Quantopian is launching a crowd-sourced quant hedge fund that will identify high-performing algorithmic trading strategies on its platform and construct a portfolio combining the best strategies. To select strategies, Quantopian will evaluate strategies based on quantitative metrics like Sharpe ratio, volatility, maximum drawdown and consistency of returns. Strategies will be ranked and a composite "Q score" assigned. The portfolio will be constructed considering cross-strategy correlations and risk exposures. Performance will be rigorously monitored over time. Quantopian aims to attract the best quant talent by maintaining an open community platform and transparent, meritocratic process for inclusion in the fund.
Crowd-sourced Alpha: The Search for the Holy Grail of InvestingQuantopian
It has been said that diversification is the only free lunch. Join Dr. Jess Stauth, vice president of quant strategy at Quantopian, and learn about the criteria we are using to select crowd-sourced algorithms with uncorrelated returns streams to achieve consistent market outperformance.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
Being open (source) in the traditionally secretive field of quant finance.Quantopian
The field of quantitative finance is intensely competitive and maniacally secretive as a rule. The tendency toward secrecy is perhaps unsurprising given that the smallest of competitive advantages can translate to substantial profits. Indeed, over the past decade a growing list of legal prosecutions for alleged code theft or misuse have underscored how high the stakes can be for developers looking to leverage and contribute to open source projects. Notable exceptions to this approach include work from Wes McKinney and Travis Oliphant, whose work on open source projects like pandas and numpy, which have gained widespread adoption. In this talk we will review some of the costs and benefits of engaging with open source as a “two way street” and frame the modern quant workflow as a mosaic of open sourced, third party, and proprietary components.
Case Studies in Creating Quant Models from Large Scale Unstructured Text by S...Quantopian
SEC filings provide a window into the health of the company and are immensely important for investors. Historically, the only feasible way to read and interpret filings has been manually, where domain experts interpret filings and provide guidance to public. However, advances in big data technologies and Natural Language processing have enabled its automation. Sameena will discuss how her team created predictive models from text in filings and social media.
This presentation was part of QuantCon 2015 hosted by Quantopian. Visit us at: www.quantopian.com.
"A Framework-Based Approach to Building Quantitative Trading Systems" by Dr. ...Quantopian
Contrary to popular wisdom the difference between a retail quant trader and a professional portfolio manager is not in "having better trade entry and exit rules". Rather it is the difference in how each approaches the concepts of portfolio optimisation and risk management.
Both of these topics are synonymous with heavy math, which can be off-putting for beginner retail systematic traders. Hence, it can be extremely daunting for those without institutional experience to know how to turn a set of trading rules into a robust portfolio and risk management system.
In this talk, Mike will discuss how to take a typical retail quant strategy and place it in a professional quantitative trading framework, with proper position sizing and risk assessment, without resorting to pages of formulas or the need to have a PhD in statistics!
Self-Directed Investing by Akhil Lodha, Co-founder of Sliced Investing, and M...Quantopian
In an ideal world an investor has access to a range of investment opportunities that allow her to create a Balanced portfolio based on her risk/return objectives. Unfortunately we don't live an in ideal world and a lot of the investment opportunities have only been available to the Institutional Investor. That trend has started to change as technology and innovation by startups like AngelList, Wealthfront, and Sliced Investing, among others are lowering the barrier to access and allowing more individuals to create a balanced portfolio that meets their investment objectives. In this talk we'll focus on the need for a balanced portfolio, the investing tools for the 'new-age' investor and the future of individual investing.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
An introduction to implementing 5 basic quant strategies on Quantopian. Presented to the Bay Area Algorithmic Trading Group and the Bay Area Trading Signals meetup groups at the Hacker Dojo Feb 6th, 2014 by Jess Stauth
Pairs Trading from NYC Algorithmic Trading Meetup November '13Quantopian
Gary Chan presented at the NYC Algorithmic Trading Meetup. More on the presentation, including a sample Excel file, on our blog http://blog.quantopian.com/gary-chan-on-pairs-trading-presentation-from-nyc-algorithmic-trading-meetup/ You can sign up for future meetups here: www.meetup.com/NYC-Algorithmic-Trading/
Algorithmic trading and Machine Learning by Michael Kearns, Professor of Comp...Quantopian
Traditional financial markets have undergone rapid technological change due to increased automation and the introduction of new exchanges and mechanisms. Such changes have brought with them challenging new problems in algorithmic trading, many of which invite a machine learning approach. In this talk, Michael will examine several algorithmic trading problems, focusing on their novel ML aspects, including limiting market impact, dealing with censored data, and incorporating risk considerations.
This presentation was part of QuantCon 2015 hosted by Quantopian. Visit us at: www.quantopian.com.
Crowd-sourced Alpha: The Search for the Holy Grail of InvestingQuantopian
It has been said that diversification is the only free lunch. Join Dr. Jess Stauth, vice president of quant strategy at Quantopian, and learn about the criteria we are using to select crowd-sourced algorithms with uncorrelated returns streams to achieve consistent market outperformance.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
Being open (source) in the traditionally secretive field of quant finance.Quantopian
The field of quantitative finance is intensely competitive and maniacally secretive as a rule. The tendency toward secrecy is perhaps unsurprising given that the smallest of competitive advantages can translate to substantial profits. Indeed, over the past decade a growing list of legal prosecutions for alleged code theft or misuse have underscored how high the stakes can be for developers looking to leverage and contribute to open source projects. Notable exceptions to this approach include work from Wes McKinney and Travis Oliphant, whose work on open source projects like pandas and numpy, which have gained widespread adoption. In this talk we will review some of the costs and benefits of engaging with open source as a “two way street” and frame the modern quant workflow as a mosaic of open sourced, third party, and proprietary components.
