Would love to use my actuarial skills to set up my own business in something (PQ pensions actuary). Any ideas?
I think entrepreneurial skills are going to be more important than your actuarial skill set. Your ability to control costs is particularly important. 80% of new businesses fail in the first year and being an FIA won't necessarily reduce that. Start with a small idea, invest a little bit of money in it, and whether it succeeds or fails you'll learn a lot. As for an idea - Alan Woods is the richest actuary in the world and he is a professional sports gambler.
I play online poker. Just won a seat in a game for £15,000 by winning a tournament with a £7.50 entry fee! 1st prize should be around 5k. I don't recommend poker to anyone though as I've lost more than I've won - hopefully this 15K competition can turn it around for me. All part of my bad-boy lifestyle.
Alan Woods died two days ago. Probably the richest man ever to receive any actuarial training http://www.tonywilson.com.au/writing/alanwoods.php I've copied most of the article here. I think its a fascinating story On how much money he has made gambling 'To be perfectly honest, I don't exactly know. I've deliberately tried to not work it out … In terms of net worth, can I say between $200 million and $500 million Australian?' His girlfriends The table is cleared by another beautiful, twenty-something Filipina who Alan introduces as Ruby. 'Ruby's younger - very sweet but maybe not so bright. Olive is smart, extremely witty and funny, but Olive is an attention *****. I sometimes call her the world's biggest bullshitter. Whereas Ruby would never tell a lie, unless she's being corrupted by Olive.' He invites the girls, whom he calls 'The Girls', to share fruit salad with us. But they are happy in the lounge room, drinking wine and listening to a Spanish pop song - 'Gasolina' by Daddy Yankee - on repeat. At some point it becomes clear Alan's going out with both of them. His introduction to gambling There was almost zero gambling in his early life. Apart from the odd sweep, his first taste didn't come until he started spending semester breaks playing solo with his parents, brother and sister, who cried whenever she lost. 'Usually she'd get her money back that way.' Alan had a knack for it - 'instinctively I seemed to take more risks than they were prepared to' - but for the most part he gambled like most punters gamble, badly. Poker machines caught his eye in Armidale and he played them until leaving for Sydney. 'I can't say I gave up poker machines because I was losing … I think it was because in Sydney they weren't available to me. Was I aware of the government rake, or the disadvantage I was betting into, in those days? No. I wasn't. Now, it seems bizarre to me that people can't be aware of the disadvantage the average punter has.' His introduction to gambling on horses Alan first bet on horses at university. 'I picked the third-favourite, a mudlark, to beat the two best horses in Australia at the time, Sky High and Wenona Girl, on a very wet track. And it won. So unfortunately my first experience on the horses was a winning one, because then I thought: Hmmm, I'm pretty good at this.'' From there a small gambling habit developed. On the horses - unlike solo or poker - he was generally a loser. He knows this because he wrote his bets down. 'What I did that was probably unusual is that I kept records of exactly how much I'd spent and how much I'd bet on each horse. As the years went by I knew my cumulative result. And then I lost $100 one day and I just quit … By the time I got involved in the horses 15 years later, I was an ex-addicted gambler and I had to force myself back into it.' His introduction to blackjack and serious gambling Woods was born in 1945 in Murwillumbah, New South Wales, 30 kilometres south of the Queensland border. In 1972 a friend named Richard Heenan was given the job of calculating the casino edge for every game at Hobart's soon-to-be-opened Wrest Point Casino. Alan sat near him and watched. The calculation for blackjack was the one that interested them, and after many months with a calculator and pen Richard worked out that the house edge on blackjack - with four decks and English rules - was 0.7%. It seemed clear-cut. The house had an advantage and, as Alan still maintains, gamblers don't win when the house has an advantage. At least in the long run. Shortly afterwards some bridge-playing Canadian friends told Alan he was wrong. You could win playing blackjack, they said, if you played correctly. Alan argued that you couldn't, that he'd seen the mathematical proof. The Canadians then explained how to count cards - how you add to the count for a low card, subtract for a face card, bet minimum when the count is low and maximum when it's high. Ten of Alan's friends went to Hobart to play blackjack and test the theory. The eight who were not card-counting lost their $500. The two that were doubled their stake to $1,000. Another test during the 1973 Australian bridge championships won Alan's team $6,000. By September 1973 he was a believer. He didn't become a serious gambler until Meredith left him in 1979. The intervening years were spent parenting, studying, and sleeping through alarms, with just the occasional bet. When Meredith was in hospital for the birth of their second child Alan was at Wrest Point Casino. 