Loss aversion means that people are more sensitive to losses than to gains. This asymmetry is backed by ample experimental evidence. Loss aversion is not the same as risk aversion, because the aversion is disproportionate towards drawdowns below a threshold. Importantly, loss aversion implies that

Many investment strategies use the mean like an official parameter. However, this estimator can be considered non-robust, being easily affected by outliers. But if we take a look at almost any financial series, we will notice that outliers may appear more often than we might think. Introduction In

Consistent with misapprehensions expressed during other recent market crises, there has been a chorus of alarmist speculation about the actions and state of risk-parity strategies during the current crash. We felt it would be helpful to revisit the concept of risk parity and take a snapshot of how a

What are the Research Questions? Planning for the expenditures needed to fund a successful retirement is one of the most important tasks individuals face, and it’s not an easy one. In fact, it is pretty common (and smart) for some investors to turn to a professional advisor to help guide them

The last few weeks have been some of the toughest in recent memory for investors, as we have observed an intense global market selloff that began in late February and continued into early March of 2020 (as of the writing of this report). Equity markets have experienced the steepest losses since

This is the article we had prepared around 1-2 weeks ago (data sample starts in October 2014 and ends on 4th of March 2020). But then coronavirus hit our country (Slovak Republic), and we were doing a lot of crisis management tasks and therefore were not able to publish it on time. Now, after the

Developer: Etienne Botes and Douglas Siepman. Source: The Vortex Indicator. Stocks & Commodities, January 2010. Concept: Momentum trading strategy based on Vortex Indicator. Research Goal: Performance verification of momentum signals. Specification: Table 1. Results: Figure 1-2. Trade Setup:

Hard currency emerging market debt outperformed local currency EM debt since 2013 EM government and corporate debt traded comparably Adding EM debt to a traditional US equity-bond portfolio would have generated only marginal benefits INTRODUCTION Forecasting the short-term outlook for the S&P

In his article in the S&C April 2020 issue, Vitali Apirine proposed a modified On Balance Volume indicator (OBVM). The hope was that OBVM crossovers and divergences make great trade signals, especially for stock indices. I got the job to put that to the test. The original OBV indicator was

I know this topic is addressed on a very regular basis on the web but I’m pretty sure sharing my experience will help some finance people. I’m currently working on Limit Order Book modeling. This means dealing with fairly big data sets. I have around 1 million observations per stock and per day.

Back in the rebalancing saddle! In our last post on rebalancing, we analyzed whether rebalancing over different periods would have any effect on mean or risk-adjusted returns for our three (equal, naive, and risky) portfolios. We found little evidence that returns were much different whether we

If an investor would state today that in ten or twenty years most portfolios would include an allocation to cryptocurrencies, they would likely be laughed at. However, a similar response would have been encountered in the Internet Bubble and someone proposed to invest in low-risk stocks. During that

Broadly speaking, Tactical Asset Allocation has weathered this storm reasonably well, but the last two days have been tough and we are by no means out of the woods. We track 50+ published TAA strategies, allowing us to draw some broad conclusions about TAA as a style. In the table below we show the

The vector autoregression (VAR) framework is common in econometrics for modelling correlated variables with bi-directional relationships and feedback loops. If you google “vector autoregression” you’ll find all sorts of academic papers related to modelling the effects of monetary and fiscal

The volume of work that has been done on insider transactions is not inconsequential, we’ve covered a variety of research on the topic in several blog posts just a few of which are here and here. This is the first time we observe corporate insider’s ability to overcome biases as an indicator of

Using strategy diversification is one of the easiest ways to improve the performance and reduce risk of your overall portfolio. Trading one strategy is risky because you never know when it may stop working or simply go into a period of under-performance. Given two strategies to trade, the questions

In this article, the author argues that alternative risk premia (ARP) strategies undergo an evolution that begins with their inception as a pure alpha -based strategy, continuing its metamorphosis into a pure beta strategy. The inevitable transformation is brought on by a number of factors and also

Most trading systems utilize indicators as a method of trading strategy design. But before building a trading system using indicators one should ask what do they indicate? The answer to that is that most of the time they are not indicating any information that can be advantageous in building a

We’ve fielded a lot of questions this morning about how Tactical Asset Allocation is faring this month. We track 50+ published strategies, so we’re able to draw some broad conclusions about the current state of TAA. Generally speaking, all is well. Individual strategies vary, but as a whole, TAA

In the last blog, we examined the steps to train and optimize a classification model in scikit learn. In this blog, we bring our focus to linear regression models. We will discuss the concept of regularization, its examples(Ridge, Lasso and Elastic Net regularizations) and how they can be

During the week of February 23rd, the S&P 500 fell more than 10%. After a prolonged bullish period in equities, this tumultuous decline caused many trend-following signals to turn negative. As we would expect, short-term signals across a variety of models turned negative. However, we also saw

SPX futures are locked limit down 5% as I write this Sunday night. The small study below looks at all other times 1) SPY was already short-term oversold (closed at a 5-day low), and 2) gapped down at least 3%, and 3) opened below the lowest close of the previous 50 days. Below is the full list of

Misinformation is everywhere. Many people believe the key to successful short selling is simply the inversion of a successful long strategy. I also used to believe this, among other short selling myths before I took the Short Selling Course by Laurent Bernut ( This article will demonstrate the

Efficient market theory assumes that all market prices incorporate all information at the same time. Realistically, different market segments focus on different news flows, depending on the nature of the traded security and their research capacity. Such specialization makes it plausible that lagged

Welcome to the second installment of our new series on generating wealth, preserving it, and then looking at a real-world illustration of strategically implementing these concepts. In our first essay, we discussed generating riches through a high-paying career, investing in public and private

