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

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

Debates abound on the relative importance of the economic cycle to investment success. Peter Lynch famously said, "If you spend more than 13 minutes analyzing economic and market forecasts, you've wasted 10 minutes.” On the flip side, macro investment houses have constructed intricate

Harry Houdini is perhaps the best-known magician of all time, gaining notoriety in the early 20th century through his daring escape acts. Houdini escaped from straight jackets while suspended from chains, fought his way out of submerged mailbags, and performed a “buried alive” stunt. Crowds

Introduction In this mini-Meucci series of posts we'll put the 10 steps of The Checklist into practice by constructing a low volatility portfolio in Python. This toy/basic example will be a short tourist trip, highlighting key attractions that you can then explore further... Of course, these

I'm currently working on three things: a VIX option trading strategy, a piece about how factors relate to earnings announcements and a Kelly criterion type thing for options. But none is particularly close to being done. So I thought i would post a few links to articles that I found

Summary For its ability to reduce risk without necessarily sacrificing potential reward, diversification is known as the only free lunch on Wall Street. Diversification provides investors with the important ability to invest in the face of uncertainty. When viewed for its pieces instead of as a

The week of Memorial Day has shown some interesting seasonal tendencies over the years. And for a long time it exhibited consistent bullishness. But it has faltered greatly the last several years. The chart below examines SPX performance from the Friday before Memorial Day to the Friday after it.

Technical Indicator is essentially a mathematical representation based on data sets such as price (high, low, open, close, etc.) or volume of a security to forecast price trends. There are several kinds of technical indicators that are used to analyse and detect the direction of movement of the

The best quant mashup links for the two weeks ending Saturday, 05/28 as voted by our readers: A simple breakout trading rule (pysystemtrade) [Investment Idiocy] Some Impressions from R Finance 2016 [Revolutions] Most popular machine learning R packages [Eran Raviv] Exploring Extreme Asset Returns

Nelson Freeburg was the editor of Formula Research, a newsletter that developed systematic timing models for the stock, bond, and commodity markets. He was also a research consultant working with institutional money managers to design proprietary timing models. Nelson had been an active trader since

When I announced R in Finance 2016 I talked about 2 days of conference and 50 speakers. I missed out the 3 days of sleep deprivation. But a pleasant 3 days of sleep deprivation it was — seeing old friends and making new ones. I’m not sure that Mother Mary believed me that in our house we still

1. Present some empirical evidence for short volatility strategies and the cyclical pattern of their P&L: alpha in good times, beta in bad times 2. Introduce a factor model with risk-aversion to explain the risk-premium of short volatility strategies as a compensation to bear losses in bad

Tail or extreme assets returns have been extensively studied. In his amazing paper: “Empirical properties of assets returns: stylized facts and statistical issues”, Rama Cont provides a framework on statistical analysis of price variations in various types of financial markets. He presents

R / Finance 2016 lived up to expectations and provided the quality networking and learning experience that longtime participants have come to value. Eight years is a long time for a conference to keep its sparkle and pizzazz. But, the conference organizers and the UIC have managed to create a vibe

I frequently get asked for updated tests on various strategies. Using Portfolio123 I ran a backtest on a Dual Momentum strategy from 1/1/2007 – 5/25/2016. The strategy is updated on Scott’s Investments monthly, the most recent update is here. The strategy invests equally in one ETF from each of

A couple posts ago, I did the RSI Analysis. This post will focus on ConnorsRSI which I created while working for Larry Connors. When creating the indicator, the focus was on short-term mean-reversion results. We will look at that here but also how does it handle longer-term holds. Since I did not

Konstantinidi et. al. state in their broad survey of Volatility-Index forecasting: "The question whether the dynamics of implied volatility indices can be predicted has received little attention". The overall result of this and the quoted papers is: The VIX is too a very limited extend (R2

The role of Algorithm in a person’s life is too substantial to be ignored. From a simple coffee-making machine to the music system in his car, from elevators to search engine like Google, all are governed by a set of logical instructions – Algorithms or Algos, which enable them to respond to a

There are a plethora of seasonal anomalies documented in academic research. For equities these include the Halloween effect (“Sell in May”), January effect, turn-of-the-month effect, weekend effect and holiday effect. For example, Bouman and Jacobsen (2002) and Jacobsen and Visaltanachoti (2009)

In this piece, I’m going to introduce a simple market model, and then use the model to illustrate certain important concepts in the debate between active and passive management. Some of these concepts have already been discussed in prior pieces, others are going to be new to this piece. Consider,

In this post we will: Take a look at a simple, momentum based, monthly rebalanced Equity/Bond portfolio. Search for what has been the optimal dates in the month to rebalance such a portfolio. Each month we allocate to two ETFs: SPY and TLT. If SPY has outperformed TLT we rebalance to 60% SPY – 40%

I think an interesting application of ML could be generating the ‘features’ for inclusion in a trading algorithm, converting non-numerical data into numerical. For example, converting market sentiment or satellite imagery to count cars in a retailer’s parking lot. More examples here. I had

Breakout. Not the classic home arcade game, seen here in Atari 2600 version, but what happens when a market price breaks out of a trading range. The Atari 2600 version was built by Wozniak with help from Jobs exactly 40 years ago. Yes that Wozniak and Jobs. Source: wikipedia In this post I'll