Case Studies in Creating Quant Models from Large Scale Unstructured Text by S...Quantopian
SEC filings provide a window into the health of the company and are immensely important for investors. Historically, the only feasible way to read and interpret filings has been manually, where domain experts interpret filings and provide guidance to public. However, advances in big data technologies and Natural Language processing have enabled its automation. Sameena will discuss how her team created predictive models from text in filings and social media.
This presentation was part of QuantCon 2015 hosted by Quantopian. Visit us at: www.quantopian.com.
"A Framework-Based Approach to Building Quantitative Trading Systems" by Dr. ...Quantopian
Contrary to popular wisdom the difference between a retail quant trader and a professional portfolio manager is not in "having better trade entry and exit rules". Rather it is the difference in how each approaches the concepts of portfolio optimisation and risk management.
Both of these topics are synonymous with heavy math, which can be off-putting for beginner retail systematic traders. Hence, it can be extremely daunting for those without institutional experience to know how to turn a set of trading rules into a robust portfolio and risk management system.
In this talk, Mike will discuss how to take a typical retail quant strategy and place it in a professional quantitative trading framework, with proper position sizing and risk assessment, without resorting to pages of formulas or the need to have a PhD in statistics!
Self-Directed Investing by Akhil Lodha, Co-founder of Sliced Investing, and M...Quantopian
In an ideal world an investor has access to a range of investment opportunities that allow her to create a Balanced portfolio based on her risk/return objectives. Unfortunately we don't live an in ideal world and a lot of the investment opportunities have only been available to the Institutional Investor. That trend has started to change as technology and innovation by startups like AngelList, Wealthfront, and Sliced Investing, among others are lowering the barrier to access and allowing more individuals to create a balanced portfolio that meets their investment objectives. In this talk we'll focus on the need for a balanced portfolio, the investing tools for the 'new-age' investor and the future of individual investing.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
An introduction to implementing 5 basic quant strategies on Quantopian. Presented to the Bay Area Algorithmic Trading Group and the Bay Area Trading Signals meetup groups at the Hacker Dojo Feb 6th, 2014 by Jess Stauth
Pairs Trading from NYC Algorithmic Trading Meetup November '13Quantopian
Gary Chan presented at the NYC Algorithmic Trading Meetup. More on the presentation, including a sample Excel file, on our blog http://blog.quantopian.com/gary-chan-on-pairs-trading-presentation-from-nyc-algorithmic-trading-meetup/ You can sign up for future meetups here: www.meetup.com/NYC-Algorithmic-Trading/
Algorithmic trading and Machine Learning by Michael Kearns, Professor of Comp...Quantopian
Traditional financial markets have undergone rapid technological change due to increased automation and the introduction of new exchanges and mechanisms. Such changes have brought with them challenging new problems in algorithmic trading, many of which invite a machine learning approach. In this talk, Michael will examine several algorithmic trading problems, focusing on their novel ML aspects, including limiting market impact, dealing with censored data, and incorporating risk considerations.
This presentation was part of QuantCon 2015 hosted by Quantopian. Visit us at: www.quantopian.com.
Stauth common pitfalls_stock_market_modeling_pqtc_fall2018Quantopian
Data Modeling the Stock Market Today - Common Pitfalls to Avoid
The lure of creating models to predict the stock market has drawn talent from fields beyond finance and economics, reaching into disciplines such as physics, computational chemistry, applied mathematics, electrical engineering and perhaps most recently statistics and what we now refer to as data science. The attraction is clear - the stock market (and the economy/internet at large) throws off massive and ever increasing reams of data from garden variety time-series to complex structured data sets like quarterly financials, to unstructured data sets like conference call transcripts, news articles and of course — tweets! While all this data holds promise - it also holds traps and blind alleys that can be deceptively tricky to avoid. In this session we’ll review some of the common (but not easy!) pitfalls to avoid in creating models for predicting stock returns; overfitting & exploding model complexity, non-stationary processes, time-travel illusions, under-estimation of real-world costs, and as many more as we have time to cover.
Algorithmic Finance Meetup: Starmine Short Interest Talk Quantopian
With the commoditization of such basic quant factors as value and momentum, in recent years systematic investors have turned more and more to sentiment based alpha signals. Aggregated open short interest level provides a profitable, low turnover signal rooted in buy-side sentiment, aka "the smart money." Dr. Stauth will cover the basics of short selling and data availability and will review the research and proprietary formulation of the StarMine short interest model as well as covering a range of sample trading strategies.
"Snake Oil, Swamp Land, and Factor-Based Investing" by Gary Antonacci, author...Quantopian
BlackRock forecasts smart beta investing oriented toward size, value, quality, momentum, and low volatility to reach $1 trillion by 2020 and $2.4 trillion by 2025. Gary’s talk will show that this growth may not be justified due to these factors' lack of robustness, consistency, persistence, intuitiveness, and investability. Gary will also show that the success attributed to these factors would be better directed toward macro momentum and the short interest ratio.
"From Trading Strategy to Becoming an Industry Professional – How to Break in...Quantopian
You have created a great trading strategy, backtested, traded it and now you want to take it to the next level. You may find that developing the strategy was just the first of many difficult steps.
With the increased availability of low cost, high quality quant modelling platforms, the field is much more open than it once was. The interest for algorithmic trading his higher than ever and anyone has the potential develop a great trading model.
But having a great trading model is not enough. The work is not done yet.
