Jared Broad
Founder and CEO of QuantConnect
Date Joined
5th December, 2013
Bootcamp progress
99% Complete
Achievements
Algorithm Sharing
Share an algorithm with the community by making your algorithm public.
2018-02-05 21:06:55
Notebook Sharing
Share a notebook with others.
2018-02-12 18:11:33
Chatter Box
Leave at least 100 comments on community posts.
2018-01-27 00:06:10
Backtester
Run at least 100 backtests on QuantConnect's cloud.
2018-01-29 20:07:22
Live Trading
Deploy a live trading algorithm using one of QuantConnect's supported brokerages.
2018-01-28 23:32:39
Parallel Live Trading
Run multiple live algorithms simultaneously.
2018-02-15 18:53:27
C# Programming
Choose C# as your preferred programming language.
2018-03-01 18:30:53
Python Programming
Choose Python as your preferred programming language.
2018-03-01 19:54:37
Popular
Receive at least 10 upvotes from different users in the community.
2018-01-29 11:51:24
Staff
Become a member of the QuantConnect team.
2018-01-24 17:39:32
Boot Camp Private
Complete a beginner bootcamp in the algorithm lab.
2019-01-25 01:08:42
Boot Camp Corporal
Complete an advanced bootcamp in the algorithm lab.
2019-10-24 23:37:42
Verified User
Verify your identity and become a verified QuantConnect user.
2019-05-02 00:09:40
Outstanding Community Service
Awarded by administrators for outstanding voluntary support of other community members.
2021-02-25 23:18:45
- Profile
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Biography
Activity on QuantConnect
We are pioneering the radical future for open-source quant finance. QuantConnect is the world's largest quant community, empowering 220,000 quants with a framework, data, and infrastructure for their investments.
Public Backtests (143)
View More25.32Net Profit
58.605PSR
0.629Sharpe Ratio
-0.007Alpha
0.694Beta
16.201CAR
9.3Drawdown
0Loss Rate
6Parameters
1Security Types
0.737Sortino Ratio
376Tradeable Dates
3Trades
0.085Treynor Ratio
0Win Rate
24.129Net Profit
59.433PSR
0.621Sharpe Ratio
-0.022Alpha
0.706Beta
15.343CAR
8.3Drawdown
0Loss Rate
0Parameters
1Security Types
0.749Sortino Ratio
379Tradeable Dates
3Trades
0.08Treynor Ratio
0Win Rate
22.877Net Profit
56.806PSR
0.572Sharpe Ratio
-0.025Alpha
0.707Beta
14.687CAR
8.3Drawdown
0Loss Rate
0Parameters
1Security Types
0.691Sortino Ratio
377Tradeable Dates
3Trades
0.074Treynor Ratio
0Win Rate
32.862Net Profit
32.037PSR
0.726Sharpe Ratio
0.505Alpha
0.362Beta
30.763CAR
76.8Drawdown
0Loss Rate
0Parameters
1Security Types
0.506Sortino Ratio
264Tradeable Dates
1Trades
1.519Treynor Ratio
0Win Rate
283.297Net Profit
19.774PSR
0.722Sharpe Ratio
0.009Alpha
0.98Beta
14.373CAR
24.2Drawdown
-0.09Loss Rate
0Parameters
0Security Types
2516Tradeable Dates
3553Trades
0.096Treynor Ratio
0.11Win Rate
Community
View MoreJared left a comment in the discussion MACDelta
Hi QUARCC! Please update to be trading more actively or unfortunately the strategy will have to be...
Jared left a comment in the discussion A Cosmic Trading Experience
I had to put "A Final Note" just incase!
Jared left a comment in the discussion Hands on AI Trading with Python, QuantConnect, and AWS
Hi Matthew! Not sure what might cause this -- the publishing formats are handled by Wiley I'll be...
Jared left a comment in the discussion Hands on AI Trading with Python, QuantConnect, and AWS
Thank you Pro!
