is an integral component of hedging strategies, risk assessment, and minimization of risk in allocation decisions. In the context of those strategies, the stock-bond correlation is typically estimated using monthly return data over a recent previous(...) Not so soft softmax [OSM]Our last post examined the correspondence between a logistic regression and a simple neural network using a sigmoid activation function. The downside with such models is that they only produce binary outcomes. While we argued (not very forcefully) that if investing is about assessing the probability(...) Bitcoin: An Asset Allocation Perspective [Light Finance]It’s no secret that 2021 has started off well for Bitcoin. Having breached a new all time high of $61,788.45 on March 13th it seems that each passing month brings with it a new milestone, new players, and greater acceptance. Recently, significant news has focused on the pace of institutional(...) Conditional Parameter Optimization: Adapting Parameters to Changing Market Regimes via Machine Learning [EP Chan]Every trader knows that there are market regimes that are favorable to their strategies, and other regimes that are not. Some regimes are obvious, like bull vs bear markets, calm vs choppy markets, etc. These regimes affect many strategies and portfolios (unless they are market-neutral or(...) Fixed Income when you’re Between a Rock and a Hard Place - Part 1/2 [Alpha Architect]Investors are stuck between a rock and a hard place. On one hand, it is painful to buy bonds that deliver paltry yields near all-time lows (Figure 2). On the other hand, many investors’ risk tolerance, compliance guidelines or liabilities preclude them from reducing their fixed income allocations.(...) What is Mutual Information? [Quant Dare]In the field of machine learning, when it comes to extracting relationships between variables, we often use Pearson correlation. The problem is that this measure only finds linear relationships, which can lead sometimes to a bad interpretation of the relation between two variables. Nevertheless,(...) Minimum Profit Optimization: Mean-reversion Trading [Hudson and Thames]In my previous articles, I introduced how to construct long-short asset pairs according to the concept of cointegration and how to build a sparse mean-reverting multi-asset portfolio. Now that we are able to answer the question “what to trade” with confidence, it is time to get down to the(...) An Investigation of R&D Risk Premium Strategies [Quantpedia]A firm as an independent entity is engaged in a wide range of activities that affect its value. While the impact of some activities on the firm’s value is immediate and indisputable, there also exists a variety of activities that might impact the firm’s value in the future, while their outcome(...) How Active Mutual Funds Use ETFs [Alpha Architect]As of 2017, and in spite of the documented negative relationship between fund performance and use of ETFs, approximately one-third of US-domiciled, actively managed mutual funds held ETFs at one time or another. Active managers justifiably make use of ETFs to improve their portfolio management(...) The Market Consequences of Investment Advice on Reddit's Wallstreetbets [SSRN]We examine the market consequences of due diligence (DD) reports on Reddit’s Wallstreetbets (WSB) platform. We find average ‘buy’ recommendations result in two-day announcement returns of 1.1%. Further, the returns drift upwards by 2% over the subsequent month and nearly 5% over the subsequent(...) Market/Volume Profile and Matrix Profile [Dekalog Blog]A quick preview of what I am currently working on: using Matrix Profile to search for time series motifs, using the R tsmp package. The exact motifs I'm looking for are the various "initial balance" set ups of Market Profile charts. To do so, I'm concentrating the investigation(...) More on the Factor Investing Replication Debate [Alpha Architect]There has been a wave of articles (and press) suggesting that academic research suffers from a replication crisis. A “replication crisis” simply means that other researchers are unable to replicate the results from prior research using similar experimental conditions. Psychology seems to be the(...) New Feature: Optimized Model Portfolios [Allocate Smartly]We track more than 60 Tactical Asset Allocation strategies. Members can combine those strategies into what we call “Model Portfolios”. Combining strategies in this way reduces the risk of any single strategy going off the rails and helps to provide smoother, more consistent investment returns.(...) Democratize Quant Conference Recap and Materials [Alpha Architect]COVID is killing conference mojo overall, but we were able to host a short and sweet “Democratize Quant” conference this morning. The speakers were terrific and I personally learned a lot from them. This post is a recap of what we heard and some resources we can make available to the public.