While it’s certain that short-term volatility exchange traded products (ETPs) like VXX, TVIX, and UVXY are doomed to march towards zero, their decay rates are not consistent. Things like bear markets and big corrections can cause big upward swings. On the downside, the term structure of VIX futures(...)

Machine Learning world is quite big. In this blog you can find different posts in which the authors explain different machine learning techniques. One of them is clustering and here is another method: Hierarchical Clustering, in particular the Ward’s method. You can find some examples in(...)

If there’s one thing I’ve done a lot of over the last few years, reading would be it. I’ve devoted a great deal of time to devouring any material that I thought might give me an edge in my trading – textbooks, academic papers, blog articles, training courses, lecture notes, conference(...)

There is a lot more luck involved in investing than people think. I’m not saying there isn’t skill involved in investing or that there aren’t ways to outperform the market over time. Even if you have a process that can be shown to outperform the market over long time periods, there can be a great(...)

For those who prefer a little more rigor in their quantitative research, I can offer more a somewhat more substantive statistical argument in favor of the IBS indication discussed in my previous post. Specifically, we can show quite convincingly that the IBS process is stationary, a highly(...)

In some ways, investing is simple. After all, we all want the same things. High returns. Low volatility. Small max drawdowns. Unfortunately, it’s very difficult–if not impossible–to have your cake and eat it too. There are always tradeoffs among these desires that have to be managed by investors.(...)

In the previous article on the Cointegrated Augmented Dickey Fuller (CADF) test we noted that one of the biggest drawbacks of the test was that it was only capable of being applied to two separate time series. However, we can clearly imagine a set of three or more financial assets that might share(...)

Python has emerged as one of the most popular language to code in Algorithmic Trading, owing to its ease of installation, free usage, easy structure, and availability of variety of modules. Globally, Algo Traders and researchers in Quant are extensively using Python for prototyping, backtesting,(...)

"Predicting rain doesn't count. Building arks does." Warren Buffett, The Oracle of Omaha (born 1930) In this penultimate leg of the tour we'll be visiting 2 more attractions along Via Meucci, Construction and Execution. Construction Portfolio Construction is another yuge! topic.(...)

We’re recently getting more and more contracts of developing systems for trading binary options. This calls for a closer look. Binary options resemble financial instruments, but are widely understood as a scheme to separate naive traders from their money. And indeed, binary options brokers make no(...)

This post will cover a function to simplify creating Harry Long type rebalancing strategies from SeekingAlpha for interested readers. As Harry Long has stated, most, if not all of his strategies are more for demonstrative purposes rather than actual recommended investments. So, since Harry Long has(...)

My last post, “Will bonds deliver crisis alpha in the next crisis?,” created quite a stir on the blogosphere. The underlying assumption of the analysis is that stocks are a core component of a portfolio and bonds are included to diversify the portfolio. The key takeaway from my analysis is that the(...)

A common way to describe a mean reversion trade is a rubber band that stretches away and then snaps back. Something that Steve, my trading buddy, and I discuss when a trade keeps going against us is that the rubber band has broken. I have never tested that concept. Meaning after N day sell-off, are(...)

How fast should individuals plan to grow net worth as they age? To investigate, we examine median levels of household (1) total net worth and (2) net worth excluding home equity from several vintages of U.S. Census Bureau data. We make the following head-of-household age cohort assumptions: “Less(...)

In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by standard deviation). We calculate the theoretical IR of a(...)

There are a wide variety of Machine Learning techniques that help us to solve Big Data problems. In this post we talk about how to apply Lasso Regression in Portfolio Management. You may have heard of this technique in the past, for that reason I’ll try to explain it in a brief introduction. Lasso(...)

Today we'll be visiting 2 sites along Via Meucci, Evaluation and Attribution. Evaluation We need some way to measure the goodness of the ex-ante portfolio across the scenarios from the Aggregation step, and for this Meucci introduces the concept of a Satisfaction index. Given the distribution(...)

