If you've been a regular reader of our blog, you already know that we recently published our first book Adaptive Asset Allocation: Dynamic Portfolios to Profit in Good Times - and Bad. As of this writing, it still stands as the #1 new release in Amazon's Business Finance category.

Adjusted stock prices are the foundation for time-series analysis of equity markets. Good analysts insist on properly-adjusted stock data. But the best analysts understand the adjustment process from first principles. This is Quandl's guide to the creation and maintenance of accurate adjusted

In previous discussions of Bayesian Inference we introduced Bayesian Statistics and considered how to infer a binomial proportion using the concept of conjugate priors. We discussed the fact that not all models can make use of conjugate priors and thus calculation of the posterior distribution would

Obsession with short-term performance against market cap benchmarks preordains the dysfunctionality of asset markets. The problems start when trustees hire fund managers to outperform benchmark indexes subject to limits on annual divergence… Benchmarking causes, first, the inversion of the

If you've been a regular reader of our blog, you already know that we recently published our first book Adaptive Asset Allocation: Dynamic Portfolios to Profit in Good Times - and Bad. As of this writing, it still stands as the #1 new release in Amazon's Business Finance category.

The value and momentum factors have earned high praise in recent years as complementary sources of risk premia for designing and managing equity portfolios. AQR’s widely cited paper “Value and Momentum Everywhere” a few years back helped popularize the idea, pointing to applications in

In the introductory text for Part I of their 2016 book, Adaptive Asset Allocation: Dynamic Global Porfolios to Profit in Good Times – and Bad, Adam Butler, Michael Philbrick and Rodrigo Gordillo state: “…we have come to stand for something square and real, a true Iron Law of Wealth Management:

"Smart beta" investing is an alternative to the traditional active and passive approaches to funds management, whereby investors adopt a systematic method that provides exposure to factors that are argued to be related with expected returns at low cost. Therefore, the question of how smart

The “practitioner Black-Scholes delta” for hedging options is a delta calculated from the Black-Scholes-Merton model (or one of its extensions) with the volatility parameter set equal to the implied volatility. As has been pointed out by a number of researchers, this delta does not minimize the

Not sure why is that, but traditionally we consider 60% stocks and 40% bonds to be a good portfolio mix. One which strikes decent balance between risk and return. I don’t want to blubber here about the notion of risk. However, I do note that I feel uncomfortable interchanging risk with volatility

Justin spoke at the Investing in Smart Beta conference this week in Fort Lauderdale, FL. He spoke alongside Research Affiliates in a session titled "The Smart Beta Checklist: Choosing The Best Strategy & Risk/Return Profile For Your Portfolio." Here's a quick description:

In part 2 our mean-variance optimal FX portfolio is allowed to choose from multiple models each week based on a measure of goodness (MSSE). The risk-adjusted return improves as a result with the annualized Sharpe Ratio rising to 0.86 from 0.49. In part 1 we estimated a sequential multivariate

The previous post was about the auxiliaries to provide some basic interfaces, classes and messages. This post is about the 3rd project for our basic server solution. This project will allow to run the simple server and enable to connect a client. The RunServer project should be a WinForm project to

In the past we have discussed how to combine value and momentum strategies to improve an equity allocation. In this piece we discuss why an investor should combine use value and momentum.* Many investors recognize that stand-alone value and momentum strategies have historically worked. Of course,

If there is a lot of overlap between your portfolio and the market, there is only so much alpha you can earn. This is obvious. Still, when you visualize this potential it sends a powerful message. Active share—the preferred measure of how different a portfolio is from its benchmark—is not a

This post is available as a PDF here. Summary Multi-factor portfolios are a great way to diversify across multiple factors that can potentially create excess risk-adjusted returns while simultaneously smoothing out relative performance volatility. There are two ways we've seen manufacturers