'He must have come back for the birth,' Meredith laughs, 'and then disappeared after I had her. He came back from one of those visits with $12,000 in cash, which in 1975 was quite a bit.' If there was any bitterness it has disappeared with time. 'He was a very family sort of person,' says Meredith, 'and he still is. He's a person with a lot of integrity. I can't remember him telling a lie.' When the marriage broke up, Alan found himself unemployed and choosing between three possible careers - professional bridge in Sydney (which paid $5 an hour), options trading or card-counting. He chose the latter, returned to Hobart and won $16,000 in four months. From there it was on to Las Vegas, where almost immediately he began earning US$4,000 a week. Within six months he had won US$100,000. He remembers thinking he was king of the world. And so Alan Woods began the 1980s travelling the world as an itinerant card-counter. He played with teams in Europe, Asia, North America and Australia. He lived and breathed the life. He knew when to hold them. He knew when to fold them. Legal casinos, illegal casinos. Sometimes he wore disguises when he thought an establishment might try to kick him out for counting. In Korea he donned a false moustache and glasses but was spotted by a host who recognised his walk. In Atlantic City he frizzed his grey hair into an afro. He was cheated in an illegal Sydney casino - the deck had been stacked with an alarming number of fives and sixes - and by a shifty dealer in Indonesia. He'd win cash in serious quantities and then face the problem of moving it to the next destination. Sometimes he used telegraphic transfer. When there was a serious risk of interrogation or confiscation, he used socks. 'I was leaving Korea, and as I remember it I had US$60,000 in cash and travellers cheques. I couldn't sleep the night before worrying about this. By the time I go through customs I've calmed right down. The guy pats me down, pats my ankle exactly where I have some $10,000 wrapped up - but having done it thousands of times a day, day after day, he doesn't notice. So I breeze through.' Another time Alan seconded the use of someone else's sock. 'I ask this young Australian guy in Manila if he's willing to carry US$20,000 in his sneakers. Then once we get on the plane he can give it to me.' As it turned out, the young man forgot his suitcase and he and his cash-stuffed sneaker had to race back to the hotel. 'Time is running short, and given the traffic in Manila I'm worried he's not going to make the plane. I'm waiting and waiting. Then we have to board the plane and he hasn't turned up. I board and they've closed the doors … and I can virtually never remember them being opened again once that's happened. Then after three or four minutes, suddenly the doors open up and these two guys are let on.' Alan breathed a sigh of relief. 'I wasn't so much worried about him stealing the money. It was just how was I going to find him back in Sydney? By the time he's in Sydney he doesn't know me from a bar of soap. Maybe he starts talking to some friends. Various thoughts can go through his mind, can't they?' In 1982 Alan retired from card-counting. He was about to marry his second (and last) wife, a woman called Linda, and he was tired of living out of a suitcase. In 1984 his mug shot finally made the 'Griffin Book' of cheaters and card-counters, which is provided to casinos every year by the Griffin Detective Agency. They were two years and several hundred thousand dollars too late. His move away from blackjack to horses and Hong Kong A founding partner in the Hong Kong venture was Bill Benter, the originator of computerised betting systems, who had devised a program at home that calculated a roulette ball's speed as it spins around and predicted which quadrant of the wheel the ball would fall in. Alan provided 60% of an initial US$150,000 bankroll and was in charge of selections through a 'favourites system', where the team bet on the horse judged most likely to win. They soon discovered they would win more if they bet only on overlays. Bill had a 30% stake and came up with the idea of building a computerised probability model. A third player, Wally Sommons, was in for 10% and did much of the early work compiling a database of past results. For the first two years the team struggled, wiping out their $150,000 bankroll. Alan injected another $40,000 and they wiped that out too. Then another $20,000. It was enough for Wally to lose his nerve but Bill and Alan, who had by now evaporated more than half his total net worth, persevered. The computer model started winning in 1987 - US$100,000 for the season - the same year that the Alan-and-Bill alliance broke up. Among various differences, Bill wanted a greater say in determining the size of each bet while Alan wanted to keep his own firm hand on the bankroll. It was a bitter split. Almost immediately, Bill set about making his own computer model, one that Alan concedes would later become a more sophisticated and successful version of his own. 'He came back to Hong Kong for the ostensible reason of discussing our partnership … But his real reason was to hijack all my data, because otherwise he was going to be missing a year or two's worth of data, and to program a self-destruct thing into my software.' I almost fall off my chair. It sounds like something out of a Mission Impossible movie, but Alan recounts it all with a certain casualness. 