This presentation will discuss turning your algorithmic trading strategy into a business or a great job, and becoming a professional trader. We’re going to talk about what it takes to move to the next level and where the common pitfalls lay. What kind of strategies are marketable are which are not. The pros and cons of trading your own money and how to go about finding external capital and gaining traction in the business.
Are you ready to take the step?
Finding Alpha from Stock Buyback Announcements in the Quantopian Research Pla...Quantopian
Stock buybacks are at record levels and several studies have established windows of alpha opportunity around stock buyback announcements. In this talk EventVestor founder Anju Marempudi and Quantopian client engineer Seong Lee will discuss buyback trends, analyzing share buybacks data for insights, conducting an event study to measure excess returns around buyback announcements, and finally building a trading algorithm with back-testing using the Quantopian Research platform.
This presentation was part of the QuantCon 2015 Conference hosted by Quantopian. Visit us at: www.quantopian.com.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
Overview of Quantopian: where we are and where we are headed.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
"Build Effective Risk Management on Top of Your Trading Strategy" by Danielle...Quantopian
Presented at QuantCon Singapore 2016, Quantopian's quantitative finance and algorithmic trading conference, November 11th.
Risk management is an essential but often overlooked prerequisite to success in trading. No one would like to see their substantial profits generated over his lifetime of trading just vanishing over a few bad trades.
In this talk, Danielle will discuss a quantitative understanding of risk. She will then share a few techniques in risk management, with a case study to show how a proper risk management system helps improve the overall performance of trading strategies.
"Quant Trading for a Living – Lessons from a Life in the Trenches" by Andreas...Quantopian
It takes hard work, skill and time to develop robust trading models, but that is just the beginning of the journey. The question then is what you can do with it, and how to go about building a career in quant finance.
If your plan is to move beyond hobby trading and build a career in in the professional quant trading field, the work is not over once you have a great model.
This presentation will discuss how to leverage your trading models into building a successful career in quant trading. We will look at the various options available, and their respective merits and faults. Whether you want to trade your own money for a living, find a job in the industry or build your own business, your model design will have to be adapted to your aim. We will discuss what type of models and results there is a market for, how to go about finding investors for your trading, and how the real economics of the business look.
Taking on Wall Street: A Comparative Study of Strategies Sourced from "The Pr...Quantopian
A unique set of data comprised of strategy returns sourced through traditional means from managers (“the pros”) and from strategies developed on Quantopian’s platform (“the crowd”) is analyzed. We detect distinct groups of strategy styles within the data: In particular, some "crowd" strategies fall into their own clusters distinct from those within the "pro" data set. A few do overlap as well. We go on to analyze the various strategy groups with respect to environmental conditions and risk factors (among other relevant features), teasing out differences in trading styles.
Ultimately we judge how well “the crowd” is doing so far, in terms of being able to compete with the established managers not only in terms of performance but also with respect to risk management and overall novelty and diversification in the trading styles that have emerged. Finally we address general notions (and pitfalls) of building meta strategies from manager return streams.
This presentation was part of QuantCon 2015 hosted by Quantopian. Visit us at: www.quantopian.com.
Should You Build Your Own Backtester? by Michael Halls-Moore at QuantCon 2016Quantopian
The huge uptake of Python and R as first-class programming languages within quantitative trading has lead to an abundance of backtesting libraries becoming widely available. It can take months, if not years, to develop a robust backtesting and trading infrastructure from scratch and many of the vendors (both commercial and open source) have a huge head start. Given such prevalence and maturity of the available software, as well as the time investment needed for development, is there any benefit to building your own?
In this talk, Mike will argue the advantages and disadvantages of building your own infrastructure, how to develop and improve your first backtesting system and how to make it robust to internal and external risk events. The talk will be of interest whether you are a retail quant trader managing your own capital or are forming a start-up quant fund with initial seed funding.
"I’ve never seen a bad backtest” — Dimitris Melas, head of research at MSCI. Quantitative Analysts rely heavily on backtests as a means of validating their trading strategies. All too often, strategies look great in simulation but fail to live up to their promise in live trading. There are a number of reasons for these failures, some of which are beyond the control of a quant developer. But other failures are caused by common but insidious mistakes. In this talk I’ll review a list of 10 pitfalls in strategy development and testing that can result in optimistic backtests. I’ll also present methods for detecting and avoiding them. This talk will be of interest to quant developers and also non-quants who are interested to know what to look out for when presented with remarkably successful backtests.
This presentation was part of the QuantCon 2015 Conference hosted by Quantopian. Visit us at: www.quantopian.com.
Book presentation: Excess Returns: a comparative study of the methods of the ...Frederik Vanhaverbeke
This is a pdf presentation of the book Excess Returns: a comparative study of the methods of the world's greatest investors. The presentation explains the various topics that are discussed in the book and show plenty of practical examples to understand the main points. It challenges the Efficient Market Hypothesis by showing some extraordinary track records in the investment world. It explains where top investors look for bargains. It shows how they perform a due diligence and how they value stocks. A separate section is devoted to the way top investors buy and sell various types of stocks, and how they buy and sell over stock market cycles. It also explains the various psychological aspects that top investors deem essential to beat the market.