(...) In Search of Lost Covered Interest Parity [Quant Dare]The puzzle of Covered Interest Parity (CIP) began in 2008 and has remained as such for many years. There have been multiple attempts to solve the mystery but none of them has reached a complete consensus and the debate is still ongoing. Nevertheless, the discussion has lead to a fair amount of(...) Is There a Replication Crisis in Finance? [Alpha Architect]In recent years the field of empirical finance has faced challenges from papers arguing that there is a replication crisis because the majority of studies cannot be replicated and/or their findings are the result of multiple testing of too many factors. For example, Paul Calluzzo, Fabio Moneta, and(...) Modelling Slippage for Limit Orders using Adaptive KDE-based Loss Severity Distribution [Quant at Risk]Placing limit orders for trade execution is both quite popular and handy method in (algo)trading. A trader expects that the executed price of his buy/sell trade will ideally match the one requested in his limit order. Unfortunately, depending on a momentary market/asset liquidity, the difference(...) An Economic Framework for ESG Investing [Alpha Architect]The 2018 Global Sustainable Investment Review reports over $30 trillion invested with explicit ESG goals as of the beginning of 2018. In the words of the authors: There is a clear tendency for many investors to own ethical companies in a saintly effort to promote good corporate behavior while hoping(...) Building a real-time market distress index [SR SV]A new Fed paper explains how to construct a real-time distress index, using the case of the corporate bond market. The index is based on metrics that describe the functioning of primary and secondary markets and, unlike other distress measures, does not rely on prices and volatility alone. Thus, it(...) Conditional Volatility Targeting [Alpha Architect]Financial economists have long known that volatility and returns are negatively correlated. Fischer Black documented this in his 1976 paper “Studies of Stock Price Volatility Changes.” This relationship results in the tendency to produce negative equity returns in times of high volatility. In(...) Research Review | 19 March 2021 | Forecasting [Capital Spectator]Predictable Financial Crises Robin Greenwood (Harvard University), et al. March 2021 Using historical data on post-war financial crises around the world, we show that crises are substantially predictable. The combination of rapid credit and asset price growth over the prior three years, whether in(...) 4 simple ways to label financial data for Machine Learning [Quant Dare]We have seen in previous posts what is machine learning and even how to create our own framework. Combining machine learning and finance always leads to interesting results. Nevertheless, in supervised learning, it is crucial to find a set of appropriate labels to train your model. In today’s(...) How to Predict Stock Returns (using a simple model) [Alpha Architect]Jack Bogle, the founder of Vanguard, created a simple explanation for predicting future stock returns. The so-called “Occam’s razor” (law of parsimony) approach is an attempt to explain projected returns as simple as possible. Mr. Bogle’s model is pretty simple: Expected returns (nominal,(...) NEW SITE: Portfolio Optimization: Minimize risk with Turnover constraint via Quadratic Programming [Dilequante]Rebalancing portfolios is an important event in the life of the portfolio manager, whether we talk about the timing or the degree of the rebalancing, i.e. the portfolio turnover, this is a sensitive operation. As well as the first one is important to avoid bad timing market effects, the second one(...) Introduction to Sell-Off Analysis for Crypto-Assets: Triggered by Bitcoin? [Quant at Risk]They say that small fishes buy and sell driven by unstable waters but only big whales make the waves really huge. Recently, this quite popular phrase, makes sense when it comes to cryptocurrency trading influenced by sudden dives of the Bitcoin price. The strategies of buying and selling executed by(...) How to Measure the Liquidity of Cryptocurrency? [Alpha Architect]n January 2020, trading in bitcoin exceeded $930 billion and has certainly grown over the past year. Unlike nearly any other asset, bitcoin can be traded 24 hours a day, 7 days a week on trading platforms around the globe. While trading cryptocurrencies has become relatively frequent, the high(...) Hierarchical Clustering in Python [Quant Insti]With the abundance of raw data and the need for analysis, the concept of unsupervised learning became popular over time. The main goal of unsupervised learning is to discover hidden and exciting patterns in unlabeled data. The most common unsupervised learning algorithm is clustering. Applications(...) Activate sigmoid! [OSM]In our last post, we introduced neural networks and formulated some of the questions we want to explore over this series. We explained the underlying architecture, the basics of the algorithm, and showed how a simple neural network could approximate the results and parameters of a linear regression.(...) Z-Score Factor Portfolio Weighting [Philipp Kahler]Factor investing has been around for some years and has shown to be a valid concept for portfolio strategies. Usually the investor selects a few factors and then goes long the 10% of stocks with the highest factors and goes short (if he wants to trade delta neutral) the 10% of stocks with the lowest(...) An Introduction to Volatility Targeting [Quantpedia]One of the most popular reports in the Portfolio Analysis section of our Quantpedia Pro tool is “Volatility Targeting”. In this article, we will explain some theory behind this portfolio management method. And then, we will go more in-depth, pick several examples and explain some common(...) Detecting Volume Breakouts [Financial Hacker]It is estimated that about 6000 different technical indicators have been meanwhile published, but few of them are based on volume. In his article in Stocks & Commodities April 2021, Markos Katsanos proposed a new indicator for detecting high-volume breakouts. And he tested it with a