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JPMorgan’s new guide to machine learning in algorithmic trading

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If you’re interested in the application of machine learning and artificial intelligence (AI) in the field of banking and finance, you will probably know all about last year’s excellent guide to big data and artificial intelligence from J.P. Morgan. You will also therefore be interested to know that the bank has just released a new report on the problems of ‘applying data driven learning’ to algorithmic trading. 

Last year’s giant report was compiled by Marko Kolanovic, the ‘half man half God’ head of JPM’s macro quant research team, with assistance from Rajesh Krishnamachari, a quant strategist who quit for Bank of America Merrill Lynch in April. This month’s smaller report is authored by five different JPM employees – Vacslav Glukhov (Head of EMEA E-Trading Quantitative Research), Vangelis Bacoyannis (a VP in eTrading Quantitative Research), Tom Jin (a quant analyst), Jonathan Kochems (a quant researcher), and…Doo Re Song (also a quant research).

The new report was presented at the NIPS conference in May 2018, but has only just been made public.

For those who want to know how ‘data driven learning’ interacts with algorithmic trading, this is what the report is saying.

Algorithms now control key trading decisions, within a few parameters set by clients

Algorithms in finance control “micro-level” trading decisions for equities and electronic futures contracts: “They define where to trade, at what price, and what quantity.”

However, algos aren’t free to do as they please. JPM notes that clients, “typically transmit specific instructions with constraints and preferences to the execution broker.” For example, clients might want to preserve currency neutrality in their portfolio transitions, so that the amount sold is roughly equal to the amount bought. They might also specify that the executed basket of securities is exposed in a controlled way to certain sectors, countries or industries.

When clients are placing a single order, they might want to control how the execution of the order affects the market price (control market impact), or to control how the order is exposed to market volatility (control risk), or to specify an urgency level which will balance market impact and risk.

The data contained in a trading order book is crazily complex

Writing an electronic trading algorithm is a crazily complicated undertaking.

For example, the JPM analysts point out that a game of chess is about 40 steps long and that a game of Go is about 200 steps long. However, even with a medium frequency electronic trading algorithm which reconsiders its options every second, there will be 3,600 steps per hour.

Nor is this the only issue. When you’re mapping the data in Chess and Go, it’s a question of considering how to move one piece among all the eligible pieces and how they might move in response. However, an electronic trading action consists of multiple moves. It’s, “a collection of child orders,” say the JPM analysts.

What’s a child order? JPM points out that a single action might be, “submitting a passive buy order and an aggressive buy order. The passive child order will rest in the order book at the price specified and thus provide liquidity to other market participants. Providing liquidity might eventually be rewarded at the time of trade by locally capturing the spread: trading at a better price vs someone who makes the same trade by taking liquidity. The aggressive child order, on the other hand, can be sent out to capture an opportunity as anticipating a price move. Both form one action. The resulting action space is massively large and increases exponentially with the number of combinations of characteristics we want to use at a moment in time.”

Right.

Trading algorithms written by humans tend to become huge and unwieldy

When humans write electronic trading algorithms, things quickly become complicated.

In the past, the JPM analysts note that electronic trading algos were, “a blend of scientific, quantitative models which expressed quantitative views of how the world works.” They contained, “rules and heuristics which expressed practical experience, observations and preferences of human traders and users of algorithms.”

Trying to encapsulate all of this is hard. Most human-compiled algos are, “tens of thousands lines of hand-written, hard to maintain and modify code.” When clients object and markets change, JPM says human algos suffer from “feature creep.” Over time, they come to, “accumulate many layers of logic, parameters, and tweaks to handle special cases.”

Regulation makes human algos more complex again

Trading algos also have to do with regulations like MiFID II and the concept of, “best execution.”

They must therefore be written to take account of, “changing market conditions and market structure, regulatory constraints, and clients’ multiple objectives and preferences.”

If the writing of algos can be automated and account of these constraints, life will be simpler.

There are three cultural approaches to the use of data when writing trading algorithms

JPM says there are three cultural approaches to using data when you’re writing a trading algorithm: the data modelling culture; the machine learning culture; and the algorithmic decision making culture.

The data modelling culture is based on a presumption that financial markets are like a black box with a simple model inside. All you need to do is to build a quantitative model that approximates the black box. Given the complexity of behaviour in the financial markets, this can be too simple.

The machine learning culture tries to use more complex and sometimes opaque functions to model observations. It doesn’t claim that these functions reveal the nature of the underlying processes.

The algorithmic decision making culture is about making decisions rather than building models. Instead of trying to map how the world works, this culture tries to train electronic agents (ie. an algorithm) to distinguish between good decisions and bad decisions. The problem then becomes trying to understand why the algorithm made the decisions it did, and injecting rules, values and constraints to ensure the decisions are acceptable.

The algorithm has to find a balance between the optimal rate of execution and the optimal execution schedule for the desired trades

Once you’ve got your algorithm it needs to make a trade-off. It can either execute a trade quickly, at the risk of effecting market prices. Or it can execute a trade slowly, at the risk that prices will change in a way that’s bad for the order (‘up for a buy order, down for the sell order’).

It’s not always clear what constitutes a successful trade 

The definition of success in algo trading is not simple. It might be about balancing this trade-off between executing a trade quickly (efficiency) and executing a trade in such a way that prices are unchanged (optimality) – it depends on client priorities.

For example, the algo’s objective might be to blend with the rest of the market. This means balancing the market impact from trading too quickly and moving the price, or trading slowly and seeing prices move against the trade. The algo writer need to find a way of representing information and actions in a way that will fit with models and machine learning methods. The market state has to be summarised despite its, “huge, variable and frequently changing dimension and order state, both parent order and child orders outstanding for model inputs.”

It doesn’t help that many opportunities are, “short lived and exist possibly on a microsecond scale only.” Moreover, JPM says it won’t always be apparent whether a trade is good or bad until after the trade has been executed or avoided: “Local optimality does not necessarily translate into a global optimality: what could be considered as a bad trade now could turn out to be an excellent trade by the end of the day”.

J.P. Morgan has been using reinforcement learning algorithms to place trades, even though this can cause problems

J.P. Morgan is all for the kinds of “reinforcement learning” (RL) algorithms which use dynamic programming and penalize the algorithm for making a wrong decision whilst rewarding it for making a good one.

“We are now running the second generation of our RL-based limit order placement engine,” say JPM’s traders, adding that they have been training the ago within a “bounded action space” using, “local short term objectives which differ in their rewards, step and time horizon characteristics.” However, training your algo can be complicated. – If you try to ‘parallize’ an algo’s training by executing the algorithm on multiple processing devices at once, you can get the wrong result because of the feedback loop between the algorithm and the environment. But if you don’t do this and try “gradient-based training” you will end up with a huge amount of irrelevant experiences and good behaviours can be forgotten.

JPM has tried to avoid this by, “applying hyper-parameter optimization techniques.” This means they have fewer sampled episodes per trial and stop uninteresting paths early. Hyper-parameter optimization techniques have enabled the bank to train its algo by running training sessions in parallel.

JPM says the main focus of research has become “policy learning algorithms,” which maximize aggregated rewards matching a specified business objective within certain parameters. It also notes that “hierarchical reinforcement learning” can be used in regions where trading algorithms have to, “produce predictable, controllable, and explainable behaviours.”

Under a hierarchical approach, the algorithm’s decision is separated into groups with different sampling frequencies and different levels of granularity. This allows the separation of some of the algo’s modules, and makes it easier to see what its up to.

J.P. Morgan developed a reinforcement learning algorithm with a “character” to deal with long tails

In most reinforcement learning situations, JPMorgan notes that it’s about the algorithm learning actions that lead to better outcomes on average. However, in finance it can be a mistake to focus too heavily on average outcomes – it’s also about the long tails. For this reason, the bank’s quants have been building algos which, “value multidimensional and uncertain outcomes.”

To achieve this, the bank has been ranking uncertain outcomes (the long tail) by looking at the expected utility they will deliver in comparison with their future distribution. This is known as Certainty Equivalent Reinforcement Learning (CERL).

Under CERL, JPM notes that the algorithm effectively acquires a character based on its risk preferences. “If the client is risk-averse, the increased uncertainty of outcomes lowers the certainty equivalent reward of an action.” This leads to the natural emergence of the discount factor γ as distribution of outcomes is broadened as risk increases and the algo looks further into the future.