In my role as chief research officer for the Buckingham Family of Financial Services, I receive many questions from investors and advisors alike, asking me to address concerns they have that originate from articles they have read or statements they hear on the financial media. I thought it worth

This is the second of three posts aimed at answering three fundamental questions in trading: How should we control risk (previous post) How much risk should we take? (this post) How fast should we trade? (TBC) These questions are extremely important, IMHO much more important than the question of

The coronavirus that’s roiling world markets and raising questions about the economic outlook has triggered a familiar shock to stocks: higher volatility. Is this a reason to change your asset allocation, rebalance the portfolio or modify risk management decisions? Maybe, but maybe not. There is

Way back in November 2007, literally weeks after SPX put in its pre-GFC all-time high, Friedman, Hastie and Tibshirani published their Graphical Lasso algorithm for estimation of the sparse inverse covariance matrix. Are you suggesting that Friedman and his titans of statistical learning somehow

The last few months got me busy like a bee... It all started in 2016 with the release of QTPyLib. I was trying to shorten the time it takes to go from an idea to live trading by abstracting all the techie stuff as much as possible (while still allowing flexibility for developers). Last year I shared

We’re taking a break from our series on portfolio construction for two reasons: life and the recent market sell-off. Life got in the way of focusing on the next couple of posts on rebalancing. And given the market sell-off we were too busy gamma hedging our convexity exposure, looking for cheap

This is one of my favorite takes of the last week. It was tweeted on Friday, which held two distinctions: (1) It capped off a helluva scary week, and (2) It just so happened to be month-end, when many TAA strategies trade by default. I couldn’t agree more. Imagine making a single risk on/risk off

Private and public companies face direct costs related to three types of climate risks: physical (i.e. extreme weather), regulatory (i.e. policies and regulations implemented to combat climate change), and technological (i.e. electric or fuel-cell-powered vehicles could disrupt traditional car

Given the increasing drawdown in the market, it seems prudent to revisit the notion of volatility vs risk. See original post here. 1) To recap, in case you just got back from a 10 day silent mediation retreat, S&P500 peaked on Feb 19th 2020, and has been in pretty much a free-fall since then,

Prior academic and practitioner research suggests that factor-based fixed income investing can create attractive return profiles and be useful when building fixed income portfolios. Using an investment universe of eight domestic fixed income asset classes, we build dollar-neutral long-short

ESG and Low Carbon portfolios feature significant, but different sector & country biases Investors should expect large tracking errors in some ETFs Some products contain stocks that are likely unexpected and undesired INTRODUCTION Investors seeking exposure to global equities with a low carbon

In February 2019, Wes asked that I share my research on what I call the “Smart Money Indicator.” I did a guest post on the subject that summarized the results of a paper introducing my research on the topic. The indicator measures the relative sentiment in equities between institutional

Hi Guys! I’m happy to kick off a new series of free video lectures devoted to Python’s library of pandas. Every week, I will be uploading something between 2 to 4 new videos especially crafted around practicalities of pandas library applied to financial data and their analysis and processing.

A Springbok antelope can reach a top speed of 55 miles per hour in the African savanna, whereas the fastest human manages barely half that speed and only for a few meters. In a short race, we are left in the dust. However, we are built for endurance and can run for hours at an almost constant speed,

When this sell-off indicator triggers, it is correct 100% of the time! On average the market is up only 2.6% in 3 months. OR NOT! After big moves in the market, we often see “research” saying that “when the market has done X it will move Y%.” I had a reader send me such research asking for

Get 15% off tickets to the next Quant Conference with the promo code QUANTOCRACY15. The Quant Conference is a forum that engages the brightest young minds and foremost thought leaders from the industry and academia to dive into the latest innovations in quant finance, foster collaboration and

I have always been curious about how deep learning frameworks are created. I use Keras, TensorFlow, and PyTorch and they all are really good, but sometimes I feel like I am playing with a black box (in some frameworks I feel it more than in others) that hides its secrets. If you feel the same way,

Well, that was painful. The increasingly hazy risk outlook linked to the coronavirus outbreak inspired a 3.35% haircut in the US stock market (S&P 500). The tumble was certainly a bracing counterpoint to the idea that sunny optimism is the only game in town. But before we let recency bias flip

What are the research questions? Although not a new topic, the first half of the article explored and documented the dependent relationship between factor returns and time-varying macroeconomic environments. In the second half of this paper, the authors provide insightful commentary and a renewed

When you are completely immersed in wanting to learn something new, you start looking for everything that surrounds the learning process. And with the aspiration to learn Algorithmic Trading, there must be certain questions crowding your mind, like: How do I learn Algorithmic Trading? What are the

While rebalancing studies typically focus on the combination of different asset classes, we evaluate a combination of two naïve trend-following strategies. As expected, we find that a rebalanced fixed-mix of the two strategies generates a concave payoff profile. More interestingly, deriving the

With corona virus news scaring the market pre-open today, I decided to look back at other time SPY has gapped down more than 2% when it had been in a long-term uptrend. As you might suspect, instances have been fairly rare. Looking ack to SPY inception, there were only 16 other instances. And upping

“The complexity of machine learning models presents a substantial barrier to their adoption for many investors. The algorithms that generate machine learning predictions are sometimes regarded as a black box and demand interpretation. Yimou Li, David Turkington, and Alireza Yazdani present a

Since predicting the future stock prices in the stock market is crucial for the investors, Time Series and its related concepts help in organizing the data for accurate prediction. In this article, we are focusing on Time Series, its analysis and forecasting. In this article, we aim to cover the

In our last post, we introduced benchmarking as a way to analyze our hero’s investment results apart from comparing it to alternate weightings or Sharpe ratios. In this case, the benchmark was meant to capture the returns available to a global aggregate of investable risk assets. If you could own