Traders in the derivative market often exercise one of the following: Call option or Put Option. “Call option” is a financial contract between a buyer and seller, whereby the buyer has the right, but not the obligation, to buy an agreed quantity of a financial instrument from the seller of the(...)

In the previous article on cointegration in R we simulated two non-stationary time series that formed a cointegrated pair under a specific linear combination. We made use of the statistical Augmented Dickey-Fuller, Phillips-Perron and Phillips-Ouliaris tests for the presence of unit roots and(...)

Think only a bear market can keep returns of a 60/40 near 0%... think again. Given the huge opportunity cost of allocating to cash or bonds at current yield levels, even generally optimistic return assumptions for stocks are enough to keep portfolio level returns near 0% real. The goal of this post(...)

How do you handle repetitive tasks? If you’re like most people, you work through a task in a variety of ways, find the most efficient approach, and then stick to that workflow. Consider email address autofill, automatic payment plans, or automatic renewal of magazine subscriptions. Because of(...)

Some say that bull markets climb a wall of worry. This is good news for those already in the market. Worriers will help the market go higher later when they finally decide to jump on the bandwagon. Herding, representativeness, and regret aversion (fear of losing out on future profits) can(...)

Summary Many investors look at fixed income as the diversifying sleeve of their portfolio, helping to safeguard capital against losses in more volatile equity positions. Traditional fixed income indices are very heavily weighted towards U.S. Treasuries and agency mortgage-backed securities,(...)

Few weeks back I gave a talk in the R/Finance 2016 conference, about forecast combinations in R. Here are the slides.

Thursday and Friday saw relatively large selloffs in SPX. After closing at a 50-day high on Wednesday it closed at a 10-day low on Friday. This triggered an interesting study from the Quantifinder that looked at relatively sharp selloffs that made at least 8-day lows. I have updated that study(...)

The best quant mashup links for the two weeks ending Saturday, 06/11 as voted by our readers: A Survey of Deep Learning Techniques Applied to Trading [Greg Harris] Diversification Will Always Disappoint [Flirting with Models] Capital correction (pysystemtrade) [Investment Idiocy] Will Bonds Deliver(...)

When I wrote my Wagner Award winning paper "Know your System! – Turning Data Mining from Bias to Benefit," I had two goals in mind: Introduce a new method to reasonably estimate the long-run expected performance of a trading system, and Provide a simple method for the average system(...)

Today we're covering a topic which can really be a concern for traders of all levels, from beginner to pro, and that is the topic of strategy evaluation. Have you ever found that real-life performance does not match expected results? Or perhaps you have a strategy that is stuck in a drawdown(...)

This is the second of a series on the future of smart beta. In our first article in this series—“How Can ‘Smart Beta’ Go Horribly Wrong?” 1—we show, using U.S. data, that the relative valuation of a strategy (in comparison with its own historical norms) is correlated with the strategy’s subsequent(...)

"In the future, instead of striving to be right at a high cost, it will be more appropriate to be flexible and plural at a lower cost. If you cannot accurately predict the future then you must flexibly be prepared to deal with various possible futures." Edward de Bono, author and thinker(...)

A strong down month in May for the state of trend following index, which solidifies the downtrend from the last two months and takes the YTD performance in the red, after the strong start to the year. Please check below for more details. Detailed Results The figures for the month are: May return:(...)

I have created a quantitative trading strategy that incorporates a simple machine learning model to trade the SPY as part of my ongoing research in quantitative trading. The focus here was not on creating a strategy with alpha but rather to develop a framework both in my mind and in code to develop(...)

We continue with our last OBSSESION… trying to capture an index trend but at the moment, not playing with future information. Markov Switching RegimesWe are going to introduce the Markov Switching Regimes (MSR) model which, as its name indicates, tries to capture when a regimen has changed to(...)