There are a few useful open source reinforcement learning frameworks

If you want to build your own trading algorithm, JPM’s researchers recommend a few places to start.

They note a few helpful early stage open source reinforcement learning frameworks, including:  OpenAI baselines, dopaminedeepmind/trfl and Ray RLlib.

Have a confidential story, tip, or comment you’d like to share? Contact: sbutcher@efinancialcareers.com in the first instance. Whatsapp/Signal/Telegram also available.
Bear with us if you leave a comment at the bottom of this article: all our comments are moderated by human beings. Sometimes these humans might be asleep, or away from their desks, so it may take a while for your comment to appear. Eventually it will – unless it’s offensive or libelous (in which case it won’t.)

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The best and worst fintech companies to work for

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By all accounts, working at a fintech company can be a bit of an acquired taste, particularly for those who have spent the majority of their career working at traditional banks and other established financial firms. On the other hand, there are many who love the feel of a startup and working with cutting-edge technologies. Stock options and lofty valuations likely don’t hurt either.

Of course, not all fintech companies are created equal. In an effort to identify those with the most fulfilled workforce, we looked at private fintech firms with the highest level of funding and the largest valuations and then cross-referenced the list with employee rankings on Glassdoor. While the rankings mainly feature companies that have yet to go public, via the Forbes Fintech 50 2018, we also included a handful of some of the more established post-IPO fintech firms, including Square, PayPal, Lending Club, MarketAxess and recently-public GreenSky. A few companies that would normally belong on the list weren’t included as the number of reviews weren’t statistically significant.

As you can see in the chart below, the runaway winner is Robinhood, makers of a commission-free trading app that saw a big boost to its user base when it enabled cryptocurrency trading. Closing on a $363m round of funding earlier this year, the startup’s valuation is nearing $6 billion. Sporting a ridiculous 4.9 rating (out of 5) on 59 reviews, Robinhood is near-universally praised by employees for its strong culture, pay and benefits. But perhaps the most common theme is the lauding of Robinhood’s mission of “democratizing America’s financial system.” The app is widely marketed in the States for serving new investors. Ironically, the only complaint is that they don’t have a 401k match. However, the company ran into some controversy a few months ago following a Bloomberg report indicating that it generates as much as 40% of its revenue by selling its customer orders to high-frequency trading firms – a common practice among retail brokerage firms but one that doesn’t necessarily jive with their “anti-Wall Street” message that some employees gravitate to.

Tying for second (4.7) is automated lending platform Kabbage, which uses machine learning to reduce the credit approval process from weeks to minutes, and U.K.-based TransferWire. Launched in Atlanta, Kabbage is lauded for its somewhat laid-back culture, including its casual dress code, free catered lunches, beer on tap, video games and its dog-friendly policy. TransferWire, which enables money management across currencies and borders, is known best for its “insane quantities” of paid time off.

Rounding out the top four is cryptocurrency exchange Coinbase, which is unique because it specifically targets experienced employees from traditional financial firms. Based in California, Coinbase opened a New York office earlier this year to focus on institutional clients with a goal of building headcount from 20 to 150 by the end of next year. Recent hires have come from traditional exchanges like NYSE and investment banks like Barclays. Current employees love management and working in the high-tech crypto space.

With a valuation of around $8 billion, Coinbase said recently that it doesn’t expect to go public anytime in the near future. The same can’t be said about Robinhood and Kabbage, which are both expected to be publicly listed at some point in 2019.

Perhaps the biggest theme throughout the rankings is that, with the exception of Square, all of the post-IPO fintech firms scored below the average. The worst performer, at least according to 126 reviews on Glassdoor, is GreenSky, an online lending platform that just went public in May. The majority of the poor reviews that dragged the company down to a 2.8 average focused on issues with management. The same story can be said about Lending Club, where employees take issue with the direction of leadership, a lack of new innovation and high attrition rates. “Hard to stay a true fintech company,” wrote one reviewer. It seems clear that the shackles of working for a public fintech company have the potential to sour the startup experience for some employees. Just ask Facebook. Check out the full rankings below.

***As a point of reference, average Glassdoor rankings for investment banks currently range from 3.3. (Deutsche Bank) to 3.9 (Goldman Sachs)


Have a confidential story, tip, or comment you’d like to share? Contact: btuttle@efinancialcareers.com
Bear with us if you leave a comment at the bottom of this article: all our comments are moderated by actual human beings. Sometimes these humans might be asleep, or away from their desks, so it may take a while for your comment to appear. Eventually it will – unless it’s offensive or libelous (in which case it won’t).

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COMMENT: The desecrated image of the Arc de Triomphe has horrified London trading desks

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Paris got ahead of itself. Ever since the start of Brexit and the tortuous negotiations of the British government, the victorious chants about the future place Paris will occupy in the Pantheon of global financial centres have been getting louder. Barely a day passes in which I don’t see a post with over 500 likes on LinkedIn that’s singing the praises of the City of Lights.

Except for now, the Gilet Jaunes movement has injected a necessary dose of reality into this utopia. It’s about time – things were getting ridiculous.

In the past few days, my colleagues in London have been stupefied to discover the context of the French city that was supposed to be the new platform for the financial monsters currently residing in the City, Canary Wharf and Mayfair.

The image of the desecrated, massacred, Arc de Triomphe has been around all our desks – To say nothing of the burned cars and the destroyed shops. What has shocked people here even more than the damage are the locations. – The Champs Élysées, the Avenue Kléber, the Trocadéro, the Place Vendôme… These are the addresses which bankers in London think of when they consider moving to Paris.

Which bank will want to place its sign in Paris after carnage of this magnitude? It’s already very difficult for foreign banks to navigate the French bureaucracy. Must they also face the risk of a civil war?

Anyone who would make Paris Europe’s financial centre needs to understand that the first foundation has to be political stability. Brexit has shaken the stability of London, but Paris has made itself seem worse by appearing to be a war zone.

The British prime minister, Theresa May, is unpopular, but London is not in flames under her leadership. While cars are burning in Paris, London is strengthening its claim to be one of the world’s major financial centres. – And Paris is showing itself to be in a totally different league.

Paul Deschamps is a French trader working in the City of London

Have a confidential story, tip, or comment you’d like to share? Contact: sbutcher@efinancialcareers.com in the first instance. Whatsapp/Signal/Telegram also available.
Bear with us if you leave a comment at the bottom of this article: all our comments are moderated by human beings. Sometimes these humans might be asleep, or away from their desks, so it may take a while for your comment to appear. Eventually it will – unless it’s offensive or libelous (in which case it won’t.)

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A top Credit Suisse sales trader in London just quit for Bank of America

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We may be late into the fourth quarter of the year, but one of Credit Suisse’s top London sales traders has just handed in his resignation – apparently for Bank of America.

Credit Suisse insiders say that Jamie Knowles, a London equities sales trader working with hedge fund clients resigned to join Bofa.

Credit Suisse declined to comment and BofA and Knowles did not respond to our request for information.

Knowles began working for Credit Suisse in September 2009 according to the UK’s Financial Conduct Authority (FCA) Register. He previously spent three years working for J.P. Morgan.

Credit Suisse has lost several members of its equities team to Macquarie this year.  The Swiss bank is also at risk of losing staff to Stephen Dainton, global head of equities at Barclays. Dainton spent most of his career at Credit Suisse and has also shown himself willing to poach ex-colleagues as he builds his team at the British bank.

Have a confidential story, tip, or comment you’d like to share? Contact: sbutcher@efinancialcareers.com in the first instance. Whatsapp/Signal/Telegram also available.
Bear with us if you leave a comment at the bottom of this article: all our comments are moderated by human beings. Sometimes these humans might be asleep, or away from their desks, so it may take a while for your comment to appear. Eventually it will – unless it’s offensive or libelous (in which case it won’t.)

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13 ways you can blitz a job interview in Asian private banking

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Private bankers are in high demand in Asia, where millionaire and billionaire wealth is surging and firms from HSBC to Julius Baer are hiring. But relationship managers in Singapore and Hong Kong still face a gruelling interview process in a sector where it’s difficult to change jobs without your clients supporting the move.

Here’s how to make it through a private banking job interview.

1. Prepare your business plan first

During the final interview rounds you will have to present a business plan on how you intend to build assets under management (AUM) and develop new clients, says an internal recruiter at Swiss private bank, who asked not to be names. But it’s best to complete this plan before your first meeting at the bank, because its content will help you to structure your early-round interview replies.

