Predicting realized volatility is critical for trading signals and position calibration. Econometric models, such as GARCH and HAR, forecast future volatility based on past returns in a fairly intuitive and transparent way. However, recurrent neural networks have become a serious competitor. Neural

News have a huge impact in the global stock market, but it’s impossible even for professionals to be constantly updated. One can ask itself: is there any way to automate this procedure? Recently in this blog we have covered the topic of summarizing news by applying the TF-IDF algorithm, which is a

One of the big problems for the first formal asset pricing model developed by financial economists, the CAPM, was that it predicts a positive relationship between risk and return. However, empirical studies have found the actual relationship to be basically flat, or even negative. In addition,

In last night’s subscriber letter I showed a few studies suggesting the market was short-term overbought in a long-term downtrend, and that there appeared to be a short-term downside edge. Below is one of those studies, which also appeared in the Quantifinder yesterday afternoon.

Performance of Gold as a Financial Asset During Different Phases of Financial Cycles Aniket Ranjan and Naveen Kumar (Reserve Bank of India) January 2022 The paper examines the fundamental relationship between gold and financial markets within the framework of unobserved components model. It measures

Indisputably, trend-following and mean-reversion are two key concepts in quantitative investing or technical analysis. The trend-following proponents suggest a performance continuation and that assets that have performed well will continue to do so. In other words, the trend-following strategies are

I recently saw some chatter about a technical paper discussing the contrast between overnight and intraday stock returns. In the paper, we learn that overnight stock returns far outpace returns seen intraday during regular trading hours. In other words, stocks move the most when markets are not

In my previous post I discussed about trading overnight, since there was a clear edge holding the SPY over night. But due to small mistake that I made in my testing the results were bad and the edge disappeared. The mistake was setting commissions as 0.05 $ per share instead of 0.005$ per share.

Risk management overlays tend to reduce stock market returns However, they also can reduce drawdowns and increase Sharpe ratios Given that diversification has become more difficult, these are becoming more relevant INTRODUCTION It is tough to have high return expectations for stocks for the coming

Who among us wouldn’t want to be the savior that predicts a market crisis and saves our clients from losses in capital — or even better — profits from them? A central topic of interest for academics is whether there are more precise tools to predict financial crises. Those who believe so

Academic research has found that factor premiums are both time-varying and dependent on the economic cycle. For example, the authors of the 2017 study “Fama-French Factors and Business Cycles” examined the behavior of six Fama-French factors—market beta (MKT), size (SMB), value (HML), momentum

The Russia-Ukraine war is a conflict that has not been in Europe since WW2. And it has great implications not only on human lives but also on security prices. It bears numerous characteristics of the cold war crises, where two nuclear powers (Soviet Union and USA/NATO) were often very close to hot

How well do quantitative investors navigate around the changes to the accounting standards that are endemic to the financial data used in quantitative strategies? The numbers reported on financial statements are wholly governed by regulation and by each firm’s interpretation of those accounting

A demon comes to you one night giving you a simple dice game to play. You're offered the chance to wager your wealth and receive a 50% increase if you roll a 6, 5% bump if you roll 2-5, or lose 50% if you roll a 1. You also get 300 rolls and get to compound your wealth with each roll of the

The average correlation between oil and oil ETFs was only 0.8 Gold ETFs provide better exposure to gold than oil ETFs to oil Gold mining stocks are hybrids that feature gold and equity beta INTRODUCTION As the war in Russia unfolded, crude oil (WTI) breached $100 per barrel, which was last seen in

Bittrex API is a method that allows us to automatically trade cryptocurrencies on Bittrex via code. What is Bittrex? Bittrex is an online cryptocurrency exchange platform that allows its users to trade over 700 trading pairs. As one of the oldest US-based exchanges, Bittrex is known for its

In a previous Mathematical Investor blog, we presented data on actively managed fund versus passive fund performance over various time horizons, based on the February 2019 Morningstar Active-Passive Barometer report. These data showed, for instance, that only 12.6% of actively managed U.S. large

Systemic crises are rare but critical for long-term performance records. When the financial system fails, good trades become bad trades and many sensible investment strategies incur outsized losses due to deleveraging and liquidation pressure. Managers have two principal sets of tools to address

As mind-bending as it sounds, although a company’s internally generated intangible investments generate future value, they are currently not accepted as assets under US GAAP. Omission of this increasingly important class of assets reduces the usefulness and relevance of financial statement

In the previous article we installed Python and set up our virtual environment. We then used pandas-datareader directly in the python terminal in order to import some equities OHLC data and plot five years of the adjusted close price. This was accomplished in a few lines of code. However, once we

It always feels a little offensive talking dollars and cents at times like this (*), but we hope that by helping investors to have a concrete strategy, we can at least take this one stress off the table. We track 60+ Tactical Asset Allocation (TAA) strategies, allowing us to draw some broad

Very brief blog post this month; I'm deep into book writing mode at the moment. Chanelling Clif Assness, I'm just going to present a few charts and lead you to draw your own conclusions. Excess / futures returns from portfolio of 60% S&P 500, 40% US Ten year treasuries (Authors own

Long-short momentum investing highlights attractive performance in Asia and emerging markets However, realized excess returns are significantly lower than theoretical ones Likely explained by transaction costs INTRODUCTION Momentum has been shown to generate attractive excess returns across eight

There’s a reason that international traders, whether they’re in Tokyo, Singapore, or London, follow the US markets. The US is the hub of global finance. It’s on Wall Street where everything is happening. Watching the reaction of European markets to the opening of US markets demonstrates this.