'Bill wasn't a really malicious person. He did warn me about this, and gave me time to fix the problem.' Alan's software did anything but self-destruct. In 1987-88 he won HK$3 million. The next season $7 million. Then 11. Then 19. One of the things that kept him motivated was his rivalry with his two peers - Bill Benter and a mysterious Australian called 'J'. In 1990 Bob Moore, the loudmouth New Zealander, betrayed Alan to go work for Bill. At the time, Alan and Bob had been sharing an apartment together. Later, to return the favour, Bob betrayed Bill, approaching Alan and offering to sell him back-data that Bill had paid Bob to supply. 'We're sitting in a Sydney restaurant, and I'm sure I tell him at least twice, Bob, it's not yours to sell.' Nevertheless, Bob does sell, and Alan buys. 'Years later,' says Alan, 'by which time he's threatening to kill me, I referred back to this episode - Bob's betrayal of Bill - and Bob shouts at me: ‘If you were a true friend, you wouldn't have allowed me to do it.'' Alan laughs and shakes his head at the strangeness of it. Bob killed himself in 1997, depressed and isolated, on a night when Alan was hosting one of his famous parties. As for Bill, Alan believes he has retired from actively managing his computer team - and it is rumoured that Bill's team was even more successful than Alan's. He lectures occasionally on the computer model and devotes his time to philanthropy and politics. There are tales of Alan giving away money too. 'We went out for [his son] Anthony's 22nd birthday and he gave me an envelope,' Meredith recalls. 'I opened it and found a cheque for a million dollars. I nearly fell on the floor. I'd had a terrible year with work and a family illness. I haven't worked since.' She's now in the Australian women's bridge team. He offered his children A$1 million if they completed an economics degree by the age of 25. Daughter Vicky succeeded and has been given her million. 'She hasn't touched it, to the best of my knowledge,' says Alan. 'It's just sitting in an account somewhere.' When he lived in Hong Kong, at Chinese New Year Alan and his staff would stuff red lycee packets with between HK$500 and HK$2,000 and distribute them throughout the discos. In October 1987, on the day he made his first million, he celebrated by walking the streets and dropping $20 notes in the laps of Filipinas sitting in the gutter. Alan has given extensively to mental health research, and he's donated at least a million to Australian bridge. In terms of donating to the taxman he is harder to pin down. For starters, it's an arguable point as to whether gambling winnings are taxable. It changes country by country, and the problem governments have is that if winnings are taxable, losers will want to deduct their losses. Then there's the question of residency. ‘I'm not resident here [in the Philippines],' he says. 'Theoretically I'm not resident anywhere, given I come here on a tourist visa. And my plan has been for some years not to be resident of any particular country for the rest of my life.' When a sum like that is being won on a mutual totaliser, somewhere else it's being lost. I ask Alan whether he ever has any moral pangs about what he does. 'I tend not to think about it too much. I would view it more that the public is going to lose the money anyway. Bill Benter thought about it fairly seriously about ten years ago and decided that what we did made us pariahs. I choose to look at it differently. There will be addicted gamblers who mess up their lives through gambling, just as you'll find people who mess up their lives through alcohol or food.' He packs up his thermos and the printout of results. Before the next meeting, the data from today will be plugged into the probability model and played through. If it justifies a change in the weighting of any of the probability coefficients, it will be made permanently. With each race the computer gets 'smarter'. As for his team, they are expanding into other countries. It is already betting in one new market and about to start in another. I'm not allowed to know where. Most likely they are racing environments similar to Hong Kong - big pools, small fields, a limited number of horses. Most probably the product of their enormous labours will be still more money. I ask Alan if being one of the world's three richest gamblers has led to a happy life. 'Generally, yes. Probably less so now than in years gone by. There's a cliche that says getting there is much more fun than arriving. If my ambition was to get enough money not to have to work, or to get enough money and then rest and relax - well, the more money you have the more work it creates.' His voice is weary, and in line with his usual post-races practice, he heads upstairs for a snooze. That day Somewhere in China his associates are using CIT machines to connect to the Jockey Club phone-lines and place today's bets. The meeting is being run at Sha Tin racecourse and they are targeting a HK$32.7 million jackpot for the Triple Trio. Back in Manila, Alan keeps in touch with team directors via instant messaging and Skype. As he scribbles away, a spreadsheet of the day's betting pings onto the monitors. The team will bet on all nine races: total outlay, HK$14 million (A$2.4 million). More than one-third will be invested in the Triple Trio, where punters have to pick the first three finishers in races four, five and