2. And pack in plenty of information

The more detailed your business plan, the more authentic it will appear. “Interviewers don’t always fully believe business plans as they suspect the figures may be inflated,” says Liu San Li, a former private banker, now a business partner at wealth management firm Avallis. “So your plan should show you’ve done adequate homework on your clients – for example, their current estimated bankable assets and the time you’ve known them for.”

3. Estimate your level of candidate support

Never walk into the first round of a private banking interview without knowing the approximate percentage of clients you can bring to the new bank. “You should also work out the percentage of transferable assets for each individual client – from 100% for clients who are like family, down to about 20% for the ones who you can’t guarantee,” says Abimanu Jeyakumar, head of recruiters Selby Jennings in Hong Kong.

4. Prepare for compliance and risk questions

“With increasing focus on risk management and compliance nowadays – especially with the highly publicised closures of BSI and Falcon Private Bank in Singapore last year – candidates must expect governance-related questions,” says Sean Kang, director of wealth management at consultancy McLagan in Singapore. “For example, you might be asked about how you balance business development with risk management.”

5. Get your presentation right from the first round

“During the first interview, the manager will be constantly assessing how you’d come across when meeting the bank’s millionaire clients,” says Jeyakumar. “So if you stumble over your answers, aren’t well presented or there’s something wrong with your body language, they’d assume you’d act the same in front of clients. You need to treat the interview as a business meeting.”

6. Look for ‘common threads’ in the following rounds

Your first interview will be with the hiring manager and/or HR and then you will move up the ranks to meet the market head. “In larger firms you’ll also speak to the heads of product and investment advisors, while in boutiques you’ll often get to meet the head of the private bank or the CEO,” says the in-house recruiter. “So meeting five or six people is quite common. Pay particular attention to any common threads in what they say that point to the real culture of the bank – this will help you decide whether you’re a good fit and whether you want to move there.”

7. Keep confident in a private banking interview

“In a private banking interview ‘confidence’ is the key word,” says Liu from Avallis. “There’s no room for error or ambiguity when presenting your business plan and convincing people of your ability to bring in new clients. Avoid using the term ‘I think’ and present your points with conviction, logic and substantiation.”

8. But remain realistic

Not all your clients will move banks with you, so don’t fall into the common trap of letting your confidence run away with you. “Be positive and realistic about asset transferability – otherwise it will come back to bite you. Remember that the interviewers were in your shoes once – they can often sense when you’re over-hyping things,” says Jeyakumar from Selby Jennings.

9. Explain how the move benefits your clients

Banks like hiring private bankers who are focused on their clients’ best interests rather than their own careers, says Jeyakumar. “So as well as talking about how many clients you can bring over, explain why the new bank’s platform would benefit them.”

10. Be prepared for product-related questions

“You’ll be asked about the products and banking facilities that your clients need,” says Liu. “Do your homework about the new product suite, and any cross-platform facilities available under the bank’s umbrella such as investment banking, corporate banking and direct access to securities trading.”

11. But don’t be a product pusher

Come across as a trusted client advisor, not a pushy salesperson. “If convince the interviewers that you have strong relationships with your clients, don’t sabotage your credibility when asked how you will move them to the new bank by replying, ‘using attractive rates’,” says Liu.

12. Don’t name your clients

While you will be grilled about your clients’ assets and the strength of your relationships, client confidentiality and banking secrecy means you won’t have to name them.

13. Be discreet in a private banking interview

As in all interviews, it’s important to provide on-the-job examples to prove your points, but don’t say anything that your clients would prefer you didn’t mention, even without naming them. “Illustrate with some story-telling, but keep this short  and be mindful that private banking is a discreet business,” advises the in-house recruiter.


Image credit: Paul Bradbury, Getty

Facebook: the big new threat to banks trying to hire in Singapore

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Like Google and Amazon, Facebook has been tapping Singapore’s banking sector for talent this year. In June, for example, Facebook appointed Bikramjit Singh Sadana, Standard Chartered’s head of process and controls for managed investments and discretionary products, as its APAC lead for developer operations management. That same month Heidi Hutchison, a senior intelligence manager at HSBC, joined the social media firm as business integrity manager for policy operations.

These recent recruits are not alone in hailing from banking. About 9% of Singapore-based Facebook employees with LinkedIn profiles have previously worked at a mainstream bank such as Citi, HSBC or DBS. Sandhya Devanathan, Facebook’s country director for Singapore, was a managing director for retail banking and payment products at Stan Chart before taking the reigns at the tech company in 2016.

Facebook now has plenty of room for the former banking professionals. Its swanky new APAC headquarters in Singapore’s Marina One Tower, which opened about two months ago, is almost four times as large as its previous Singapore office. Facebook employs about 1,000 people there but has space for 3,000 as it looks to bolster its headcount.

If moving from finance to Facebook appeals to you, our analysis of the company’s local job postings (see the table below) suggests there are plenty of options in Singapore.

This is particularly the case with technology-related jobs, which make up 27% of all local Facebook openings (when the figures for software engineering, enterprise engineering, data and analytics, design and user experience infrastructure, advertising technology, and security are combined). Moreover, although global tech firms in Singapore do sometimes hire from banks’ middle and front offices, they have recently been keener on poaching developers and engineers.

What type of Singapore-based tech roles is Facebook currently offering that would suit banking technologists? Most obviously, it has a partner engineer vacancy for its payments and finance platform. This calls for at least five years’ experience in “fintech, banking, finance or payment solutions” as well as software development skills in languages such as JavaScript/Node, PHP, Objective-C, Java, C++, .NET, Python, and Ruby. The catch? Fluency in Bahasa Indonesia is a must.

If you want to work in an expanding high-profile team, try business integrity (BI), which is responsible for keeping people and businesses safe from bad players on Facebook. Needless to say, this is a challenging gig, given the various scandals that have plagued the company over the past two years. In Singapore right now, BI wants to hire an internal solutions engineer – who boasts technical skills such as PHP, Hack, Haskell, Haxl, JavaScript and React – to work on new products. Because of the sheer size of the problems faced by BI, the team is understood to need “really talented engineers”.

Facebook in Singapore is also recruiting at the junior end. Its developer support engineer vacancy demands only one year’s experience as well as working knowledge of its platform API and expertise in developing for mobile. If you’re a young programmer at a bank, moving to this role will see you supporting “hundreds of thousands of developers around the world” through machine learning and AI tools across Facebook, Messenger and Instagram.

Banks in Singapore believe Facebook, Google and Amazon pose a serious threat to their technology recruitment and retention plans, especially given the tight domestic labour market and government restrictions on work visas. Local banking technologists now have the option of joining US tech giants located right on their door steps as headcounts rise and offices come to resemble those in Silicon Valley.

“We can’t put slides in offices like a tech firm can,” an in-house recruiter from a bank told a recent eFinancialCareers discussion forum. Facebook doesn’t have slides in Marina One either, but it does have vending machines for electronic gadgets, a giant Instagram wall, and a poster-design work room.

Have a confidential story, tip, or comment you’d like to share? Contact: smortlock@efinancialcareers.com

Image credit: coffeekai, Getty

Morning Coffee: Mass job cuts at the high paying hedge fund that poached junior bankers. Jamie Dimon’s activist appendage

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When blue-chip hedge funds start making offers to junior bankers, there’s a clear trade off between risk and return. On the one hand, it’s the buy-side and hedge funds can pay very well indeed. On the other, hedge fund jobs can be precarious and fluctuations in investment performance can see you abruptly let go through no fault of your own.

The downsides are currently making themselves felt at Balyasny Asset Management. Balyasny was one of the most aggressive hirers last year, taking staff from UBS, JP Morgan, Goldman Sachs and Morgan Stanley. The fund nearly doubled the size of its London operation, raising average salaries by 24% in order to do so. It was particularly aggressive in hiring from the sell-side and from investment banking, rather than from other hedge funds. All the signs were that Balyasny were building up a substantial operation, with a particular focus on equity research and trading.

It didn’t last. Earlier this year, Balyasny employees in London started dropping off the FCA Register and showing up at new employers. Ten traders were cut from the “macro trading program”, and portfolio managers and analysts started leaving, often after having spent less than two years at the company.  Some of the departures – like a five person team moving to Point72 – might have reflected other growing hedge funds following a similarly aggressive approach. Others couldn’t really be explained in this way; few had any obvious signs of being performance related.