As explained in my latest book, “The Incredible Shrinking Alpha,” which I co-authored with Andrew Berkin, accompanying the rapid growth of the actively managed mutual fund industry, the average performance of mutual funds has been trending downward over the past few decades. Teodor Dyakov, Hao

The best quant mashup links for the two weeks ending Saturday, 03/19 as voted by our readers: How to Learn Advanced Mathematics Without Heading to University - Part 1 [Quant Start] When Measures Become Targets: How Index Investing Changes Indexes [Investor's Field Guide] Meet the DIY Quants Who

Everyone agrees the normal distribution isn’t a great statistical model for stock market returns, but no generally accepted alternative has emerged. A bottom-up simulation points to the Laplace distribution as a much better choice. A well-known problem in financial risk assessment is the failure

Carnegie Mellon's Steve Shreve is out with an interesting post on careers in quantitative finance, with his commentary on the changing landscape in quantitative research and the implications for financial education. I taught at Carnegie Mellon in the late 1990's, including its excellent

I. Trading Strategy Developer: Toby Crabel (Setup: NR7 Pattern); Laurence A. Connors, Linda B. Raschke (Entry: Price Breakout with NR7). Source: (i) Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc; (ii) Laurence A. Connors,

While being a vibrant subfield of computer science, machine learning is used for drawing models and methods from statistics, algorithms, computational complexity, control theory and artificial intelligence. It focuses on efficient algorithms for inferring good predictive models from large data sets

Because of the magnitude, persistence, pervasiveness and robustness of their related premiums, several factors have dominated the academic literature. Among them are market beta, size, value, momentum and profitability. However, despite their persistence, each factor has undergone even fairly long

For this episode I spoke with returning guest Nick Radge, who was originally on episode number 4. But in case you missed it; Nick is a systematic trend follower and momentum trader, most active in Australian and US equity markets. This time around, we discussed mean reversion strategies and why they

In the high desert plain of New Mexico, Roger Hunter monitors automated trades on hog futures and currency pairs. Roger Hunter in his home office. Roger Hunter in his home office. Photographer: David Paul Morris/Bloomberg Four computer screens display a dizzying array of price charts and program

How about trying to find any use of the famous Monty Hall problem in a stock index context? Let your imagination run… First of all, some of you may be confused because neither “Monty Hall problem” nor “Let’s make a deal” are familiar to you so I will refresh you what these names are

A Newfound, we try to embrace March Madness as an opportunity to foster some good-natured competition within the company. This year we decided to mix things up and go with our own version of ReSolve's unique March Madness Challenge. When Corey originally suggested the idea, my initial reaction

Equity index covered calls have historically provided attractive risk-adjusted returns largely because they collect equity and volatility risk premia from their long equity and short volatility exposures. However, they also embed exposure to an uncompensated risk, a naïve equity market reversal

I have got a great trading system for you. I mean, look at that equity curve! It’s very straight, no drawdowns, and $30,000, compounded, became almost $120,000 over time. What’s the catch? They say (and I’m not sure who “they” are) that the average retail investor hates to book a loss, and

I came on an idea recently that I had tested. I have tested adding max loss stops to a mean reversion strategy, with no success. See this post for more on that. About eight years ago, I tested scaling out of trades. But this person claimed that adding the two together was how to improve a mean

Sooner or later, every quant is tempted by forbidden fruit. These all-too-human traits can permeate even the most sophisticated analysis. Keep these tips in mind as you develop strategies, and you just may turn vice into virtue. Quandl_7_sins_v04 (1) Download the printable version here.