25.32Net Profit
58.605PSR
0.629Sharpe Ratio
-0.007Alpha
0.694Beta
16.201CAR
9.3Drawdown
0Loss Rate
6Parameters
1Security Types
0.737Sortino Ratio
376Tradeable Dates
3Trades
0.085Treynor Ratio
0Win Rate
24.129Net Profit
59.433PSR
0.621Sharpe Ratio
-0.022Alpha
0.706Beta
15.343CAR
8.3Drawdown
0Loss Rate
0Parameters
1Security Types
0.749Sortino Ratio
379Tradeable Dates
3Trades
0.08Treynor Ratio
0Win Rate
22.877Net Profit
56.806PSR
0.572Sharpe Ratio
-0.025Alpha
0.707Beta
14.687CAR
8.3Drawdown
0Loss Rate
0Parameters
1Security Types
0.691Sortino Ratio
377Tradeable Dates
3Trades
0.074Treynor Ratio
0Win Rate
32.862Net Profit
32.037PSR
0.726Sharpe Ratio
0.505Alpha
0.362Beta
30.763CAR
76.8Drawdown
0Loss Rate
0Parameters
1Security Types
0.506Sortino Ratio
264Tradeable Dates
1Trades
1.519Treynor Ratio
0Win Rate
283.297Net Profit
19.774PSR
0.722Sharpe Ratio
0.009Alpha
0.98Beta
14.373CAR
24.2Drawdown
-0.09Loss Rate
0Parameters
0Security Types
2516Tradeable Dates
3553Trades
0.096Treynor Ratio
0.11Win Rate
25.459Net Profit
59.88PSR
1.55Sharpe Ratio
0.537Alpha
-0.169Beta
97.424CAR
23.2Drawdown
-1.19Loss Rate
0Parameters
0Security Types
122Tradeable Dates
159Trades
-3.202Treynor Ratio
1.56Win Rate
92.151Net Profit
20.312PSR
0.565Sharpe Ratio
0.083Alpha
0.102Beta
15.095CAR
27Drawdown
33Loss Rate
0Parameters
1Security Types
0.69Sortino Ratio
1168Tradeable Dates
287Trades
0.905Treynor Ratio
67Win Rate
115.041Net Profit
80.438PSR
1.679Sharpe Ratio
0.259Alpha
1.271Beta
65.214CAR
25.8Drawdown
42Loss Rate
0Parameters
1Security Types
2.141Sortino Ratio
384Tradeable Dates
1732Trades
0.316Treynor Ratio
58Win Rate
40.675Net Profit
34.755PSR
0.598Sharpe Ratio
-0.009Alpha
1.422Beta
25.081CAR
25.5Drawdown
45Loss Rate
0Parameters
1Security Types
0.755Sortino Ratio
384Tradeable Dates
2023Trades
0.106Treynor Ratio
55Win Rate
88.154Net Profit
84.034PSR
1.684Sharpe Ratio
0.07Alpha
1.728Beta
53.106CAR
17.9Drawdown
20Loss Rate
0Parameters
1Security Types
2.101Sortino Ratio
0Tradeable Dates
550Trades
0.18Treynor Ratio
80Win Rate
98.915Net Profit
24.876PSR
0.622Sharpe Ratio
0.03Alpha
0.738Beta
15.952CAR
25.5Drawdown
51Loss Rate
0Parameters
2Security Types
0.683Sortino Ratio
1696Tradeable Dates
523Trades
0.13Treynor Ratio
49Win Rate
65.619Net Profit
87.598PSR
1.077Sharpe Ratio
0.032Alpha
0.285Beta
12.67CAR
7.4Drawdown
9Loss Rate
0Parameters
2Security Types
0.844Sortino Ratio
1065Tradeable Dates
89Trades
0.214Treynor Ratio
91Win Rate
66.379Net Profit
92.979PSR
1.704Sharpe Ratio
0.068Alpha
0.906Beta
36.305CAR
7.8Drawdown
32Loss Rate
0Parameters
1Security Types
2.272Sortino Ratio
0Tradeable Dates
1678Trades
0.214Treynor Ratio
68Win Rate
66.379Net Profit
92.997PSR
1.706Sharpe Ratio
0.068Alpha
0.906Beta
36.375CAR
7.8Drawdown
32Loss Rate
0Parameters
1Security Types
2.278Sortino Ratio
0Tradeable Dates
1678Trades
0.214Treynor Ratio
68Win Rate
73.231Net Profit
79.668PSR
1.493Sharpe Ratio
0.044Alpha
1.505Beta
45.013CAR
17.8Drawdown
24Loss Rate
0Parameters
1Security Types
1.793Sortino Ratio
0Tradeable Dates
512Trades
0.172Treynor Ratio
76Win Rate
84.228Net Profit
64.035PSR
1.273Sharpe Ratio
0Alpha
0Beta
51.139CAR
27.6Drawdown
40Loss Rate
0Parameters
1Security Types
1.518Sortino Ratio