Modeling the Stock Market: Common pitfalls and how to avoid them!Jess Stauth
The lure of creating models to predict the stock market has drawn talent from fields beyond finance and economics, reaching into disciplines such as physics, computational chemistry, applied mathematics, electrical engineering and perhaps most recently statistics and what we now refer to as data science. The attraction is clear - the stock market (and the economy/internet at large) throws off massive and ever increasing reams of data from garden variety time-series to complex structured data sets like quarterly financials, to unstructured data sets like conference call transcripts, news articles and of course — tweets! While all this data holds promise - it also holds traps and blind alleys that can be tricky to avoid. In this session we’ll review some of the common (but not easy!) pitfalls to avoid in creating models for predicting stock returns; overfitting & exploding model complexity, non-stationary processes, time-travel illusions, and under-estimation of real-world costs.
Data Driven Product Management - ProductTank Boston Feb '14Quantopian
Practical Ideas and Tools PMs Can And Should Use to Make Decisions
Talk given at Boston ProductTank Meetup. http://www.meetup.com/ProductTank-Boston/events/165579612/
Trade Like a Chimp: Unleash Your Inner Primate by Andreas Clenow at QuantCon ...Quantopian
It is a long established fact that a reasonably well behaved chimp throwing darts at a list of stocks can outperform most professional asset managers. It is less known why this is the case. While there would be obvious advantages with hiring chimps over hedge fund traders, such as lower salaries and calmer tempers, there are also a few practical obstacles to such hiring practices. For those asset management firms unable to retain the services of a cooperative primate, a random number generator may serve as a reasonable approximation of their skills.
The fact of the matter is that even a random number generator can, and will, outperform practically all mutual funds. Such random strategies may seem like a joke, and perhaps they are, but if a joke can outperform industry professionals we have to stop and ask some hard questions.
When designing investment strategies, it can be very useful to have an understanding of random strategies, how they work and what kind of results they are likely to yield. Given that random strategies perform quite well over time, they can act as a valid benchmark. After all, if your own investment approach fails to outperform a random strategy, you may as well outsource your quant modeling to the Bronx Zoo.
Stauth common pitfalls_stock_market_modeling_pqtc_fall2018Quantopian
Data Modeling the Stock Market Today - Common Pitfalls to Avoid
The lure of creating models to predict the stock market has drawn talent from fields beyond finance and economics, reaching into disciplines such as physics, computational chemistry, applied mathematics, electrical engineering and perhaps most recently statistics and what we now refer to as data science. The attraction is clear - the stock market (and the economy/internet at large) throws off massive and ever increasing reams of data from garden variety time-series to complex structured data sets like quarterly financials, to unstructured data sets like conference call transcripts, news articles and of course — tweets! While all this data holds promise - it also holds traps and blind alleys that can be deceptively tricky to avoid. In this session we’ll review some of the common (but not easy!) pitfalls to avoid in creating models for predicting stock returns; overfitting & exploding model complexity, non-stationary processes, time-travel illusions, under-estimation of real-world costs, and as many more as we have time to cover.
Algorithmic Finance Meetup: Starmine Short Interest Talk Quantopian
With the commoditization of such basic quant factors as value and momentum, in recent years systematic investors have turned more and more to sentiment based alpha signals. Aggregated open short interest level provides a profitable, low turnover signal rooted in buy-side sentiment, aka "the smart money." Dr. Stauth will cover the basics of short selling and data availability and will review the research and proprietary formulation of the StarMine short interest model as well as covering a range of sample trading strategies.
"Snake Oil, Swamp Land, and Factor-Based Investing" by Gary Antonacci, author...Quantopian
BlackRock forecasts smart beta investing oriented toward size, value, quality, momentum, and low volatility to reach $1 trillion by 2020 and $2.4 trillion by 2025. Gary’s talk will show that this growth may not be justified due to these factors' lack of robustness, consistency, persistence, intuitiveness, and investability. Gary will also show that the success attributed to these factors would be better directed toward macro momentum and the short interest ratio.
"From Trading Strategy to Becoming an Industry Professional – How to Break in...Quantopian
You have created a great trading strategy, backtested, traded it and now you want to take it to the next level. You may find that developing the strategy was just the first of many difficult steps.
With the increased availability of low cost, high quality quant modelling platforms, the field is much more open than it once was. The interest for algorithmic trading his higher than ever and anyone has the potential develop a great trading model.
But having a great trading model is not enough. The work is not done yet.
This presentation will discuss turning your algorithmic trading strategy into a business or a great job, and becoming a professional trader. We’re going to talk about what it takes to move to the next level and where the common pitfalls lay. What kind of strategies are marketable are which are not. The pros and cons of trading your own money and how to go about finding external capital and gaining traction in the business.
Are you ready to take the step?
Finding Alpha from Stock Buyback Announcements in the Quantopian Research Pla...Quantopian
Stock buybacks are at record levels and several studies have established windows of alpha opportunity around stock buyback announcements. In this talk EventVestor founder Anju Marempudi and Quantopian client engineer Seong Lee will discuss buyback trends, analyzing share buybacks data for insights, conducting an event study to measure excess returns around buyback announcements, and finally building a trading algorithm with back-testing using the Quantopian Research platform.
This presentation was part of the QuantCon 2015 Conference hosted by Quantopian. Visit us at: www.quantopian.com.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
Overview of Quantopian: where we are and where we are headed.
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.
More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.
In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.
"Build Effective Risk Management on Top of Your Trading Strategy" by Danielle...Quantopian
Presented at QuantCon Singapore 2016, Quantopian's quantitative finance and algorithmic trading conference, November 11th.
Risk management is an essential but often overlooked prerequisite to success in trading. No one would like to see their substantial profits generated over his lifetime of trading just vanishing over a few bad trades.
In this talk, Danielle will discuss a quantitative understanding of risk. She will then share a few techniques in risk management, with a case study to show how a proper risk management system helps improve the overall performance of trading strategies.
