Forward Simulator and Variance Testing

Build Alpha allows users to simulate how a strategy would perform in the next x trades based on varying win percentages. It uses the back test's distribution to simulate future performance.

E-Ratio

Edge Ratio or E-Ratio measures how much a trade goes in your favor vs. how much a trade goes against you. The x-axis is the number of bars since the trading signal. A higher y-value signifies more “edge” at that step in time.

BuildAlpha: Measurements are normalized for volatility; this allows us to use e-ratio across all markets and regimes. Once normalized for volatility, 1 signifies that we have equal amounts of favorable movement compared to adverse movement.

In other words, the y-axis is an expression of how many units of volatility more or against you your trade gets. A measure of 1.2 would indicate .2 units more of favorable volatility and a measure of 0.8 would indicate .2 units more of adverse movement.

Build Alpha: The blue line is for the selected strategy’s signal and the red line is for a “random” strategy for the same market. The red line is to serve as a baseline to beat. Ideally, you’ll want to see a blue line above 1 and above the random line.

You may find many “good” strategies, but they may have an E-Ratio less than the red baseline or less than one. This would make us less confident that our signal will withstand the test of time.
Additionally, if E-Ratio falls off a cliff at bar 6… then it probably does not make sense to hold for 15 bars!

Another tool to make sure Build Alpha + Trader = Success.

How to calculate:

1. Record Maximum Adverse Excursion and Maximum Favorable Excursion at each time step since signal.
2. Normalize MAE and MFE for volatility. To compare across markets we need a common denominator. Let’s use ATR or a unit of volatility.
3. Average all MFE and MAE values. Now you should have average MFE and average MAE at 1 bar since signal. Average MFE and average MAE at 2 bars since signal…
4. Divide Average MFE by Average MAE at each time step.

Originally Posted: https://www.buildalpha.com/e-ratio/

Features of Good Stock Market Investing Tools

Investment is putting money into some plan which an investor believes will generate more money or a nice return on his/her investment. There are different investment instruments also known as financing instruments used for getting loan by pledging them for e.g. share certificate or a promissory note. Various tools which helps you to achieve your financial goals like investing in the equity market or in different bank products are termed as investing tools.

There are different types of trading apps and tools that are available online which helps the investors in getting good result in the market. One such tool is Build Alpha which is helping the industry expert as well as the people who are new to the idea of investing. Build Alpha allows the investor to search for investing strategies across any asset class, analyze risk and reward historically and make estimates of what to expect going forward with advanced (but easy to use) statistical methods.

What to Look for in a Trading Software?

There are many big and small things that you need to look for in trading software before buying it. Few of the essential features you need to look for when you decide as to which stock analysis tools you want to use. BuildAlpha has all the under mentioned qualities you need to get in your trading software to achieve success in life.

Accurate Test Results

The most essential feature that a trader and investor should look for in software is the accurate analysis of investment and trading strategies. This enables the investor to make the best possible decisions on the most reliable data before risking any hard-earned money in the live markets.

Customizable tools

Another is the need for software which you can customize according to your need. Every trader is different and therefore have different needs and trading patterns. As trading plans vary so drastically, it’s probable to interview different traders and get completely contradictory answers when examined what makes a good research tool. So here is where Build Alpha comes into the scene and help traders who operate on all time horizons, asset classes and markets across the world.

An easy format of the tool

Traders and investors can be most productive if they can easily use the tool. Build Alpha has an intuitive design and layout that offers the most productivity to the investor. The best research tool is worthless if it’s too difficult to work and use. Aim for maximum productivity to ideally achieve maximum returns!

Originally Posted: http://buildalpha.org/features-good-stock-market-investing-tools/

Strategy Validation with Dave Bergstrom

With the toolsets we have available to us today it’s really quite easy to create a trading strategy by just mining market data.

Build Alpha: As we’ve just heard in that opening bit of audio and also from previous podcast guests too, if you try enough combinations you can find something that appears to work purely by chance or by luck.

The challenge however is trying to identify something that could be sustainable.

Something that may persist long enough in the future for us to take advantage of, and hopefully make some money from.

Our guest for this episode, Dave Bergstrom from BuildAlpha, has spent years researching, building, testing, and implementing market making and trading strategies for a high frequency trading firm, CTAs, money managers, individual clients, and even aspiring retail traders.

In this episode Dave is going to share some of his insights into strategy development and validation, including:

• How adjusting the ratio of in-sample/out-of-sample data can lead to creating different types of strategies
• Variance testing – what is it and how can it be used in the strategy creation process
• How E-ratios can be used to determine how an edge decays over time & weed out potentially poor strategies with good backtest results
• Why volume and volatility are important factors to consider when building trading strategies
• Loads of other ideas to test and validate the robustness of trading strategies.