Now we have the latest move. Bloomberg reports that 125 employees, including 40 investment professionals, have been let go.  That’s roughly a fifth of Balyasny’s total workforce and just under a sixth of the investment professional headcount.  Some of the junior bankers might still be there, but Balyasny’s cuts are unusually deep. The fund has eliminated 13 teams from a total of roughly 80. People leaving include big names in the hedge fund space, like Arancha Cano (formerly of Moore Capital) and Jay Rao (previously at Millennium). The cause appears to be the most basic hedge fund economics; the assets under management have been falling. November was not a good month for Balyasny’s flagship Atlas Global Fund (it lost 3.9%) and a combination of investment performance and client withdrawals mean that the overall group is likely to start 2019 with $7.3bn under management, $4bn less than it opened the year.

This is the risk that one has to bear in mind. Hedge funds are more strategically nimble than big banks, but this means that they can be quicker to cut as well as quicker to grow.  Even if your own job performance is good, you’re exposed to the overall cycle and to the firm’s ability to grow assets under management in a much more leveraged way than you are in the bulge bracket.  And if you happen to have a poor year (as everyone does), you’re in an even weaker position.  If you’ve already got a good franchise, and a pot of cash, you can probably handle this risk.  The people who need to be a bit more cautious are the junior bankers who joined hoping for a pot of gold and who are now back on the market in distinctly worse hiring conditions than those of last year.

Separately, everyone’s got their own problems … Jamie Dimon has an unusual set of troubles, though, mainly related to his high profile and longevity in the top role at JP Morgan Chase. His track record and punchy personal style (which have also caused him to be talked about as a potential write-in candidate for a Presidential run) mean that he’s one of the few bankers that people recognize by name. And that means that lots of people who have an axe to grind against the banking system will choose to grind it with Jamie, personally.

Wherever the JP Morgan Chase CEO goes, particularly if he’s delivering a public speech, there is now a community of political activists who follow him about, carrying out publicity stunts and challenging him. Since JPM is so big, it’s connected to almost everything going on in the world that someone might protest against; most recently, his apartment building has been subject to recordings of crying children in order to protest banking relationships with two Texas firms that run immigration detention facilities.  An activist called Ruth Breech has now interrupted so many Dimon speeches with protest banners against fossil fuels that he greets her with a, “Nice to see you again”.

“I don’t know why they’re following me around”, Dimon apparently said to a bank analyst, and he has also been known to exasperatedly explain to protestors that JPM has no role in setting government energy policy. But that’s one of the problems of successfully taking a bank through the crisis; people think you can do things.

Meanwhile …

A US court officially rules that “it is not illegal to be smarter than your counterparties.” Don Wilson, of swaps trading firm DRW, thought he had found a mispricing in interest rate contracts which led to potential arbitrage profits.  However, his own trades were big enough to systematically move the price, leading the CFTC to prosecute him and his firm for manipulation.  Today, the charges were thrown out and the regulators censured for failing to make a case that a “false price” had been established. (FT)

Damned if you do, damned if you don’t – after banks have been warned to get ready for Brexit moves, the FCA has now started handing out warnings to not move too many clients to their EU subsidiaries, unless they can be sure it’s in the clients’ interests to do so. (FT)

Crazy tales of spending on plastic surgery and luxury consumption, as millions of dollars of sports stars’ money sat idle, from the trial of Australian hedge fund Goldsky and its former car salesman founder (AFR, also background)

International Assets Advisory, a Florida wealth management firm, specializes in hiring advisors with some trouble in their past.  Some of them stole a hot dog while drunk in college, some of them racked up dozens of regulatory sanctions or marketed fraudulent products.  The marketing pitch to clients seems to be effectively “we keep a better eye on our staff, because we have to”. (Business Insider)

In the #MeToo era, some male bankers have decided the best way to protect themselves against hypothetical sexual harassment claims is to commit actual sex discrimination, and are withdrawing opportunities and mentorship from female colleagues. (Bloomberg)

Combining today’s themes of “job security” and “second chances”, a profile of David Sproul, an Arthur Andersen veteran who managed to overcome the stigma to become chairman of Deloitte.  He’s described as “just dull enough that the clients love him”. (FT)

And the big question of the day – why are octopuses so intelligent, and given they’re so intelligent, why don’t they live longer? (NYT)

Have a confidential story, tip, or comment you’d like to share? Contact: sbutcher@efinancialcareers.com in the first instance. Whatsapp/Signal/Telegram also available.
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This is what happens when you stop being a tech associate at Goldman Sachs

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Just as corporate finance divisions lose junior staff to private equity funds and sales, and trading divisions lose them to hedge funds, so big banks’ technology divisions are also at risk of suffering seepage of their own. – Why work in technology for an investment bank when you could be doing something more exciting in an fintech start-up?  Equally, why work for an investment bank when you can do something bigger and better in the retail banking sector?

Rofiya Hussain, a former associate in Goldman Sachs’ technology division, illustrates the allure of both alternatives. In 2014, Hussain graduated from the UK’s Warwick University with a Masters in Physics. Four years later, she’s just joined Bó, the trendy new mobile bank set up by Natwest which is named after the Danish word ‘to live.’ There she will be a ‘product owner’ – although which product Hussain will own is not clear, and she did not respond to a request to elaborate.

Hussain only spent three years at Goldman Sachs, but her career reads like a guide to how quickly you can progress in tech if you only spend a few years in an investment bank before quitting and leveraging your CV elsewhere. At Goldman, Hussain worked in UX and as a scrum manager and product owner (again). Immediately after leaving Goldman, she spent 18 months at Virgin Digital. Despite being a mere associate at GS, at Virgin she was head of payments and cards.

Hussain is just one case, but if you’re Goldman Sachs you might want to take note. It’s not just fintechs that are after your junior technology staff, but the technology divisions of retail banks too – some of which can offer more exciting job titles and ostensibly more exciting jobs.  Bó, which currently employs a core of around 30+ staff in the UK, is pitching itself as a rival to Monzo, Revolut (set up by an ex-Morgan Stanley trader) and Starling Bank. By comparison, climbing the technology ladder at Goldman Sachs might seem rather boring.

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Do you suffer from ‘buy-side personality disorder’?

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There is never a nice time to talk about nasty things. But there is a phenomenon in our industry which many people suffer from – it’s an occupational hazard and it needs to be brought out into the open. At this time of year, when people in finance are often forced into close social proximity by the party season, it’s more important than ever to talk about that most unspoken of conditions – ‘Buy Side Personality Disorder’.

As a syndrome, BSPD has a fairly obvious set of root causes – overwork, stress and salespeople. To work in the modern asset management industry is to spend long days in the thankless task of trying to outperform ever-more efficient markets. In the process, it becomes incumbent upon practitioners to give up on any real prospect of a social life outside of work.

So far, so traditional – people in finance have always tended to rely upon the office for socialization. Except that now, as investment managers cut staff and concentrate on passive and quant investment, it gets harder and harder to find much meaningful interaction in the office, either. And that means that today’s high-achieving buy side professional ends up being someone who has surprisingly little social contact with anyone except sell-side brokers.

There’s nothing wrong with the sell side, not intrinsically. Some of them are very clever and some of them are nice people; a few are both. But, painful though it is to admit, the first four letters of the phrase “sell-side” form a word which is not ornamental to the concept. They’re selling something, the buy-sider is their customer, and this simple fact shapes every conversation between the two parties. The problem is that it’s really not psychologically healthy to spend too much time in the exclusive company of people who know it’s commercially suicidal to tell you that you’re wrong. If you’re in an environment where at least half the time you definitely are wrong, and the market will be along to prove it in a short while, the cognitive dissonance can become unbearable.

Buy Side Personality Disorder is the result of a combination of an underlying insecurity, combined with excessive exposure to sycophancy. It can manifest itself with a varied gallery of symptoms, and at different levels of seriousness.