"Quant Trading for a Living – Lessons from a Life in the Trenches" by Andreas...Quantopian
It takes hard work, skill and time to develop robust trading models, but that is just the beginning of the journey. The question then is what you can do with it, and how to go about building a career in quant finance.
If your plan is to move beyond hobby trading and build a career in in the professional quant trading field, the work is not over once you have a great model.
This presentation will discuss how to leverage your trading models into building a successful career in quant trading. We will look at the various options available, and their respective merits and faults. Whether you want to trade your own money for a living, find a job in the industry or build your own business, your model design will have to be adapted to your aim. We will discuss what type of models and results there is a market for, how to go about finding investors for your trading, and how the real economics of the business look.
Taking on Wall Street: A Comparative Study of Strategies Sourced from "The Pr...Quantopian
A unique set of data comprised of strategy returns sourced through traditional means from managers (“the pros”) and from strategies developed on Quantopian’s platform (“the crowd”) is analyzed. We detect distinct groups of strategy styles within the data: In particular, some "crowd" strategies fall into their own clusters distinct from those within the "pro" data set. A few do overlap as well. We go on to analyze the various strategy groups with respect to environmental conditions and risk factors (among other relevant features), teasing out differences in trading styles.
Ultimately we judge how well “the crowd” is doing so far, in terms of being able to compete with the established managers not only in terms of performance but also with respect to risk management and overall novelty and diversification in the trading styles that have emerged. Finally we address general notions (and pitfalls) of building meta strategies from manager return streams.
This presentation was part of QuantCon 2015 hosted by Quantopian. Visit us at: www.quantopian.com.
Should You Build Your Own Backtester? by Michael Halls-Moore at QuantCon 2016Quantopian
The huge uptake of Python and R as first-class programming languages within quantitative trading has lead to an abundance of backtesting libraries becoming widely available. It can take months, if not years, to develop a robust backtesting and trading infrastructure from scratch and many of the vendors (both commercial and open source) have a huge head start. Given such prevalence and maturity of the available software, as well as the time investment needed for development, is there any benefit to building your own?
In this talk, Mike will argue the advantages and disadvantages of building your own infrastructure, how to develop and improve your first backtesting system and how to make it robust to internal and external risk events. The talk will be of interest whether you are a retail quant trader managing your own capital or are forming a start-up quant fund with initial seed funding.
"I’ve never seen a bad backtest” — Dimitris Melas, head of research at MSCI. Quantitative Analysts rely heavily on backtests as a means of validating their trading strategies. All too often, strategies look great in simulation but fail to live up to their promise in live trading. There are a number of reasons for these failures, some of which are beyond the control of a quant developer. But other failures are caused by common but insidious mistakes. In this talk I’ll review a list of 10 pitfalls in strategy development and testing that can result in optimistic backtests. I’ll also present methods for detecting and avoiding them. This talk will be of interest to quant developers and also non-quants who are interested to know what to look out for when presented with remarkably successful backtests.
This presentation was part of the QuantCon 2015 Conference hosted by Quantopian. Visit us at: www.quantopian.com.
Book presentation: Excess Returns: a comparative study of the methods of the ...Frederik Vanhaverbeke
This is a pdf presentation of the book Excess Returns: a comparative study of the methods of the world's greatest investors. The presentation explains the various topics that are discussed in the book and show plenty of practical examples to understand the main points. It challenges the Efficient Market Hypothesis by showing some extraordinary track records in the investment world. It explains where top investors look for bargains. It shows how they perform a due diligence and how they value stocks. A separate section is devoted to the way top investors buy and sell various types of stocks, and how they buy and sell over stock market cycles. It also explains the various psychological aspects that top investors deem essential to beat the market.
Modeling the Stock Market: Common pitfalls and how to avoid them!Jess Stauth
The lure of creating models to predict the stock market has drawn talent from fields beyond finance and economics, reaching into disciplines such as physics, computational chemistry, applied mathematics, electrical engineering and perhaps most recently statistics and what we now refer to as data science. The attraction is clear - the stock market (and the economy/internet at large) throws off massive and ever increasing reams of data from garden variety time-series to complex structured data sets like quarterly financials, to unstructured data sets like conference call transcripts, news articles and of course — tweets! While all this data holds promise - it also holds traps and blind alleys that can be tricky to avoid. In this session we’ll review some of the common (but not easy!) pitfalls to avoid in creating models for predicting stock returns; overfitting & exploding model complexity, non-stationary processes, time-travel illusions, and under-estimation of real-world costs.
Data Driven Product Management - ProductTank Boston Feb '14Quantopian
Practical Ideas and Tools PMs Can And Should Use to Make Decisions
Talk given at Boston ProductTank Meetup. http://www.meetup.com/ProductTank-Boston/events/165579612/
Trade Like a Chimp: Unleash Your Inner Primate by Andreas Clenow at QuantCon ...Quantopian
It is a long established fact that a reasonably well behaved chimp throwing darts at a list of stocks can outperform most professional asset managers. It is less known why this is the case. While there would be obvious advantages with hiring chimps over hedge fund traders, such as lower salaries and calmer tempers, there are also a few practical obstacles to such hiring practices. For those asset management firms unable to retain the services of a cooperative primate, a random number generator may serve as a reasonable approximation of their skills.
The fact of the matter is that even a random number generator can, and will, outperform practically all mutual funds. Such random strategies may seem like a joke, and perhaps they are, but if a joke can outperform industry professionals we have to stop and ask some hard questions.
