This is Part 1 of a new series I'm doing in semi real-time to build a functional options data dashboard using Python. There are many underlying motivations to attempt this, and several challenges to implementing a tool like this from scratch. Where to get the data? Is it affordable? Easily

Recently, Yahoo Finance – a popular source of free end-of-day price data – made some changes to their server which wreaked a little havoc on anyone relying on it for their algos or simulations. Specifically, Yahoo Finance switched from HTTP to HTTPS and changed the data download URLs. No doubt

On 18 May 2017 the ichart data api of yahoo finance went down, without any notice. And it does not seem like it is coming back. This has left many (including me) with broken code and without a descent free end-of-day data source. Something needs to be done. Now. Apparently Yahoo! does not want us to

We introduce a new approach to algorithmic investment management that yields profitable automated trading strategies. This trading model design is the result of a path of investigation that was chosen nearly three decades ago. Back then, a paradigm change was proposed for the way time is defined in

Just a quick post in the light of a very recent event. Users of financial functions of R, MatLab, Python, or Zorro got a bad surprise in the last days. Many scripts and programs based on historical price data suddenly don’t work anymore. And our favorite free historical price data provider, Yahoo,

This post will be about creating constant expiry (E.G. a rolling 30-day contract) using VIX settlement data from the CBOE and the spot VIX calculation (from Yahoo finance, or wherever else). Although these may be able to be traded under certain circumstances, this is not always the case (where the

Why do CEOs decide to pay dividends? That is an interesting question, and one that academics have been researching for years. Miller and Modigiliani in 1961 show that if one assumes perfect and efficient capital markets, and investors should have no preference as to whether or not a firm pays

This is the second in a series of posts written by Frank Smietana, an expert guest contributor to QuantStart. In this detailed post Frank takes a look at the different ways in which an algorithmic trading business can be established—and why you might want to consider it. - Mike. Setting up an

We suspect you’re skeptical, and that’s a good thing. In fact, the more skeptical you are, the more you need to download our full 26-page paper “Tactical Alpha: A Quantitative Case for Active Asset Allocation.” In it, we discuss research from such luminaries as Brinson, Ibboston and Kaplan,

"Today the VIX traded below 10 briefly intraday. A pretty rare occurrence. Since 1993, there have been only 18 days where it traded below 10 intraday and only 9 days where it closed below 10." (source: some random dude on my linkedin feed) ... indeed 18 observations is a long.... long...

A lot of people look at this bull market, valuations, and think somehow that value has forsaken us. And that the much discussed CAPE ratio doesn’t work. They look at the CAPE ratio, at a current value of about 30 in the US, and think somehow that markets rising along with multiples expanding

This review is a book review of Gary Antonacci’s Dual Momentum Investing book. The TL;DR: 4.5 out of 5 stars. So, I honestly have very little criticism of the book beyond the fact that the book sort of insinuates as though equity momentum is the be-all-end-all of investing, which is why I deduct a

Bitcoin, Ethereum and some other cryptocurrencies seem to be in the spotlight again due to their most recent acceleration. C_y2pGfXoAApvdI Source: CEOTechnician Ethereum is up multiples since January. I thought we could take a look at importing Etherum price data in R and then seeing if we can draw

In this case study, we explore building a simple, low cost, systematic municipal bond portfolio. The portfolio is built using the low volatility, momentum, value, and carry factors across a set of six municipal bond sectors. It favors sectors with lower volatility, better recent performance, cheaper

To date QuantStart has generally written on topics that are applicable to the beginner or intermediate quant practitioner. However we have recently begun to receive requests from academics and advanced practitioners asking for more content on research-level topics. This is the first in a new series

The Oracle of Omaha just commented on the Chinese stock market in this year’s Berkshire’s annual meeting: …Markets have a casino characteristic that has a lot of appeal to people, particularly when they see people getting rich around them. And those who haven’t been through cycles before are