Originally Posted: http://bettersystemtrader.com/079-strategy-validation-dave-bergstrom/

Greatest Traders of All Time

As a quantitative trader, I could not have been more excited for the new book “The Man Who Solved the Markets” by Gregory Zuckerman which details Jim Simons incredible story.

Jim Simons averaged a 66% return over the past 30 years and a 39% return after his 5% management and 44% performance fee (pg 316 of book).

I plowed through the book and had, what I believe, are some major takeaways to share:

1. Edge is important; not the story of why it exists. 

In other words, data mining is ok.

This is something I’ve long defended since the launch of Build Alpha. You do not need a hypothesis or explanation of why a certain investing/trading edge exists if it is statistically relevant or significant.

In my opinion, it is possible we simply cannot comprehend why a pattern or edge exists because it exists in a dimension too complex for our current understanding. Therefore, we should not discard edges that we do not understand.

This is why I (and BuildAlpha) search the market for edges and let the data tell us where the edge is. Remove the human bias, false ‘truths‘ and the need to explain/justify everything with a hypothesis or reason why it is happening. Many of these patterns are ‘overlooked’ because they don’t have an explanation, but have clearly been profitable for Renaissance!

Here are a few quotes to drive home takeaway #1:

“Simons and his researchers didn’t believe in spending much time proposing and testing their own intuitive trade ideas. They let the data point them to the anomalies signaling opportunity. They also didn’t think it made sense to worry about why these phenomena existed. All that mattered was that they happened frequently enough to include in their updated trading system, and that they could be tested to ensure they weren’t statistical flukes”. (pg 109)

“Simons and his colleagues hadn’t spent too much time wondering why their growing collection of algorithms predicted prices so presciently. They were scientists and mathematicians, not analysts or economists. If certain signals produced results that were statistically significant, that was enough to include them in the trading model” (pg 150).

“I don’t know why the planets orbit the sun. That doesn’t mean I can’t predict them” – Simons (pg 151).

“More than half of the trading signals Simons’s team was discovering were non-intuitive, or those they couldn’t fully understand. Most quant firms ignore signals if they can’t develop a reasonable hypothesis to explain them, but Simons and his colleagues never liked spending too much time searching for the causes of market phenomena. If their signals met various measures of statistical strength, they were comfortable wagering on them.” (pg 204).

“Volume divided by price change three days earlier, yes, we’d include that” – Simons (pg 204).

2. Everyone struggles with discipline and following their system. Even the Greatest of All Time (G.O.A.T)

Discipline is key and the ability to consistently follow your system(s) can be the difference between winning and losing. We all believe discipline becomes easier if you have more reliable edges or have grown your account quite a bit, but Jim Simons would probably argue that is simply not true!

BuildAlpha: In Dec 2018, Simons (worth approx. $23B at the time) called his advisor and wanted to override his systems (pg 308). The systems that have created the most incredible track record in history.

In the “Quant Quake” of 2007, Simons overrode his systems before the eventual rebound. One employee was quoted as saying it cost the firm money (pg 260). Moral of the story.. follow your system and trust your research! Everyone struggles with this, but we must.

Note: Majority of his career Simons was actually the one advocating to NOT override the systems and may be a large part of his success. These were just two small examples.

“Trust the model. We have to let it ride; we can’t panic” – Simons (pg 216

3. Surround yourself with a great team

This one should be obvious, but no one becomes the G.O.A.T alone. Brady has Belichick, Jordan had Pippen, Kobe had Shaq, Ruth had Gehrig, etc.

A large portion of the book chronicles how Jim sought out help from brilliant individuals, hiring them away from prestigious positions (science, tech and academia) by offering to double their salary. I won’t go over every individual, but a lot of chapters in this book are dedicated to the spectacular individuals that helped create the incredible returns which give Jim Simons the G.O.A.T title.

He recruited great talent to his team. Surround yourself with those that are experts in things you are not or inspire you to push past your limits.

Incorporate different approaches to your own similar to how Simons did. Trading is a lonely business at times.. you don’t need a hedge fund to build your own team.

4. Build strategies using different data.

Sure price and volume are great but the book mentioned other areas of alternative data Renaissance found useful.

Here are some simple ideas the book mentioned:

– sentiment

– correlations and relative moves

– number of times a stock’s ticker appears in major publications (regardless of sentiment)

Additionally, here is a previous See It Market blog I did using Commitment of Traders report to generate a trading signal: https://www.seeitmarket.com/how-to-improve-market-returns-using-alternative-data-17806/

5. Edge doesn’t have to be big.

Renaissance searched for “overlooked” edges and joked about a 50.75% win rate while utilizing the law of large numbers to win in the long-run.

Often times we get caught up searching for the holy grail or the perfect entry/exit for our trading or strategy development. But even with all these PhDs, RenTech was excelling trading a nearly 50% winning system to generate such astronomical returns. Much more can be gained by combining and adding unique smaller edges together than wasting time hunting for the perfect holy grail strategy!