May 2016 Trend Following: DOWN -7.37% / YTD: -1.71% This time, the negative performance for the index last month takes the Year-To-Date performance in the red, for the first time in 2016. Below is the full State of Trend Following report as of last month. Performance is hypothetical. Chart for May:(...)

I am sure you also don't run after the most recent best performing investment strategy. I stopped doing this, a long time ago, after I (quite a few times) discovered I was the last to jump on the strategy just as it stopped working. But I suspect you also find it interesting to see what has(...)

This post is about how should you adjust the trading capital you have at risk given the profitability (or not) of your trading account. I'm posting this for three reasons. Firstly it's a pretty important topic. I address, in some detail, how to set your risk target for a given amount of(...)

To paraphrase the old adage; "a monkey throwing darts will outperform most fund managers". I have seen this concept explored several times in relation to the SP500, but I was interested to see if it had any relevance to the ASX200. Our monkey with darts will be a random number generator,(...)

We relate the performance of trend following strategy to the difference between a long-term and a short-term variance. We show that this result is rather general, and holds for various definitions of the trend. We use this result to explain the positive convexity property of CTA performance and(...)

Bonds are often viewed as being great diversifiers due to the perception that they perform well during tough times for stocks. Historically this has been a true statement. But will it continue? Our answer: unclear. Most investors use correlation to measure the diversification benefit an investment(...)

Answering whether a strategy should be a core holding or an alternative holding often has less to do with the investment strategy itself and more to do with an investor’s understanding of how that strategy will perform. Asset classes and strategies that investors are comfortable with, and have a(...)

A member of our slack channel recently asked if there was an equivalent of "sell in May" for volatility trading. Does the volatility premium, the difference between implied volatility and the subsequent realized volatility, differ during summer and winter months? To test this idea for the(...)

Markets are efficient if new information is incorporate instantly and essentially without any trading, i.e. price jumps to the correct level that represents all available information at the time. If you believe markets are indeed perfectly efficient, there seems to be no point in using news as a(...)

"Guessing before proving! Need I remind you that it is so that all important discoveries have been made?” Henri Poincaré, French mathematician (1854-1912) In this second leg of The Checklist tour, Estimation, we are going to make some educated guesses about the true unknown distribution of the(...)

In the Operational Risk Management, given a number/type of risks or/and business line combinations, the quest is all about providing the risk management board with an estimation of the losses the bank (or any other financial institution, hedge-fund, etc.) can suffer from. If you think for a second,(...)

Internal Bar Strength (IBS) is an idea that has been around for some time. IBS is based on the position of the day’s close in relation to the day’s range: it takes a value of 0 if the closing price is the lowest price of the day, and 1 if the closing price is the highest price of the day. More(...)

We just wrote a piece for Forbes on financial bubbles in the lab. Punchline: investors initially underreact to fundamentals, then they overreact, and eventually prices correct. But how common are crashes? Ben has some interesting thoughts, but the results are limited to the US market. Now, one of(...)

This study analyzes the complete historical performance of Jim Cramer’s Action Alerts PLUS portfolio from 2001 to 2016 which includes many of the stock recommendations made on Cramer’s TV show “Mad Money”. Both since inception of the portfolio and since the start of “Mad Money” in 2005 (when it was(...)

I. Trading Strategy Developer: Larry Connors (The 2-Period RSI Trading Strategy), Welles Wilder (The RSI Momentum Oscillator). Source: (i) Connors, L., Alvarez, C. (2009). Short Term Trading Strategies That Work. Jersey City, NJ: Trading Markets; (ii) Wilder, J. W. (1978). New Concepts in Technical(...)

Feature Selection is the automatic selection of attributes in your data (such as columns in tabular data) that are most relevant to the predictive modeling problem you are working on. Feature selection methods aid you in your mission to create an accurate predictive model. They help you by choosing(...)

A while back we considered a trading model based on the application of the ARIMA and GARCH time series models to daily S&P500 data. We mentioned in that article as well as other previous time series analysis articles that we would eventually be considering mean reverting trading strategies and(...)