While writing my presentation for TradersFest 2018, I wanted to add the trader’s emotional curve. But looking at it closer, it did not capture my feelings as I go through the cycle of up and downs of trading a strategy. Here is my curve. I have been on every part of this curve multiple times.

I. Trading Strategy Developer: Gerald Appel. Source: Appel, G. (2005). Technical Analysis. NJ: Pearson Education, Inc; Star, B., PhD (2016). Zero In On The MACD. Stocks & Commodities, May 2016. Concept: Trend following trading strategy based on the MACD (Moving Average Convergence Divergence)

A new interesting financial research paper gives an idea to build a diversified portfolio of leveraged ETFs (scaled down to have the same risk as a benchmark asset allocation built from a non-leveraged ETFs) to beat benchmark asset allocation. However, caution is needed as the most of the

A question we have been receiving recently is the following: How should I use trend following within a portfolio? Generally, the questions are related to our Global Value, Momentum, and Trend Index, which allocates to the (1) Value, (2) Momentum, and (3) Trend factors. A big difference between the

This post will review Kris Boudt’s datacamp course, along with introducing some concepts from it, discuss GARCH, present an application of it to volatility trading strategies, and a somewhat more general review of datacamp. So, recently, Kris Boudt, one of the highest-ranking individuals pn the

Let's begin this post with a gross generalisation: Professional traders tend to measure risk and target risk using standard deviation. Amateur traders tend to use a funky little number called the ATR: 'Average True Range'. Both try and achieve the same aim: summarise the typical

Diversification within a portfolio can be quantified using the diversification ratio, which measures how much the volatility is reduced relative to a scenario where all assets are perfectly correlated. By maximizing the diversification ratio, we can construct the most diversified portfolio for a

What are the research questions? USES: Can investors really separate “alpha” from “beta”? What are the ins-and-outs of understanding the exposures in a portfolio and their contribution to “alpha”? ABUSES: Are there differences in the way strategies are constructed in academic articles

This research note was originally published by the CFA Institute’s Enterprising Investor blog. Here is the link. SUMMARY Private equity returns can be replicated with small cap equities Small, cheap and levered stocks would have achieved higher returns since 1988 Valuation and debt multiples are

How have costs of U.S. stock trading data evolved in recent years? In his October 2018 paper entitled “Retail Investors Get a Sweet Deal: The Cost of a SIP of Stock Market Data”, James Angel examines costs of U.S. stock market data. He also describes the production of these data and their

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 don’t (yet) include every published TAA model, these strategies are

The correlation of equity and high grade sovereign bond returns is a powerful driver of portfolio construction and the term premia of interest rates. This correlation has turned from positive in the 1970s-1990s to negative in the 2000s-2010s, on the back of similar shifts in the correlation between

Factor Investing: Get Your Exposures Right! François Soupé (BNP Paribas Asset Management), et al. October 26, 2018 This paper is devoted to the question of optimal portfolio construction for equity factor investing. The first part of the paper focusses on how to make sure that a given equity

A reader pointed me the November 2018 issue of Technical Analysis of Stocks & Commodities to an article about a trend following indicator on S&P500 stocks. I liked the concept of the indicator and the article had backteted results and AmiBroker code. How could I resist not looking into this?

Deep Reinforcement Learning applications in finance are still largely unknown. Nonetheless, recent developments in other fields have pushed researchers towards exciting new horizons. I believe that there is a huge potential for Reinforcement Learning in finance. As investment guru Ray Dalio, founder

While the SPX closes higher on Tuesday, NYSE breadth was weak – both from an % Up Issues and % Up Volume standpoint. This triggered the study below from the Quantifinder. I also discussed it in last night’s subscriber letter. 2018-11-28-1 Here we see numbers suggesting a substantial bearish edge

Broadly speaking, we can classify financial markets conditions into two categories: Bull and Bear. The first is a “todo bien” market, tranquil and generally upward sloping. The second describes a market with a downturn trend, usually more volatile. It is thought that those bull\bear terms

SUMMARY Statistical arbitrage behaves similarly across markets Volatility is the main performance driver Attractive strategy for diversifying an equity portfolio INTRODUCTION Strategies like Value or Momentum are like staples that deserve a permanent allocation in investors portfolios. In contrast,