 “We’re right 50.75 percent of the time… but we’re 100 percent right 50.75 percent of the time. You can make billions that way” (pg 272)

Bonus:

Build Alpha: Money isn’t the be all end all. He’s had tremendous tragedy in his personal life. Remember to enjoy LIFE while on the financial quest we are all on! The market isn’t going anywhere.I enjoyed the book and hope you do/did as well.

Originally Posted: https://www.seeitmarket.com/5-lessons-from-one-of-the-greatest-traders-of-all-time-jim-simons/

Tracking Sigma Scores Of Price Changes For Regime Shiftsh

Measuring price moves is the name of the game.

However, measuring price moves given recent context can add additional benefits to your trading performance.

Build Alpha: At times, the market can get very quiet which can make a 1% price drop feel like a 10% price drop (think summer trading). At other times, a 10% price drop can feel like a 1% price drop (think 2008). This is a driving force in why I often prefer to view price moves in standardized form and expressed as “sigma” moves. A sigma score basically tells you how many standard deviations can fit between the mean and the current price move. To calculate sigma you simply subtract the mean from the underlying value and then divide that difference by the standard deviation.

Sigma = (X – Mean) / Stdev

In our case we will have X = the natural log of the one bar price change or log(close[t] / close[t-1])

The astute reader would question the lookback period used to calculate the mean and standard deviation of X used in our sigma calculation, and that brings us to a very unique indicator I often view.

I personally like to track the rolling window of one month (22 trading days) and one year (252 trading days). I then like to compare the one month sigma score of price changes to the one year sigma score of price changes. This gives an indication of how current volatility compares to more long-term volatility.

Below is a plot of the sigma score calculated on a rolling monthly basis and on a rolling yearly basis. You can see the monthly sigma scores stay “bounded” between -4 and +4 whereas the yearly sigma scores vary a tad more.

All of this is great, but how can we use this and why am I telling you about this…

Build Alpha: Well when the monthly sigma minus the yearly sigma difference becomes greater than 1.5 we start to identify some key trading periods or moments in the S&P 500. For example, the instances where the difference between the monthly and yearly sigma reach 1.5 or more include the peak in 2007, the bottom in 2008, the flash crash in 2010, the European Debt Crisis of 2011, and the ETF meltdown of 2015.

Yesterday, May 17, was a significant down move but we are not near “significant” moments in history (yet) as the yearly sigma score stays subdued. This is definitely something to keep an eye on if this volatility persists throughout the summer.

Over at Build Alpha, I produce software that automatically creates systematic trading and investing strategies, allows the validation and testing of each strategy, and generates exportable and executable code for each strategy – no programming necessary.

Originally Posted: https://www.seeitmarket.com/tracking-sigma-scores-of-price-changes-for-regime-shifts-trading-16878/

Providing efficiency in Trading

Trading is a phenomenon which is not a cake walk. One cannot become an expert in this field unless one has gained some experience and knowledge in it. You need to seek guidance in the initial stages of trading. For taking help you can either reach out to some expert in this field or find advanced trading software that comes with training. As the trading in securities markets is based on interpretation of the market forces which in a lot of sense depends upon the market forces so the human interpretation can lack at times in analyzing certain aspects of it.

This is where software like Build Alpha comes into play and can help regulate your operation. This is a software which helps us in making strategies, testing our ideas, and building our confidence to run automated strategies in real-time. This is one of the best trading softwares to date and serves the needs of traders. Anticipating the trend or mean reversion becomes much easier if you do it through build alpha software solution. The best part… no programming is needed!

Trading software is a computer program designed to help traders and investors to trade and analyze stocks, commodities, futures and various currencies in forex market. It also gives you access to the latest news that affects the price movements of stocks and their trends. There are different types of trading softwares for both beginners and experts. BuildAlpha is one such software which is helping the traders to achieve the success in trading regardless of their skill level. It allows you to stress test each and every strategy.

View in and out of sample test results with ease, has data included, and generates actionable trading code all from one command center. There are fund managers who study short and long term charts with the help of these softwares. There are softwares available to know technical and fundamental aspects of the stocks. Many stock brokers provide softwares to their clients to trade on their own. The main features of the software are order placement and proper analysis of stocks. These softwares are built by third party and licensed to online brokers.

The software gets new updates every week which makes it more unique and worthy than other softwares which are alike in the trading market. The new peculiarities that are coming out every now and then are amazing it seems like trading has become easy with the aid of this software. You will experience the difference after using the Build Alpha software. You will become a person who will start analyzing what is important. Get efficiency in trading markets with the expert analyst feature of this software, which helps you in analyzing trends more specifically.

Originally Posted: http://buildalpha.us/build-alpha-providing-efficiency-in-trading/