When designing investment strategies, it can be very useful to have an understanding of random strategies, how they work and what kind of results they are likely to yield. Given that random strategies perform quite well over time, they can act as a valid benchmark. After all, if your own investment approach fails to outperform a random strategy, you may as well outsource your quant modeling to the Bronx Zoo.
This slide presentation is an overview of Conner Management Group, LLC (CMG), an investment management firm. CMG is an SEC registered investment advisor.
If your company needs to submit a Investment Advisory PowerPoint Presentation Slides look no further.Our researchers have analyzed thousands of proposals on this topic for effectiveness and conversion. Just download our template, add your company data and submit to your client for a positive response. http://bit.ly/2UCGDB8
If your company needs to submit a Wealth Management Advisory Services Proposal PowerPoint Presentation Slides look no further.Our researchers have analyzed thousands of proposals on this topic for effectiveness and conversion. Just download our template, add your company data and submit to your client for a positive response. http://bit.ly/37gnhEr
If your company needs to submit a Financial Advisory Proposal PowerPoint Presentation Slides look no further.Our researchers have analyzed thousands of proposals on this topic for effectiveness and conversion. Just download our template, add your company data and submit to your client for a positive response. http://bit.ly/2HwkAEs
TRADE LIKE A HEDGE FUND - Harness the Power Of Technology to Gain Market Edge...Geoffrey Hossie
Presentation by Geoffrey Hossie of Pairtrade Finder to the Marbella Business Institute, 24 February 2017.
An introduction to Pair Trading and Why It Matters To You.
It is good to know the basics before making investments in Stock Markets. History has recorded scores of investors who have made fortune out of stock market. And if your investments are timed well, you could be the next fortune maker in the market.
This presentation presents and compares the managed account investment vehicle against alternatives such as the 401K, IRA, and several others. The presentation then goes on to present the uniqe service proposition offered by CMG, LLC as an investment manager and managed account provider.
If your company needs to submit a Wealth Advisory Proposal PowerPoint Presentation Slides look no further.Our researchers have analyzed thousands of proposals on this topic for effectiveness and conversion. Just download our template, add your company data and submit to your client for a positive response. http://bit.ly/2SeQewq
Building a systematic stock portfolio in only a few hours per yearStockopedia
Ed Page Croft reveals the simple but powerful systematic stock portfolio strategy that has helped him consistently achieve market-beating returns. To access the webinar in full please visit: http://why.stockopedia.com/creating-a-portfolio/
DSP US Flexible Equity Fund - An Open Ended Fund Of Funds Scheme Investing in a US Equity Fund
*The term “Flexible” in the name of the Scheme signifies that the Investment Manager of the Underlying Fund can invest either in growth or value investment characteristic securities placing an emphasis as the market outlook warrants.
This Open-ended Fund of Funds Scheme is suitable for investors who are seeking*:
1. Long-term capital growth
2. Investment in units of overseas funds which invest primarily in equity and equity related securities of companies domiciled in, or exercising the predominant part of their economic activity in the USA
3. High risk (Brown)
*Investors should consult their financial advisors if in doubt about whether the Scheme is suitable for them.
Note : Risk may be represented as :
(Blue) : Investors understand that their principal will be at low risk
(Yellow) : Investors understand that their principal will be at medium risk
(Brown) : Investors understand that their principal will be at high risk
There are multiple niches in the microcap space where GeoInvesting’s track record has proven that consistent alpha can be achieved. Each strategy provides favorable percentage returns, but is limited in size. A combination of well-defined strategies can enhance portfolio returns by offering the benefit of diversifying into uncrowded situations with low market correlation without overexposing to a single stock.
We believe the best way for a company of your size to approach a microcap strategy would be to deploy a target capital amount across a few basket portfolios of around 5 stocks each. These baskets can vary by strategy and time horizon. Around these baskets, we can implement one-off ideas as they emerge based on very high probability special situations
Catalyst are experts in optimising our clients’ balance sheet, reducing the total cost of trading and enabling regulatory compliance. We work in joint teams with our clients, combining our experience in financial markets and programme execution to deliver results. We provide honest guidance to help you succeed. We are Catalysts for enduring excellence
Similar to Quantopian is Launching a Crowd-sourced Hedge Fund (20)
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
where can I find a legit pi merchant onlineDOT TECH
Yes. This is very easy what you need is a recommendation from someone who has successfully traded pi coins before with a merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi network coins and resell them to Investors looking forward to hold thousands of pi coins before the open mainnet.
I will leave the telegram contact of my personal pi merchant to trade with
@Pi_vendor_247
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
how can i use my minded pi coins I need some funds.DOT TECH
If you are interested in selling your pi coins, i have a verified pi merchant, who buys pi coins and resell them to exchanges looking forward to hold till mainnet launch.
Because the core team has announced that pi network will not be doing any pre-sale. The only way exchanges like huobi, bitmart and hotbit can get pi is by buying from miners.
Now a merchant stands in between these exchanges and the miners. As a link to make transactions smooth. Because right now in the enclosed mainnet you can't sell pi coins your self. You need the help of a merchant,
i will leave the telegram contact of my personal pi merchant below. 👇 I and my friends has traded more than 3000pi coins with him successfully.
@Pi_vendor_247
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
how can I sell pi coins after successfully completing KYCDOT TECH
Pi coins is not launched yet in any exchange 💱 this means it's not swappable, the current pi displaying on coin market cap is the iou version of pi. And you can learn all about that on my previous post.
RIGHT NOW THE ONLY WAY you can sell pi coins is through verified pi merchants. A pi merchant is someone who buys pi coins and resell them to exchanges and crypto whales. Looking forward to hold massive quantities of pi coins before the mainnet launch.