462Tradeable Dates
589Trades
0Treynor Ratio
60Win Rate
180.716Net Profit
72.991PSR
4.023Sharpe Ratio
4.147Alpha
0.173Beta
426.555CAR
65Drawdown
0Loss Rate
0Parameters
2Security Types
5.551Sortino Ratio
194Tradeable Dates
2Trades
24.065Treynor Ratio
0Win Rate
180.28Net Profit
73.008PSR
4.042Sharpe Ratio
4.176Alpha
0.175Beta
429.114CAR
65Drawdown
0Loss Rate
0Parameters
2Security Types
5.59Sortino Ratio
193Tradeable Dates
2Trades
24.04Treynor Ratio
0Win Rate
902.667Net Profit
93.526PSR
4.135Sharpe Ratio
3.001Alpha
0.5Beta
436.573CAR
37.2Drawdown
0Loss Rate
0Parameters
2Security Types
6.201Sortino Ratio
425Tradeable Dates
2Trades
6.105Treynor Ratio
0Win Rate
0Net Profit
0PSR
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
0Parameters
3Security Types
0Sortino Ratio
1Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
0Parameters
1Security Types
376Tradeable Dates
25.51Net Profit
58.704PSR
0.659Sharpe Ratio
-0.027Alpha
0.758Beta
16.319CAR
10.3Drawdown
0Loss Rate
6Parameters
0Security Types
375Tradeable Dates
3Trades
0.083Treynor Ratio
0Win Rate
0Net Profit
0PSR
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
0Parameters
1Security Types
0Sortino Ratio
0Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
24.921Net Profit
78.85PSR
0.89Sharpe Ratio
0.009Alpha
0.36Beta
15.975CAR
7Drawdown
-0.05Loss Rate
4Parameters
0Security Types
377Tradeable Dates
239Trades
0.168Treynor Ratio
0.06Win Rate
0Net Profit
0PSR
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
1Parameters
0Security Types
5996Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
0Net Profit
0PSR
0Sharpe Ratio
0Alpha
0Beta
0CAR
0Drawdown
0Loss Rate
1Parameters
0Security Types
5996Tradeable Dates
0Trades
0Treynor Ratio
0Win Rate
-4.079Net Profit
0.594PSR
-0.043Sharpe Ratio
-0.012Alpha
0.048Beta
-0.829CAR
33.8Drawdown
-0.1Loss Rate
7Parameters
0Security Types
1258Tradeable Dates
22533Trades
-0.17Treynor Ratio
0.43Win Rate
24.732Net Profit
72.445PSR
1.013Sharpe Ratio
-0.008Alpha
0.759Beta
21.361CAR
10.2Drawdown
0Loss Rate
3Parameters
0Security Types
285Tradeable Dates
3Trades
0.127Treynor Ratio
0Win Rate
9.984Net Profit
20.06PSR
0.03Sharpe Ratio
-0.036Alpha
0.768Beta
6.51CAR
14.3Drawdown
0Loss Rate
3Parameters
0Security Types
377Tradeable Dates
3Trades
0.005Treynor Ratio
0Win Rate
3.494Net Profit
18.028PSR
-0.464Sharpe Ratio
-0.03Alpha
0.394Beta
2.758CAR
7.6Drawdown
0Loss Rate
1Parameters
0Security Types
318Tradeable Dates
1Trades
-0.068Treynor Ratio
0Win Rate
Jared left a comment in the discussion Getting 443 when using yfinance
Hi Darren Mo – Yahoo changed their API, we'll need to update the package in the foundation for...
Jared left a comment in the discussion MACDelta
Hi QUARCC! Please update to be trading more actively or unfortunately the strategy will have to be...
Jared left a comment in the discussion A Cosmic Trading Experience
I had to put "A Final Note" just incase!
Jared left a comment in the discussion Hands on AI Trading with Python, QuantConnect, and AWS
Hi Matthew! Not sure what might cause this -- the publishing formats are handled by Wiley I'll be...
Jared left a comment in the discussion Hands on AI Trading with Python, QuantConnect, and AWS
Thank you Pro!