Thus far in the series we've explored the idea of using Gaussian mixture models (GMM) to predict outlier returns. Specifically, we were measuring two things: The accuracy of the strategy implementation in predicting return distributions. The return pattern after an outlier event. During the

Are portfolio managers skilled in stock-picking? It is a popular subject for academic research and majority of papers show that active funds underperform their respective benchmarks. But... It doesn't mean professionals do not know how to pick stocks. It can simply mean that a lot of managers

There are a number of recent studies that propose a more rigorous criteria for evaluating the practical significance of factors published in academic research journals. First, Harvey, Liu, and Zhu (2015) argue that a t-stat of 3 should be replacing the old 2 as a rule for statistical significance.

Here it goes, finally a strategy backtest (sort of) on this blog (what an intro). In their 1973 paper “Risk, Return and Equilibrium: Empirical Tests”, Fama and MacBeth introduce a method for estimating betas and risk premia for any risk factors that determine asset prices. Under the assumption

Shrinkage in statistics has increased in popularity over the decades. Now statistical shrinkage is commonplace, explicitly or implicitly. But when is it that we need to make use of shrinkage? At least partly it depends on signal-to-noise ratio. Introduction The term shrinkage, I think, is the most

The role of luck in (algorithmic) trading is ever present. Trading is undoubtedly a field that experiences vast amounts of randomness compared to mathematical proofs or chess, for example. That being said, a smart trader must be conscious of the possibility of outcomes and not just a single outcome.

This is a test of the Tactical Permanent Portfolio from the brains at GestaltU and ReSolve Asset Management. The strategy adds a number of dynamic features to a classic buy & hold strategy to better manage volatility and losses. Results from 1970, net of transaction costs, follow. Read more

Well, Its here, spot Vix close below 10. From what i read from the web, people are piling into short vol strategies on an escalating scale. I suspect unwinding of that trade will be rather brutal. I wish good luck to every short vol trader out there and dont forget to wear a helmet 🙂 1 2 3 4 5 6 7

Over the last several months I have shared the results from an extensive set of backtests of SPX iron condors (IC). In all, I backtested 600,912 individual SPX IC trades entered at varying days to expiration (DTE) between January 2007 and September 2016. The prior articles can be found at the links

Market expectations are a key input in the portfolio construction process. These expectations can be either qualitative or quantitative. How to form expectations for more complex strategies (e.g. managed futures, covered calls, and alternatives) is often less straightforward than forming

In today’s algorithmic trading having a trading edge is one of the most critical elements. It’s plain simple. If you don’t have an edge, don’t trade! Hence, as a quant, one is always on a look out for good trading ideas. One of the good resources for trading strategies that have been gaining

Financial research has uncovered many relationships between investment factors and security returns. Given that popularity is a curse in investing, the growing popularity of factor investing has led to worries that factors have become overvalued, posing risks to investors in these strategies. For

As the old joke says, “math is what mathematicians do.” Somehow this simple tautology is lost in the dishonest world of finance Quantitative investing: A crisis waiting to happen In a recent WSJ article, Jason Zweig brilliantly summarizes the unbearable hype and hubris exhibited by some

Does the conventional wisdom to “Sell in May” (and “Buy in November”, hence also the term “Halloween Effect”) work over the long run, perhaps due to biological/psychological effects of seasons (Seasonal Affective Disorder)? To check, we turn to the long run dataset of Robert Shiller.