six. It's a $4.6 million wager to win $32.7 million. He loses on the first. Several hundred thousand Hong Kong dollars. I study his face for signs of pain or distress, but there are none. It's all part of his meticulous approach. His team selects the overlays. Bet-size is determined according to Kelly's Criterion, a theory devised by John L. Kelly in 1956, which says that to maximise profit, a gambler bets to win a percentage of bankroll that is equal to his percentage advantage on a particular wager - so, for a Win Expectation of 1.05, you bet to win 5% of total bankroll. Because betting 100% Kelly can lead to a frightening, roller-coaster existence, Alan's team bets closer to two-thirds Kelly, which is calculated to reap around 90% of maximum profit. At one six-race meeting a few years ago they dropped HK$23 million. 'We just won a million dollars.' He says it in the sedate tone of someone announcing the Epping train's arrival on Platform 6. By 'we', I'm figuring he means him and his computer team rather than him and me. 'I checked the computer on the way back from the bathroom. We're up a million on today's meeting.' I try to ask a few questions but Alan doesn't want to say any more about it. His betting team has been branching out into new territories and he doesn't want competing teams to know where. Instead our eyes swing back to the TV screen. Alan's so excited about his HK$3 million win on Race 2 that he goes off for a sleep. He's never been a sound sleeper; indeed he sometimes gives his sleep disorder credit for his spectacular success. After marrying Meredith in 1972 he worked for a firm of consulting actuaries. Later, with two young children to help support, he was an investment analyst for a merchant bank. 'I had a sleep problem which caused me to be unable to get up to go to work on time or sometimes to make it to work altogether. So if we had a 9 o'clock start, I often wouldn't arrive before 11 or 12. And sometimes if there were too many late starts I'd be embarrassed and wouldn't turn up at all. So I got fired.' Alan returns from his sleep to discover that Able Prince has won Race 3. It's a 1.83 Win Expectation, so the team has supported it heavily. I ask Alan if he's happy. He shrugs. 'I'd probably prefer that I lost today.' Alan receives a printout of all his live Triple Trio tickets (all 70 of them), but it's difficult to tell exactly which combination to barrack for. Eventually he catches my enthusiasm for Gallant Knight as it dives for the line. It's a beautiful moment: bookmaker and punter, both cheering for the same mount. 'Gallant Knight gets out and chases for Prebble. Win Again a length. Gallant Knight continues to stay but Win Again is too good, and wins well.' A few minutes later, Prebble does the right thing and protests first against second. But the final trio in the Triple looks settled: Win Again, Gallant Knight, Lucky Stravinsky. Alan's team has one winning $10 ticket out of a total of five winning tickets. It translates to a collect of HK$8,364,000 (A$1.453 million) - an 82% return on investment. For the second-last race, my bookmaker decides to extend some generosity to me in the form of punting advice. He pulls out his magic A4 sheet and points to Lotzatow in Race 8. 'We've got a big overlay there. It's a 0.22 probability that is paying $10. So it's a 2.21 Expectation.' Conceding that blind superstition has done me few favours, I jump on board. Lotzatow never looks like losing. We're both on a collect - A$79 for me, and Alan to the tune of A$850,000 (minus $79). He insists on paying me my winnings, even though I've leached food and drinks from him all weekend. I thank him, reminding myself that generosity is still generosity, even when your host's betting team has just collected A$1.77 million over a nine-race card. How he does it The good news is that the fundamental principles are relatively simple: Alan and his computer team win by capitalising on bad betting by the general public. The bad news is that the key to doing so is having more information than the public. Much more. Alan's team employs a dozen or so staff to review, analyse and compile data for every horse running in Hong Kong, every time it runs. They are a disparate bunch, scattered across Asia and Australasia, coming together only in the cyber-confines of an email inbox. The data is then plugged into a computer program, and using a formula based on past results that has been refined over many years, a probability for every horse in every race is calculated. Producing the formula is the tough bit. It has been mathematically chiselled out of all the factors that Alan and his team have determined decide races. Each factor is a coefficient in the formula. Some factors - gender, track, distance, weight, last-start result - are objective and can be collected from the humble form guide. The key is getting the weighting of these objective factors right. For example, early on, Alan and his then team partner Bill Benter worked out that number of starts was more important than age. Apparently the data bears it out: the more times a nag is flogged around a racetrack, the less enthused it gets about the whole idea. Then there's form: second in an eight-horse field might not be as impressive as fourth in a 14-horse field. We chat about barrier numbers, and Alan tells me about the time in November 1995 when the computer model stopped working for a month or two. Eventually Alan worked out that the last turn at Happy Valley had been re-cambered - which means the track is shaped to slope upwards from the inside rail - creating a disadvantage for inside horses as the outside horses shifted in. His team adjusted the coefficients relating to barrier position and immediately resumed their winning ways. Other factors are more subjective, which is why Alan's team employs expert analysts to watch every horse in every race. 