Jared left a comment in the discussion Hands on AI Trading with Python, QuantConnect, and AWS
Great to hear Mickias!
Jared submitted the research Micro Study: Yen Carry Trade
Abstract
This micro-study investigates the Yen Carry Trade, a strategy leveraging low Japanese interest rates to invest in higher-yield assets like US Treasuries. The study examines the recent unwinding of this trade, prompted by Japan's interest rate hike from 0% to 0.25%, which led to rapid strengthening of the Yen. Using QuantConnect, the strategy was modeled with USDJPY FX pair and BIL US ETF Bond, simulating $80M in holdings with $1M collateral. Despite a Sharpe ratio of 16 for most of 2024, the strategy faced a 60% drawdown recently. Future improvements could include risk controls and monitoring central bank decisions.
Jared submitted the research Idea Streams #3 - Seeking Diversification Amidst Global Market Correlations
Abstract
In this QuantConnect discussion, the focus is on seeking diversification amidst global market correlations. The rise in correlation between the CSI 300 Index and the S&P 500 index is attributed to the disruption caused by the coronavirus. To study this, the correlation plot is reproduced using ETFs such as SPY, FXI, EWI, VGK, GLD, and SHY. A trading algorithm is then implemented to rebalance the portfolio daily, allocating half to SPY and half to the asset with the lowest correlation to SPY over the last 120 days. Backtesting the strategy resulted in a 0.813 Sharpe ratio and a 17.9% drawdown, outperforming the market benchmark.
Jared submitted the research Idea Streams #1 - Tranche Rebalancing Risk Parity
Abstract
In this QuantConnect discussion, the topic of tranche rebalancing risk parity is explored. The traditional strategy of allocating 60% to equities and 40% to bonds has been successful in the past, but during the 2020 market crash, both equities and bonds suffered simultaneously, causing many funds to struggle. The fluctuating prices of stocks and bonds require periodic rebalancing, and the tranche method suggests only partially correcting the weights when rebalancing. AQR and Bloomberg found that rebalancing only 25% of the way to the target allocations resulted in smaller trades and lower turnover during times of high volatility. The authors of this discussion sought to reproduce these results and test the effectiveness of tranche rebalancing compared to fully rebalancing. The backtest was conducted using the SPY ETF for equities and the SHY government bond ETF, with the start date set to January 1, 2003.
Jared submitted the research Idea Streams #2 - Modeling Unemployment Rates with SKLearn
Abstract
In this QuantConnect discussion, the focus is on modeling unemployment rates using the SKLearn library. The article highlights the significant increase in the US unemployment rate due to the COVID-19 pandemic and explores the potential relationship between unemployment rates and the stock market. The analysis involves gathering unemployment rate and initial claims datasets from the Federal Reserve Economic Database and adjusting the timestamps to remove lookahead bias. Linear regression models are then trained using the datasets to predict the price of SPY. The results show high R-Square values for the training regression models, indicating a strong correlation between the unemployment rates and stock market prices. However, the testing regression results show lower R-Square values, suggesting that the models may not perform well on out-of-sample data.
Jared submitted the research Vix Predicts Stock Index Returns
Abstract
This discussion explores the relationship between the VIX Index and stock index returns. The VIX Index is calculated based on the implied volatilities of options on the S&P100 index. Extreme levels of the VIX Index can indicate future equity index returns. The algorithm aims to determine if the VIX Index can be used as a forward-looking indicator for stock index returns. To do this, the algorithm defines large and small implied volatility levels by creating 20 equally spaced percentiles for the VIX Index's historical close prices. The algorithm imports daily VIX data and compares the current VIX index price to these percentiles. The S&P100 Index is used as the corresponding stock index.
Jared submitted the research Three Common Implementation Mistakes
Abstract
In this QuantConnect discussion, the focus is on three common implementation mistakes that even experienced quants make in their strategies. The first mistake is not debouncing the algorithm, which means ensuring it only fires once per trading signal to increase efficiency. The second mistake is triggering orders multiple times per signal, which can lead to cash flow mismanagement. The third mistake is using too many variables and optimizing the algorithm excessively, which can result in curve fitting and unreliable profitability. To help users avoid these mistakes, QuantConnect offers a free video tutorial on coding the Exponential Moving Average Strategy, providing a coding walk-through and tips on building a strategy while avoiding these common pitfalls.
