Quantitative management is a sophisticated management since it uses statistics and mathematics to develop an approach based on a rigorous procedure. Indeed, it ignores any intuitive or emotional element.
It consists in a modern management which is grounded on computer performances in order to obtain fully objective and essential data for portfolio management. Quantitative models are developed with the sole purpose of better managing the investors’ assets.
ALTIA Investment is intended to implement quantitative management solutions from innovative proprietary algorithms.
We have developed a new kind of quantitative management model which is able to identify, analyze and make use of data. The modeling of our algorithm is endowed with Artificial Intelligence.
ALTIA Investment offers a different approach to asset management. Indeed, investment decisions are partly dictated by algorithms used to design the most powerful and modern microprocessors. These algorithms rely heavily on branch prediction.
Due to its design, our model also has the ability over time to learn from its successes and mistakes. He will increase its understanding of market movements a little more every day and, as a result, refine its predictions.
Our management is modern. It allows Science to serve Finance in an unprecedented way
Embracing the new era of asset management
Our industry will face new realities and challenges. One of them is the ability to adapt very fast. This has become the new Graal.
Adaptability: this is our credo and our DNA.
We are entering a new era where financial markets will be impacted by the technological innovation faster than ever. This predicts more complicated market dynamics.
We have the ability to adapt to violent regime changes and economic conditions filling the gap between the passive index industry and traditional asset managers offering.
We are the New Generation of Asset Managers. Thanks to our Artificial Intelligence models, we are adapting our strategies fast enough to answer the constant innovation and technological changes that occur and which impact business and economic changes.
Today, the financial market is dominated by the ETF industry and traditional Asset Management. We are convinced that a big shift will happen soon. With the poor performances of traditional managers being unable to beat consistently their benchmarks and the massive positioning in index funds and passive investing industry, a fantastic opportunity lies ahead for ALTIA Investment: We can offer an « unprecedented approach » by adapting very fast to economic conditions and changes thanks to our AI models.
The Opportunity: markets are not completely efficient
Efficient Market Hypothesis: an incomplete theory?
Efficient Market Hypothesis (EMH) has been adopted by the investment industry and most finance academics. EMH means that there is no such things as a free lunch: if financial market prices already fully incorporate all relevant information, trying to beat the market is a hopeless task. Instead, you should all put your money into passive index funds that diversify as broadly as possible and stay invested in stocks for the long run. Today, index funds and passive investing are an enormous part of the financial landscape, an amazing success for the EMH. However, this hypothesis has a deeply uncomfortable implication in reverse: if no amount of analysis is going to help an investor to beat the market, what are we to make of George Soros breaking the Bank of England, or John Paulson’s 20 bn$ profit from 2007/2008 betting against the housing bubble, or the extraordinary careers of the computer scientist David Shaw and the Mathematician James Simmons, whose hedge funds have consistently managed to beat the market? The standard explanation under the EMH is that these people where somehow just « lucky », that their returns were simply the tail end of the statistical distribution rather than the result of a particular skill. However, when we look at the details of their extraordinary track records, as well as those of many others wildly successful hedge fund managers, we have to wonder whether something else is going on.
EMH has been embraced by the financial industry some decades ago with Vanguard being the first mover, founded by J.Bogle in 1975 and managing today almost 5.5 trillion $. This is the theory that we teach in business schools today. In 2013, Eugene Fama was awarded the Nobel Prize in Economic Sciences specifically for this notion of market efficiency. Another caveat of the EMH is that it assumes a world of Homo Economicus, perfectly rational human beings. But only the most ardent disciples of the EMH truly believe that human beings are economically rational. Most economists know that humans are prone to error, poor judgment, mental haze,
and so on. Nevertheless, the followers of the EMH would say that human irrationality has little effect on market behaviour, because more rational buyers and sellers in the market would quickly eliminate that irrationality in pursuit of profit. Although the EMH hypothesis has been the dominant theory of financial markets for decades, it is clear that individuals aren’t always rational. We shouldn’t be surprised then that markets aren’t always efficient, because Homo Sapiens isn’t Homo Economicus. The truth is that we are neither entirely rational nor entirely irrational, hence neither the rationalists nor the behaviorists are completely convincing. We need a new narrative for how markets work.
As an experienced Portfolio manager, I know this theory is not wrong but probably incomplete.
Our view and our Proposition:
The market prices need not always to reflect all available information, but can deviate from rational pricing relations from time to time because of strong emotional reactions like fear and greed. It implies that the market risk isn’t always rewarded by market returns. It implies that investing in stocks on the long run may not always be a good idea, especially if your savings can be wiped out in the short run. It implies that changing business conditions and adaptive responses are often more important drivers of investor behaviour and market dynamics than enlightened self interest.
Markets do look efficient under certain circumstances, namely, when investors have had a chance to adapt to existing business conditions, and those conditions remain relatively stable over a long enough period of time. However, business conditions often shift violently and “long enough” depends on a lot of things. The challenge remains, for human beings, to be able to foresee and rightly time these sudden changes. Can we do it in a consistent manner? I doubt – so, you will always have a Fund Manager making a killer in a specific situation, but rarely able to reproduce it systematically.
What is our credo then? It’s all about human capacity to keep a rational judgment in difficult times when fear and greed are back in the game. As Homo Sapiens, while our fear reflexes may protect us from injury, or adapt to situations in the savannah, they do little to prevent us from losing large sums of money. Psychologists and behavioural economists agree that sustained emotional stress impairs our ability to make rational decisions. Fear leads us to double down on our mistakes rather than cutting our losses, to sell at the bottom and buy back at the top, and to fall into many other well-known traps that have confounded most small investors, and not a few financial professionals. Our fear makes us vulnerable in the market place. This is why we think we need a new approach to financial markets, one that incorporates the fear factor as well as rational behaviour. At this stage, Artificial Intelligence, Machine Learning provided by ALTIA Investment models seems to be the right answer, being a great solution to adapt fast enough to regimes changes and behavioural features. Today, more than ever, we need to adapt to the financial environment at a much faster speed to economic expansions and contractions.
For the past fifty years, academic finance has been dominated by highly mathematical models and methods, it has spawned an unprecedented wave of innovation in finance. These new quantitative models became part of the standard of financial toolkit for traders. May be the extreme mathematization of “finance/physics” has gone too far, they might have underestimated the importance of the “evolution” variable compared to static models. We at ALTIA Investment are one step ahead of the classic « quant » approach thanks to our unique technology. Our models are dynamic and constantly changing, adapting and most importantly learning (thanks to the machine learning technique we conceived at ALTIA Investment) every day to new conditions. This explains why our models are outperforming their classic benchmarks in 2017 and 2018. Our Algorithm adapts constantly to market changes and makes us confident in our ability to be consistent outperformers in the years ahead.
Vincent Rennella, CIO – January 2019.