Strategy Factory workshop - Learn how to develop algorithmic trading This is not your typical trading course: This is a complete workshop on Think about that for a minute - these traders all paid for the online workshop, How To Recognize Testing Pitfalls .. What if I cannot make any of the dates/times listed below?. Stephens clapped inside his “resolutions” while a boy inside his far hours that he yahoo dating · algorithmic trading strategies and their pit falls of online dating. Online dating and book-recommendation and travel websites would not , partly because of currency trades triggered by algorithms. . We need to ask them to think about their thinking – to look out for pitfalls and inherent biases .. Amazon uses machine learning to optimize its sales strategies.
Just ask stock market "buy and hold" advocates about that strategy. No matter what strategy you use to trade, your best bet is to assume it will stop working, and plan accordingly.
Having new strategies waiting to be traded is the best way to survive the trading game. Another reason to have multiple strategies is diversification. If you trade one strategy, you are at mercy of that strategy. If it starts doing poorly, as all strategies do, you are in trouble. If you add one or more uncorrelated strategies to your portfolio, your equity curve will get smoother, and drawdowns typically will decrease.
Having a strategy factory allows you to develop, implement and trade multiple, uncorrelated strategies. Finally, as your account grows, you'll want to trade more strategies. With larger accounts, you might run into trade size issues. Having more trading strategies, developed with a Strategy Factory, will allow you to add new strategies, diversify your portfolio and keep your size manageable as your equity grows. This Course Can Be Free! Click here for more details.
As voted by the readers at TraderPlanet. Think about that for a minute - these traders all paid for the online workshop, concluded they received a ton of value, THEN decided to spend more time and money to travel to Cleveland to collaborate with other Strategy Factory students.
That to me shows you the value of the workshop - traders are actively using the Strategy Factory process in their daily trading! These traders are all active in the Strategy Factory Club, so as you submit strategies, you will be sharing with some of these traders. First, a week before the all day workshop, you can have a 15 minute online meeting with me, one on one or you can save it for later. I want to understand your experience, your likes and dislikes, and your learning style to help me present the right info to you during the class.
Remember, there are limited new students in each workshop, so you'll end up feeling like I am talking to you, and you alone!
During the class, over the course of 8 hours, you'll learn: I rose quickly over the years at the firms I worked. As a Wall St trader, I closely watched and studied every trader I met.
As a broker, I observed the strategies and PnL's of well over 35, traders and their accounts. Yet in all this time, I never observed a trader as consistently successful as Kevin Davey. Kevin's secret sauce is his process. I never saw a trader who had a process as thorough and well-developed as Kevin Strategy Factory Process. Therefore it should be no mystery why I never observed trading success that was as consistent and reproducible as Kevin Davey's. This stuff can be learned, but it is seldom taught.
Kevin's Strategy Factory Workshop and its support are pure Gold. Really, really good stuff. Sincere thanks, Kevin for an idea-enriching workshop!! The email replies were usually within an hour. That is great service. The support after the seminar is invaluable. It will take you a while to get through it all, but once you do you will be able to start developing strategies.
Plus, you are invited to the full day, live online event, so you can ask questions live and hear the questions of other students. The combination of recorded material, followed by a live class, has been shown to be a great way to learn new material.
This is a live online event, but don't worry if you have to step away and miss some of the workshop. Each workshop is recorded, so you can review the material over and over. Plus, as long as space is available, you can attend later workshops for a "refresher," to ensure you absorb all the information - at no additional charge! My goal is to get you developing good trading strategies!
Basically, you can benefit from all other students who produce winning strategies. I call it the "Strategy Factory Club. This free membership is pretty simple: Develop an algorithmic trading strategy, using the Strategy Factory process and principles Have your trading strategy pass an evaluation phase live simulated trading Share your trading system with other students In return, you get verified strategies from other students This Club is a great way to increase your number of strategies very quickly!
Just watch this 2 minute video The Workshop gave me the tools to be able to develop my own strategies. However, the Club is what keeps me actively practicing what I learned in the Workshop.
On top of that the Club provides a method for developing diversity amongst my systems that I would not be able to do as quickly on my own. For the first 2 months of the Club, I provided 2 strategies and as part of the outcome, I now have 7 strategies all of which have been vetted through the criteria of the Strategy Factory Workshop and are ready to trade immediately.
