Adam Grimes has been a trader for more than 20-years, he’s traded all major asset classes, across various timeframes. He’s traded independently, with a prop firm, and he’s run other trading businesses also. The main focus of this episode is to explore some of the things which discretionary

This is the second in a series of posts on how to use the native python API for interactive brokers. This post is an update of the post I wrote here, which used the 3rd party API swigibpy. Okay so you have managed to run the time telling code in my last post. Now we will do something a bit more

Until quite recently interactive brokers didn't offer a python API for their automated trading software. Instead you had to put up with various 3rd party solutions, one of which swigibpy I use myself. Swigibpy wrapped around the C++ implementation. I wrote a series of posts on how to use it,

Almost a year ago QuantStart discussed deep learning and introduced the Theano library via a logistic regression example. Given the recent results of the QuantStart 2017 Content Survey it was decided that an up to date beginner-friendly article was needed to introduce deep learning from first

When it comes to momentum investing, everyone is always looking for a better way to implement a momentum-based stock selection strategy (the same goes for a value strategy). We highlight a few methods in our book, Quantitative Momentum, as well as on our blog. We recently came across a paper from

On the heels of last year’s fun and successful March Madness Bracket Challenge (“WHERE SKILL PREVAILS!”), we are happy to invite any and all to 2017’s version. Feel free to read the post for this year’s rules, but bear in mind this year’s pool is limited to 250 entrants, so don’t wait:

This article reviews the backtest results of iron condors (IC) entered at 66 days to expiration (DTE). These tests covered 9 IC variations, with short strike deltas at four locations (8, 12, 16, 20), utilizing 12 exits. In all, there were 432 test runs (9 variations x 4 deltas x 12 exits). Each test

After wonderful and rewarding 2-day workshop devoted to Python for Algo-Trading on March 4-5, it is my pleasure to announce a new, upcoming, on demand 2-Day Workshop on Machine Learning in Python for Finance (May 20-21, 2017). Since Machine Learning is the latest hottest topic covering different

Prospect theory states that the pain of losses exceeds the pleasure of equivalent gains. An oft-quoted ratio for this pain-to-pleasure experience is 2-to-1. Evidence suggests a similar emotional experience is true for relative performance when investors compare their performance to common reference

In a previous post, Copulas in Risk Management, I covered in detail the theory and applications of copulas in the area of risk management, pointing out the potential benefits of the approach and how it could be used to improve estimates of Value-at-Risk by incorporating important empirical features

Theory predicts that securities with greater limits to arbitrage are more subject to mispricing and thus should command a higher return premium. We test this prediction using the unique regulatory setting from the Hong Kong stock market, in which some stocks can be sold short and others cannot. We

With the toolsets we have available to us today it’s really quite easy to create a trading strategy by just mining market data. As we’ve just heard in that opening bit of audio and also from previous podcast guests too, if you try enough combinations you can find something that appears to work

One of the perennial problems in building trading models is the spareness of data and the attendant danger of overfitting. Fortunately, there are systematic methods of dealing with both ends of the problem. These methods are well-known in machine learning, though most traditional machine learning

The buy-and-hold crowd, including many mutual fund companies and a large cross-section of vocal pundits, like to talk about how missing the N best days/months in the market causes a serious impairment to long-term investor returns. What they fail to mention is that, because stock market volatility

Johnny Paycheck has a great country song centered around the following lyric: Take this job and shove it…I ain’t working here no more… Campell Harvey, in the 2017 AFA Presidential Address, elaborates an analogous comment on the current state of the financial economics field: Take this alpha

Check out our awesome new book library curated by four of the top rated authors in our community: Investment Idiocy (Rob Carver): General Quantitative Finance, Market History, Hedge Funds, General Programming Quant Start (Michael Halls-Moore): Python, C++, Financial Math, Quant Jobs & Interviews

In this entry, we discover the secrets behind prices transformation in financial series. Do you use price series in things such as technical analysis visualisation? Do you use return series in things such as volatility calculations? Do you use equity series in things such as comparing products with

Momentum has been found to be a persistent and pervasive factor in the returns not only of equities, but in other asset classes (including bonds, commodities and currencies). With equities (compared to the market, value, size, profitability and quality factors), during the period 1927 through 2015,

This is a summary of the recent performance of a number of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies are broadly representative of the

In a recent letter to its investors, Crispin Odey commented as follows:(1) Money managers specializing in picking stocks and bonds are being driven out by mindless passive investing. Odey is a London based hedge fund manager, whose flagship fund lost almost 50% in 2016.(2) Photo courtesy of Wes. All

The behavior gap is the difference between the returns on an investment and the returns that an investor realizes in that investment. Behavioral biases ingrained in human nature, such as anchoring, hindsight, and overconfidence drive emotional decisions that can lead to a behavior gap, but

Who is Andrey Markov? What is the Markov Property? What is a Markov Model? What makes a Markov Model Hidden? A Hidden Markov Model for Regime Detection Conclusion References Who is Andrey Markov? Markov was a Russian mathematician best known for his work on stochastic processes. The focus of his

I've read too many posts / articles that outline why a rise in rates is good for long-term bond investors (as that would allow reinvestment at higher rates). While this can be true depending on the duration of bonds owned and/or for nominal returns over an extended period of time, it is

The performances of factor investing rely heavily on short sales, not only for building the initial long-short strategy, but also for regularly rebalancing the positions. Since short selling is subject to both legal restrictions and substantial costs, this paper examines how severely restrictions on

Why dual momentum? Because strategies based on highest relative momentum show great results in the long run, but can experience deep falls and have little participation in the posterior rebounds after large market falls. To sidestep these drawbacks, here it is laid out a strategy based on Gary

According to Morningstar, as of June 2016, the assets in smart beta exchange traded products totaled $490 billion. BlackRock forecasts smart beta using size, value, quality, momentum, and low-volatility will reach $1 trillion by 2020 and $2.4 trillion by 2025. This annual growth rate of 19% is

My last post on Country ETF Rotation generated several ideas of what to test to improve the results. See the original post for the list ETFs being traded. One important test I left out from the original post was a baseline case. An idea applied to all the tests was trading more ETFS. For all tests,

As my co-author, Andrew Berkin, and I(1) explain in our new book, “Your Complete Guide to Factor-Based Investing,”(2) one of the big problems for the first formal asset pricing model developed by financial economists, the CAPM, was that it predicts a positive relation between risk and return.