trading(...) Autoregression: Model, Autocorrelation and Python Implementation [Quant Insti]Time series modelling is a very powerful tool to forecast future values of time-based data. Time-based data is data observed at different timestamps (time intervals) and is called a time series. These time intervals can be regular or irregular. Based on the pattern, trend, etc. observed in the past(...) Low Volatility Factor Investing: Risk-Based or Behavioral-Based or Both? [Alpha Architect]The low-risk effect (aka low volatility) is based on the empirical observation that assets with low risk have high alpha. Specifically in this research, the effect is defined as the risk-adjusted return spread between low-risk and high-risk portfolios and not just low-risk stocks. Since the low-risk(...) NER For Stock Mentions on Reddit (h/t @PyQuantNews)eddit has been at the epicenter of one of the biggest movements in the world of finance, and although it seemed like an unlikely source of such a movement — it’s hardly surprising in hindsight. The trading-focused subreddits of Reddit are the backdrop for a huge amount of discussion about what(...) Does it make sense to change your trading behaviour in different periods of volatility? [Investment Idiocy]A few days ago I was browsing on the elitetrader.com forum site when someone posted this: I am interested to know if anyone change their SMA/EMA/WMA/KAMA/LRMA/etc. when volatility changes? Let say ATR is rising, would you increase/decrease the MA period to make it more/less sensitive? And the bigger(...) Momentum Factor Investing: What's the Right Risk-Adjustment? [Alpha Architect]The momentum factor represents one of our core investment beliefs: buy winners. So when research presents itself that may contradict our beliefs it provides the opportunity to dig deeper and think harder about the factors we hold so dearly. Erik Theissen and Can Yilanci begin their paper by warming(...) Adding candlesticks to mean reversion setup [Alvarez Quant Trading]My preferred chart style is a candlestick chart but I have never investigated candlestick formations to see if they can help provide an edge in my trading. I recently ran into this blog post, Do Candlesticks Work? A Quantitative Test Of 23 Candlestick Formations, where he did his own investigation.(...) Testing a Risk Premium Value Strategy [Allocate Smartly]This is a test of a Risk Premium Value strategy (RPV) that allocates to major US asset classes based on current risk premium valuations relative to historical norms. Readers will note the similarity between RPV and other related strategies, such as CXO Advisory’s SACEVS. Backtested results from(...) Does Crowdsourced Investing Work? [Alpha Architect]Historically, as Richard Thaler pointed out in his book Misbehaving, financial academics have looked at humans as “Econs.” An Econ, unlike a human, values everything down to a penny before they make a decision, knows all possible alternatives, weighs them accurately, and always optimizes. 1 In(...) Does X work, some brief thoughts and choose your adventure [Investment Idiocy]When I was a spotty teenager I was a walking nerd cliche. I liked computers; both for programming and games. I was terrified of girls. I was rubbish at nearly all sports*. And I played D&D (and Tunnels and Trolls, and Runequest). * Nearly all: Not, I'm not talking about the(...) Nothing but (neural) net [OSM]We start a new series on neural networks and deep learning. Neural networks and their use in finance are not new. But are still only a fraction of the research output. A recent Google scholar search found only 6% of the articles on stock price price forecasting discussed neural networks.1 Artificial(...) VIX and More: The Evolution of the VIX (1) [VIX and More]Volatility is notorious for clustering in the short-term, mean-reverting in the medium-term and settling into multi-year macro cycles over the long-term. I have chronicled each of these themes in this space in the past. Apart from volatility, I have also taken great pains to talk about the movements(...) A Robust Approach to Multi-Factor Regression Analysis [Quantpedia]Practitioners widely use asset pricing models such as CAPM or Fama French models to identify relationships between their portfolios and common factors. Moreover, each asset class has some widely-recognized asset pricing model, from equities through commodities to even cryptocurrencies. However,(...) Correlation and correlation structure (5) – a new coefficient of correlation [Eran Raviv]This is the fifth post which is concerned with quantifying the dependence between variables. When talking correlations one usually thinks about linear correlation, aka Pearson’s correlation. One serious limitation of linear correlation is that it’s, well.. linear. By construction it’s not(...) The Forecasting Power of Value, Profitability, and Investment Spreads [Alpha Architect]Studies such as the 2019 paper “Value Return Predictability Across Asset Classes and Commonalities in Risk Premia,” have demonstrated that while it is difficult to time investments based on their value spreads 1 which we’ve covered occasionally here and here, value spreads do contain(...) Research Review | 26 February 2021 | Inflation [Capital Spectator]The Increased Toxicity of the U.S. Treasury Security Market Scott E. Hein (Texas Tech University) January 2, 2021 This short research paper documents the fact that exclusively watching for rising yields on conventional U.S. Treasury securities to reflect increased inflationary fears in the U.S. is(...)