What are the Research Questions? The authors propose an estimation of the capital stock that involves all identifiable and measurable financial and nonfinancial assets in the world economy. This portfolio seeks to represent the so-called “Global Market Portfolio,” that all MBA students learn to

With so much focus often on the actual trading strategies or investments, portfolio construction can sometimes become an afterthought… or not even considered. However, as we’re going to hear about today, portfolio construction and optimization has the potential for huge increases in wealth…

The term structure of sovereign credit default swaps (CDS) is indicative of country-specific financial shocks, because rising country risk affects short-dated maturities more than longer-dated ones. This feature allows disentangling global and local risk factors in sovereign CDS markets. The latter

I get asked this question at least once a week. As those of you that have met me IRL ('in real life') will know I have limited patience and I'm easily bored. I'm definitely bored of answering this question. This post is the last time I'll answer it. There are broadly two

In a series of five presentation slide sets (Lectures 1-8 of 10) on “Advances in Financial Machine Learning”, Marcos Lopez de Prado provides part of Cornell University’s ORIE 5256 graduate course at the School of Engineering (“Special Topics in Financial Engineering V”). The course

First off, Happy Thanksgiving! If time permits in the coming months I’d like to explore more on how I look at High Frequency (HF) data. Hopefully along the way I can spark some new discussion and improve on my thought process. HFT strategy “simulation” is no easy task. I am referring to this

Decision Trees, are a Machine Supervised Learning method used in Classification and Regression problems, also known as CART. Remember that a Classification problem tries to classify unknown elements into a class or category; the output always are categorical variables (i.e. yes/no, up/down,

Have you ever needed to estimate the probability of a rare event? So rare that you haven’t been able to encounter it in real data? Well, what if I told you that there exists a way to calculate a statistically correct approximation. Oh, and you won’t even need a calculator! Recently I have just

Portfolio construction decisions tell us about more than just our objective: they tell us about our beliefs. In practice, our beliefs extend beyond views of returns, volatilities, and correlations; we also hold views about our ability to measure these concepts and our confidence in those measures.

Who are the buyers and sellers of volatility-contingent strategies? How extensive is volatility trading and put selling currently? Could a volatility “cascade” cause a crash across correlated asset classes? Are there mechanisms that might provide stabilization? What are the Academic Insights?

This research note was originally published by the CAIA Association’s AllAboutAlpha blog. Here is the link. SUMMARY Zombie firms, where interest payments exceed operating profits, are on the rise Zombie stocks perform surprisingly well They are expensive, volatile stocks from diverse sectors

The time around Thanksgiving has shown some strong tendencies over the years – both bullish and bearish. I have discussed them a number of times over the years. In the updated table below I show SPX performance results based on the day of the week around Thanksgiving. The bottom row is the Monday

The volatility risk premium compensates investors for taking volatility risk. Conceptually it is based on the difference between options-implied and expected realized volatility. In equity markets this premium should be positive in the long run and fluctuate overtime depending on the market’s

This week Ryan and I discuss three topics. First, we examine the returns to U.S. stock broken down by (1) size and (2) factors (mega-cap stocks were the place to invest over the last 5 years!). Second, we examine a post by Adam Tkaczuk on Opportunity Zones–a must read for those with low basis

Recent asset allocation articles (tactical or otherwise) that you might have missed: When Simplicity Met Fragility (Newfound Research) Yes, yes, yes. A must read. “Research suggests that simple heuristics are often far more robust than more complicated, theoretically optimal solutions. Taken too

First an apology. It's been quite a few months since my last blog post. I've been in book writing mode and trying to minimise outside distractions. Though looking at my media page since my last blog post I've done two conferences, a webinar, a book review, a guest lecture, a TV panel

The “stock market,” at least as measured via the S&P 500, has been on an epic performance run — especially relative to almost all asset classes. It doesn’t matter whether you look at the other asset classes by geography (e.g., US, developed, emerging), style (e.g., value, momentum), or

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

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

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

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

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

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

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:

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.”

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 Let’s start. For any

The Trading Show Chicago is the only event that combines quant, automated trading, exchange technology, big data and derivatives. Whether you’re focused on new quantitative models, adopting low latency systems or managing risk, The Trading Show Chicago provides unparalleled opportunities to

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

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

October 2018 Trend Following: DOWN -6.13% / YTD: -14.45% Please find this month’s 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 -

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

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