Here are just some of the hypothetical strategies former students have created, using the principles I teach in the Strategy Factory workshop. Many of these come from students who never before produced a properly designed trading system, until they learned how from me!
What Do Previous Attendees Say? When I present the Strategy Factory workshop, I always try to get feedback from participants. I want the full day to be as jam packed as possible with information, and I want all students to walk away knowing their hard earned money was well spent. A quality event is always my goal! Since I started the Strategy Factory Workshop, every single class, except for a couple, has been sold out in advance!
Participants had anywhere from 1 - 40 years of trading experience, and afterwards most took a short survey. Here is what they said: So, hopefully that gives you an idea of what you are getting with the Strategy factory webinar. Quality education, from a champion trader, at a terrific value! Does the vendor even trade? Has the vendor ever traded? What is the vendor's reputation in trading forums, and on the internet? How much can you trust and believe who you are dealing with?
Well, here are some important facts about me: But, I've learned from my mistakes. You can learn from my mistakes, too - and for a lot less than it cost me! I trade real money. Vendors that do not trade raise a HUGE red flag.
It is a grueling 12 month competition against some of the best traders on the planet. My book also won Traderplanet. That is a critical point. I'm not one of those circus clowns you see at every Trading Expo out there. Most vendors "sell the dream," but I "live the dream" by trading! I have a solid history of helping others become better algorithmic traders.
My nickname is "kevinkdog" on both. You can easily check out the quality of my advice at either place. I think you'll find it easy to discern. I do not pass you off to some inferior trader or wannabe trader, like so many vendors do. I will be with you the whole time! Finally, please google my name " Kevin Davey trader" for examplegoogle KJ Trading Systems, and do your own due diligence before you sign up.
You'll find I am not a sleazy snake oil, rainbow selling trading vendor. Since my reputation is something I hold dear, most sleazy trading vendors hate me!
What Happens After The Workshop? After the workshop, I won't turn you loose to flounder. You'll have 2 months of e-mail help. You simply e-mail me whatever questions you may have, and I'll respond - typically the same day. Also, you have a 15 minute one-on-one call with me before or after the workshop.
Finally, if you wish, I'll help you connect with other attendees. Talking to someone on the same path as you can also greatly help you. Some attendees say this is the best part of the workshop I disagree - I think the 2 months of one-on-one support is the best part - but who am I to argue? You get the complete code plain English and Tradestation format to all 7 of the strategies - for your own personal use, to use or modify as you wish.
Hypothetical Results Shown Below: I put my money where my mouth is! Using these strategies, we will walk the complete strategy development process. That way, you'll see both what the strategy is, and more importantly how it was developed. You can start learning today!
Algorithmic Trading Glossary
No worries - I give you the code with plain English rules, too! Many traders use this to clarify some course material, to get motivated, or just to talk to a real full time trader! Areas of extra instruction include incubation, rollovers, account sizing, real life entries and exits, Monte Carlo testing, walkforward analysis, interviews with successful and non-successful students and MORE! And of course, you will only pay a fraction of that amount. But I am going a step further - I am including a bunch of bonuses to push this deal over the top!
No worries - I supply the code in plain English rules, too! I'll provide detailed instructions after you sign up. For many traders, my course is eventually free. But I am not done yet! Many traders have submitted one strategy to the Club, and gotten 10 or more good strategies in return, to personally trade as they wish! My biggest fear is that, unless we tune our algorithms for self-actualization, it will be simply too convenient for people to follow the advice of an algorithm or, too difficult to go beyond such adviceturning these algorithms into self-fulfilling prophecies, and users into zombies who exclusively consume easy-to-consume items.
Every time you design a human system optimized for efficiency or profitability you dehumanize the workforce.
That dehumanization has now spread to our health care and social services. When you remove the humanity from a system where people are included, they become victims.
Who is collecting what data points? Do the human beings the data points reflect even know or did they just agree to the terms of service because they had no real choice? Who is making money from the data? There is no transparency, and oversight is a farce.
Worse, they repackage profit-seeking as a societal good. We are nearing the crest of a wave, the trough side of which is a new ethics of manipulation, marketing, nearly complete lack of privacy. The Common Good has become a discredited, obsolete relic of The Past. Humans will lose their agency in the world.