Trend-following strategies – such as managed futures and tactical equity – have historically provided crisis alpha against sustained drawdowns. For short-horizon events (e.g. single day, week, or month events), the effectiveness of these approaches in managing risk is largely based on the luck

In the previous article on Hidden Markov Models it was shown how their application to index returns data could be used as a mechanism for discovering latent "market regimes". The returns of the S&P500 were analysed using the R statistical programming environment. It was seen that

We’ve added a major new feature to our members area: historical allocation analysis. Every strategy that we track now includes a brand new subpage, which is updated daily and devoted to helping members better understand how each asset class has contributed to the strategy’s performance. In this

Limited data is the financial modeler’s biggest challenge. Making assumptions about risk is tough enough under the best of circumstances. All too often it’s even tougher when the historical record is thin. There are several ways to manage this challenge, including bootstrapping, aka resampling

Spx is on a low volatility streak, taking a look at how long the streaks usually last and how the current streak relates to past instances. Also looking at Spx returns once the spell breaks – as do probably most others, i expected volatility to pick up, that does not seem to be the case. Bill Luby

Our epic piece on factors from a few weeks ago is still ringing in our own ears: Are factors even real? Or just data-mining? The conclusion: who knows. We need more data. And more data we can find. To include a recent master’s thesis on nordic country equities, which looks at Size, value,

Over the last twenty five years significant advances have been made in the theory of asset processes and there now exist a variety of mathematical models, many of them computationally tractable, that provide a reasonable representation of their defining characteristics. While the Geometric Brownian

A few words about outliers In statistics, outliers are as thorny topic as it gets. Is it legitimate to treat the observations seen during global financial crisis as outliers? or are those simply a feature of the system, and as such are integral part of a very fat tail distribution? I recently read a

One of the popular investing truisms is the following (inspired by Bill Sharpe): For somebody to beat the market (win) someone else has to lag the market (lose). This becomes an even more daunting (efficient market) statement when changed to the following: For someone to consistently beat the market

The Alpha Architect mission is to empower investors through education.(1) We can’t accomplish our mission without help. Fortunately, “finance twitter” and an explosion of bloggers are helping us achieve our goal. Awesome! Of course, with so many new blogs hitting the scene, we now face an

This post will introduce John Ehlers’s Autocorrelation Periodogram mechanism–a mechanism designed to dynamically find a lookback period. That is, the most common parameter optimized in backtests is the lookback period. Before beginning this post, I must give credit where it’s due, to one Mr.

Stocks usually perform poorly when inflation is on the rise. Using the inflation rate, we developed a market timer according to two simple rules. Switching according to the Timer signals between the S&P500 with dividends and a money-market fund would have provided from Aug-1953 to end of

Random forest is one of the most well-known ensemble methods and it came up as a substantial improvement of simple decision trees. In this post, we are going to explain how to build a random forest from simple decision trees and to test how they actually improve the original algorithm. Maybe you

A quantmod user asked an interesting question on StackOverflow: Looping viewFinancials from quantmod. Basically, they wanted to create a data.frame that contained financial statement data for several companies for several years. I answered their question, and thought others might find the function I

A recent theory paper from researchers at NYU and Rutgers attempts to explain the empirical evidence on stock serial correlation (e.g., short-term reversal, long-term stock reversal, and classic stock momentum). The interesting wrinkle with this paper is the authors don’t need to assume irrational

Based on our post from earlier today ("Anatomy of a Bull Market"), we received a request to decompose U.S. equity returns over rolling 10-year periods. The graph presenting this data is below. To perform these calculations, we calculate the annualized return generated by each source

The first talks from QuantCon 2017 have just been announced. Come out and hear insightful talks on overfitting, backtesting, Bayesian global optimization, and more! QuantCon Talks on April 29th Marcos López de Prado, Senior Managing Director at Guggenheim Partners, and Dr. Michael Kearns, Professor

I’m strongly considering entering into a substantial investment in bitcoin as part of my passively managed, fully long portfolio. Before I do that, I decided to look into two questions regarding bitcoin’s role in a portfolio: What is bitcoin’s correlation with other financial assets? Can

Long-term average stock returns smooth over the bull and bear markets that investors experience, and no two market cycles ever unfold the exact same way. Bull and bear markets can vary significantly in both duration and magnitude. But there are other characteristics of bull markets that can also

In this article the issue of when to retire a trading strategy will be considered. It will present brief reasons why strategies eventually end up underperforming. It will discuss how this can be measured over time and then describe an implementation in QSTrader that provides this functionality. The

This is the last week to snag yourself a free ticket to this year’s QuantCon in NYC in April. Quantopian has generously offered the Quantocracy community 3 free tickets worth a total of $2,497. A number of very smart people on our mashup will be speaking, including EP Chan, Rob Carver (Investment

The 200 day moving average is perhaps one of the most well-known tactical asset allocation filters and many analysts suggest that you should be long the stock market if the Index is greater than the 200 day MA, and flat the stock market if the Index is less than the 200 day MA. For example, the