Do you work on the buy-side? Are you a sufferer? Think about the last four weeks. During that period have you ever:

1. Made a comment at an internal meeting which you took from a sell-side note and passed it off as your own idea?
2. Claimed that you only take a sales call “to find out what the Street is thinking”?
3. Told yourself that a sell-sider of the opposite (or indeed same) gender genuinely fancies you, and that if it wasn’t unprofessional you’d probably be dating?
4. Blamed a sell-sider for a stock that you bought and lost money on?
5. Tutted to yourself about the formatting of an earnings model that you got an analyst to send to you?
6. Ordered a bottle of wine at lunch that you probably guessed would be over the salesperson’s expense limit?
7. Made a weak joke about an investor relations person and basked in the laughter and applause of a group of sell-siders at a conference?
8. Won an argument with one sell-side analyst purely by quoting the research of another?
9. Made an impassioned pitch at an investment committee for a stock that you had not heard of until two days ago?
10. Complained about the unacceptable volume of free research in your inbox?

If you answered “yes” to more than three of these questions, it’s quite likely that you are suffering from some form of BSPD. If you answered yes to seven or more, it’s extremely likely that your sell-side contacts (the ones that are really polite to your face) have a WhatsApp group dedicated to discussing your behaviour. Many people suffer from BSPD and never find out, until the day that their employer has a round of downsizing and they need to “reach out” to their former sellside contacts on LinkedIn. Don’t let it get that far.

Luckily, Buy Side Personality Disorder is as easy to cure as it is to diagnose. And with the holiday season coming round, effective treatment is close at hand. When you go back home for Christmas, try to speaking to your mum or your siblings in the same way that you interact with your brokers. Not only will you quickly find out whether you have BSPD, you’ll get a more or less immediate dose of shock therapy that will bring you back to earth with a bump. In the meantime, thanks for taking the call!

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The most in-demand programming languages at every Wall Street bank right now

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In terms of raw job openings, December appears to be one of the worst months to be looking for work in banking. The number of job vacancies tends to drop as hiring managers wait for new budgets to be approved. However, this is only one side of the equation. – The number of people who apply to banks during the month of December falls at an even faster clip. While there are fewer jobs to apply to, our analysis suggests you’ll face less competition before the holidays than at any other time of the year, particularly with tech openings.

With that in mind, we scoured through the career pages of the five big U.S. investment banks and tallied the number of tech jobs based on programming languages, both to find out which banks are currently desperate for engineers in New York as well the programming expertise that’s most in-demand at each firm. The first chart totals the number of job openings by programming language across Wall Street, including Goldman Sachs, J.P. Morgan, Morgan Stanley, Citi and Bank of America. We then break down each specific bank below. (Note: The numbers also include jobs located in nearby Jersey City, where every bank except Morgan Stanley has an office).

As expected, Java remains the most in-demand language on Wall Street. That said, Python has made a huge leap in recent years, particular over the last 12 months. As you’ll see below, two of the five banks have more current job openings that ask for experience in Python than Java. The uptick in Python usage can be at least partially attributed to the fact that non-developers have recently begun utilizing it. Python’s unique modeling capabilities and relative ease of use have caught the eye of analysts, traders and researchers, who now use it in their own work.

Goldman Sachs

Based on current job postings, Goldman Sachs relies on Java more than any other New York bank. While J.P. Morgan (barely) has more Java-related openings, it also has a bigger footprint in New York and more local tech vacancies overall. In addition to Java, Goldman appears keen on C++ and Scala experience. It has more current openings featuring those two programming languages than any of the other five banks. It’s also worth pointing out that not all programming jobs at Goldman are engineering roles. More than a dozen sit in their securities division as quants and strats.

J.P. Morgan

Compared to Goldman Sachs, J.P. Morgan appears more amenable to Python and Java. However, the bank has more Java-related job openings in Jersey City than at its tech hubs in Manhattan and Brooklyn combined. That’s not the case with Python, where well more than half of vacancies are in New York City proper. Compensation for J.P. Morgan tech employees tends to be lower in Jersey City.

Morgan Stanley

Not much sticks out with Morgan Stanley other than the fact that it has fewer New York openings than its two biggest competitors. Much of the disparity can be attributed to its lack of a Brooklyn or Jersey City tech hub. It has “near-shored” many of its U.S. tech jobs away from the New York metropolitan area.

Citigroup

Currently, Citi has more openings that desire experience in Python than they do Java. This is actually rather unsurprising considering Citi just started offering Python coding classes to banking analysts and traders as part of its continuing education program. The bank appears all-in on Python.

Bank of America

Based in Charlotte, Bank of America has the fewest New York-based programming openings among the five big U.S. investment banks. However, it’s interesting to note that, like Citi, it too seems particularly keen on Python.

The main takeaway is clear: if you want a programming job at a bank in New York, Goldman Sachs and J.P. Morgan are currently your best bet.


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COMMENT: I am a hedge fund analyst and my portfolio manager is sucking all my pay

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The year is nearly over. If you work in finance, this is a special time. It’s when we can look back and think about lessons learned, be thankful for our families and co-workers. A time to… hahaha, Just kidding. Bonus time is coming! This is when we find out if we’re buying a Corolla or a Ferrari. If we can afford to move on to our third wife.

If you work on the buy-side, compensation is all about the team. If the firm does well, so should you. If the team does well, so should you. In theory, it’s all about sharing the wealth – at least that’s what they will tell you at the start of the year.

At the end of the year, it’s a whole different story. There may not be an ‘I’ in “team”, but there is an ‘I’ in “compensation”. Two I’s in “getting paid”. And four I’s in “making it rain, bitches!!!”

I Before E? I Definitely Comes Before U.

I am an analyst in a hedge fund. The problem with being me – and any analyst – is that I am not the one deciding how to allocate the compensation. It’s the portfolio manager (PM) that decides comp. So the PM becomes the “I”, and the analyst becomes the “U”. I’m not sure when I comes before E, but I definitely comes before U. Also, there is no U in Ferrari.

Now, everyone on the buy-side is greedy. And PMs are the greediest.  Whenever I’ve had a bad year, no PM has ever paid me more than what they were obligated to. None of them ever said, “You didn’t have a great year, but I’m going to pay you more, because we’re a team.”

However, this does not work both ways. If you’re an analyst who has outperformed the rest of your group, you know the “team” speech is coming. “Yes, you generated the majority of the profits this year. But you can’t look at it like that. We’re a team, so we need to distribute it evenly. Don’t worry, you’ll appreciate it when you have a bad year.”
Let me give you a hint – you won’t.

If you’ve read through this carefully, you’ll notice that the analyst has gotten underpaid when he/she has outperformed the rest of the group, as well as underperformed the rest of the group. So where did all the money go??? This is why your PM drives the Ferrari, and you drive the Corolla.

Have a confidential story, tip, or comment you’d like to share? Contact: sbutcher@efinancialcareers.com in the first instance. Whatsapp/Signal/Telegram also available.
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Google’s DeepMind keeps pinching talent from investment banks

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DeepMind, the Google artificial intelligence division that has just found a way to predict protein folding, is hiring. At the end of 2017, it had 700 staff, up from around 100 three years earlier. It currently has 58 jobs open, of which 20 are in London. Banks may want to get defensive – DeepMind has a habit of hiring their technology staff.

The latest DeepMind hire is Elena Buchatskaya, a former credit strat from Goldman Sachs. Buchatskaya joined Deepmind this month after three years at Goldman and two years at J.P. Morgan. She graduated from the Moscow Institute of Physics and Technology in 2010 and took an MA in economics and econometrics at Russia’s new school. In moving to DeepMind, Buchatskaya appears to be pivoting away from finance.

She’s not the only one. DeepMind has hired various people with a finance background in London, including a former J.P. Morgan software developer who’s now working on its machine learning infrastructure, a former Goldman equities strat who’s now working on the same TensorFlow team, and a quantitative analyst from Bank of America’s model risk team who’s now a research engineer at the Google subsidiary.

Notably, few of DeepMind’s London finance hires have a PhD – most are simply qualified to masters level, even though DeepMind CEO Demis Hassabis said last year that 400 of his 700 staff were PhD qualified.

For the year ending in December 2017, DeepMind’s UK wage bill was £201m, up from £105m the previous year. The company made an operating loss of £279m (up from £124m one year earlier) and paid an estimated £280k ($363k) per head.

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COMMENT: “Junior bankers in Hong Kong are way too obsessed with joining the buy-side”

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I’m a fourth-year analyst at Goldman Sachs in Hong Kong. My fellow analysts and I often chat about our career plans, so I’m now familiar with where bankers my age want to work in the future.