We are heading for a nightmare. I exaggerate for effect. But not by much. Biases exist in algorithmically-organized systems Two strands of thinking tie together here. One is that the algorithm creators code writerseven if they strive for inclusiveness, objectivity and neutrality, build into their creations their own perspectives and values. The other is that the datasets to which algorithms are applied have their own limits and deficiencies.
Moreover, the datasets themselves are imperfect because they do not contain inputs from everyone or a representative sample of everyone. The two themes are advanced in these answers: Most people in positions of privilege will find these new tools convenient, safe and useful. The harms of new technology will be most experienced by those already disadvantaged in society, where advertising algorithms offer bail bondsman ads that assume readers are criminals, loan applications that penalize people for proxies so correlated with race that they effectively penalize people based on race, and similar issues.
Experts on the Pros and Cons of Algorithms
Much of it either racial- or class-related, with a fair sprinkling of simply punishing people for not using a standard dialect of English. To paraphrase Immanuel Kant, out of the crooked timber of these datasets no straight thing was ever made.
One of the greatest challenges of the next era will be balancing protection of intellectual property in algorithms with protecting the subjects of those algorithms from unfair discrimination and social engineering. The people writing algorithms, even those grounded in data, are a non-representative subset of the population. Garbage in, garbage out.
Many dimensions of life will be affected, but few will be helped. Oversight will be very difficult or impossible.
First, they predicted that an algorithm-assisted future will widen the gap between the digitally savvy predominantly the most well-off, who are the most desired demographic in the new information ecosystem and those who are not nearly as connected or able to participate. Second, they said social and political divisions will be abetted by algorithms, as algorithm-driven categorizations and classifications steer people into echo chambers of repeated and reinforced media and political content.
And that divide will be self-perpetuating, where those with fewer capabilities will be more vulnerable in many ways to those with more. Brushing up against contrasting viewpoints challenges us, and if we are able to actively or passively avoid others with different perspectives, it will negatively impact our society.
It will be telling to see what features our major social media companies add in coming years, as they will have tremendous power over the structure of information flow. The overall effect will be positive for some individuals. It will be negative for the poor and the uneducated. As a result, the digital divide and wealth disparity will grow. It will be a net negative for society. Positive impact will be increased profits for organizations able to avoid risk and costs.
Negative impacts will be carried by all deemed by algorithms to be risky or less profitable.
Something Interesting to Read May - Forex Market - Trading Systems - MQL5 programming forum
The level of privacy and protection will vary. So the scenario is one of a vast opening of opportunity — economic and otherwise — under the control of either the likes of Zuckerberg or the grey-haired movers of global capital or …. Gendered exclusion in consumer targeting. Class exclusion in consumer targeting ….
Nationalistic exclusion in consumer targeting. Keeping some chaos in our lives is important. Unemployment will rise The spread of artificial intelligence AI has the potential to create major unemployment and all the fallout from that. What will then be the fate of Man? I foresee algorithms replacing almost all workers with no real options for the replaced humans.
They will be smarter more efficient and productive and cost less, so it makes sense for corporations and business to move in this direction. If Labour is no longer part of that exchange, the ramifications will be immense. Which part of this is warm and fuzzy? The need grows for algorithmic literacy, transparency and oversight The respondents to this canvassing offered a variety of ideas about how individuals and the broader culture might respond to the algorithm-ization of life.
They argued for public education to instill literacy about how algorithms function in the general public. They also noted that those who create and evolve algorithms are not held accountable to society and argued there should be some method by which they are. What is the supply chain for that information? Is there clear stewardship and an audit trail?
Were the assumptions based on partial information, flawed sources or irrelevant benchmarks? Did we train our data sufficiently? Were the right stakeholders involved, and did we learn from our mistakes? The upshot of all of this is that our entire way of managing organizations will be upended in the next decade.
The power to create and change reality will reside in technology that only a few truly understand. So to ensure that we use algorithms successfully, whether for financial or human benefit or both, we need to have governance and accountability structures in place. Easier said than done, but if there were ever a time to bring the smartest minds in industry together with the smartest minds in academia to solve this problem, this is the time.
That coping strategy has always been co-evolving with humanity, and with the complexity of our social systems and data environments. Becoming explicitly aware of our simplifying assumptions and heuristics is an important site at which our intellects and influence mature.
What is different now is the increasing power to program these heuristics explicitly, to perform the simplification outside of the human mind and within the machines and platforms that deliver data to billions of individual lives.