This is because pi network is not doing any pre-sale or ico offerings, the only way to get my coins is from buying from miners. So a merchant facilitates the transactions between the miners and these exchanges holding pi.
I and my friends has sold more than 6000 pi coins successfully with this method. I will be happy to share the contact of my personal pi merchant. The one i trade with, if you have your own merchant you can trade with them. For those who are new.
Message: @Pi_vendor_247 on telegram.
I wouldn't advise you selling all percentage of the pi coins. Leave at least a before so its a win win during open mainnet. Have a nice day pioneers ♥️
#kyc #mainnet #picoins #pi #sellpi #piwallet
#pinetwork
Exploring Abhay Bhutada’s Views After Poonawalla Fincorp’s Collaboration With...beulahfernandes8
The financial landscape in India has witnessed a significant development with the recent collaboration between Poonawalla Fincorp and IndusInd Bank.
The launch of the co-branded credit card, the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card, marks a major milestone for both entities.
This strategic move aims to redefine and elevate the banking experience for customers.
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
Poonawalla Fincorp and IndusInd Bank Introduce New Co-Branded Credit Cardnickysharmasucks
The unveiling of the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card marks a notable milestone in the Indian financial landscape, showcasing a successful partnership between two leading institutions, Poonawalla Fincorp and IndusInd Bank. This co-branded credit card not only offers users a plethora of benefits but also reflects a commitment to innovation and adaptation. With a focus on providing value-driven and customer-centric solutions, this launch represents more than just a new product—it signifies a step towards redefining the banking experience for millions. Promising convenience, rewards, and a touch of luxury in everyday financial transactions, this collaboration aims to cater to the evolving needs of customers and set new standards in the industry.
If you are looking for a pi coin investor. Then look no further because I have the right one he is a pi vendor (he buy and resell to whales in China). I met him on a crypto conference and ever since I and my friends have sold more than 10k pi coins to him And he bought all and still want more. I will drop his telegram handle below just send him a message.
@Pi_vendor_247
how to sell pi coins on Bitmart crypto exchangeDOT TECH
Yes. Pi network coins can be exchanged but not on bitmart exchange. Because pi network is still in the enclosed mainnet. The only way pioneers are able to trade pi coins is by reselling the pi coins to pi verified merchants.
A verified merchant is someone who buys pi network coins and resell it to exchanges looking forward to hold till mainnet launch.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
how to sell pi coins at high rate quickly.DOT TECH
Where can I sell my pi coins at a high rate.
Pi is not launched yet on any exchange. But one can easily sell his or her pi coins to investors who want to hold pi till mainnet launch.
This means crypto whales want to hold pi. And you can get a good rate for selling pi to them. I will leave the telegram contact of my personal pi vendor below.
A vendor is someone who buys from a miner and resell it to a holder or crypto whale.
Here is the telegram contact of my vendor:
@Pi_vendor_247
when will pi network coin be available on crypto exchange.DOT TECH
There is no set date for when Pi coins will enter the market.
However, the developers are working hard to get them released as soon as possible.
Once they are available, users will be able to exchange other cryptocurrencies for Pi coins on designated exchanges.
But for now the only way to sell your pi coins is through verified pi vendor.
Here is the telegram contact of my personal pi vendor
@Pi_vendor_247
2. What is Quantopian?
• We are the world’s first algorithmic investing
platform built in the cloud.
• We provide the data, tools and infrastructure
quants need to research, create, test and invest
with algorithms from their browser.
• We offer a community of quants, scientists, and
hackers collaborating to find better investment
ideas.
• We are launching a crowd-sourced quant hedge
fund.
3. Quantopian is Launching a Hedge Fund
• What is a hedge fund and why do people invest
in them?
• Alternative investment strategies
• Aspire for low-correlation to general market movements
• “Hedged” against large market shock events like the Tech Bubble
burst of 2000, and financial crisis of 2008 where many stocks went
down >50% over ~3 months.
• The very best funds succeed via small gains achieved
consistently over time.
• Rarely suffering large losses allows for consistent compounded
growth of the portfolio
4. To be a Great Hedge Fund…
…is NOT…
• Hitting homeruns and making 50% per year
• Large investors actually frown on funds with huge single year gains because
it signals excessive risk taking
...but rather is…
• 12% per year annual return
• 6% per year annual volatility
• Sharpe Ratio of 2.0 is a huge achievement in the hedge fund game
• Never suffering more than a 10% loss from peak-to-trough
• Do this for 10 years straight and you’re in the top 1% of all funds
CONSISTENCY = $$$$$$
5. Running a Hedge Fund is Hard
• Typically funds generate strategy ideas from very few
people
• Built upon the few areas of expertise of the portfolio
managers
• Fundamental investing
• High-frequency trading
• Long-only investing, with simple hedging
• Sector specific investing (e.g. Tech companies, etc.)
• Very difficult to minimize your fund’s risk across various
business cycles when your expertise is limited to a few
areas
6. More Heads Are Better Than One!
• Crowd-sourcing opens a fire hose of ideas.
• Diversity of ideas will result in a diversified hedge fund
portfolio
• Quantopian has unique access to tens of thousands of
quants which allows for idea generation at an
unprecedented scale.
• Our challenge is to:
• attract and identify consistent high-performers
• construct a portfolio
• re-evaluate and re-balance strategies frequently for ongoing
CONSISTENCY in portfolio returns.
7. 1. Strong investment rationale. Quantopian is looking for strategies that are built
upon a solid understanding of financial, macro-economic and behavioral drivers in
the market. Being able to articulate a strong investment rational about why a model
works provides the framework for a rigorous research process and the potential for
a long-running successful strategy.