But when I started as a full-time banker in 2015 I was shocked by how fixated people were on moving to the buy-side in the near future. After all, we had only just joined the banking sector and we had got jobs at Goldman Sachs.

While jumping to a hedge fund or private equity firm is a common aspiration, most of my cohort are obsessed with it. I think this is silly. It’s unwise to focus so much on moving down the track, because the market is changing so rapidly that they don’t really know where they will stand in, say, 2019. They should instead enjoy what they are doing here and now.

When analysts think too much about a fantastical buy-side future, it makes the IBD work in front of them seem more mundane. Ironically, this could affect their performance and make them less likely to be snapped up by a hedge fund. Moreover, in Asia, there are even fewer buy-side job openings than in the West, and the deal-flow is a lot less. Buy-side moves here are even more of a pipedream than they are in the US or Europe.

Analysts should be much more focused on creating new opportunities for themselves within Goldman Sachs, a large bank where they’re a known quantity and their performance is clear for all to see. In private equity, you’re competing against hundreds of other people for a small amount of roles at organisations who don’t know who you are.

Investment banking, at Goldman and other budge bracket firms, is still the best way for graduates in Hong Kong to start and then grow their careers – so make the most of it! The hours will get better as you get promoted. As for me, I don’t have a long-term career plan, and I certainly don’t want to make MD at Goldman. I’m just looking to enjoy being here for a few years, and then see what the market is like if and when I actually have a good reason for moving.

Quentin Tam (a pseudonym) is in his third year as an analyst at Goldman Sachs in Hong Kong.


Image credit:  Digital Vision, Getty

Think Uber has stopped hiring in Singapore? Actually, it’s just poached from Citi

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Banking professionals can no longer order an Uber from Raffles Place, Marina Bay, or anywhere else in Singapore – but they can still get a job at the company.

Uber, which announced the sale of its local Singapore and Southeast Asian operations to ride-hailing rival Grab in March, retains an office in Singapore, which it uses as its headquarters for the wider Asia Pacific region. Among its latest recruits is regional program manager Sambhav Jain, who previously spent almost three years as an investments product manager at Citi in Singapore, according to his online profile.

Uber employed about 500 people in Singapore before the sale to Grab (some Uberites became Grabbers as a result of the acquisition, while others left or transferred internally), but it still has “well over 100” staff in the Republic, reports TechCrunch.

Jain is now working with a number of former finance professionals at the stripped-down Uber. There are 18 people at the company’s Singapore office who have previously worked for mainstream banks, according to LinkedIn results. They include Brooks Entwistle, chief international business officer at Uber, who worked for Goldman Sachs for more than 18 years, latterly as a partner and chairman of South East Asia.

Uber decided to keep its APAC head office in Singapore reportedly because Japan and Australia were deemed too remote and because drivers in Hong Kong have faced legal crackdowns. This means there are likely to be vacancies opening up in Singapore for the foreseeable future as the city supports APAC markets where Uber still runs its ride services, including Hong Kong, Taiwan, Japan, Korea, Australia and India.

The fact that Uber hasn’t exited Singapore isn’t good news for banks, which have faced increased competition for talent from large tech firms this year. For example, the company that ousted Uber from Singapore’s streets, Grab, recruited Gary Wong from OCBC in May as the head of its mobile wallet app, GrabPay. Amazon, Facebook and Google have also been staffing up their sizeable Singapore operations with help from the banking talent pool.

New Uber recruit Jain, who is an Indian national and Singapore permanent resident, joined Citi in 2015 following a stint of more than two years on the rice trading desk of Louis Dreyfus Commodities in Singapore, according to his public profile. He specialised in “fixed income, structured products and leverage” within Citi’s wealth management wing, and was involved in digital initiatives, such as the roll-out of e-signatures for investment subscriptions.

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Image credit: JasonDoiy, Getty

Morning Coffee: The best job in finance turns out to be a facade. Ominous utterances at Nomura

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Who hasn’t dreamed of working for a hedge fund? After all, there’s the pay, the prestige and the opportunity to prop trade rather than simply making a market. Hedge fund jobs have it all. – Don’t they?

Try suggesting that to 55 year-old David Goldburg, formerly of the GS prop desk, Michael Milken’s organisation and his own (putative) hedge fund. Bloomberg has got a photo of Goldburg looking curiously pallid and distraught at the state of his chosen profession. We are informed that Goldburg has been looking for a job and that despite (or maybe because of) his credentials, no one hiring. If you want to work in a hedge fund and you have more than 15 years’ experience then good luck.

It’s all down to that old fiend – juniorization.  First it came for the banks and now it’s come for the fancy jobs in the hedge funds. Bloomberg says even the shops which are hiring are only interested in “juniorification” of their ranks. In other words they want three or four twenty-something MBAs (or twice as many outsourced analysts in Mumbai) rather than one senior guy with a track record.

Not only is it therefore unlikely that you will find a hedge fund pot at the end of your rainbow, but if you do it may not be filled with gold. As our anonymous correspondent “MarginOfSaving” put it yesterday, hedge fund portfolio managers (PMs) will never willingly pay even the very best analysts more than they think they can get away with.  And in a market where the alternative bid has disappeared, that’s going to be a low number.  It could be even worse than that; if your PM thinks that you are a bit too expensive or fancies an upgrade, there are now at least 40 investment professionals recently laid off by Balyasny to choose from…

Worse, as Goldburg also discovered to his detriment, this is the worst possible time to be doing what successful hedge fund analysts have historically done: trying to monetise a good track record by starting your own fund.  Seed capital is hard to find and even if you were lucky enough to find it, good investment ideas are more scarce and risks significantly higher than they have been for years.  As well as closing down potential alternative alleys, this has interrupted the usual upward promotion ladder; senior guys with good performance are not leaving, so they’re not creating vacancies for the level below them, and that has a ripple effect all the way down the food chain, until it reaches the analysts at the bottom.

So what to do?  As always, the biggest firms, with enough diversification of strategies and investors to smooth the impact of market conditions, are the ones most able to carry out long term planning.  Citadel are still hiring at the analyst level, although they’re also firing.  GLG is still running its two-year program to bring analysts on to managing money, on the rationale that breaking the pipeline now is bound to cause problems in the future.  But other than that, people might have to start leaving hedge funds altogether, going to the sell-side or into industry.

That’s what David Goldburg has done.  He’s now employed at Merida Capital Partners, a private equity firm which according to its Twitter profile is “focusing on the ancillary verticals in the emerging cannabis industry”.  This has led him to give the decidedly double edged quote that “before I found cannabis, it was very depressing”.  He’s talking about the industry, of course, which is “so much more interesting and exciting [than hedge funds] from a growth perspective and a money making perspective”.  So for one hedge fund analyst at least, there has been a happy ending.  – Although you would never know that from his photo.

Separately, employees on the sell side are hardly having a party either. Take the confused messages being emitted by Nomura. On one hand, the Japanese bank eradicated 50 recently hired traders in the summer. On the other, it’s been hiring new people as it chases a 25% increase in credit trading revenues.  Now, Nomura’s London employees have new reasons to fear for their futures. The wholesale bank moved into loss in fiscal Q2 and that trend appears to have continued into the current quarter.

Bloomberg reports that Nomura CEO Koji Nagai made an investor presentation yesterday saying there was a good start to October, but wholesale activity dropped off a cliff in November “with both individual and institutional investors”.  Ominously, the London office is going to be converted from a global booking centre to one which only serves the EMEA region, reducing its allocated capital from $5bn to $3bn.  It’s hard to see that happening without further job cuts.

This is the age old story of Japanese banks’ international operations; they tend to lurch from feast to famine, depending on the extent to which the domestic franchise is throwing off enough cash to sustain ambitions of trying to reach critical mass and profitability in the American and European markets.  This is not the first such cycle and it might not even be the last.  For the time being, though, it looks very much like the global employees of any Japanese investment bank, not just Nomura, are playing defense rather than offense.