The team over at ReSolve recently posted about their very unique March Madness Challenge. The crux of their idea is that the rules governing a more traditional bracket system is fundamentally flawed since it inherently reduces the sample size upon which skill is measured. For example, nearly

I. Trading Strategy Developer: Toby Crabel (Setup: NR7 Pattern); Laurence A. Connors, Linda B. Raschke (Entry: Price Breakout with NR7). Source: (i) Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc; (ii) Laurence A. Connors,

One of the most important issues in finance concerns the relationship between risk and expected return. John Lintner, William Sharpe and Jack Treynor are generally given most of the credit for introducing the first formal asset pricing model, the capital asset pricing model (CAPM), which was

Last week’s podcast was pretty negative on the value of machine learning in trading, so this week I wanted to provide my own counterpoint and explore life within the limits I identified earlier. Specifically, I wanted to begin mapping the things machine learning algorithms might really be great at

We apply a (sequential) multivariate stochastic volatility model to five FX pairs. Using non-optimized settings our model beats a benchmark portfolio – both from a total return and risk-adjusted point of view. Following an equity-centric start to our blog’s life with random portfolios (part 1

When I learned how to ski, my teacher thought trial by fire would be a good, if not entertaining, way to teach me. Somehow, that day I managed to find the small creek on the side of the slope, spent about 30 minutes under a chairlift searching for my yard-saled skis and poles, and managed to stop

Summary The "rules of the game” are crucial in investing. Specifically, care should be taken to ensure that the rules used in portfolio construction align with client expectations. Anecdotally, we see two situations where these rules differ. First, performance is often evaluated over time

There is a seasonal influence that could have a bullish impact on the market this week. Op-ex week in general is pretty bullish. March, April, October, and December it has been especially so. S&P 500 options began trading in mid-1983. The table below is one I have showed on the blog in years

This four part series will explore the NeuroEvolution of Augmenting Topologies (NEAT) algorithm. Parts one and two will briefly out-line the algorithm and discuss the benefits, part three will apply it to the pole balancing problem and finally part 4 will apply it to market data. This algorithm

There are many problems with p-values, and I too have chipped in at times. I recently sat in a presentation of an excellent paper, to be submitted to the highest ranked journal in the field. The authors did not conceal their ruthless search for those mesmerizing asterisks indicating significance. I

In this post I continue building the basic server application. In previous post I created the service host project including the WCF service interfaces. They implement all operation contracts to establish incoming and outgoing connections. This time I continue with another project from the server

My newest research paper, Understanding Modern Portfolio Construction, is available on SSRN. This paper is the culmination of years of work and I consider it to be the most important piece of research I’ve published. I wrote this paper in much the same way that I wrote my paper, Understanding the

"I'm actually really optimistic about the future of quants. The industry is more technical than ever, and there is as much need to understand the risks in the system as ever." - Robert C. Merton, quoted in "Risk," August 2012 In 1997, when Robert Merton won the Nobel Prize

Here’s a stupid system. In fact, I call it the “Stupid 10 Days” system. You look at the last ten days of trading. If the market at the closing bell is up from the market close of 10 days ago, you buy at the next open. You hold for 10 days, then sell at the next open. A classic momentum play.

I am often asked in emails how to go about learning the necessary mathematics for getting a job in quantitative finance or data science if it isn't possible to head to university. This article is a response to such emails. I want to discuss how you can become a mathematical autodidact using

Understanding Modern Portfolio Construction Cullen O. Roche (Orcam Financial Group) February 22, 2016 Over the last 75 years there have been great strides in modern finance, portfolio theory and asset allocation strategies. Despite this progress the process of portfolio construction remains grounded

For context, you can read my previous post on alphadraft betting for CS:GO here. After we have developed a concrete model for drafting our line-ups, we want to focus more on the bettor's bankroll management over time to minimize risk, maximize return and reduce our probability of ruin. In this

When was the last time you had an idea that resulted in the threat of your torture? In the early 1600s, Galileo was expanding upon Copernicus’ idea that the earth revolves around the sun. The easy-going church was slightly less than enthused. In short, things escalated… The Pope got involved…

This is cross-posted from SkewU, our sister blog. We don’t normally do this sort of thing, but this is important because: 1. You should check out SkewU, as it’s quite a bit different than GestaltU. Our posts over there are more diverse and whimsical if that’s something that interests you. 2.