1. Rigorous research process. The single biggest concern we hear from allocators
looking at quant managers is the fear of data-mining, over-fitting and sensitivity to
simplistic model assumptions. A hypothesis-driven research process that explicitly
controls for model over-fitting using techniques such as "in" vs. "out of sample"
testing as well as walk-forward testing, statistical analysis of uncertainty based on
the number of free parameters fit, as well as best practices facilitated by
Quantopian's infrastructure to keep research both survivorship bias and look ahead
bias free, has the best likelihood of successful real-money performance.
1. Thoughtful risk management. Long-lived successful professional quant
managers will tell you that ‘it’s all about surviving the drawdowns’. Understanding
and controlling what risk factors your strategy is exposed to (e.g. market risk,
liquidity risk, sector risk, etc.) and how to tell when those exposures breach
historical norms is equally as important as identifying un-correlated alpha
strategies.
Identify High-Performers:
3 Core Principles of Good Quant Strategies
8. Identify High Performers:
Key Performance Metrics
• Sharpe Ratio
• Penalizes you for taking excessive risk in achieving your returns
• Annual Volatility
• Expected 1 standard deviation fluctuation in your portfolio over 1
year period
• Max Drawdown
• “peak-to-trough” worst loss suffered historically
• Consistency of Returns
• Is the volatility of your portfolio consistent over time?
9. Identify High Performers: It’s Not Just About the Returns.
2012 2013 2014
$100
$150
• Our job is to build a fund by filtering out the ORANGE algos, and investing in a lot of RED algos, as well as
hopefully some closer to the BLUE idealized line.
• After investing in a RED algo, monitor it in the event it turns ORANGE
10. Identify High-Performers:
Quantitative Evaluation Process
• Filter strategies based on quantitative metrics to select
• Consistent quants, with
• Low volatility in their returns,
• Across various market cycles (bull/bear/recession)
• Rank managers against each of the criteria, and generate a
composite ‘Q score’ for each trader.
• Construct a portfolio of strategies based on independent Q-
score AND on consideration of cross-strategy correlations and
risk exposures.
• Rigorously re-evaluate strategy performance over time to
monitor deviation from expected returns/risk
• Red flag is raised when they become inconsistent
12. Returns to a Simple Equal-weight Portfolio of
the Same 5 Managers (where data available)
12
13. How will Quantopian attract the best
quant talent to be managers in our fund?
Align our business with the quant as our north-star
customer. This means:
• Community based platform. Build the best platform for quant
mentorship, research, algo development and trading and keep it
free.
• Independence and ownership. Quants retain ownership of their
own intellectual property and code base.
• Transparent, meritocratic capital allocation. As we formalize
the process for being selected in Quantopian’s fund we’ll continue
our open dialogue with the community with the same level of
transparency you now expect.
Evaluating managers along these ‘Core principles’ tends to be a subjective and time-intensive process that can often introduce additional biases (e.g. behavioral biases to ‘trust’ that managers with good pedigrees will be better at risk management). Tackling this type of evaluation head on is a pretty well characterized problem faced by every external manager allocator and to some extent every investor. So much so that there exists a whole segment of the investment management sector that handles ‘outsourced’ diligence. We don’t intend to disregard, or ‘throw out’ these principles, however we DO intend to work towards quantifying and automating as much of this diligence as possible – something that will likely be a work in progress over the first few years of our fund’s launch. Working in our favor is that fact that we are no only going to be an allocator, but we are also the core software platform where our quants will do their research, strategy development and trading – so we have access to more and more timely data about the strategies, as well as a backtester we can use to stress-test strategies under a consistent set of conditions (most allocators get a pitch book with a bunch of plots that they have no way of verifying or modifying).
While quantifying a good research process or thoughtful risk management is more subjective, there do exist a host of quantitative measures designed to evaluate how ‘good’ a quant strategy is that we can leverage right off the bat. These are just four of the most common performance metrics we are using to study the strategies trading on Quantopian today. We expect all four of these measures (in some form or other) to play a large role in scoring strategies.
So why bother with all of this risk-adjusted measures? Shouldn’t we just care about how much money each strategy has made and invest in the most profitable ones? This chart is a nice illustration comparing three toy equity curves that all end up with an (admirable) 50% return over just two years. If you put yourself in the investors shoes for a moment and imagine your day to day blood pressure over these two years it should be apparent pretty quickly which path you’d prefer to take. To be more systematic about it, higher volatility strategies with larger drawdowns will carry much higher ‘risk of ruin’ which could be defined as margin calls or investor redemptions, and which will stop you out before you get to find out if you’re about to hit the next big upswing.
Our current pilot process for identifying high performers is driven by two steps of basic filtering and then ranking on the key performance metrics. The final step involves constructing a portfolio of strategies with the end goal of building a consistent track record of ‘fund level’ performance that meets our definition of a ‘great hedge fund’.
So by now you’re probably wondering, does Quantopian have anyone trading one of these desirable strategies today? Happily the answer is yes (and full disclosure, knowing the traction that we were getting with live trading and looking at preliminary analyses of returns already told us this and drove our confidence in pursuing this model). BUT – we need more!
So thinking back to the ‘challenges’ we outlined on an earlier slide. If we assume that we can put together a rational and repeatable process for identifying high performers, the next challenge is for us to grow the farm team and attract top talent, and critically to actually help DEVELOP top talent from previously untapped sources (e.g. cs, hard sciences, hackers, hobbyists, etc.)