At this point, even hard core efficient market fans will likely admit that behavior can influence investment decisions. Humans aren’t robots. However, just because some investors exhibit bad behavior that doesn’t mean they can influence prices. As the story goes, smart investors are prepared to

We recently updated, expanded, and put a new face on a whitepaper we had written last year called, “Why Tactical Fixed Income is Different.” You can access the new paper here. In the original version, we looked at some of the reasons why a simple tactical strategy that commonly works in equities

We’ve discussed return seasonalities in the past, especially as they pertain to our approach to momentum. Turns out seasonality effects aren’t confined to momentum — they are literally everywhere and they are incredibly strong. This paper will blow your mind once you let the results settle in

If you’re like most investors, you’re asking the wrong questions. I was chatting with a group of advisors this week down in La Jolla and a question arose. I’ll paraphrase: “Meb, thanks for the talk. We get a steady stream of salespeople and consultants in here hawking their various asset

In a previous post I showed you how to use my open source python backtesting package, pysystemtrade, to estimate forecast weights and instrument weights. At the time I hadn't included code to calculate costs. Now that has been remedied I thought I should also write some code to demonstrate the

How effective is your method of managing portfolio risk? We compare and contrast different approaches – including fixed income, managed futures, low volatility equities, and tactical – to explore the relative protection they can deliver versus the return drag they can create.

Machine learning and trading is a very interesting subject. It is also a subject where you can spend tons of time writing code and reading papers and then a kid can beat you while playing Mario Kart. In the nexts posts, we are going to talk about: Optimize entries and exits. This and only this could

My friend Ben from A Wealth of Common Sense poses the interesting question, How Should Alternative Investments Be Benchmarked? Please go read his post for a number of interesting thoughts on that topic. In this post, rather than rehash his arguments, I'll go a different direction and will try

The goal of this research is to find various set-ups and exit strategies that could be used for trading the opening range breakouts. The time frames we will be looking at are 10min, 15min and 30min opening range breakouts. We will focus our attention on the very liquid futures markets in particular

Low volatility funds are everywhere. The reasons for their proliferation are clear: Who wouldn’t want to own something with the label “low volatility” and Recent performance has been great. Open the AUM floodgates! But perhaps not all is well in low volatility land. A recent snippet by Josh

In this post I want to discuss ways to make use of signals from relevant market indices in your trading. These signals can add value regardless of whether you trade algorithmically or manually. The techniques described here are one of the most widely applicable in the quantitative analyst's

Last week I organised for Attilio Meucci to give a webinar to members of CFA Singapore and NUS Risk Management Institute on an Introduction to “The Checklist” – Ten Steps for Advanced Risk and Portfolio Management. It served the dual-purpose of a professional development talk and marketing of

I have spent the last few weeks trying to get my recursive sine wave formula for period calculations to work, but try as I might I can only get it to do so under ideal theoretical conditions. Once any significant noise, trend or combination thereof is introduced the calculations explode and give

It’s been about a year since we launched Quantocracy. Over that time, we’ve sent about 450,000 clickthroughs to sites in the quant community, and that doesn’t even include RSS, Twitter, StockTwits and Facebook. To all of the denizens of Quantocracy: a big mahalo, gracias, 謝謝 and thank you

The good thing about using open-source software is the community around it. There are very many R packages online, and recently CRAN package download logs were released. This means we can have a look at the number of downloads for each package, so to get a good feel for their relative popularity. I

The math of losses is not a secret: as losses grow, the return required to hit breakeven grows asymmetrically. At losses below -15%, this relationship is nearly linear; at higher levels, the gap grows dramatically. By reducing the “capture ratio” of an investment approach, we can exploit this

The best quant mashup links for the week ending Saturday, 05/14 as voted by our readers: Machine learning for financial prediction: experimentation with Aronson’s latest work – part 2 [Robot Wealth] Deep Learning with Theano – Part 1: Logistic Regression [Quant Start] How To Compute Turnover

The analysis presented below combines two separate frameworks that were previously outlined: Avoiding Bear Markets to Improve Risk-Adjusted Returns The Case for Put Writing / Further Improving PutWrite Performance The first post outlined how avoiding bear markets (by only holding equities when they

I have been trying to use dimensional analysis to understand asset-pricing problems. In many hard physical problems, it is possible to gain some insight about the functional form of the solution by examining the dimensions of the relevant input variables. In the canonical example of this brand of

Remember 52 Pick-Up? A dubious sibling, usually older, would ask if you wanted to play a game while holding a deck of cards. Emphatically, you agree, only to be showered with the deck of playing cards and told to pick them up. Wikipedia in its infinite wisdom defines 52 pick up as "a game of

Value investing is an investment philosophy that has been extensively discussed and examined at least since the days of Ben Graham, who popularized it as a discipline in the 20s and 30s. While there are some who are dismissive of its advantages as a long-term strategy, the historical evidence is

Over the last ten years the subject of deep learning has been one of the most discussed fields in machine learning and artificial intelligence. It has produced state-of-the-art results in areas as diverse as computer vision, image recognition, natural language processing and speech recognition.

In exploratory data analysis, we often need to visualize our data in different formats, in order to gain more understanding about the numbers and the relationship between the parameters. One such wonderful and informative representation is the ‘Heatmap’, which is basically a colored image, the