Meanwhile …

Some rare good news for Deutsche Bank, as it manages to settle one of the Frankfurt prosecutor’s cases in the growing “Cum-Ex” tax fraud scandal for only €4m, reflecting its relatively minor role as a custodian bank (Bloomberg)

The thundering herd is back? Despite a good year in equity IPOs, Bank of America has missed out on what it considers to be its “natural” market share in US mid-market investment banking deals.  Since it’s having a good year overall, it can afford to spend money on filling this gap and so it’s hiring investment bankers. (Business Insider)

A copy of Confusion de Confusiones, the first ever book written about stock trading (and options trading; 17th century Amsterdam had a surprisingly sophisticated derivatives market) is up for sale at Sotheby’s with a guide price between $200,000 and $300,000 for one of the last ten remaining first editions in existence. (Bloomberg)

Good news at Morgan Stanley too, where 2018 equity trading revenue is expected to reach an all time record in 2018 (Forbes)

SWIFT, the global payments system, has launched a product aimed at competing with blockchain by using its own API and database to allow banks to cross-check payment instructions before sending them, rather than relying on a distributed ledger to confirm everything. (FT)

Jamie Dimon continues to be a trouble magnet; his presentation to the GS Financials conference was interrupted twice by protestors against JPM’s lending to companies which run immigrant detention facilities (CNBC)

The latest application of AI is to search through expense receipts, trying to detect when, for example, someone has claimed for a “client dinner” that’s actually a strip club. (Bloomberg)

Have a confidential story, tip, or comment you’d like to share? Contact: sbutcher@efinancialcareers.com in the first instance. Whatsapp/Signal/Telegram also available.
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COMMENT: Is Python really the best language for data science in finance?

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Programming languages… How many of us haven’t witnessed debates on advantages of one programming language over another? These debates are at least as common as those on the relative merits of Emacs versus Vim or tabs versus spaces (the author has even witnessed a physical fight which tried – but failed – to resolve this age-old question).

Still, the question, “Which programming language shall I use?” is not just about aesthetics. Make a bad choice, and it will come back to haunt you at later stages of the project.

Many programmers, especially the very smart ones, having sampled the programming languages created by humanity to date, may come to the conclusion that none of them suits their needs. They then decide to embark on an adventure: write a new programming language. These geniuses often hide from themselves the true reason for doing so: writing a programming language is fun. Programming languages are usually initiated by individuals: APL by Kenneth E. Iverson, C by Dennis Ritchie, C++ by Bjarne Stroustrup, Java by James Gosling, kdb+/q by Arthur Whitney, LISP by John McCarthy, Perl by Larry Wall, Python by Guido van Rossum… And yet much of their success is determined by concerted efforts of the respective programming communities.

We now live in the age of data science and machine learning. The data scientist’s primary goal is to discover hidden relationships in a dataset – a collection of observations or readings – be it stock prices, medical records, or lists of insurance claims. Speed of development and convenience are of the essence. Python’s syntax is very terse (just think of list comprehensions!), yet natural and readable. It’s hardly surprising that Python is often the data scientist’s weapon of choice.

Many machine learning algorithms are easy to use but difficult to implement. It would be naïve (and wasteful) for the data scientist to implement them themselves: some things are best left to experts. Usually these algorithms come packaged in reusable libraries. Python is known for the abundance of excellent libraries backed by large communities of programmers: NumPy for dealing with multidimensional arrays, SciPy for linear algebra and scientific computing, Matplotlib for visualisation, Pandas for time series data (and most of the data in finance comes in the form of time series), Keras for neural networks, to name but a few. In data science Python has few competitors except, perhaps, R, which is known for its excellent statistical libraries.

Software engineers (rather than data scientists), who develop large, robust, industrial-grade software systems, will probably exclaim at this stage: but Python is slow and unsafe! Slow, because the Global Interpreter Lock (GIL) prevents multiple threads from executing Python bytecode at once. Unsafe, because Python is dynamically, rather than statically, typed, and lacks the compile-time type checks that prevent users from running nonsensical code –  the type checks that would be afforded by the stipulation of data types in function signatures. In Python, you can pass just about anything to a function: the code will run as long as the object passed to the function supports all method signatures and attributes expected of that object at run time. This laissez-faire approach is known as duck typing in honour of a phrase by the Indiana poet James Whitcomb Riley: “When I see a bird that walks like a duck and swims like a duck and quacks like a duck, I call that bird a duck.”

Pythonistas will reply: true, but Python is a perfect language to write wrappers around libraries written in other languages, safer and more performant, so it is often used as a kind of programming “glue”.

Indeed, Python’s strengths are, dialectically, also its weaknesses. The obsessive type-safety of members of the C-family programming languages, such as C++, Java, and C#, makes them more cumbersome for data science and quick prototyping, but makes it easier to write boringly robust (and sometimes even beautiful) systems that function well under stress in production.

Nothing beats the speed of C++ (apart from perhaps raw C, which is even closer to the metal), but its speed comes at a price: the need for complex, labour-intensive debugging of memory allocation. While the author himself is a C++ programmer, he would probably choose Java and C# when not writing a low-latency trading system.

In our trading systems, we usually use Python for data science. The models are prototyped, calibrated, and tested in Python, the results are then passed on to a production system, which is implemented in Java. This division of labour between Python or R and a C-family language is common among quant teams. The creators of the Julia programming language are attempting to combine the merits of Python/R for data science and prototyping and Java-like languages for production. This is a noble and challenging effort, and we are watching it with interest.

There are other programming languages, which we think a good data scientist should know. One of them is kdb+/q. To be more precise, q is the programming language and kdb+ is a database implemented on top of it. kdb+/q is irreplaceable when a data scientist is dealing with huge – tens of millions of rows upwards – datasets, and needs to make sense of them quickly. It is also used to power data captures in environments where data arrives in real time, such as algorithmic trading.

There are practical considerations to take into account when choosing a programming language, not only aesthetics. And while it takes relatively little time to learn the syntax of the language, time and exercise are required to become fluent in it. In this sense, programming is a bit like playing chess: it is easy to learn the rules of the game, but difficult to become a master. Until then, your best bet is to learn Python, and to keep repeating: “The rain in Spain stays mainly in the plain” – or hope for a miracle.

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The top 25 universities for getting a front-office job at J.P. Morgan

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The latest in our series on top universities for high-paying finance jobs focuses on J.P. Morgan, which says it receives north of 45 CVs for every job that it advertises. It helps, therefore, to study at the universities that JPM likes to hire from.

Perhaps the biggest takeaway from the research isn’t the order of the rankings (below), but how tightly bunched the schools were. There wasn’t a huge drop-off after the top five like the rankings for Goldman Sachs and the big three consulting firms. J.P. Morgan clearly has target schools, but it tends to cast a wider net than Goldman, McKinsey, Bain and Boston Consulting Group. As with our previous research, we looked at the total number of alumni from each school currently working at J.P. Morgan, courtesy of LinkedIn, combined with employment data from our own internal database that allows us to break down the percentage of graduates from each school who work in front-office roles at the bank. We also took into account total enrollment numbers from each university.

The top of the list isn’t all that surprising. As with the Goldman Sachs rankings, London School of Economics rose to the front of the line. NYU actually has a few more alumni working at J.P. Morgan, but not in the front-office. Harvard’s positioning at 7th was a bit of an eye-opener. Eleventh-ranked Cornell has one-third more alumni working at J.P. Morgan, but Harvard has a much higher percentage of graduates working in front-office positions like M&A and sales and trading. Harvard alums don’t seem to be a big fan of the middle or back-office at JPM.

However, the big headliner is Manhattan’s Baruch College, which has been quietly feeding Wall Street for decades with its finance-heavy curriculum and its close proximity to Wall Street. More Baruch alumni currently work at J.P. Morgan than any other school, according to our research. Like Cornell, the city college only finished 5th on the list because a vast majority of their graduates work in middle and back-office roles. Baruch is best-known in banking circles for its top-ranked financial engineering program. So to is Carnegie Mellon, producer of a large number of quants and strats at the master’s degree level.

Meanwhile, J.P. Morgan isn’t near as popular among Princeton grads as is Goldman Sachs. University of California, Berkeley and University of Michigan send plenty of graduates to J.P. Morgan, though they are two of the largest schools in the rankings, so their placement percentage isn’t quite as high as those in the top 10. That said, there are plenty of alumni from each school roaming the halls at J.P. Morgan, which can obviously be a great help. As with Goldman, Oxford and Cambridge are the second and third biggest U.K. feeders to J.P. Morgan, behind the London School of Economics.

Click here to check out the rankings for Goldman Sachs for the sake of comparison.