Credit Spreads, Daily Business Cycle, and Corporate Bond Returns Predictability Alexey Ivashchenko (University of Lausanne) May 4, 2017 The part of credit spread that is not explained by corporate credit risk forecasts future economic activity. I show that the link with aggregate business risk and

April 2017 Trend Following: DOWN -1.35% / YTD: -11.65% April was another down month for the Wisdom State of Trend Following, with the index already in double-digit territory, on the negative side, for the year. Below is the full State of Trend Following report as of last month. Performance is

I have been troubled by the following paradox in the past few years. If a stock's log returns (i.e. change in log price per unit time) follow a Gaussian distribution, and if its net returns (i.e. percent change in price per unit time) have mean m and standard distribution s, then many finance

Over the past few years, we’ve been asked questions related to the relationship between stock prices and interest rates. Forms of the question typically look like the following: If interest rates rise, what happens to stock prices? What is the relationship between stocks prices and bond yields?

The S&P 500 index (SPX) is an American market index based on the stocks of 500 large companies. It’s one of the world’s most important market indexes and, therefore, predicting its movements is the goal of many finance analysts. In previous posts we have reproduced the SPX through clustering

In Simple ConnorsRSI Strategy on S&P500 Stocks I showed a ConnorsRSI strategy on S&P500 stocks. In ConnorsRSI Strategy: Optimization Selection, I narrowed down the optimization to three potential variations that one could consider trading. This post will explore Sensitivity Analysis (also

Factor investing (value, momentum, low volatility, carry, trend, etc.) is well-known in equities but less discussed in other asset classes. However, many of these factors are just as prevalent in other asset classes, such as bonds, commodities, and currencies. In this case study, we explore the

In our previous post we demonstrated an approach to modeling US Treasury ETF performance in an era of rising interest rates. We showed results like the ones below, simulating the performance of various constant maturity ETFs from the interest rate peak in 1981 to the present (left half of the

Wednesday is a Fed Day. Fed Days have historically shown an upside tendency. I have documented this tendency in great detail over the years, with the most complete documentation coming in The Quantifiable Edges Guide to Fed Days. Based on what the market did Tuesday, this does not seem to be the

In trading and in trading-related research one could be quickly overwhelmed with the sea of ink devoted to trading strategies and the like. It is essential that you “pick your battles” so to speak. I recently finished reading Machine Trading, by Ernest Chan. Here is what I think about the book.

Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. The momentum effect is one of the most pervasive asset pricing anomalies documented in the financial literature: Stocks

As you'll know if you've been following any of my numerous social media accounts I spent the weekend in New York at QuantCon, a conference organised by Quantopian who provide a cloud platform for python systematic trading strategy backtesting. Quantopian had kindly invited me to come and

This is the first in an exciting series of posts written by Frank Smietana, a new expert guest contributor to QuantStart. In this insightful new article Frank looks at the different career roles that are available in the systematic trading space. - Mike. The changing role of humans in capital

Position sizing and portfolio allocation have not received much attention in the options trading community. In this post we are going to apply a simple position sizing rule and see how it performs within the context of volatility trading. An option position can be sized by using, for example, a

As you are reading this blog you are definitely familiar with the concept of backtesting trading strategies, and probably have done so a significant amount of times. But do you also backtest your risk metrics? They are as important of a building block of your portfolios overall performance as the

I had some time yesterday while waiting for an appointment, and re-read "A Comparison of Tail Risk Protection Strategies in the U.S. Market". One particular sentence in the paper caught my attention: "Remarkably, of the 24 months with greater than 5% loss in the S&P 500 between

In the previous post, we reviewed momentum’s robustness. We looked at how momentum has stood the test of time. We also stress-tested the Global Equities Momentum (GEM) strategy to see whether it’s performance is not overly sensitive to changes in the strategy’s settings (i.e. the 12-month

This is a summary of the recent performance of a wide range 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

At the settlement time of the VIX Volatility Index, volume spikes on S&P 500 Index (SPX) options, but only in the out-of-the-money options that are used to calculate the VIX, and more so for options with a higher and discontinuous influence on VIX. We investigate alternative explanations of

ETFs and factor investing are on the tip of everyone’s tongue these days. Factor investing is being couched as a “new” thing, despite the fact that institutional investors have been deploying these strategies for years. (See this working paper discussing the effective use of smart beta