'We had a factor called bad rides. We had a factor called not trying. If a couple of horses disputed the lead together, the guys would give it numbers for that. Premature speed - if the horse went too fast too early. Late speed - if it came home very fast in the last 400.' It's the kind of stuff any experienced punter might consider. What the computer teams do is systemise the process, eliminating sentiment and superstition and minimising human error. ****** Alan hands me a single A4 page. We're in his home office now, with its view of brown, green and grey shanty roofs. It's a narrow, air-conditioned room with a desk on either side - Alan sits at one, me at the other - and two flat-screen TV monitors behind us. We're thousands of kilometres away from Hong Kong's Sha Tin racetrack. There's ocean between us and the roar of the crowd, the thunder of the hooves. If some stallion or other is 'rock hard in the mounting yard' we're not going to know. And yet for the first time in my gambling life, I'm staring at an A4 page that is set up to create advantage where usually there is only disadvantage. It's the form guide they hand out in heaven - except if everyone had one, it wouldn't work. Alan's success depends as much on the misinformation, blind loyalty, poor analysis and binge drinking of the average punter as it does on his own meticulous preparation. Think of the bad decisions punters make: investing in lucky numbers; betting on 'Maythehorsebewithyou' because you like Star Wars; plumbing for Reckless because his trainer is a sweet old digger. It's all misguided moolah being tossed in the pool, and it's the professionals - like Alan Woods and the other computer teams out there - who own the Kreepy Krawlies. They do it by searching for what they call overlays. An overlay is any horse that has been under-bet by the public and whose odds, as a result, are inflated. An underlay is a horse that has been over-fancied - one whose odds are too short given its real prospects. In Hong Kong there is a government and Jockey Club rake of 18% - that is, 18 cents out of every dollar gambled is removed from the pool and not returned to punters as dividends. This means computer teams like Alan's can't survive solely on small overlays; when Alan sits down at his A4 sheet, he is looking for massive overlays. It's not that these overlays always win. It's just that for long-term players they are the value bets. Fortunately for Alan, people are idiots and there is usually at least one per race. Heaven's form guide has four important columns: the horse's number, its current odds, its computer-calculated probability of winning (expressed to three decimal places) and a figure Alan calls its 'Win Expectation'. Win Expectation, which is obtained by multiplying a horse's computer-calculated probability by its current odds, identifies the amount a team can expect to receive for each dollar bet on a particular horse. The formula goes: E (return) = P (win) x current odds If the Win Expectation is greater than one, the horse is an overlay - an attractive, potentially profit-making horse. If the Win Expectation is less than one, the horse is an underlay and should be avoided. If the Win Expectation is between 0.82 and 1, the horse is a small overlay but an unwise investment because of the Jockey's Club rake. For example, if a horse has been calculated by Alan's team to have a 0.25 probability of winning, and if she is paying $2.00 for a win, then her Win Expectation equals 0.50 (0.25 x 2.00 = 0.5). This doesn't mean she won't win. She is fancied for a good reason. It just means she has been over-bet in the market and that, in the long term, a team that consistently bets on horses with such a low Win Expectation number can statistically expect to lose. Alan's team works out a Win Expectation for every horse, then makes similar calculations for exotics such as the quinella, trio (box trifecta) and Triple Trio (box trifecta, three races in a row). These exotic pools are attractive because they generate massive jackpots, but they are also trickier because the computer must consider probabilities in combination as well as predict dividends. Naturally tips, which are so beloved of the mug punter, rarely produce overlays, for the simple reason that if someone is telling you then it is likely other people know too, and so the horse will be over-bet. Alan remembers one Thursday night when he bounced around three different discos and received tips for four different horses in one race. Of course, the public was hearing these tips too, and so those four horses became significant underlays, enough to push Alan's computer towards the other three. The race was run and the computer's selections finished first, second and third. 'You could say,' says Alan, sitting on the floor, legs tucked into his chest, 'that our whole theory behind betting on horses is to take a contrarian approach to whatever the public is doing.'