Have a confidential story, tip, or comment you’d like to share? Contact: btuttle@efinancialcareers.com
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Millennium Management poaches another Goldman Sachs veteran

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Millennium Management continues to pick on Goldman Sachs as it looks to fill seats left vacant by rampant poaching from ExodusPoint, the new hedge fund led by former Millennium star trader Michael Gelband. The latest win for Millennium is former Goldman Sachs managing director Ankit Raj, who joined the hedge fund last month as a fixed income portfolio manager in New York.

Millennium has had an interesting year when it comes to staffing. It has lost at least a dozen portfolio managers and traders to ExodusPoint in New York and London as Gelband continues to target his former employer, with which he reportedly left on iffy terms. Millennium Management hasn’t stood still while watching some of its talent walk out the door. The hedge fund has hired a number of former sell-side quants and traders over the last few months, including several with ties to Goldman Sachs.

This includes Dan Cleland-James, Goldman’s former head of synthetics and quant sales, and Uberto Palomba, an ex-Goldman Sachs managing director and former head of EMEA emerging market trading at Citadel who is said to be joining Millennium in February. Millennium also hired junior analyst Manan Bhandari, who was poached from Goldman Sachs’ macro equities team, and recently partnered with Neil Chriss, founder of now-defunct hedge fund Hutchin Hill Capital who counts himself as a Goldman alumnus. The game of musical chairs seemingly has no end.

Raj spent the last six years at Goldman as an interest rate volatility and options trader, according to LinkedIn. He previously held similar roles at Credit Suisse and Barclays. Raj has his master’s in financial engineering from the University of California, Berkeley Haas School of Business.


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Speedboats, not spreadsheets: inside the life of a 26-year-old private banking professional in Singapore

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The private banking sector may be expanding across Asia and suffering from chronic talent shortages, but students in Singapore are largely unaware of job opportunities in the industry, says a recent graduate now working at Credit Suisse.

“I don’t think many students here, even those studying finance, generally have enough understanding about what private banks do and what jobs in private banking involve,” says Singapore-based Jacelyn Ng Sin Yee, an assistant relationship manager (ARM) covering the Philippines ultra-high net worth (UHNW) market. “This is despite private banking having become a very dynamic part of financial services in Asia, thanks to rapidly rising levels of private wealth.”

Ng says there’s “typically a lot of discussion among students” about graduate roles in investment banking, asset management and technology. “But the perception is that there aren’t many junior opportunities in private banking,” she adds. “This means we need to do more to educate students about how to get into private banking and about why it’s such an innovative sector to work in.”

The young Ng, however, never needed any convincing that wealth management would be her future career path. “When I was 12 my dad gave me a book about investment and that hooked me on the idea of letting money work hard for you,” she says. Aged just 15, Ng decided to focus her education purely on finance, so instead of joining her peers in junior college, she took a Diploma in Financial Informatics at Singapore Polytechnic. After graduating top of her poly cohort, Ng then completed a Bachelor of Business Administration at NUS and joined the Credit Suisse private banking analyst programme in 2016.

But while being an investment banking analyst traditionally involves spending long hours working on pitch books and Excel spreadsheets, what does a graduate in private banking actually do all day? The PB analyst programme that Ng has just been through has at least three things in common with many IB traineeships: it lasts for two years, includes about a month of classroom-based learning, and involves rotations across several different parts of the bank.

Ng’s stints included the COO office, Indonesia desk, and various product advisory teams. “It’s not just about learning to become a banker right away; it’s about learning how the bank works from the back to the front end,” says Ng. “For example, I spent some of my time in the trust estate and advisory unit. While that may not sound like an obvious team to include in a rotation, estate planning is increasingly core to the private banking sector in Asia as more wealth is transferred to the next generation.”

Having finished the programme earlier this year, Ng is now an assistant RM, a job which can potentially lead to becoming a fully-fledged RM with your own set of clients. In investment banking, however, a third-year role doesn’t come with an ‘assistant’ tag. Ng says that while ARMs do support bankers, the position is far from subservient. She works with a single RM and a team of product specialists to help provide services such as financial planning, portfolio management and trading.

If that still sounds a bit plain vanilla, Ng insists that it’s not. “Many of our clients are entrepreneurs running a variety of businesses, so we get very different product requests every day,” she says. “It’s not just about buying and selling stocks – I might be asked to manage the purchase of a new private jet or boat, for example.”

Graduates shouldn’t opt to work in private banking because they think it will be any easier than a job in IBD. “Be prepared for a fast-paced and intensive work environment. Clients can put in challenging requests, and I’ve spent a few late nights working on client projects,” says Ng. “And be aware that the amount of compliance you need to do can be daunting at first. But having received great compliance training, I now enjoy that part of my role.”

Above all, Ng recommends that young private banking professionals take advantage of the contact they have with senior bankers. “As a junior it’s good to work so closely with seniors because you can observe how they build relationships with clients, and use this to improve your own communication skills,” she says. “I’ve already accumulated a lot of knowledge about how clients can behave and how bankers should react to them.”

Have a confidential story, tip, or comment you’d like to share? Contact: smortlock@efinancialcareers.com

Image credit: DKart, Getty

Another Asian tech unicorn tipped to take talent from banks (it’s not Grab)

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As Go-Jek launches its ride-hailing app in Singapore, it’s also hiring technologists to support its expanding operations – and that means more tempting job opportunities are opening up for developers currently working at banks.

Indonesia’s Go-Jek, which is valued at about $5bn and is backed by Google, Temasek and Tencent, started trialling a beta version of its app last week in Singapore and plans to roll it out island-wide in the first quarter. But while its need to recruit more drivers has so far dominated local headlines, behind the scenes the company is also ramping up its tech hiring.

Go-Jek, whose Indonesian operations now span 18 platforms including food delivery and digital payments, primarily uses its Singapore office in Shenton Way for data science and engineering work. It currently has six Singapore-based jobs on its careers site (all in tech), but that number is expected to gradually rise over the next six months as Go-Jek expands locally, says a Singapore technology recruiter who asked not to be named.

Go-Jek is recruiting only for high-end specialist jobs in Singapore. It employs most of its tech staff across its offices in Jakarta, Bangalore and Thailand, where labour costs are much lower than in Singapore. For example, Go-Jek is looking for a Singapore-based applied researcher in deep learning who will sit in the data science team and work on projects such as large-scale recommendation engines, real-time forecasting framework, and image recognition. Candidates need at least four years’ machine learning experience and knowledge of deep learning frameworks such as TensorFlow, Keras, PyTorch and Caffe.

While this job doesn’t require experience in a particular industry, Go-Jek could easily source a candidate from the Singapore banking sector, which is now one of the country’s major employers in data science and machine learning. DBS alone has hundreds of staff in its data and analytics team, while JP Morgan is hiring people with machine learning skills, for example.

Similarly, just as banks in Singapore are expanding their mobile-development teams, so is Go-Jek. It’s after an Android engineer with “strong foundations” in Java, OOPs, design patterns and clean code fundamentals. Go-Jek also wants an engineering lead for products, who will “maintain a balance between building sustainable, high-impact projects and shipping things quickly”. This role also hints at further recruitment within engineering – the manager will “work closely with the Go-Jek recruiting team to hire high potential candidates”.

While tech hiring is predicted to increase at Go-Jek, do not expect a boom. Its Singapore development team is unlikely to be as large as rival Grab’s any time soon. Niranjan Paranjape, chief technology officer, said in October that Go-Jek has adopted an “ultra-lean” engineering approach, partly shaped by a Chicago-based consultant ThoughtWorks. Go-Jek has about 200 engineers globally – about one per 500k monthly users. “Ten good engineers is better than 100 average engineers”, Paranjape added.

But why would a developer want to leave a large bank to join a company that is (despite being Indonesia’s only tech unicorn) still in the early stages of its Singapore build-out? One of the main attractions, according to the Singapore recruiter, is the sheer variety of development projects potentially on offer as Go-Jek attempts to become a so called super-app, offering a WeChat-like range of services, aside from ride-hailing. Engineers at the firm already work on a plethora of products – from hair styling to car maintenance and bill payments.

Banks in Singapore have faced increased competition for talent from Asian unicorns and US tech firms this year. Grab, for example, recruited Gary Wong from OCBC in May as the head of its mobile wallet app, GrabPay. AmazonFacebook and Google have also been staffing up their sizeable Singapore operations with help from the banking talent pool.

Have a confidential story, tip, or comment you’d like to share? Contact: smortlock@efinancialcareers.com

Image credit:  afif c. kusuma, Getty

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