Most investors focus solely on the profitability of their investment strategy. And, even though having a profitable strategy is important, it is not everything. There are still numerous other things to consider. One of them is the size of the investment. The investment size can increase or decrease

As I am sure all of you know Russia has began a full scale war against my home country Ukraine. Please make no mistake - Putin's goal in not to stop the expansion of NATO, not to install puppet government, and certainly not to bring peace. The goal is genocide of Ukrainian people. When Ukraine

Holding stocks overnight is when we buy the close and sell the following day on the open. Is there any edge in this approach in comparison to buying the open and selling the close. Today we will check this phenomenon. We will check the performance of the SPY, then we will try to check it on

I am delighted to share the video from my QuantMinds presentation that I made in Barcelona in December 2021. Many thanks to QuantMinds organizers for allowing me to share this video. First, it was nice to attend the onsite conference in a while and to meet old friends and colleagues. I was

Delta hedging is a trading strategy that aims to reduce the directional risk of short option strategy and reach a so-called delta-neutral position. It does so by buying or selling small increments of the underlying asset. Similarly, grid trading is a trading strategy that buys/sells an asset

I am excited to share the latest paper with Prof. Alexander Lipton. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4035813 We find the semi-analytical solution to one of the unsolved problems in Quantitative Finance, which is to compute survival probabilities and barrier option values for

Diversification has been around since the early 1950s and is often considered a “free lunch” in finance. But is that actually the case? We’ve highlighted here and here that the reality is more complicated than the theory. Consider the two basic assumptions about correlations in the context of

Incorporating market expectations and forecasts into asset allocation used to be more of an art than an analytical process in the 80s. In this post we will review Fisher Black’s elegant and very practical solution to portfolio construction, going through a sector allocation example. The Black

At Quantpedia, we love seasonality effects, and our screener includes several strategies that exploit them. These anomalies are fascinating since they usually offer a favorable risk and reward ratio and are commonly invested only during short periods. Frequently, these strategies are valuable

From 1991 to 2018, capital expenditures as a percentage of total sales remained relatively flat, at about 10 percent. On the other hand, personnel expenses almost doubled during that time. In fact, by 2018 personnel expenses (the costs for hiring, wages, salaries, and bonuses; social security and

I’ve been writing this blog for nine years now. Sometimes I am amazed about topics I have not covered and this is one of them. When developing a new strategy, these are the indicators I likely test: RSI, Historical Volatility and Internal Bar Strength (IBS). I had a reader send me an email

Previous articles in this series examine, from a digital signal processing (DSP) frequency domain perspective, various types of digital filters used by quantitative analysts and market technicians to analyze and transform financial time series for trend-following purposes. An Introduction to Digital

The Fisher Transform converts data to or from a Gaussian distribution. It was first used in algorithmic trading by John Ehlers (1) , and became a common part of indicators since then. In a TASC January 2022 article, Ehlers described a new indicator, the Elegant Oscillator, based on the Inverse

Passive investing enjoys substantial popularity and subsequently attracts the attention of researchers. We blogged about the boom of passive investing and market inelasticity in the past. However, the novel research by Li (2021) examines a different perspective. With the boom of passive investing,

When reading Denev’s book Probabilistic Graphical Models – A New Way of Thinking in Financial Modelling, commented on my blog back in Summer 2020, I put a note in my todo list to model Matalan probability of default using a Bayesian network (for fun, not work). I was rather familiar with this

Financial Cycles – Early Warning Indicators of Banking Crises? Sally Chen (Bank for Int’l Settlements) and Katsiaryna Svirydzenka (IMF) April 2021 Can the upturns and downturns in financial variables serve as early warning indicators of banking crises? Using data from 59 advanced and emerging

Factor investors face numerous choices that do not end even after picking the set of factors. For instance, should they neutralize the factor exposure? If the investor pursues sector neutralization, does the decision depend on a particular factor? Or are the choices different for the long-only

The question of whether or not the FED considers or responds to the stock market in its policy decisions has been studied fairly extensively, however, the subject of the existence of the “FED put” continues to pop up in the literature. In this particular revival of the issue, the authors are

Smart money, crowd intelligence, and AI ETFs have underperformed the S&P 500 since their inception Somewhat surprisingly, all three have almost the same factor exposures Negative exposure to value, and positive exposure to size and momentum factors INTRODUCTION Welcome to the qualifying round of

The Ulcer Performance Index1 (UPI) is a portfolio reward-risk measure introduced by G. Martin2 similar in spirit to the Sharpe Ratio, but using the Ulcer Index (UI) as a risk measure instead of the standard deviation. In this blog post, I will present the mathematics behind the Ulcer Performance

The performance of a portfolio during a single period can be attributed to a set of factors, but in order to aggregate those daily factors and get a breakdown of the portfolio’s total performance during a multi-period (for example 1Y), we have to make use of an smoothing algorithm. This is due to

From 2017 through March 2020, the relative performance of value stocks in the U.S. was so poor, experiencing its largest drawdown in history, that many investors jumped to the conclusion that the value premium was dead. It is certainly possible that what economists call a “regime change” could

This is a short follow up post to one I did a couple of years ago, on "Exogenous risk management". This was quite an interesting post which dug into why expected risk changes for a typical diversified futures trading system. And then I introduced my risk overlay: "Now we have a better

In several articles on this site (see, for instance, A and B), we have commented on the dangers of backtest overfitting in finance. By backtest overfitting, we mean the usage of historical market data to develop an investment model, strategy or fund, where many variations are tried on the same fixed

A lot of ink has been spilled on a seemingly simple question: Why does the momentum factor exist? We have done our fair share contributing to the question and our collective conclusions are in our book Quantitative Momentum. We walked away from the question and determined the following: We will

Mid-2020, I read a book on probabilistic graphical models (PGMs) applied in finance by Alexander Denev. Mid-2021, I hosted a machine learning meetup with an application of PGMs to predict the future states of economic and financial variables, and geopolitical events based on forward-looking views