Jared submitted the research The Importance of Benchmarking
Abstract
In this QuantConnect discussion, the importance of benchmarking in measuring strategy performance is highlighted. The two techniques for measuring performance are relative and absolute performance. Absolute return strategies aim for consistent returns regardless of market conditions, while relative return strategies compare the strategy to a market index. The choice of benchmark can vary, with the S&P500 being a common choice. QuantConnect has integrated benchmarking functionality into the results panel, allowing users to compare their strategy's performance to major indices. To demonstrate this functionality, a video has been created showcasing the implementation of the "Sell in May and Go Away" strategy benchmarked against the S&P500. The implementation achieved similar returns with lower volatility, resulting in an overall better than market strategy.
Jared submitted the research RSI Indicator with Martingale Position Sizing
Abstract
Abstract: This discussion explores the use of the Martingale position sizing technique in trading strategies, specifically in combination with the Relative Strength Index (RSI) indicator. The Martingale technique involves increasing bet sizes after losses to potentially recover losses and generate profits. The discussion highlights the risks associated with Martingale position sizing, including limited leverage and fluctuating win-loss probabilities in real trading scenarios. The authors present a martingale position management algorithm and backtest it on 15 years of data using QuantConnect. The results show that the algorithm outperforms the absolute return of the SPY over the same period but exhibits higher volatility and a lower Sharpe Ratio. The discussion concludes by suggesting areas for further experimentation to enhance the strategy's performance.
Jared started the discussion New Feature - Stock Order Plotting
After a few long nights hacking we've released an awesome new feature - stock price plotting with...
Jared started the discussion New Blog - The Importance of Bench-marking
Today we released another video in our QuantConnect University series called "The Importance of...
Jared started the discussion QCU RSI-Martingale Position Management
Algorithm uses Relative Strength Index (RSI) to control entry into market, and then martingale to...
Jared started the discussion QCU Weather Based Rebalancing
We took NYC temperature weather data imported from an external source and used it as a weighting...
Jared started the discussion Math Libraries?
We're adding C# math/science libraries at the moment so its an ideal time to take requests -- I've...
Jared started the discussion SPY Dollar Averaging
2012 was a rough year for SPY.
Jared started the discussion QCAlgorithm Open Sourced
You can now compile your entire algorithm locally, using your local IDE, local autocomplete etc. We...
Jared started the discussion Bug Reports
Lets face it - bugs are almost a certainty! QuantConnect has tens of thousands of lines of code and...
Jared started the discussion Adjusted Pricing
Just an notice -- we changed the pricing to use adjusted pricing. This gives continuity of pricing...
Jared started the discussion Statistics & Reporting Calculations
Hello all, we updated the statistics calculations to tidy them up -
Jared started the discussion Server Costs Correlation with BitCoin Prices?
We've seen a dramatic rise in the cost of our servers that run the back tests in the recent weeks....
Jared started the discussion Trade-Equity Validation Excel WorkSheet
We made an excel worksheet I thought we'd share. It is used to confirm the running portfolio equity...
Jared started the discussion Missing Stock Symbols
Occasionally users find symbols which aren't in the database, or have confusing symbol names. If...
Jared started the discussion QCU-Sell in May
A algorithm for easy cloning to go with the blog "Sell in May"...
Jared started the discussion QCU-Exp. Moving Average Cross 50d-10d
An implementation of the classic exponential moving average cross for the QuantConnect University...
Jared started the discussion 5 Minute Bar Consolidator
QCU example summary code for creating X-minute bars from 1 minute TradeBar data. The open source...
Jared started the discussion Nice smooth curve, but low sharpe.
Experiment using equity GE and very small trading packets. Perhaps could be better with some...
Jared started the discussion New Members - Say Hello!
This was just created for fun for new people to say hello! Don't be shy reach out and let us know...
Jared started the discussion New Dataset - Crowd EPS Predictions
We just added a new high quality datasets from our data partners Estimize.com! You can request this...
Jared started the discussion LaTeX Formatting Support
We added LaTeX formatting support for beautiful algorithms, if you'd like more information on how...
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Jared left a comment in the discussion Getting 443 when using yfinance
Hi Darren Mo – Yahoo changed their API, we'll need to update the package in the foundation for...
19 hours ago