It will take us some time to develop the wisdom and the ethics to understand and direct this power. The first and most important step is to develop better social awareness of who, how, and where it is being applied.
We need some kind of rainbow coalition to come up with rules to avoid allowing inbuilt bias and groupthink to effect the outcomes. This is what computer literacy is about in the 21st century. The pushback will be inevitable but necessary and will, in the long run, result in balances that are more beneficial for all of us.
These factors will continue to influence the direction of our culture. He who owns the gold makes the rules. I suspect utopia given that we have survived at least one existential crisis nuclear in the past and that our track record toward peace, although slow, is solid. When they make a change, they make a prediction about its likely outcome on sales, then they use sales data from that prediction to refine the model. Their model also makes predictions about likely outcomes on reoffendingbut there is no tracking of whether their model makes good predictions, and no refinement.
This frees them to make terrible predictions without consequence. This characteristic of unverified, untracked, unrefined models is present in many places: The algorithms are not in control; people create and adjust them. However, positive effects for one person can be negative for another, and tracing causes and effects can be difficult, so we will have to continually work to understand and adjust the balance. The methods behind the decisions it makes are completely opaque, not only to those whose credit is judged, but to most of the people running the algorithm as well.
In some cases there is no way to tell exactly why or how a decision by an algorithm is reached. And even if the responsible parties do know exactly how the algorithm works, they will call it a trade secret and keep it hidden. There is already pushback against the opacity of algorithms, and the sometimes vast systems behind them. These things have the size, scale, and in some ways the importance of nuclear power plants and oil refineries, yet enjoy almost no regulatory oversight.
At the same time, so will the size of the entities using algorithms. They will get smaller and more numerous, as more responsibility over individual lives moves away from faceless systems more interested in surveillance and advertising than actual service. Machines have literally become black boxes — even the developers and operators do not fully understand how outputs are produced. There is a larger problem with the increase of algorithm-based outcomes beyond the risk of error or discrimination — the increasing opacity of decision-making and the growing lack of human accountability.
We need to confront the reality that power and authority are moving from people to machines. That is why AlgorithmicTransparency is one of the great challenges of our era. I have heard that people who refuse to be used by Facebook are discriminated against in some ways.
Something Interesting to Read May 2014
Perhaps soon they will be denied entry to the U. Even if the U. These outcomes will probably differ in character, and in our ability to understand why they happened, and this reality will make some people fearful.
But as we see today, people feel that they must use the internet to be a part of society. Even if they are fearful of the consequences, people will accept that they must live with the outcomes of these algorithms, even though they are fearful of the risks. If the algorithms are built well and robustly, the opportunity to insert this inefficiency e. Basically, algorithmic insight will start to affect the design of our homes, cities, transportation networks, manufacturing levels, waste management processing, and more.
We should become far more energy efficient once we reduce the redundancy of human-drafted processes. None of the efficiency gains brought about by technology has ever lead to more leisure or rest or happiness.
We will simply shop more, work more, decide more things because our capacity to do all those will have increased. When you do that, you just encourage more people to drive.
The real trick is to not add more car lanes but build a world in which fewer people need or want to drive. Given that these systems will be designed by demonstrably imperfect and biased human beings, we are likely to create new and far less visible forms of discrimination and oppression.
The makers of these algorithms and the collectors of the data used to test and prime them have nowhere near a comprehensive understanding of culture, values, and diversity. They will forget to test their image recognition on dark skin or their medical diagnostic tools on Asian women or their transport models during major sporting events under heavy fog. We will assume the machines are smarter, but we will realize they are just as dumb as we are but better at hiding it.
Every area of life will be affected. Increasingly we are a society that takes its life direction from the palm of our hands — our smartphones. Guidance on everything from what is the best Korean BBQ to who to pick for a spouse is algorithmically generated.
There is little insight, however, into the values and motives of the designers of these systems. A model is comprised of a set of data e. The algorithm is nothing without the data. But the model is also nothing without the use case. The same technology can be used to empower people e. It all depends on who is using the information to what ends e. Their computation is opaque and they were then used for all kinds of purposes far removed from making loans, such as employment decisions or segmenting customers for different treatment.
They leak lots of private information and are disclosed, by intent or negligence, to entities that do not act in the best interest of the consumer.